Compact Size UWB Monopole Antenna with Triple Band-Notches

This paper presents triple band notched ultra wide band (UWB) monopole antenna with overall size of 36 × 32 mm fed by microstrip transmission line. In order to achieve a good impedance matching from 2.7 GHz to 13.4 GHz, a tapered transition between the rectangular patch and the feeding line is utilized. The three notched frequency bands are accomplished by a defected microstrip structure (DMS) which is inserted in the microstrip feeding line and by an open loop slot etched in the radiating patch. The three band notches are 3.15–4 GHz, 5.7–6.3 GHz and 7.9–8.6 GHz. They prevent the receiving of the signals of IEEE 802.16 WiMAX band, WLAN band, and ITU applications respectively. The UWB antenna was designed and simulated, then fabricated and tested in order to investigate its impedance and radiation characteristics. Good agreement between the simulated and measured data is achieved. The obtained results show that the proposed antenna is convenient for UWB applications.

Introduction
Recently, the rapid growth in the field of wireless communications and electronics has been extended. Ultra wide band (UWB) antennas play critical role in the UWB communication systems. The UWB antennas are designed to cover range 3.1-10.6 GHz assigned by FCC (Federal Communication Commission) [1]. The UWB technology has several advantages such as high data rate, low power consumption, simple hardware configuration in practical applications and good resistance for multipath [2], [3]. The UWB antenna is considered as one of the important components to realize the UWB communication systems. Therefore, UWB antenna has to achieve several requirements such as high and stable gain, omnidirectional radiation pattern, wide impedance matching through all frequency bands, low cost and compact size [4], [5].
Presently, printed UWB monopole antennas are used due to their merits such as small size, easy of fabrication, low cost and their compatibility with RF components [6][7][8][9][10]. However, there are many narrowband communication systems that interfere with the UWB systems such as WiMAX (3.3-3.7 GHz), IEEE 802.11/b/g (5.15 GHz to 5.825 GHz) WLAN band and X-band operating at 7.725 GHz to 8.275 GHz for ITU applications. In order to reduce the potential interferences from these undesired narrowband signals, UWB antennas with filtering behavior (notched characteristics) are designed. There is a number of antennas of this type presented in literature working with different elements assuring the notched characteristic -stop-bands. Some of them are: Paper [11] presents the antenna using the stepped impedance resonator and forkshaped stubs. The antenna presented in [12] applies an annular strip etched above the radiating element and two slots, one C-shaped and one arc-shaped embedded in the radiating patch. Rather complex resonator enlarging the area taken by the antenna is used in [13]. Microstrip twoport filtering structure composed of a couple of modified capacitance loaded loop resonators is used in [14]. Each antenna designed in [15] comprises a half-circle shaped patch with an open rectangular slot and a half-circle shaped ground plane.
In this paper, a compact microstrip fed monopole UWB antenna with three stop bands and overall size of 36 × 32 mm 2 is presented. The notched frequency bands are achieved by employing open loop resonator etched in the patch and defected microstrip structure (DMS) stopband filter inserted in the feeding line. First of all, a reference antenna is designed, which exhibits radiating characteristics in the frequency band 2.7-13.4 GHz. The first and the third notches are achieved by using DMS at frequency bands (3.15-4 GHz and 7.9-8.6 GHz). The second notch is achieved by using open loop slot at frequency band (5.7-6.3 GHz). The proposed antenna has been designed, simulated, fabricated and measured. The designed antenna performance has been validated using the electromagnetic full wave simulations. The commercial software HFSS was employed in the full wave simulations.

UWB Antenna Configuration
The UWB antenna design is comprised of the steps: First of all, conventional patch antenna with partial ground plane is designed (case I) to achieve UWB behavior from 3.1 GHz to 10.6 GHz as shown in Fig. 1(a). The VSWR of this antenna plotted in Fig. 2 shows that the antenna operates from 3.5 GHz to 6.5 GHz with VSWR lower than 2. Matching of the UWB antenna can be improved by using a tapered transition in the radiator (case II) as illustrated in Fig. 1(b). The VSWR of the designed antenna illustrates that the antenna works from 3.1 GHz to 12 GHz (UWB applications). Finally to achieve good matching properties, simple rectangular slot is added in the ground plane (case III) as shown in Fig. 1(c). The case III is therefore used as our reference UWB antenna. The wide band operation of the UWB antenna has been achieved by optimizing the dimensions of the radiating patch and the partial ground plane. The UWB antenna is designed on RO4003 substrate with relative permittivity  r = 3.38, loss tangent equal to 0.0027 and thickness h = 0.813 mm. The monopole antenna is fed by 50 Ω microstrip line.

DMS Band-Stop Filter Design
DMS plays an important role in designing filters due to several advantages such as size and complexity reduction. It also reduces the radiation loss which enhances the stop band attenuation. The 2-D layout of the DMS filter is shown in Fig. 3. It is considered as a simple slot inserted in the microstrip line. This slot changes the effective capacitance and inductance of the microstrip line which leads to band stop behavior. The dimensions of the DMS filter were optimized to achieve the desired resonant frequency. The simulated S-parameters (return loss and insertion loss) of the DMS filter are plotted in Fig. 4. It is clear that the filter has two rejected frequency bands. The first band is 3.15 to 4 GHz and the second band is 7.9-8.6 GHz.

Open Loop Resonant Slot
The simulated current distribution of the reference antenna at 6 GHz is plotted in Fig. 5 (a). It can be noticed that the surface current is concentrated near the input of the patch and decreases away from the center of the patch. Therefore    optimized to achieve the band notched characteristics. The simulated current distribution at 6 GHz for monopole antenna with the loop resonator is shown in Fig. 5(b) and it is obvious that the surface current is concentrated around the slot, which means that the antenna does not radiate at this frequency band.

Proposed UWB Antenna Design
The 2-D layout of the proposed UWB monopole antenna is illustrated in Fig. 6. The detailed dimensions are stated in Tab Fig. 8. It is obvious from Fig. 8 that the current is concentrated around the DMS filter and practically no current passes through the patch. This confirms the fact that the DMS acts as dual band-stop filter and the antenna does not radiate at these two frequency bands.

Experimental Results
The proposed UWB antenna has been simulated, fabricated and then tested using Agilent N9918A vector network analyzer (VNA). The antenna was fabricated on RO4003 substrate with relative dielectric constant of 3.38, thickness of 0.813 mm and dielectric loss tangent equal to 0.0027. The photographs of the fabricated antenna are shown in Fig. 9. The VSWR of the antenna was measured and compared with the simulated one as demonstrated in Fig. 10. As seen from the plot, there is a good agreement between basic shapes of simulated and measured VSWR. The measured rejection level in the three notched band is not as good as predicted by simulations. This is with the highest probability caused by fabrication tolerances and by the used SMA connector. The results show that the proposed antenna is working as UWB antenna from 2.7 GHz to 13.45 GHz. However, there are three notches at 3.15-4 GHz, 5.7-6.3 GHz and 7.9-8.6 GHz with VSWR which is higher than 2.
A comparison between simulated and measured realized gain of the proposed triple band notched UWB monopole antenna is illustrated in Fig. 11(a). The average measured realized gain of the UWB antenna is nearly constant around 3 dBi, except the three notched frequency bands with values equal -2 dBi, -1.5 dBi and -1.1 dBi respectively. The radiation efficiency of UWB antenna is illustrated in Fig. 11(b). It is seen from Fig. 11(b) that the average efficiency of the UWB antenna equals around 85 %. However the efficiency of UWB antenna is reduced to 30 %, 20 % and 30 % at the three notched frequency bands.
The radiation patterns of the proposed antenna in the x-z plane, y-z plane and x-y plane (see the coordinate system in Fig. 6(a)) were measured inside anechoic chamber at 3.1 GHz, 5.3 GHz, and 9.1 GHz. The normalized simulated and measured radiation patterns in x-z, y-z and x-y planes of the proposed antenna are shown in Fig. 12 and , and x-axis in (c). It follows from Fig. 12 that the UWB monopole antenna has nearly omnidirectional patterns in y-z plane and almost bi-directional patterns in x-z and x-y planes at the three different frequencies, which implies that the proposed antenna has a large and uniform coverage confirming the fact that the proposed antenna is convenient for UWB application.
Comparison between our proposed antenna and other in literature presented designs in terms of measured values is illustrated in Tab. 2. Table 2 presents notch frequencies, realized gain at these notches. It can be concluded from this comparison that the proposed antenna has compact size and higher bandwidth. The gain at centers of notched band is comparable, or somewhat higher.

