promising high - speed mobile networks enable the 
 deployment of new advanced services , facilitating the development of emerging 
 services in the electronic healthcare area .
obstacles for healthcare services 
 are time and space between the providers and the patients .
wireless technology 
 came to encompass the e - health monitoring everywhere from any given location , 
 providing the so - called m - health services .
the benefits of wireless technology 
 have been illustrated in a number of different examples and cases , especially for mobile applications . during the last years
, there has been increased 
 research efforts on the production of commercial mobile health systems based on 
 wireless fidelity ( wifi ) , general packet radio service ( gprs ) , and 3rd 
 generation universal mobile telecommunications system ( 3 g umts ) networking 
 technologies .
the introduction of high - speed data rate , wide 
 bandwidth , digital and encrypted communication technology makes possible the 
 delivery of audio , video , and waveform data to wherever and whenever needed .
it 
 is hoped that the current deployment of 3g - based systems with global 
 operational morphologies will improve some of the limitations of the existing 
 wireless technologies and will provide a well - organized platform for mobile 
 healthcare services . in emergency cases , where immediate medical 
 treatment is the key issue , studies revealed 
 that early and specialized prehospital patient management contributes to 
 the patient 's major possibility of continued existence 
 [ 4 , 5 ] . especially for the cases of serious injuries , the way the incidents are treated and transported on 
 the way to the hospital is crucial for the survival of the patients .
for 
 example , in case of car accidents , emergency transportation and real - time 
 diagnosis are the most vital parameters for giving the precise rehabilitation 
 during the critical minutes toward the hospital and increasing the 
 possibilities of 
 surviving .
thus , people in ambulances who are the first to handle these 
 emergency situations do not always have the required advanced background and 
 experience to manage sufficiently all cases .
wireless transmission of vital biological 
 signals and scene video of the patient along with video conference with an 
 experienced doctor at the hospital can achieve proper first aid of the patient . 

nevertheless , collaborative teleconsultation by moving physicians , in terms of 
 retrieving significant healthcare records , is imperative and in most of the cases 
 valuable . in this context , high speed packet access ( hspa ) 
 for uplink and downlink , together with 3 g and 4 g systems , such as wimax [ 7 , 8 ] , is expected to enforce the m - health applications 
 and overcome the boundaries between time and space .
previous studies of 2 g   and 3 g networks 
 [ 10 , 11 ] showed performance assessment that aims to 
 support m - health services evaluating the end - user perceived service 
 performance , in relation to the performance of a 2 g and 3 g network , in order to 
 improve the end - to - end delay characteristics of the telemonitoring service , as 
 well as to optimize the throughput behavior .
high usability , support for 
 multimedia services with good reliability and low - transmission cost , 
 personalization of the services , more capacity , and spectrum efficiency are 
 some of the key features of the evolving mobile technologies .
such technologies 
 will make available both mobile patients and end users to interactively get the 
 medical attention and advice they need , when and where is required in spite of 
 any geographical obstructions or mobility constrains .
the scope of this study was to design and 
 evaluate via simulation an integrated high - speed uplink mobile telemedicine 
 system for emergency and near - emergency conditions .
hspa is an evolving mobile 
 technology newly deployed and commercially utilized by a small number of 
 operators so far , thus the need for system simulation was demanding prior to 
 real - time operation .
the simulation trials were selected to represent a range 
 of services and to include both asynchronous and synchronous applications 
 ( nonreal - time , near real - time , and real - time requirements ) in medical data 
 transmission . the overall goal was to test the ability of 3 g and beyond 3 g infrastructures 
 to support value - added services .
the trials were evaluated in terms of 
 admission control and quality of service ( qos ) provisioning , the total 
 throughput that the network can accomplish versus the category of patient 
 condition , the priority of the patient in case of an emergency , the data rate , 
 and the congestion of the 3.5 g network , planned for uplink circumstances . 

