1. Technical Field
The invention relates to digital communications. More particularly, the invention relates to a method and apparatus for efficient preamble detection in digital data receivers.
2. Description of the Prior Art
Data communications systems may generally be grouped into two basic forms: continuous data communications systems, and discontinuous, or burst data communication systems. In burst systems, a block of data is sent over a finite period of time, and then transmission is halted until a later point in time. To aid in the recovery of data bursts, most burst-mode systems use a preamble, which is a predefined data pattern that is sent prior to the data to be communicated. It is well understood that the efficiency of detecting this unique preamble pattern is of utmost importance because the complexity of preamble detection has a major impact on overall receiver complexity. The invention described herein is concerned with identifying a reduced-complexity method of preamble detection in burst-mode data transmission systems.
Another method of classifying data communications is between synchronous and asynchronous communications systems. In synchronous systems, the transmitter and the receiver use some means to communicate symbol timing information, in addition to the data to be transmitted. Because the addition of symbol timing information necessarily mandates increased channel bandwidth, many data communications systems use asynchronous data communication. In an asynchronous system, the receiver must perform symbol timing recovery to identify the optimum signal phase at which to recover the received data. The invention herein disclosed focuses upon asynchronous burst-mode systems.
A wide variety of modulation techniques have been created to communicate digital data asynchronously. One of the most commonly used is known as Quadrature Phase Shift Keying, or QPSK. In QPSK and its variants, two bits of information are transmitted every symbol interval. Changes in the phase of the transmitted signal are used to communicate information. This is performed by modulating two independent waveforms, historically known as I and Q, onto a single carrier. FIG. 1a shows a representative constellation diagram of a transmitted QPSK signal, where the I and Q axes are plotted together to demonstrate how two bits of information represent four distinct signal phase states in QPSK. To recover this signal, a receiver must estimate which of the four phases was transmitted during each symbol interval. To prevent interference between the two modulating waveforms, a 90-degree fixed phase shift is introduced between I and Q during the modulation process. This phase shift makes it possible to recover the I and Q information independently, despite the use of a single transmission carrier. Throughout this document, QPSK modulation is used as an example to illustrate the core concept of the invention, but the concept may be applied to a wide variety of different modulation formats.
In any asynchronous communications system that uses carrier-based modulation such as QPSK, there is an incommensurate relationship between the frequency of the transmitted carrier and the frequency of the receiver. Physical component limitations always lead to a finite frequency error between the two devices. FIG. 1b shows the consequence of a typical frequency error. As indicated, the constellation diagram actually rotates over time, making it more difficult for the receiver to identify the signal phase that was actually transmitted properly.
There are two primary techniques to correct for the signal impairment that is caused by frequency error. In the first method, the receiver performs carrier frequency/phase recovery to correct for the rotation prior to making a symbol decision. Receivers that use this technique are said to use coherent detection. In the second method, the absolute phase of the received signal is deemed to be irrelevant. The transmitter instead performs differential encoding to allow the relative phase difference between sequential symbols to convey information. Receivers that rely solely upon differential phase to recover the transmitted signal phase are said to use differential detection. Note that it is possible for a receiver to use both of these methods simultaneously. If so, the result is known as coherent detection of a differentially encoded signal. This combination is very commonly used because the process of performing carrier recovery on a QPSK signal inevitably leads to a 90 degree phase uncertainty. The carrier recovery logic in a coherent receiver can lock on to any of four different absolute signal phases. By using differential encoding, the absolute phase ambiguity is irrelevant because only relative phase changes encode signal information.
Once a receiver has completed preamble detection, symbol timing recovery and carrier frequency/phase recovery, it then must demodulate the incoming signal to transform it from a waveform representation into digital data bits. As mentioned previously, this entails identifying which of the four possible QPSK waveform states were most likely sent by the transmitter during each symbol interval. During demodulation, the I and Q waveform values are often treated as a single complex number, and hence may be plotted as shown in FIG. 1a in constellation diagram form, with I and Q forming the real and imaginary components of the input sample values.
The theoretically optimum technique for coherent demodulation of a QPSK signal performs a Euclidean distance search between the complex received sample values and each of the four ideal QPSK states. The QPSK state having the shortest distance to the sample value is declared to be the received symbol value. For efficiency, most QPSK systems incorporate a fixed 45-degree rotational offset for the four ideal phase points, such that the QPSK signaling states are located at phases of 45 degrees, 135 degrees, 225 degrees, and 315 degrees. In this case, the complex Euclidean distance search may be replaced with a simple sign() comparison for the I and Q values.
In the case of pure differential detection, the theoretically optimum demodulation technique multiplies the complex received sample values by the complex conjugate of the signal as delayed by one symbol time. The resulting product represents a differential phase sample that indicates the relative phase from the previous symbol to the current symbol. Stated more precisely, given an input sample stream Rk, the complex differential phase sample Zk is computed as:Zk=Rk·R*k-N   (1)where N is the number of samples that are acquired by the receiver per symbol time, and R*k-N is the complex conjugate of the previous symbol's sample value. Note that this phase sample may also be considered a vector, with the (0,0) origin as the assumed initial endpoint. Once the differential phase vector has been computed, four separate complex derotations, corresponding to the negative value of the four ideal QPSK phases, are performed in parallel upon Zk. The ideal phase derotation that results in the greatest positive magnitude is selected as the current symbol value (for example, see D. Divsalar, M. Simon, Multiple-Symbol Differential Detection of MPSK, http://d1.comsoc.org/cocoon/comsoc/servlets/GetPublication?id=147684; FIG. 1). As with coherent detection, more efficient techniques are commonly used which obviate this degree of complexity. Given a complex differential phase vector Zk, one such technique is:x=sign(real(Zk)+imag(Zk))  (2)y=sign(real(Zk)−imag(Zk))  (3)
Depending on the signaling convention used by the specific implementation, the values of x and y correlate directly with the two data bits that underlie each symbol's QPSK state, yielding two bits of recovered information per symbol time.
It is important to point out one additional processing step that is performed by nearly all burst receivers, and that is the computation of the received signal's input power level. Signal power is important for many reasons for example, some devices display the signal power in the form of a logarithmic received signal strength indicator, while others compute the Signal/Noise Ratio of a signal as a quality metric by following the well-known power formula:SNR(dB)=10* log10((Signal Power)/(Noise Power))  (4)where the signal power S and noise power N levels are computed by:powerk=real(Rk)2+imag(Rk)2   (5)
Most burst mode receivers also require some form of signal power estimation during preamble detection. Without knowing the power level of the received signal, random noise may frequently yield false-positive preamble detection. While this is not harmful in and of itself, falsely triggering on noise can mask the start of subsequent data bursts, leading to a loss of valid data bursts. For this reason, signal power estimation is a very important element of most burst-mode data receivers.
It would be advantageous to provide a method and apparatus for efficient preamble detection in digital data receivers.