Conclusion
The design of the compact size monopole UWB antenna with triple band notches has been presented. A tapered transition between the rectangular patch and the feeding line has been used to achieve good impedance matching from 2.7 GHz to 13.4 GHz. The defected microstrip structure and the open loop slot etched in the radiation patch have been used to produce triple band notches. The three band notches are 3.15-4 GHz, 5.7-6.3 GHz and 7.9-8.6 GHz for IEEE 502.16 WiMAX band, WLAN band, and ITU respectively. Moreover, good agreement has been achieved between the simulated and measured results. This confirms that the proposed antenna is suitable for UWB applications. Jan MACHAC is a professor at the Department of Electromagnetic Field, Faculty of Electrical Engineering, Czech Technical University in Prague, Czech Republic. His main scientific interests are: investigation of planar passive elements and subsystems of microwave technology, planar antennas, planar microwave filters, propagation of electromagnetic waves in periodic structures, and metamaterials. Prof. Machac is an author or co-author of more than 250 publications in scientific journals and scientific interna-tional and national conferences. He is a Senior Member of IEEE Microwave Theory and Technique Society, member of the IEEE MTT-S Int. Microwave Symposium TPRC, since 2008, member of the TPC of the European Microwave Conference during 1995-1997, and since 2013, reviewer of: IEEE Transactions on Microwave Theory and Techniques, IEEE Microwave and Wireless Components Letters, Electronics Letters, and IET Microwave Antennas and Propagation.


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FM-UWB: Towards a Robust, Low-Power Radio for Body Area Networks

The Frequency Modulated Ultra-Wideband (FM-UWB) is known as a low-power, low-complexity modulation scheme targeting low to moderate data rates in applications such as wireless body area networks. In this paper, a thorough review of all FM-UWB receivers and transmitters reported in literature is presented. The emphasis is on trends in power reduction that exhibit an improvement by a factor 20 over the past eight years, showing the high potential of FM-UWB. The main architectural and circuit techniques that have led to this improvement are highlighted. Seldom explored potential of using higher data rates and more complex modulations is demonstrated as a way to increase energy efficiency of FM-UWB. Multi-user communication over a single Radio Frequency (RF) channel is explored in more depth and multi-channel transmission is proposed as an extension of standard FM-UWB. The two techniques provide means of decreasing network latency, improving performance, and allow the FM-UWB to accommodate the increasing number of sensor nodes in the emerging applications such as High-Density Wireless Sensor Networks.

Introduction
The recent advances in circuit design, combined with technology scaling, enabled highly miniaturized, ultra-low power radios that have been the key driving force behind the development of Wireless Body Area Networks (WBANs). These highly localized wireless networks find use in various medical and consumer applications [1]. In order to allow for the unobtrusive use, the size and the battery life of WBAN nodes are critical issues. The need for frequent replacement is undesirable and in the case of implanted nodes unacceptable, which sets the limit to the power consumption of the devices used in sensor nodes, in particular the radios, as they are often identified as the dominant source of power consumption. With the increasing popularity of WBAN, the number of applications continues to grow, as well as the number of connected devices. Furthermore, some applications require that a large number of devices coexist in a small area. One example is the WiseSkin concept (Figure 1), where sensor nodes embedded in a kind of artificial skin are placed on top of a prosthetic arm. The nodes communicate wirelessly between each other and transmit the information from sensors to the central processing unit that drives the actuators and provides a sense of touch to the patient [2]. The WiseSkin application is one example of a High-Density Wireless Sensor Network (HD-WSN). To deal with a large number of nodes operating in a small area, new protocols are needed, and a communication system that could support Frequency Division Multiple Access (FDMA) and multi-user communication is waveforms are used to modulate the RF carrier and create the wideband signal. In this way, a flat spectrum with a steep spectral roll-off is obtained. The Physical (PHY) layer specifications in the IEEE 802.15.6 standard only define a 2-FSK sub-carrier modulation at a single mandatory RF channel and a single sub-carrier channel. As we intend to show in this paper, standard FM-UWB can easily be extended to higher data-rates and higher order FSK modulations without a significant increase in complexity and power consumption, which would result in a higher efficiency of the entire system. Since the IEEE 802.15.6 was not intended for a large number of devices, the potential of the FM-UWB was not fully exploited. The sub-carrier FDMA (SC-FDMA), which was demonstrated in [5][6][7], allows multiple nodes to communicate at the same time, which can bring a lot of benefits as the number of nodes in a network increases. Here, capabilities and limitations of multi-user communication are discussed, and the case with up to four users at the same RF channel is demonstrated. The concepts from [5] are further extended to provide a simple approximation for Bit Error Rate (BER) estimation. Furthermore, multi-channel transmission is proposed via a simple modification of the standard FM-UWB, which could allow simultaneous transmission to multiple nodes, as yet another technique that might find use in HD-WSNs. The paper is organized as follows. The review and analysis of existing FM-UWB transmitters and receivers, pointing out the power reduction trends, are given in Section 2. In the following sections, the potential of FM-UWB beyond a simple 2-FSK sub-carrier modulation is demonstrated using one of the existing receivers. Single carrier communication is described in Section 3 and the SC-FDMA approach is explored in Section 4. The new multi-channel transmission is explained in Section 5, while Section 6 provides concluding remarks.

FM-UWB Receivers
Different FM-UWB receiver implementations can be found in the literature. A simplified block diagram of each of the proposed architectures is shown in Figure 3. The wide-band FM demodulator based on a delay-line (DL) demodulator (Figure 3a) was initially proposed in [8]. Assuming that the delay is relatively small, the demodulated signal can be represented as [8] where A is the amplitude of the demodulator input signal, ω c is the carrier frequency and φ(t) is the useful frequency-modulated signal. The delay τ must be chosen to be an odd multiple of the carrier frequency in order to cancel out the offset in the demodulated signal [8]. The choice of N is a trade-off between the conversion gain and the bandwidth of the demodulator. Lower value of N leads to lower conversion gain, but also increases the useful frequency range. In practice, it will be very difficult to achieve high precision of the delay (due process variation), and so a small offset in the demodulated signal will always be present. However, since the transmitted signal is at least 500 MHz wide, this small offset should not have a major impact on the receiver performance. The first fully integrated FM-UWB receiver based on a DL demodulator was described in [6]. It achieves a sensitivity of −88 dBm while consuming 9.4 mW. The demodulator itself consumes around 5.8 mW, while the Low Noise Amplifier (LNA) consumes 3.6 mW.  An LNA that provides high gain across a large bandwidth inevitably requires more power compared to a narrowband LNA. In order to reduce the power consumption, a narrow-band regenerative receiver was proposed in [9]. This approach allowed to preserve high gain and relatively good noise figure, while minimizing the power consumption. The high-Q band-pass filter behaves as a frequency discriminator that converts the input FM signal into an AM signal, which is then converted to Intermediate Frequency (IF) using an envelope detector. Due to the high-Q factor of the filter that results in a very nonlinear Frequency Modulation to Amplitude Modulation (FM-AM) conversion characteristic, the demodulated signal will be a train of pulses whose frequency corresponds to the sub-carrier frequency ( Figure 4). The receiver from [9] consumes 2.2 mW while achieving -84 dBm sensitivity. A later implementation presented in [10] introduced several improvements at the circuit level (most notably current reuse among several blocks), which resulted in power consumption of only 560 µW and a slight reduction of sensitivity. Although the regenerative receiver achieved significant power savings, there are some downsides to this architecture. Narrow-band interferer rejection mostly relies on the high-Q input filtering. If the interferer falls inside the pass-band, it could easily saturate the stages following the LNA and prevent reception. The second downside comes from the nonlinear FM-AM conversion. If several FM-UWB signals were to occupy the same RF band, the weaker signals would be attenuated in the nonlinear conversion process, which would prevent correct demodulation. This is known as the capture effect [11] and limits the regenerative receiver to cases where only one FM-UWB signal is transmitted in a given RF band. In an attempt to improve the linearity of the regenerative demodulator, a modified architecture was proposed in [12]. Instead of using just one band-pass filter, a second branch was added (Figure 3d), resulting in a Dual Band-Pass Filter (DBPF) demodulator, otherwise known as a balanced frequency discriminator. The two filters are tuned to the two extreme frequencies in the FM-UWB signal spectrum, and are followed by the two envelope detectors that are removing the RF carrier from the signal. The difference of the two IF signals finally gives the demodulated sub-carrier. The equivalent linearized characteristic is shown in Figure 4. Compared to the original regenerative receiver, the Q-factor of the two filters can be lowered, which allows some power savings per filter, but two filters are now needed, as well as a wide-band LNA, which is again the dominant source of power consumption. The two architectures perfectly illustrate the trade-off between linearity and power consumption in FM-UWB receivers. The implementation from [12] consumed 3.8 mW, and achieved −78 dBm of sensitivity. The same architecture was reused in [13] for demodulation of a Chirp-UWB signal, where symbol-level duty-cycling of the receiver was used to bring down the average power consumption to 0.6 mW. The DBPF receiver exhibits better narrow-band interferer rejection compared to a standard regenerative receiver and should perform better in scenarios with multiple FM-UWB users, although such capability was not confirmed by measurements.
In all of the mentioned examples, the most power hungry blocks are the ones that operate at high frequencies. Typically, this is the LNA, but also the demodulator in the case of the DL architecture. Assuming that the oscillator can be made sufficiently low power, the input signal could be downconverted to IF first and then amplified and processed, allowing for achieving the same gain at a lower cost in terms of power. This approach was first proposed in [14] for a narrow-band OOK receiver. Similar architecture was applied to the case of FM-UWB in [7], it uses an active mixer-first topology to downconvert the signal and then amplifies it using IF amplifiers. In order to achieve low power consumption, a ring oscillator is used to generate the Local Oscillator (LO) signal. Increased phase noise and frequency drift due to Process-Voltage-Temperature (PVT) variations are not a big concern owing to the large FM-UWB signal bandwidth. The demodulator used in this receiver is again a DL demodulator. Since in this case it operates at baseband instead of RF, quadrature signals are needed for correct demodulation. Compared to the RF-DL demodulator, the delay τ no longer depends on the carrier frequency, and does not need to be set precisely. Furthermore, by moving the demodulator from RF to baseband, its power consumption can be reduced by more than two orders of magnitude (from 5.8 mW to 26 µW). The obvious downside of any mixer-first receiver is the increased noise figure that results in lower sensitivity. The receiver from [7] achieved -70 dBm of sensitivity while consuming 420 µW and is so far the lowest power FM-UWB receiver. Even though there is a penalty when it comes to sensitivity, this receiver can still distinguish multiple FM-UWB signals, and provide SC-FDMA, which is a useful property in dense WBANs. In fact, the aforementioned receiver was designed specifically for communication between the nodes on a prosthetic limb [2] and trades sensitivity for power consumption and FDMA capability. In cases where higher path losses are expected and the number of nodes is smaller, such as in [15], a different receiver would be more optimal.
A performance summary of different FM-UWB receivers is given in Table 1. Each of the proposed architectures has its own advantages and disadvantages. Receiver from [6] generally has the best performance but is also the most power hungry. Regenerative receiver can provide a very low power consumption while maintaining good sensitivity, but at the cost of linearity. Finally, the DL based receiver from [7] sacrifices sensitivity but achieves the lowest power and preserves FM-AM linearity.