moreover , various simulation scenarios were implemented in order to incorporate 
 the typical m - health scenarios for high - speed data transfer .
the remainder of the paper is organized as follows ; in section 2 , the evolving technology 
 of the hspa is described in relation to the general m - health requirements , 
 while in section 3 , the specific operational m - health scenarios under study are 
 presented .
section 4 includes the description of the developed simulation 
 model , whereas in section 5 , experimental results regarding patient condition 
 ( emergency or simple patient monitoring ) , making use of m - health services 
 session dedicated to video application , voip , web browsing , medical and file data 
 transfer , are presented .
the main objective of these experiments is the 
 validation of the system throughput for the aforementioned scenarios , the delay 
 of the packets transmission , the jitter and the latency of the system , and the 
 overall congestion of the cell .
the evolving technology for 3 g is called hspa 
 which is a packet - based cellular system deployed on top of the current wcdma 
 networks .
hspa is an evolution of wcdma - umts technology , achieving greater bit 
 rates and reduced delays .
the commercial utilization of this technology is 
 rather new , since new hsdpa ( downlink ) networks are launched by european 
 providers continuously , while the first enhanced uplink ( hsupa - uplink ) 
 networks were implemented only during the last year .
theoretically , on the 
 downlink the maximum achieved bit rate is about 10.7 mbps using 16-qam 
 modulation , while on the uplink the maximum bit rate exceeds 5.5 mbps per base 
 station ( node - b ) .
currently , 3.6 mbps and around 1.5 mbps are the common peak bit 
 rates provided by mobile providers for downlink and uplink , correspondingly . 

hspa incorporates a significant number of innovative features , such as adaptive 
 modulation and coding , short transmission time interval ( 2 milliseconds ) , fast hybrid automatic repeat request 
 ( harq ) , customized schedulers for the proper manipulation and routing of the 
 data , as well as the possibility for a multiple input multiple output ( mimo ) 
 add - on .
figure 1 depicts the enhanced uplink architecture and the interconnection 
 of the fundamental elements , such as the radio network controller ( rnc ) , the 3 g 
 base station ( node - b ) , and the user equipments ( ues ) .
the main characteristics 
 of fast node - b scheduling are depicted during the uplink session and the 
 required procedures between the ue and the node - b , which is responsible for 
 controlling the transmission rate and assigning of ue .
the scheduling process 
 is performed by node b in order to make the noise rise ( signal - to - noise power ) 
 of a required level .
layer 1 ( l1 ) signal of node - b limits the maximum rate and 
 therefore the power offset for dedicated physical control channel ( dpcch ) . 

since the control delay is shorter than that of rnc , adaptive control is 
 performed in association with noise rise fluctuation .
ue sends control signals 
 for uplink as rate request to node - b , while node - b returns ue l1 signals as rate 
 grant .
l1 signal from ue for rate request has a rate - increasing requirement 
 based on the total buffer size .
ue ends layer 2 signal as rate request including 
 buffer size of the highest priority data flow and the total buffer size . 

downlink control signals are absolute grant ( ag ) and relative grant ( rg ) .
ag 
 means the absolute value of the power offset permitted for the power usage , 
 thus node - b , that controls a serving cell , can send ag .
rg is used for controlling 
 fluctuations for power offset and is sent from all cells in enhanced uplink neighboring 
 cells .
the ability of hspa to serve simultaneously a 
 sufficient number of mobile terminals running multiple demanding applications 
 while keeping the end to end delay low makes it an ideal candidate for a vast 
 number of new services . due to the increased capacity that hspa is able to 
 offer and its packet - based nature ,
the implementation of a variety of 
 applications over cellular networks is now feasible 
 [ 15 , 16 ] . considering the constant geographical expansion and 
 technical development of hspa networks , they should be soon ready to credibly 
 host e - health services , emphasizing on mobile e - health , emergency and patient 
 followup applications .
electronic healthcare applications , 
 including those based on wireless technologies span the areas of emergency 
 health care , telemedicine in various forms ( telecardiology , teleradiology , 
 telepathology , teledermatology , teleophthalmology , and telepsychiatry ) , and 
 electronic access to health records .
the range and complexity of 
 telecommunications technology requirements vary with specific medical or health 
 applications . except for medical images and running through full motion video , 

the majority of biosignal medical devices require relatively low - data 
 transmission rates [ 17 , 18 ] .
regarding the transmission of 
 medical images , there are essentially no theoretical bandwidth requirements , 
 but lack of bandwidth needs longer transmission time . yet
, high - quality medical 
 images such as a single chest radiograph may require from 40 to 50 megabytes . 
 in practice , it is desirable to transmit medical images during a single patient 
 visit , so as to at least avoid a followup visit .
medical image compression 
 techniques have primarily focused on lossless methods , where the image has to 
 be reconstructed exactly from its compressed format due to the diagnostic use . in regards to the digital video 
 compression , the digital imaging and communications in medicine ( dicom ) 
 committee has not yet adopted any standard .
the adoption of mpeg-2 is possible , 
 but this is limited by the mpeg-2 requirement for constant delay method for 
 frame synchronization . on the other hand ,
it is important to distinguish among the requirements for 
 real - time video transmission , offline video transmission , medical video and 
 audio for diagnostic applications , and nondiagnostic video and audio .
real - time 
 video transmission for diagnostic applications is clearly the most demanding . 