FM-UWB Transmitters
Unlike the FM-UWB receivers, the architecture of the FM-UWB transmitters has remained unchanged over the past several years. Considering its simplicity ( Figure 2), it is clear that there is not a lot of potential for improvement on the architectural level. In fact, the reduction of power on the transmitter side is mainly a result of improvements on the circuit level. Every FM-UWB transmitter consists of three blocks, the sub-carrier generator, the Voltage Controlled Oscillator (VCO) (sometimes as a part of a PLL or a Frequency Locked Loop (FLL)) and a power amplifier (PA).
The sub-carrier generator generates the triangular waveform that is used to drive the VCO. As the sub-carrier frequencies are rather low (typically 1-2 MHz), this block does not contribute significantly to the overall transmitter consumption. One way to implement it is a Direct Digital Synthesis (DDS) as described in [20]. The advantages of digital implementation are the simple and precise frequency control without the need for calibration. The drawback of the fully digital approach becomes apparent at higher data rates, where higher sub-carrier frequencies are needed. In [21], 51 MHz sub-carrier frequency is used. Since roughly 20 points per period are needed to generate a reliable sub-carrier waveform, a DDS would need to operate at a clock speed of more than 1 GHz, which would be difficult to implement and would consume a significant amount of power. Instead, a relaxation oscillator is used within a PLL, as a more optimal solution. Another interesting approach that leads to very low power consumption is a free-running relaxation oscillator, which is periodically calibrated using an FLL [22]. Digital frequency control is provided through a capacitor bank; however, this approach is usually not precise enough if multiple sub-carrier channels are to be used.
The two parts of the FM-UWB transmitter that essentially determine its power consumption are the VCO and the PA. In the case where transmitted power is 10 dBm or more, the transmitter efficiency was dominated by the PA, however at lower output powers, such as, at −10 dBm, the contribution of the VCO becomes quite significant. In some of the earlier implementations, the RF carrier was synthesized using an LC VCO within a PLL [21,23]. To decrease power, the frequency synthesizer is duty cycled, making the frequency dividers active for only 10% of the time. Although this allowed some savings, the power consumption was still on the order of 10 mW. A significant improvement was made when the LC oscillator was replaced with a ring oscillator [22,24]. This was possible owing to the loose phase noise constraints of the FM-UWB modulation. Additionally, instead of the quasi-continuous PLL, an FLL calibration loop was used [22]. Since the FM-UWB spectrum is very wide, the center frequency can deviate slightly without a major impact on performance and it does not need to be monitored continuously. Therefore, once calibrated, the VCO can operate in a free running manner until temperature or some other external factor causes a significant frequency shift. Since these external processes are usually slow, calibration only needs to be done once in a few hours or days, which makes the average power consumption of such an FLL practically negligible. The described approach led to the first sub-milliwatt FM-UWB transmitter [22]. The next step in reducing the VCO consumption was reducing the frequency of oscillation. Since an N-stage ring oscillator produces N equally spaced phases, these phases can be combined to produce a frequency that is N times higher [25]. It is then possible to use a ring oscillator that works at a frequency that is N times lower than the carrier center frequency. The approach was demonstrated in [25] and used for the FM-UWB transmitter in [10] to reduce the power consumption down to 0.63 mW.
Even though the VCO cannot be neglected, the PA remains the most power-hungry block in the system. The key to further reducing the power consumption of an FM-UWB transmitter is an efficient power amplifier; however, the design of an integrated PA for such a low power and wide band poses a number of challenges. In standard narrow-band applications targeting relatively high output power, the most efficient approach is to use a switching PA such as class D or E. However, due to the high driving requirements, lack of voltage gain and difficulties in implementing a wideband matching network, switching PAs leads to sub-optimal solution. The linear power amplifiers, classes A, AB, B and C, generally do not achieve as high efficiency, but the driving requirement is also lower. Moving from class A to class C operation, the maximum attainable efficiency increases, but the power gain decreases and larger driving signal is necessary, thus shifting the burden from the PA to the driver. A good compromise is the class AB that attains decent efficiency and does not need a rail-to-rail input signal. In fact, all of the transmitters reported in [10,22,24], which achieve the lowest power consumption so far, use a complementary class AB power amplifier. Finally, by applying the current reuse technique, as demonstrated in [10], where the PA and the driver share the same current, efficiency can be further improved. This led to a record breaking low power FM-UWB transmitter as can be seen in Table 2.

Summary
The above sections described the most important power reduction techniques applied in the FM-UWB transceivers. These techniques, combined with technology scaling, led to sub-milliwatt power levels in today's implementations. The evolution of power consumption over the past eight years is illustrated in Figure 5 for both transmitters and receivers.

6]
R e g e n .
[ 9 ] R e g e n .
[  Although there has been a decrease by a factor of 20, the narrow-band receivers still have the edge, at least when it comes to power consumption. Proposed wake-up receivers found in literature consume from 100 µW [26] all the way down to 100 nW [27]. FM-UWB can hardly compete with such low levels, a simple consequence of the fact that wide-band circuits require more power to achieve the same performance in terms of gain and noise figure. On the other hand, the FM-UWB brings higher resilience to interferers without off-chip components such as SAW filters, better performance in frequency selective channels and more potential for miniaturization. All of these are very favorable capabilities that could assure a place for FM-UWB in short-range applications such as Body Area Networks.