offline video transmission is essentially limited by the requirement to provide 
 patient doctor interaction .
real - time diagnostic audio applications include the 
 transmission of stethoscope audio , or the transmission of the audio stream that 
 accompanies the diagnostic video .
a typical application will require a 
 diagnostic audio and video bit stream , in addition to a standard teleconferencing 
 bit stream [ 19 , 20 ] .
future challenges in 
 m - health systems are already mentioned in , and were partially covered in this study .
in general , 
 m - health applications may be categorized in two groups depending on the 
 required transmission mode : 
 real - time applications : these are referred to multimedia connections 
 between centers and moving vehicles including audio and video exchange , 
 biomedical signals , and vital parameters transmission , such as 
 electrocardiogram ( ecg ) signal , blood pressure , oxygen saturation , and so forth;near real - time applications : these correspond to applications enabling 
 access to administrative files and electronic patient report ( epr ) transfer 
 ( from medical data exchange between centers and moving vehicles or specialty 
 sections ) , clinical routine consults during accesses to databases , queries to 
 medical report warehouse , and so forth . 


 in this study , we deal with applications from both 
 groups , used in emergency situations and for teleconsultation purposes , 
 respectively .
therefore , the qos requirements for the discussed m - health 
 services are set to the highest level for emergency and medium to low level for 
 near real - time applications , as depicted in table 2 .
real - time applications : these are referred to multimedia connections 
 between centers and moving vehicles including audio and video exchange , 
 biomedical signals , and vital parameters transmission , such as 
 electrocardiogram ( ecg ) signal , blood pressure , oxygen saturation , and so forth ; near real - time applications : these correspond to applications enabling 
 access to administrative files and electronic patient report ( epr ) transfer 
 ( from medical data exchange between centers and moving vehicles or specialty 
 sections ) , clinical routine consults during accesses to databases , queries to 
 medical report warehouse , and so forth .
most of them are already covered , but due to the extended 
 performance of the enhanced uplink in terms of throughput , new m - health services 
 were implemented via simulation procedure .
thus , in this section we initially 
 discuss potential scenarios of mobile healthcare services , incorporating 
 emergency real - time and near real - time applications .
this service refers to the support of transport 
 healthcare units ( i.e. , ambulances ) or primary care units ( i.e. , rural centers ) 
 in case of accidents .
recent 
 studies conclude that early and specialized prehospital patient management 
 contributes to emergency case survival . especially in cases of serious injuries 
 of the head , the spinal cord , and internal organs the way of transporting and 
 generally the way of providing care is crucial for the future of the patient . 