Single-User FM-UWB Communication
Although different FM-UWB receiver architectures have been explored, most of them (with the exception of [13]) focused on standard 2-FSK sub-carrier modulation, targeting data rates below 100 kb/s. Transmitters proposing higher data rates (1 Mb/s) and more complex M-FSK modulations have been implemented, but the full communication has never been demonstrated with one of the existing receivers. Here, the receiver from [7,19] was used to demonstrate the feasibility of communication at higher data rates and using M-FSK without any modification to the wideband FM demodulator. In fact, any of the architectures shown in Figure 3 could be used to accommodate different sub-carrier modulations. Minor modifications would be needed only in the baseband circuitry. As the power consumption of the baseband part is typically negligible compared to the RF part, increasing communication speed up to a certain point would only result in a small increase of the overall consumption. It is therefore expected that higher speed leads to a higher energy efficiency of the entire system.
The transmitted signal was generated using two signal generators. A 12 GS/s, 12-bit arbitrary waveform generator M8190A provides the quadrature baseband FM-UWB signal. This generator allows generation of any signal up to 4 GHz of baseband bandwidth and was used to create different transmission scenarios (including the multi-user communication). The quadrature signal is then upconverted to 4 GHz using the PSG signal generator. The whole test setup is shown in Figure 6. Signal power at the receiver is controlled using a variable attenuator. The output data from the FM-UWB receiver is digitized and then processed off-line to obtain the Bit Error Rate (BER).
The BER curves for different data rates are shown in Figure 7. In all cases, orthogonal frequencies are used with a modulation index of 0.5. As expected, the sensitivity of the receiver decreases due to increased bandwidth of the sub-carrier signal. Nevertheless, if the distance between nodes is small enough and the channel is sufficiently good, higher communication speeds can be used to decrease latency in the network. In this case, the limitation to data rate comes from the filter following the FM demodulator, which was designed for sub-carrier frequencies from 1-2.5 MHz. Figure 8 shows the test setup that demonstrates over the air communication. The distance between the two antennas is approximately 2 m, roughly corresponding to the distances that are targeted for short range communications in a WBAN (although still simplistic compared to a real use-case scenario). The signal is transmitted at −15 dBm, somewhat lower than the allowed power in the UWB frequency range. Oscilloscope screen shows the spectrum of the demodulated signal (using the FFT). Two cases are presented. In the first, there is a line of sight propagation between the transmit and the receive antenna, while, in the second, an obstacle is placed between the two antennas. The degradation of the link quality can be observed on the oscilloscope screen once the obstacle is in place; however, it is still possible to establish communication. In the first case, BER is below 10 −5 , while, in the second, it increases to 3.1 × 10 −4 . In both cases, 100 kb/s 2-FSK modulation is used. The two examples are shown; however, the BER will vary as the location of the obstacle changes, as well as the surroundings in general.
The example in Figure 9 shows performance, in terms of Symbol Error Rate (SER), for different M-FSK modulations. With the implemented receiver baseband bandwidth, up to 8-FSK signal can be received at 100 ksym/s. In general, M-FSK offers better sensitivity for the same data rate; however, it also requires a more complex M-FSK demodulator. The selection of the most efficient modulation then depends on the targeted application.
The spectrum at the output of the wideband demodulator is shown in Figure 10 for some of the used modulations. If only a single transmitter is using the given RF band, there is no reason not to use the entire available sub-carrier band; however, if multiple nodes need to transmit, the bandwidth can be reduced to provide enough room for additional channels. This potential for configurability is one of the strong points of FM-UWB.

Multi-User FM-UWB Communication
Frequency Division Multiple Access is a concept that has been exploited for a long time. Compared to wireless communication on a single frequency channel, which requires some form of Time Division Multiple Access (TDMA), it enables us to speed up data transfer from multiple nodes in a network and therefore decrease latency and improve response time to environment changes. The FDMA not only provides multiple access for devices in a WBAN but also offers the potential to separate WBAN traffic by service type and priority, which facilitates tailoring to the needs of the application. For example, a real-time application can operate on a separate channel, while bursty low rate sensor data is aggregated on another channel.
When it comes to FM-UWB, there are two ways to implement FDMA. First, the straightforward way is to use different UWB channels at RF. Although it may seem simple, it requires a fairly large bandwidth in the receiver front-end and may lead to significantly larger power consumption. Nearly all of the receivers reported in literature support only a single RF UWB channel, thus showing the impracticality of the aforementioned approach. The second way is to use multiple sub-carrier frequencies (SC-FDMA), while only transmitting on a single RF channel. The main advantage of SC-FDMA is that the modifications are primarily needed in the low frequency part of the receiver. As the power overhead remains relatively low, this approach is more appealing for applications such as body area networks and will be discussed in this section.
The SC-FDMA was proposed in [8] and further studied in [5]. The main principle is shown in Figure 11, where multiple transmitters are using the same RF band, but can be distinguished due to the fact that they use different sub-carrier frequencies. In order to perform successful demodulation, the wideband FM demodulator must provide sufficient linearity in order to avoid distortion and FM capture effect. In that regard, the DL demodulator is the best candidate, and, so far, the only one that has demonstrated such capability [6,7].  Figure 11. Multiple transmitters sharing the same RF band.
In order to allow simultaneous demodulation, the baseband FSK demodulator must be replicated for each sub-channel. A fully analog approach was described in [8,28], and digital sub-carrier processing is proposed here. Firstly, the dynamic power consumption of digital circuits decreases with technology scaling and is likely to provide a lower power solution in the future. Furthermore, Analog to Digital Converters (ADCs) are now capable of achieving very low power operation, such as the 10 MS/s, 8-bit ADC implemented in [29] that consumes only 26 µW. Secondly, the digital approach offers easier configurability, meaning that the same receiver could be used to either receive data from multiple users at a lower speed, or to increase speed and efficiency for single user communication.
A block diagram of an FSK demodulator based on correlators for processing a single sub-channel is shown in Figure 12. The proposed demodulator only illustrates the principle, and different simplifications can be used to optimize power consumption. For example, instead of using a sine wave, a square wave sgn(sin(ω sc )t) could be used, which would allow for removing multipliers and reducing complexity. The channel filter, which is the most demanding block here, only needs to be used if significantly stronger adjacent sub-channels are present; otherwise, it can be switched off to save power.
Effectively, replicated sub-channel demodulators constitute a correlator bank. In cases where only one transmitter is used, this correlator bank could be exploited to demodulate the M-FSK signal, allowing higher speed in a single sub-channel as mentioned earlier. Different variations could also be supported, trading the number of channels with the data rate per sub-channel. The given example highlights the potential and versatility of the digital approach. The same FM-UWB receiver can be used to adapt to different conditions in the network, maximizing system efficiency and providing more room for improvement at the protocol level. To measure the performance in the presence of multiple FM-UWB signals the same setup from Figure 6 was used. The measured BER performance is presented in Figure 13a for a number of users varying from 1 to 4. The data rate on each sub-channel is 100 kb/s resulting in 200 kHz bandwidth, with 100 kHz separation between the channels. Orthogonal 2-FSK modulation without pulse shaping is used in all cases. The output spectrum is shown in Figure 13b.
The multi-user interference and noise performance of the FM-UWB were studied in [5,8] for the case of a delay-line demodulator. However, the results from [5] only addressed limits due to inter-user interference and did not take noise into account. Inter-user interference becomes a dominant factor only at large variations in power between the sub-channels, and it is of interest to assess the BER performance and sensitivity degradation in other cases. Following the same reasoning used by Gerrits in [5,8], assuming that the delay is sufficiently small and the noise autocorrelation function R n (τ) = 0 the demodulator output voltage, in the case of two users, becomes where k is the constant of the demodulator that has a dimension V −1 . Since this constant does not affect the output Signal to Noise Ratio (SNR), it can be dropped from further consideration. The factors V 2 s1 and V 2 s2 are the two demodulated sub-channels. The useful signal power on channel i is then proportional to where S i is the input signal power on channel i. The other terms in Equation (3) correspond to cross-products of signal and noise (V si V n ) and the two input signals (V si V sj ), and noise squared (V 2 n ) [8]. We can then write: where N is the input noise power. The total output noise power, as a function of input signal power and noise power is then given by Finally, the SNR at the demodulator output is given by where factor B RF /B sub is the processing gain coming from the spread spectrum FM-UWB technique [8].
Let us now assume that the two sub-carrier channels have equal power S 1 = S 2 . The output SNR becomes This expression can be compared to the SNR in the case of a single user FM-UWB: It should be noted that the output SNR is a non-linear function of the input SNR, which is a consequence of the square characteristic of the demodulator. Although the derived SNR expressions are a rather coarse approximation, they provide some intuitive insight into the performance limitations. First, the achievable BER is now limited by the inter-user interference (4S 1 S 2 ), which fundamentally limits the number of users or the maximum difference in powers between the two users. This factor, however, remains relatively small compared to noise at low SNR values. What can be noted in this region is that the "noise floor" has now increased due to cross-modulation of several input signals with noise (8S 1 N). In case a small number of channels is used, and the power difference between channels is small, this factor will dominantly determine the sensitivity degradation. The same derivation can be applied to the cases with three and four users: The probability of error can then be calculated using the standard formula for the orthogonal 2-FSK modulation: where R is the data rate. The presented calculation can be used to estimate the sensitivity loss due to the presence of multiple users, sensitivity defined as BER = 10 −3 . The calculation is compared to measurements in Figure 14. A slight deviation from calculation can be noticed in the case with four users. The likely cause is the non-linearity of the baseband circuits. The third order intermodulation product (IM3) from channels 3 and 4 falls directly on top of channel 2 (used for measuring the BER), which degrades the equivalent SNR:

Limitations to Multi-User Communication
The first fundamental limitation comes from the inter-user interference, which limits the minimum achievable BER. In the high SNR region, the noise can be neglected and Equation (10) can be rewritten as [5] Assuming orthogonal FSK, 500 MHz RF bandwidth and 100 kHz data rate, a 21 dB stronger RF signal using sub-channel 2 will limit the BER on channel to 10 −3 . In other words, the desired BER imposes the maximum difference in power of different channels that can be tolerated. In the same way, inter-user interference will limit the number of equal power channels that can be used. If multi-user performance is to be improved, the only remaining degree of freedom is to increase the processing gain. It should be noted that, due to the quadratic characteristic of the demodulator, 21 dB difference of power at RF corresponds to 42 dB difference in the power of the sub-carriers. This shows that it is actually more likely that the difference in channel power will be limited by the dynamic range of the receiver than the inter-user interference. Typically, there is a trade-off between power and dynamic range in amplifiers, so the capability to handle larger sub-channel power difference will come at the price of an increased power consumption. One way to avoid this is to regulate transmit power in order to avoid the need for high dynamic range and hence higher power (as it is done in CDMA).
The second limitation comes from distortion. Any frequency selectivity present in the channel due to multipath propagation or non-linear demodulator characteristic will cause AM to appear on top of the FM-UWB signal. These amplitude variations transform into harmonic distortion in the process of demodulation and pollute the spectrum. If the minimum sub-carrier frequency is f sub , then the spectrum at 2 f sub and above will contain significant components due to unwanted AM as illustrated in Figure 15. Placing a channel directly on top of these frequencies would result in significant BER degradation, and, for this reason, wouldn't be practical. The sub-carrier band is therefore limited to one octave. If a larger band is required, the solution would be to move to higher sub-carrier frequencies.
In the case shown here, frequencies from 1.1 MHz to 2.2 MHz are allocated to sub-carrier channels.
The third limitation comes from the Adjacent Channel Leakage Ratio (ACLR). The spectrum of the FSK modulated sub-carrier spreads beyond the sub-channel bandwidth. If one sub-carrier is significantly stronger than others, spectral leakage might prevent correct detection on adjacent channels. To prevent this, channels can be separated, but then the total number of available sub-channels decreases. Otherwise, pulse shaping can be applied on the transmitter side to reduce the ACLR, but at the cost of increased complexity. In the case presented here, pulse shaping is not used, and 100 kHz channel separation was sufficient, but, in general, different parameters of the FM-UWB system can be set to conform to the specific needs of the application and provide the optimal solution.

Multi-Channel Transmission Using FM-UWB
If a small modification is introduced, the FM-UWB can be used to transmit on multiple sub-carrier channels simultaneously. Instead of driving the VCO using a single sub-carrier signal, a sum of multiple sub-carrier signals could be used ( Figure 16). In this way, a single transmitter can broadcast different messages to different receivers at the same time-a capability that could be useful if, for example, multiple actuators needed to be driven synchronously. Regarding power consumption, the proposed technique would only result in a minor increase. Since the most power-hungry blocks are the VCO and the power amplifier, increasing the number of baseband sub-carrier generators would not cause a significant overhead. As an example in [10], the VCO and the PA consume 92% of the overall power, while the SC generator consumes around 2%. Using four SC generators would thus result in an overhead of less than 10% in terms of power consumption, assuming minor modifications in other baseband blocks. In many ways, the proposed scheme is similar to having multiple parallel transmitters; however, there are some differences.   The FM-UWB spectrum is relatively flat and has a steep spectral roll-off that is a consequence of the triangular sub-carrier signal. Since several sub-carrier signals are summed here, the output spectrum will no longer be flat. In fact, the exact shape of the spectrum will depend on the number of sub-carriers and their initial phases. Furthermore, the sum of sub-carriers must be scaled in order to maintain the RF bandwidth. If N sub-carrier signals are combined, the sum must be divided by N. The output spectrum resulting from the addition of three sub-carrier channels is shown and compared to a standard FM-UWB spectrum in Figure 17. The scaling of sub-carriers is essentially equivalent to reducing the spreading factor of each sub-carrier. As a consequence, the power of each demodulated sub-carrier will be lower compared to the single sub-carrier case, which will result in worse sensitivity as the number of sub-channels increases. A degree of freedom that can be exploited here is using different scaling factors for different sub-channels. This is equivalent to allocating different power to sub-channels. If the information is transmitted to nodes at different distances, more power can be allocated to channels intended to more distant nodes in order to improve the link quality. One important difference between SC-FDMA with multiple transmitters and a single transmitter is that, in the latter, sub-channels are perfectly synchronized. For multiple transmitters, even if the orthogonal frequencies are used for different sub-channels, the orthogonality is preserved only if symbols are perfectly synchronized. Since it is practically impossible to synchronize multiple transmitters, sub-channels must be separated and a channel filter is required. In the case of a single transmitter, the sub-channels remain orthogonal, so there is no need for separation, which allows for increasing the number of available channels. As long as the orthogonality is maintained, this separation will not influence the BER. In that regard, the proposed FDMA scheme is similar to the Orthogonal Frequency Division Multiplexing (OFDM) combined with the FM-UWB spread spectrum technique. The spectrum of the demodulated signal with and without separation is shown in Figure 18. The BER curves for different number of sub-channels are shown in Figure 19. Compared to the case with multiple transmitters, a significant sensitivity loss can be observed. This is a consequence of scaling since the SNR of a single channel is proportional to 1/N 2 , where N is the number of sub-channels. Nevertheless, for short range applications, where distance between nodes does not exceed several meters, such as BAN, the proposed scheme could still be used and could be of particular interest when a large number of nodes are present.  Figure 19. BER for a single transmitter broadcasting on multiple sub-channels.

Conclusions
The FM-UWB has been recognized as a technique that finds use in applications such as WBANs due its very low power consumption, potential for miniaturization and low complexity. Although FM-UWB receivers can never achieve as low power as the narrow-band wake-up receivers, they compensate with small size, robustness in multi-path channels and resilience against interferers. The FM-UWBs became part of the IEEE 802.15.6 standard; however, the standard specifications limit the use of FM-UWB to the very basic case of the 2-FSK sub-carrier modulation. If a small increase in the complexity of the receiver can be afforded, FM-UWB can achieve higher data rates, either by simply increasing the speed and the sub-carrier frequency or by using higher order modulations such as 4-FSK and 8-FSK. The FM-UWB also provides support for communication on multiple sub-carrier frequencies through SC-FDMA and, with a minor modification of standard FM-UWB, multi-channel transmission.
All of the aforementioned techniques could prove to be useful in future applications. The SC-FDMA allows multiple transmitters to transmit either to a single receiver or to different receivers at the same time, without a significant performance loss. It can also be combined with the multi-channel transmission to speed up communication in both directions. Finally, a relatively simple configurable transceiver could be implemented that would allow for trading a number of channels for the data rate per channel in order to conform to the specific needs of the application. The methods described here could eventually provide the basis for implementation of more advanced techniques at higher levels of abstraction, such as, for example, channel hopping [30], and generally lead to more optimal system performance.


extfieldsofstudy:
Psychology
Computer Science

s2fieldsofstudy: Business Education

text:
An Investigation of Factors Impacting the Wellness of Academic Library Employees

The term “wellness” is fast garnering attention on how it affects one’s professional and personal life. This study explores the multi-dimensions of wellness and investigates factors that might impact the “wellness” of employees in academic libraries. The research topic was addressed through quantitative analyses of responses to multiple choice, ranking and qualitative analyses of responses to open-ended items. With a total of 1123 respondents, key findings include: there are statistical relationships between how respondents characterize themselves and how often they felt overwhelmed; the respondents’ age and how often they felt overwhelmed; the respondents’ age and how important they feel eating healthy is; the respondents’ current position and how important is being optimistic is to them.

Introduction
Feeling stressed or overwhelmed at work could negatively affect an individual's job satisfaction₁ and general well-being, and could in turn negatively affect the organization. As workers' health and general well-being suffer, companies have to spend more money on insurance premiums, which could then negatively impact their revenue and potentially lead to layoffs or even bankruptcies. According to the World Health Organization (WHO), work stress costs American businesses over $300 billion a year. 2 Therefore, "wellness" as a concept is garnering attention in the workplace.
Many employers are providing wellness support to their employees as means for combating illness-related loss of productivity due either to absenteeism or to reduced productivity while at work (presenteeism). 3 These efforts comprise workplace wellness programs that focus primarily on the prevention of chronic disease, such as lifestyle risk factors and lifestyle management, and secondarily on improving disease control. Furthermore, "workplace wellness programs are a primary component of the Patient Protection and Affordable Care Act (PPACA) or healthcare reform law commonly referred to as the ACA. The ACA allows employers to reward workers who participate in wellness programs, and penalize those who refuse, with discounts or increases of as much as 30 percent of their insurance costs." 4 As a result, many of the workplace wellness programs tend to focus on nutrition and weight management activities as well as modify student behaviour and balance the needs of different user groups are cited as stressors." 14 Another recent study surveyed librarians to identify possible stressors such as role ambiguity, role overload, perceived stress, burnout, life satisfaction, work withdrawal, and health conditions. The findings of the study showed that academic librarians largely reported role ambiguity and role overload as common stressors in the profession. 15 The authors of that study defined "role ambiguity" as stemming from "unclear expectations about specific job-related responsibilities" and "role overload" as the perception of a job to be excessively demanding with the requirement to work harder, longer, and/or faster.
Wellness in academic libraries has been discussed in literature as an additional service that libraries can provide to their users. Some academic libraries have embraced the idea of wellness as a user service and outreach strategy in part because of their close connection to student life and student success on campus. Hinchliffe and Wong discuss using a "wellness wheel" approach for shifting an academic library's services to an integrative learning and student-centered endeavor. Possible ways of adopting a "wellness wheel" approach include partnering with other campus departments to bring wellness services into the library, developing collections to support a lay understanding of different wellness concepts, and creating wellness-related outreach focused on high-stress times in the academic calendar, such as finals week. 16 Mills and Lodge suggest that information professionals use the concepts of Emotional Intelligence and an understanding of the information environment to create positive librarian-user interactions. 17 However, when addressing wellness in the work of academic library workers, few studies have been published that holistically examine the ways workers, from students to top-level administration, view workplace wellness at their organization and that examine their own wellness beliefs and habits. One example of such a study focuses on the job satisfaction of professional and paraprofessional library staff at the University of North Carolina at Chapel Hill. The study notes that differences in levels of satisfaction largely suggest that academic library professionals are more satisfied than their paraprofessional counterparts in the areas of work enjoyment, coworkers, promotion, pay, and overall satisfaction. 18