unfortunately , general practitioners in remote health centres or ambulance 
 personnel , who usually are the first to handle such situations , do not have the 
 required advanced theoretical knowledge and experience . since , for practical 
 and financial reasons , primary care or transport healthcare units can not be staffed by specialized physicians , general doctors can 
 only rely on directions provided to them by experts .
an m - health service in 
 this case allows specialized physicians located at a hospital site to 
 coordinate remote - located primary care or ambulance services paramedical staff 
 via telediagnosis and interactive teleconsultation means .
table 3 summarizes the typical data transmitted 
 in emergency services in case of accidents .
recent developments 
 in networking and computing technologies and the expansion of the electronic 
 health record system have enabled the possibility of online collaboration 
 between geographically distributed medical personnel . in this context , a 
 teleconsultation session implements a collaborative working environment for 
 physicians in dispersed locations , by enabling ( a ) electronic exchange of 
 medical data , ( b ) voice / video / chat communication , and ( c ) common workspace 
 management ( i.e. , common image processing toolbox , annotations , etc . ) ( see 
 table 4 ) . in case one at least of the commuting doctors is 
 moving or in a random location with no availability of fixed networks , a 3.5/4 g platform may be used as a communication medium .
this service is related to 
 applications , enabling the mobile ubiquitous delivery of medical data and 
 implementations of mobile electronic health records ( ehrs ) , accessible by pdas or tablet pcs .
this service is provided to physicians that require immediate 
 access to patient 's medical data from random locations .
therefore , only broadband cellular systems ( i.e. , 
 3/4 g ) may be used due to the corresponding data sizes .
the medical data 
 transmitted in a mobile ehr system are depicted in table 5 .
in order to evaluate the performance 
 of the mobile healthcare applications over the 3.5 g system under study ( specifically 
 high speed enhanced uplink aka hsupa ) a simulation campaign is among the 
 optimum solutions [ 24 , 25 ] . in this case
though we will only refer to the reverse link hereafter , 
 both forward and reverse link of the network were implemented in the simulator 
 used . during the development of any platform ,
necessary simplifications have to 
 be taken into account , usually leading to a slight overestimation of the 
 system 's performance . all the fundamental elements ( rnc , node - b , air interface , 
 ue , etc . ) of a complete cellular network were simulated , to such an extent for 
 each one , so as to be precise enough for our scope .
there is also a traffic 
 generator process , which simulates several applications as will be mentioned 
 later on .
the model consists of a single 
 hexagonal cell , while the first layer of six identical adjacent cells has been 
 virtually deployed ( i.e. , handover is not allowed and mobile terminals are 
 restricted within the coverage area of central cell ) in order to accurately 
 incorporate interference effects .
all the attributes of the network were 
 adjustable ; therefore a variety of scenarios may be investigated .
the sessions may 
 be statically created ( e.g. , at the beginning of a simulation run ) or 
 dynamically inserted into the network using equivalent distributions 
 ( exponential , poisson ) and may run one or multiple services .
mobility has been 
 taken into account for each terminal , corresponding to vehicular and pedestrian 
 profile .
the propagation model calculates path loss , 
 shadowing , and small scale fast fading , adapted to a dense urban environment . 

rayleigh fading is considered 
 , whereas doppler power spectral density is modelled 
 by the well - known jakes formula .
channel samples are generated offline through a 
 matlab implementation of the above channel model . a detailed methodology for 
 extracting these samples
is described in . as enhanced uplink is an interference limited 
 system , calculations for the admission of a new session into the network and 
 power allocation per time transmission interval ( tti ) also exist .
the traffic process is capable of 
 generating all the typical applications running over a cellular network .
voip , web 
 browsing , video application , and ftp are typical examples of applications 
 provided .
some of these were simulated based on their standards ( e.g. , voip ) , 
 while for others trace files from real networks were used ( e.g. , h.263 codec medical 
 video ) .
different load mixes may be examined , as the 
 percentage of each service in the total load is arranged for each simulation 
 run . in this performance ,
voip is considered to incorporate all possible 
 enhancements , resulting to a bit rate of 12.2 kbps per user , with an adaptive 
 multirate ( amr ) codec .
web browsing is a common bursty source , while ftp service is 
 a source of constant bit rate .
congestion control will shortly detect a 
 build - up delay ( or lost packets ) and inform the node - b about it .
the scheduler 
 is responsible to maintain uplink interference below the threshold level , by 
 signaling the mobile terminals to adjust their transmission power .
it is 
 evident from the results of the simulation procedure that the end - to - end delay 
 per application for the voip and video sessions is quite low and that enhanced 
 uplink is able to withstand the meet of service 's requirements .
first of all , after the establishment of a session , 
 the only part which is able to terminate the connection is the ue .
this means 
 that the network is not able to drop a session for any reason ( e.g. , congestion 
 of the network ) .
a single cell network was used throughout the paper and all 
 ues were bounded to move within the area of coverage of this cell ( if a ue 
 leaves this area , the mobility process will force it to reenter ) .
also , no 
 erroneous packet reception was considered and no packet discard was allowed , 
 leading to a slight loss in the quantitative ( but no qualitative ) accuracy of 
 the results .
considering the aforementioned setup , the simulator 's environment 
 and results are as realistic and accurate as possible .
as discussed in section 3 , three primary 
 scenarios were taken into consideration , and a step - by - step performance evaluation 
 was accomplished arranging the network for serving a number of possible occasions . 