Dimensions of Wellness
Traditionally, the concept of wellness is viewed from two perspectives. The "clinical tradition" focuses on dealing with depression, anxiety, and stress, while the "psychological tradition" is about life satisfaction. 19 Dr. Bill Hettler followed the "psychological tradition" of wellness and created a model of an "active process through which the individual becomes aware of and makes choices toward a more successful existence." 20 He maintained that "wellness" could be divided into 6 basic dimensions: 1) Intellectual wellness measures the degree to which one engages his or her mind in creative, stimulating mental activities. An intellectually well person uses the resources available to expand his or her knowledge in improved skills, along with expanding potential for sharing with others. 2) Emotional wellness measures the degree to which one has an awareness and acceptance for one's feelings. This includes the degree to which one feels positive and enthusiastic about oneself and life. It measures the capacity to appropriately control one's feelings and related behavior, including the realistic assessment of one's limitations. 3) Physical wellness measures the degree to which one maintains cardiovascular flexibility and strength; the behaviors that help one to prevent and detect early illnesses; and the degree to which one chooses foods that are consistent with the dietary goals as prescribed by physicians and nutritionists.

4)
Social wellness measures the degree to which one contributes to the common welfare of one's community. 5) Occupational wellness measures the satisfaction gained from one's work and the degree to which one is enriched by that work. 6) Spiritual wellness measures one's ongoing involvement in seeking meaning and purpose in human existence. It includes a deep appreciation for the depth and expanse of life and natural forces that exist in the universe. 21 For this study, the concept of "wellness" will refer to this multifaceted definition of holistic wellness that focuses beyond the scope of physical health and illness prevention.

Participants
To reach a range of academic library employees, the survey was distributed to the e-mail lists and Facebook pages listed in appendix A. The invitation included an explanation of the survey, a statement of the goal of the project, and a hyperlink to the survey. The survey (see appendix B), which was administered through Qualtrics, included a consent form and 20 questions consisting of a mix of multiple choice, ranking, yes/no, and open-ended questions. Upon completion of the survey, participants were presented with a message thanking them for their time. The survey was active between January 17 and February 13, 2015. Of the 1,123 total respondents, 906 fully completed the survey. Participation in the survey was voluntary. As an incentive for completing the survey, participants were presented with the option to enter a drawing for one of two $25 Amazon gift cards (provided out of personal funds of the co-investigators). Only respondents who chose to record their e-mail addresses in the survey were entered into the drawing. To protect respondents' confidentiality, all identifying information was stripped from responses before analysis, leaving no way to tie responses to a particular e-mail address. All other responses were completely anonymous. The survey instrument was approved by the Institutional Review Boards of University of Alabama, which was one of the researchers' institutions at the time of survey distribution.

Survey Design
The survey questionnaire began with a screening question that required respondents to indicate the type of library in which they worked. Respondents who do not work at academic libraries are directed to a thank-you message and the end of the survey. The research design of this study was nonexperimental. It sought to examine the correlational relationships of library employees' perceptions of wellness and their behavior contributing toward their well-being, as well as their outlook on life and demographic characteristics (such as age, gender, position in their organization, and the size of their libraries). An additional aim of the survey was to explore library employees' views of the role of academic libraries in promoting and providing wellness support to users and to explore some of the workplace wellness programs provided to the respondents. These data and results will be presented in a separate paper. The focus of this paper is on analyzing library employees' perception of wellness and their behavioral and perceptional aspects of the survey data.

Results
The research objective of this study was to investigate 1) whether library employees are feeling overwhelmed; 2) If so, what are the possible causes? What actions are they taking to relieve the feeling? and 3) How much do library employees value the different dimensions of wellness and their behavior in achieving wellness in the different dimensions?
The survey begins with a screening question asking respondents to indicate what types of libraries they worked at. A total of 1,098 individuals responded. Respondents who selected "nonacademic" (n = 2) were directed to the end of the survey. Of the remaining respondents, 75 percent (n = 819) selected "four-year academic library", 11 percent (n = 126) selected "two-year academic," and 14 percent (n = 151) selected the "other academic library" option. This distribution is shown in figure 1.
The survey identified respondents' current positions at their libraries. Of the 974 individuals who responded to this question, 72 percent (n = 697) indicated that they were in Professional Librarian positions, which was by far the largest group, followed by Administration (16%; n = 151), and Support Staff (10%; n = 96). A small percentage, 1 percent (n = 11) were Student Employees.
Respondents were also asked to indicate their gender and age. Of the 969 responses, 13 percent were Male (n = 128), and 87 percent were Female (n = 841); 4 percent were 25 years old and under (n = 34), 33 percent were between 26 and 35 years old (n = 317), 24 percent were between 36 and 45 years old (n = 235), 19 percent were between 46 and 55 years old (n = 180), and 21 percent were 56 years old and over (n = 203). This distribution of respondents' age is shown in figure 2.
Respondents were asked to indicate how long they have worked in libraries. Of the 972 responses, 3 percent (n = 28) indicated less than 1 year. A total of 26 percent

FIGURE 1
At which type of institution do you work?
The survey asked respondents to indicate how optimistic or pessimistic they would characterize themselves. Out of 1,085 responses, only 1 percent (n = 8) characterize themselves as "very pessimistic," while a much larger percentage of the respondents (18%; n = 199) characterized themselves as "very optimistic." Seventeen percent (n = 180) characterized themselves as "somewhat pessimistic," and a similar percentage of people (14%; n = 154) saw themselves as "neither pessimistic nor optimistic." The largest group of respondents (50%; n = 544) saw themselves as "somewhat optimistic." This distribution is shown in figure 3.
Respondents were asked how often they felt overwhelmed in the past 6 months. Out of 1,081 responses, the largest percentage (48%; n = 524) answered "sometimes," followed by "frequently" (34%; n = 370). Four percent (n = 45) reported that they always felt overwhelmed, while 12 percent (n = 129) rarely felt overwhelmed, and 1 percent (n = 13) never felt overwhelmed in the past 6 months. This distribution is shown in figure 4.

FIGURE 3
How would you characterize yourself?

FIGURE 4
In the last 6 months, how often did you feel overwhelmed?
The survey then asked respondents to rank which of the following (Health, Family, Work, Life Fulfillment, Finance, and Other) typically overwhelmed them the most ("1" being the most overwhelming, and "6" being the least overwhelming). There were 1,003 responses to this question, and the largest number of respondents selected "Work" as the number one most overwhelming aspect (n = 455). A low mean value (0-6) indicates higher rankings of the aspect overall. "Work" has a mean value of 2.12, which is noticeably lower than all the other aspects ("Finance" = 3.11; "Family" = 3.11; "Life Fulfillment" = 3.45; "Health" = 3.49; and "Other" = 5.71).
Respondents were asked what they tend to do when they feel overwhelmed. A list of 22 choices were given, and the respondents were asked to select all that applied. A total of 1,035 respondents replied to this question. The number one answer was "Eat More" (49%; n = 506), followed closely by "Avoid Social Interactions" (47%; n = 491), and "Watch TV/Movies" (44%; n = 460). "Eat Less Healthy (40%; n = 418) and "Sleep Less" (40%; n = 416) rounded up the top five responses. At the other end of the responses, answers with the fewest selection were mostly contradictory activities to the top five choices; they were therefore consistent with their overall results. The bottom five answers were "Smoke More" (2%; n = 23), "Eat Healthier" (3%; n = 35), "Eat Less (7%; n = 74), "Socialize with Others" (7%; n = 75), and Meditate (9%; n = 95). This distribution is shown in figure 5.