we kick off by examining the requirements for serving emergency cases , continue 
 by studying collaborative sessions between moving physicians and finally the scenario 
 of ubiquitous mobile access to electronic health records is presented .
results 
 are mainly presented in terms of end - to - end delay , as this metric is widely 
 considered to be amongst the optimum indicators in order to evaluate a 
 network 's performance , influencing directly or indirectly most of the other 
 performance metrics . during these scenarios , significant contributions for the 
 optimization of a remote healthcare - oriented enhanced uplink network were 
 exhibited . in order to 
 extract conclusions about the overall performance of enhanced uplink ,
the first test case 
 to be examined for this scenario is the concurrent existence of two emergency 
 sessions in the network .
table 7 depicts the parameters of this simulation run , while the 
 selected services and bit rates correspond to those of table 3 .
the two established sessions require 
 approximately 2 mbps in total , while during video bursts this value may rise 
 even 20% or more .
an important factor was that no packet drop was 
 allowed , no matter the delay until the packet was finally routed .
figure 2 is the most characteristic graphic result of this 
 case study , showing the probability of the delay in terms of cdf ( cumulative 
 distribution function ) versus time .
it is evident from figure 2 that the network is not able to cope with two 
 simultaneous emergency sessions .
the delay of mpeg video service is constantly 
 increasing , while this trend shows no tendency to decrease or at least 
 stabilize . at this point
, we should conduct a brief analysis of the network 's structure and 
 capabilities . due to
enhanced uplink 's nature , the allocation of excessive bit 
 rate ( above 1 mbps ) to a single session raises a series of issues .
enhanced uplink 
 is  as far as its capacity is concerned  an interference limited system .
this 
 interference caused by every emission is additive and the main sources 
 contributing to the build up of this summation were the ue 's of the cell , which 
 utilized the system 's resources and the interference from other cells . by 
 allocating high bit rate to one ue ( which needs a high - power allocation to achieve 
 this bit rate ) ,
usually this session increases dramatically the interference in 
 the cell , consuming a large portion of the rot margin . by exceeding or abusing rot , 

another high - bit rate allocation within the same tti is either no more 
 available in many cases , or marginally feasible in others .
this is the case 
 here , as the first session actually blocks the second one and vice versa per 
 tti , leading delay to an unacceptable level .
the previous conclusion will be 
 verified along with the second test case of this scenario .
the main difference is that the second emergency 
 session has been replaced by two new ( not emergency ) sessions with lower bit 
 rate requirements each , though the aggregate bit rate requirement is 
 approximately the same as above .
the delay results are shown in figure 3 . in figure 3 , the delay for all applications was kept in 95% of 
 the samples below 80 milliseconds and in 98% of the samples below 150 milliseconds 
 ( hereafter the term  delay  we mean the time one packet waits in the sender 's 
 buffer to be routed ) .
it seems that there has been a drastic overall 
 improvement of system 's performance due to the fact that each of the two new 
 sessions does not require high - bit rate allocation .
this result confirms the initial 
 assumption that enhanced uplink can not always sufficiently manage two demanding 
 sessions , as total throughput is not the ultimate decisive factor .
a rule of 
 thumb could be assumed , demonstrating that remote healthcare - oriented enhanced 
 uplink should bound bit rate allocation to 768 kbps per session , which is 
 satisfactory for almost all typical cases . from another point of view , most 
 contemporary commercial enhanced uplink platforms practically do not support 
 greater bit rates ( considering the fact that serving only one ue at any given 
 time is rather seldom ) .
there are 
 several solutions that may be applied to solve the aforementioned issue . among 
 them ,
the most efficient and realistic ones are 
 as smooth video 
 reception is of vital importance in emergency medical situations , the 
 transmission bit rate should be constrained to 512 kbps , which yields to a 
 quite adequate quality for this service.if a session demands 
 more than 768 kbps and consists of two or more applications , then these 
 applications could be automatically or manually torn down to two sessions , even 
 decreasing in some cases the total interference caused to the network . 
 supposing that the equivalent building blocks exist on the network 's and on the 
 terminal 's side and that appropriate user equipment is available ( e.g. , laptop 
 with two access cards ) , such an action is possible to be implemented.as a last measure , if 
 a finest quality video is considered to be necessary , then the network should 
 be tuned in such a way , while during video bursts ( or when the video delay 
 increases beyond a threshold value ) , all services would be prioritized according 
 to their significance , in order to temporarily mute low - priority services .
this 
 muting may also include voip if we use real - time video which includes audio 
 stream .
this is considered to be a worst case and clearly suboptimum congestion 
 control measure . 
 