FIGURE 5 When I feel overwhelmed. I tend to (check all that apply)
Next the researchers were interested in determining the importance of each wellness dimension to the respondents. The choices were: 1) Eating healthy (physical wellness); 2) Exercising regularly (physical wellness); 3) Pursuing continuing education for my career (occupational wellness); 4) Giving (social wellness); 5) Living consistently with my values and beliefs (spiritual wellness); 6) Being optimistic (emotional wellness); and 7) Challenging my mind with intellectual and creative pursuit (intellectual wellness).
Respondents were given five choices from "Very Important" (value = 5) to "Not Very Important" (value = 1). The middle three values were "Somewhat Important" (value = 2), "Moderately Important" (value = 3), and "Important" (value = 4). As there is not negative importance, the authors used a unipolar five-point scale. The choices were presented at the top of a matrix table with increasing values from left to right. The endpoints of the response scale were maximally differentiated. The authors adhered to the common Likert scale practice of assigning "somewhat important" a lower value than "moderately important." 22 A high mean value indicates respondents consider the activity important. Out of the seven activities, "Living consistently with my values and beliefs" has the highest mean value (4.19), followed closely by "Challenging my mind with intellectual and creative pursuit" (4.14) and "Eating healthy" (4.08). The activity with the lowest mean value is "Pursuing continuing education for my career" (3.38). The full table is shown in figure 6.
When comparing what respondents considered important with how often respondents engage in those activities, the results are consistent. When asked how frequently they engage in these activities, respondents were given five choices from "A great deal" (value = 5) to "Not at all" (value = 1). The middle three values were "Quite a bit" (value = 4), "Somewhat" (value = 3), and "Very little" (value = 2). As there is not negative frequency, the authors used a unipolar five-point scale. The choices were presented at the top of a matrix table with increasing values from left to right. The endpoints of the response scale are maximally differentiated. The authors adhered to the common Likert scale practice of assigning "Quite a bit" a lower value than "A great deal." 23 A higher mean value indicates that respondents engage more frequently in the activity. Out of the seven activities, "Living consistently with my values and beliefs"

FIGURE 6
How important are these activities to you? has the highest mean value (3.98), followed closely by "Eating healthy" (3.83), and "Challenging my mind with intellectual and creative pursuit" (3.75). The activity with the lowest mean value is Giving (such as contribute to the common welfare of our community, live in harmony with others; donating time, money, talent; practicing kindness) (3.18). This distribution is shown in figure 7.

Analysis of Data and Discussions
Chi-square statistical analysis shows that there is a statistically significant relationship (X 2 (20, N = 976) = 0.01, P = .05) between how many hours respondents worked in a typical week and the number of full-time employees working in the respondent's library building. Respondents who work in libraries with a higher number of employees tend to work more hours in a typical week. While not captured in this study, a possible

FIGURE 7
How frequently do you engage in these activities? explanation could be that libraries with a higher number of employees are likely to be serving larger user populations, and therefore require more staff power to operate.
With the trend of library budgets being stagnant or decreasing in recent years, it is very possible that larger libraries, even with a higher number of staff and librarians, are still short staffed, which results in their employees working longer hours on average.
Chi-square statistical analysis shows that there is a statistically significant relationship (X 2 (20, N = 1081) = 0.00, P = .05) between how many hours respondents work in a typical week and how often they felt overwhelmed in the last 6 months. Respondents who work "51-60 hours" or "60 hours or more" tend to feel overwhelmed much more frequently than respondents who work fewer hours in a typical week, including those who work a more "regular" schedule of 31-40 hours per week.

FIGURE 9 In the last 6 months, how often did you feel overwhelmed? (Respondents who work over 60 hours a week)
This could mean that library employees in larger libraries are more prone to feeling overwhelmed.
Chi-square statistical analysis shows that there is no statistically significant relationship (X 2 (4, N = 969) = 0.29, P = .05) between gender and how respondents characterize themselves (as optimistic or pessimistic); nor is there a statistically significant relationship (X 2 (4, N = 969) = 0.74, P = .05) between gender and how many hours respondents work in a typical week. However, Chi-square statistical analysis shows that there is a statistically significant relationship (X 2 (4, N = 969) = 0.00, P = .05) between gender and how often respondents felt overwhelmed in the last 6 months.
Female respondents tend to be more frequently overwhelmed in the past 6 months than male respondents. According to the survey on Stress and Gender 24 from the American Psychological Association (APA), "women are more likely than men to report that their stress levels are on the rise. They are also much more likely than men to report physical and emotional symptoms of stress." In APA's data, "Almost half of

FIGURE 10
In the last 6 months, how often did you feel overwhelmed? (Male respondents)

FIGURE 11 In the last 6 months, how often did you feel overwhelmed? (Female respondents)
all women (49 percent) surveyed said their stress has increased over the past five years, compared to four in 10 (39 percent) men." The difference of the percentage is similar to the finding on academic library employees.
Chi-square statistical analysis shows that there is a statistically significant relationship (X 2 (16, N = 1079) = 0.00, P = .05) between how the respondents characterize themselves and how often they felt overwhelmed in the last 6 months. The pattern suggests that the more optimistic respondents tend to feel overwhelmed less frequently than the pessimistic respondents.
While this finding could suggest that a positive attitude could have a positive effect on countering stress or feeling overwhelmed, it is also possible that respondents were more optimistic because they felt less stress in their work or in general.
Chi-square statistical analysis also shows that there is a statistically significant relationship (X 2 (16, N = 969) = 0.02, P = .05) between respondents' ages and how often they felt overwhelmed in the last 6 months. The pattern indicates that respondents

FIGURE 12
In the last 6 months, how often did you feel overwhelmed? (Respondents who characterize themselves as very optimistic)

FIGURE 13
In the last 6 months, how often did you feel overwhelmed? (Respondents who characterize themselves as somewhat optimistic) "56 years and older" tend to feel overwhelmed less frequently than respondents in the "26-35" and "36-45" age ranges. There is also a statistically significant relationship (X 2 (16, N = 969) = 0.00, P = .05) between respondents' ages and how they characterize themselves. Respondents in the "26-35" and "36-45" age groups tend to be more pessimistic overall than the other age groups.
There is a statistically significant relationship (X 2 (20, N = 969) = 0.00, P = .05) between respondents' ages and how many hours they spend on work in a typical week. However, even though a higher percentage of respondents "56 years old and over" work more than 41 hours a week than the other age groups, the group as a whole felt overwhelmed less frequently than the younger groups. These two findings are also consistent with the online survey of 2,020 U.S. adults, conducted in 2013 by Harris Interactive for APA, which finds that the Millennials generation (aged 18-33) reported higher than average stress. The APA survey finds that 19 percent of Millennials have been told they have depression, compared with 14 percent of Generation Xers (ages 34-47); 12 percent of Baby Boomers (ages 48-66) and 11 percent of those ages 67 and older. 25

FIGURE 14
In the last 6 months, how often did you feel overwhelmed? (Respondents who characterize themselves as neither optimistic nor pessimistic)

FIGURE 15 In the last 6 months, how often did you feel overwhelmed? (Respondents who characterize themselves as somewhat pessimistic)
These relationships could suggest several possible causes: 1) Respondents work longer hours because their workload is heavier than others and need more time to complete their work. Respondents who are younger might be more aggressive in taking on more work, as they are either at the beginning or the prime of their careers. A higher workload is therefore the main cause of their feeling overwhelmed. This reasoning could also explain why the oldest group, who worked longer hours than other groups, did not feel overwhelmed as frequently as some other groups. 2) Respondents work longer hours because they are not as productive as others and find it difficult to complete their work in the regular work hours; therefore, they have to work longer hours. Younger respondents might be less proficient in their work at the earlier stages of their career and are still learning. They feel overwhelmed because of their lack of competency. Applied to the oldest group, who might possibly be the most experienced, this reasoning could also explain why they did not feel overwhelmed as often. 3) Respondents work longer hours because they feel obligated to be at work or doing work outside regular work hours. Younger respondents who are at earlier stages of their career might want to impress their supervisors by working longer hours. The perception of obligation is therefore the main cause of feeling overwhelmed in this scenario. Future studies could ask more in-depth questions on causes of respondents feeling overwhelmed. In terms of how respondents value the different dimensions of wellness, Chi-square statistical analysis shows that there is a statistically significant relationship (X 2 (16, N = 969) = 0.03, P = .05) between respondents' ages and how important is "Eating Healthy" (physical wellness) to them. A much higher percentage of respondents in the "56 and over" age group viewed it as "very important" than other age groups, while the two youngest age groups (25 and under, and 26-35) have the lowest percentage of respondents selecting "very important" as their answers. However, there is no statistically significant relationship (X 2 (16, N = 963) = 0.22, P = .05) between respondents' ages and how frequently they engage in "Eating Healthy." As people age, it makes sense to be more aware of the importance of a healthy diet. However, since there is no statistically significant relationship between respondents' ages and how frequently they actually eat healthy, it could be said that simply having the awareness of the importance of a healthy diet does not necessarily translate to the behavior of eating healthy.
There are also significant statistical relationships between age and "Pursuing continuing education for my career" (X 2 (16, N = 969) = 0.00, P = .05); "Giving" (X 2 (16, N = 969) = 0.00, P = .05); "Being Optimistic" (X 2 (16, N = 966) = 0.00, P = .05). The younger respondents tend to place more importance on pursuing continued education for their career than their older colleagues, which makes sense as the younger respondents are likely to be in the growth period of their careers. Respondents in the "26-35" and "36-45" age groups have the lowest percentage of people selecting "Very Important" for "Giving." The same two age groups also tend to place less importance in "Being Optimistic." One interpretation of this finding is that the age groups might not have the financial security to allow them to "give" at this stage of their lives. From starting and/or raising families, to possibly not commanding high salaries at this stage of their lives, it is also understandable to not feeling optimistic or placing a lot of importance on the giving dimension of wellness.

Conclusions and Future Directions
This study reveals that most academic library employees feel overwhelmed quite frequently. While age and working overtime are factors, the attitude of the individual also has an impact. Work is the number one cause of respondents feeling overwhelmed. When respondents felt overwhelmed, they tended to "Eat More," "Avoid Social Interactions," "Watch TV/Movies," "Eat Less Healthy," and "Sleep Less." Age again seems to be an important factor regarding respondents' perception of the different dimensions of wellness. It could be argued that people in different stages of their lives place different values on the different dimensions of wellness. For example, younger respondents tend to value continuing education more than their older counterparts do, and the older respondents place more importance on eating healthy than their younger colleagues do. Overall, respondents placed higher importance on their spiritual wellness and intellectual wellness than physical wellness.
Further research into what affects academic library employee wellness can include an examination of the different types of academic libraries. Does the Carnegie Classification of Institutions of Higher Education (that is, Research University versus community college) have an impact on perceptions and attitudes toward wellness? For Professional Librarians, does faculty status (tenure vs. non-tenure track) or academic professional/staff status have an impact on wellness? What relationship does the student to librarian or student to library worker ratio have on academic library employee wellness? Additional investigation of this nature could prove valuable for academic libraries and institutions of Higher Education as employers to develop programs and policies to support employee wellness.
As this study suggests, library employees value more than just the physical aspect of wellness. The next step for the researchers will be to explore the potential of workplace wellness programs that cater to multiple dimensions of wellness by analyzing the data collected in the survey on the types of workplace wellness programs offered by the respondents' employers and the types of workplace wellness programs respondents would personally be interested in. Additional research would need to be conducted on workplace wellness efforts in both libraries and other industries that extend benefiting employees beyond physical wellness. The results of this study are important to academic libraries because they show that simply focusing on the physical aspect of wellness may not be the most effective way to support library employees. With the knowledge that library employees highly value living consistently with their values and beliefs, libraries could positively affect their employees' spiritual wellness by creating shared visions, paying attention to their motivation, personal life vision, and career goals. In addition, library employees value challenging their minds with intellectual and creative pursuits. Libraries could provide suitable professional development opportunities and support to help positively affect intellectual wellness as well.

Bibliography
Ardell, D.B. "The History and Future of Wellness." Health Values 9, no. 6 (1985) We are conducting this survey to learn more about the perceptions and behaviors of people who work academic libraries in the concept of work/life quality and wellness. If you decide to participate, you will take a survey that should take approximately 10 minutes to complete.
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UvA-DARE (Digital Academic Repository) A queueing-theoretic analysis of the threshold-based exhaustive data-backup scheduling policy

ARTICLES IN On the optimal use of a slow server in two-stage queueing systems Abstract. We analyse the threshold-based exhaustive data backup scheduling mechanism by means of a queueing-theoretic approach. Data packets that have not yet been backed up are modelled by customers waiting for service (back-up). We obtain the probability generating function of the system content (backlog size) at random slot boundaries in steady state.

INTRODUCTION
The last decade has witnessed a tremendous growth in data produced and stored. In a recent McKinsey report, it was stated that "by 2009, nearly all sectors in the US economy had at least an average of 200 terabytes of stored data (twice the size of US retailer Wal-Mart's data warehouse in 1999) per company with more than 1,000 employees" and that "the increasing volume and detail of information captured by enterprises, the rise of multimedia, social media, and the Internet of Things will fuel exponential growth in data for the foreseeable future" [1]. This creates various challenges, among which extracting valuable data from large data sets, i.e., data mining, security (authenticity, integrity), making backups to protect against data loss due to hardware failure, accidental deletion, theft, et cetera.
In order to alleviate the backup assignment of the huge amounts of data of various users, research has been carried out to reduce the amount of data to backup, e.g. by compression techniques. We refer to Tan et al. [2] and Vrable et al. [3] and the references therein. However, even with these data reduction techniques, the amount of data to be backed up and the number of users remain large. Hence, there is a need for efficient data backup scheduling policies, tackling the trade-off between not backing up too frequently to maintain sufficient capacity while keeping the age of data and backlog size sufficiently small to minimize the amount of data at risk of loss.
We analyse a basic data backup scheduling mechanism by means of a queueing-theoretic approach. The backup scheduling mechanism considered here is a threshold-based exhaustive policy, that is, a data backup is initiated as soon as the backlog size reaches or exceeds some threshold, and an ongoing backup is finished when the backlog size becomes zero, that is when all data is backed up including new data that has been created during the backup process. The corresponding queueing model is described and its analysis is briefly sketched in the subsequent sections.
To the best of our knowledge, there is a lack of formal mathematical models for backup scheduling. We are only aware of the paper of van de Ven et al. [4], where a discrete-time queueing model for a distributed backup scheduling protocol for corporate networks with homogeneous users (i.e., same data production and connectivity patterns) is

DATA BACKUP QUEUEING MODEL
The objective of developing a queueing model is to obtain a formula for the backlog size, that is the data that has not yet been backed up. The queueing model has the following features: • Time is slotted, that is, a discrete-time queueing model is considered.
• Data packets that have not been backed up are modelled to await backup (service) in a queue.
• During a slot a number of packets can arrive at the queue, that is, new packets are created; the number of arrivals during some slot k is denoted by A k and {A k ; k ≥ 0} is modelled as a sequence of independent and identically distributed (iid) random variables, with common probability mass function (pmf) a(n), n ≥ 0 and probability generating function (pgf) A(z). The mean number of arrivals during a random slot is denoted by λ. • When no backup is being carried out, a backup will be initiated at the first slot boundary where the backlog size, that is the system content, reaches or exceeds the threshold l. • The capacity of the backup server equals c, meaning that maximum c packets can be backed up in a slot.
• The server continues backing up until the backlog size becomes 0 again. Hence, at backup completion, the backlog size equals 0. • Arriving customers can immediately, that is in their slot of arrival, be taken into service if service is going on in that slot and capacity is available. This feature is in literature referred to as early arrivals.
In fact, the queueing model considered here is a discrete-time queueing model with batch service and N-policy (with N = l). In literature, the combination of batch service and N-policy has rarely been considered. To the best of our knowledge, only Arumuganathan and Jeyakumar [5], and Reddy et al. [6] incorporate both features, but in continuous time, which is not useful for our purpose.

ANALYSIS OF THE MODEL
Through a partial-generating function approach, we obtain the pgf U(z) of the system content, that is the data that has not yet been backed up, at random slot boundaries in steady state. The pgf U(z) is obtained as follows: 1} , • U k : system content at slot boundary k, • τ k = 0 if no backup is going on in slot k; τ k = 1 otherwise, • U 1 (z) := ∞ n=1 u 1 (n)z n . After some calculations, the following expression for U 1 (z) is obtained: Equation (1) contains c + l unknown constants u 0 (0), . . . , u 0 (l − 1), v 1 (1), . . . , v 1 (c), which can be determined once a set of c + l linearly independent equations in these unknowns are determined. First, c − 1 linearly independent equations are found by means of the standard approach of relying on Rouché's theorem and the analytic property of pgfs [7]:

200002-2
with z i the c − 1 zeroes of z c − A(z) different from 1 inside the closed complex unit disk {z ∈ C : |z| ≤ 1}. The other equations can be found through probabilistic reasoning, that is linking the state in a slot with feasible states in the previous slot, leading to and by applying the normalization condition on U(z):

CONCLUSIONS AND FUTURE WORK
A queueing system is developed and analysed to model a threshold-based exhaustive backup policy. This paper is one of the first to address the data backup challenge from a queueing-theoretic point of view. To the best of our knowledge, only van de Ven et al. also consider this point of view [4]. Whereas we study a threshold-based policy, van de Ven et al. examine a probabilistic backup policy, that is at each time slot the user decides with some probability whether to initiate a backup, regardless of the backlog size.
There are several directions for future research. The assumption of iid sequence {A k } may be relaxed, because in practice it is likely that the arrival process exhibits some cyclic pattern, as described by van de Ven et al. [4]. Our approach will then have to be slightly adapted by using partial or vector generating functions instead of probability generating functions, in order to keep track of the position within the cycle. Also, other backup policies could be studied and compared one to another. We have started analysing the threshold-based gated backup policy through a similar analysis technique, but we have obtained a functional equation which we have not yet been able to solve. Another possibility is to study a model that combines a threshold policy with a timer policy to ensure that the age of the data does not become excessive. This would result in some kind of discrete-time batch-service queueing model with NT policy.