as smooth video 
 reception is of vital importance in emergency medical situations , the 
 transmission bit rate should be constrained to 512 kbps , which yields to a 
 quite adequate quality for this service .
if a session demands 
 more than 768 kbps and consists of two or more applications , then these 
 applications could be automatically or manually torn down to two sessions , even 
 decreasing in some cases the total interference caused to the network . 
 supposing that the equivalent building blocks exist on the network 's and on the 
 terminal 's side and that appropriate user equipment is available ( e.g. , laptop 
 with two access cards ) , such an action is possible to be implemented . as a last measure ,
if 
 a finest quality video is considered to be necessary , then the network should 
 be tuned in such a way , while during video bursts ( or when the video delay 
 increases beyond a threshold value ) , all services would be prioritized according 
 to their significance , in order to temporarily mute low - priority services .
this 
 muting may also include voip if we use real - time video which includes audio 
 stream .
this is considered to be a worst case and clearly suboptimum congestion 
 control measure .
the 
 parameters for this simulation run are depicted in table 9 , supposing that for this kind of session , voip and 
 video services of 12.2 and 512 kbps were needed .
a stream service of 10 kbps 
 for common workspace management controls was also included .
finally , during the 
 session 27 mb of data were transmitted from a database .
these data were 
 distributed as follows : 100 kb for demographic data , 1 mb for laboratory , 
 clinical data , and medical history , 24 mb of prerecorded medical video for diagnosis 
 and medical images , as described in table 4 .
in addition , results from this scenario are given in 
 figures 4 and  
 5 .
according to figure 4 , enhanced uplink network can easily handle the 
 traffic required to sufficiently serve all services for this scenario . the 
 delay for each separate application running within the primary session was low , 
 as 95% of the samples
have a delay below 40 milliseconds , while 98% of the 
 samples have a delay below 50 milliseconds .
served throughput equals actually the 
 nominal bit rate of each application and it was extremely steady . conclusively , 
 enhanced uplink definitely surpasses the demands of this scenario by providing 
 adequate quality of service for all the services of our session . on the other hand , one 
 problem becomes noticeable by observing figure 5 . in order to acquire the 27 mb from database ,
this comes as no surprise , as from the previous 
 scenario the maximum bit rate allocation has been bounded to 768 kbps . due to 
 the fact that mpeg video utilizes 512 out of the total 768 kbps , control tools 10 
 and voip 12.2 kbps , about 230 kbps remain for other data . at this speed ,
although the size of 27 mb 
 is considered high , it might represent an important portion of an ehr , 
 necessary for a teleconsultation session .
undoubtedly , a physician does not 
 have the luxury to spend so much time for file transfer .
the obvious one is to place db transaction 
 services at a different session . this way the transaction will finish much 
 earlier ( as 27 mb divided by 768 kbps yields a result of less than 5 minutes ) . 

the interference induced by this new session to the network was not an 
 important discouraging factor , as db transaction is a background service .
in 
 case the platform needs the resources , they will be immediately released simply 
 by temporarily cutting off the db transaction service ( the other session 
 containing voip + controls + mpeg video will not be affected by the interrupt ) . 

after the transaction 's end , the resources will be returned to the network in 
 order to be reused . in this simulation run , 
 the feasibility of mobile access to electronic health records via an enhanced 
 uplink network was examined .
the main attributes of this run are summed up in table 10 and afterwards figures 6 and   7 depict the results of this simulation .
the 60 mb of 
 data from the database were distributed as follows : 100 kb for demographic 
 data , 1 mb for laboratory , clinical data , and medical history , and the rest is 
 medical image and diagnostic video data , according to table 5 .
indicative of this statement is that 
 for the 95% of the samples the delay did not exceed 15 milliseconds , while the 
 equivalent value for the 98% was 30 milliseconds .
the services of our primary 
 session were background ( ftp and db transaction ) and do not require a great 
 quantity of dedicated resources .
the key feature of this 
 simulation run was the behavior of the db transaction service .
undoubtedly , 60 mb is a significant capacity of data , taking up a lot of time to be acquired 
 ( around 15 minutes , at a speed very close at the maximum allocated per session ) . 
 in the previous scenario , where we came across the same problem , we assigned a 
 separate session for the db transaction to be accomplished . at this point
, the particular 
 solution would not yield any significant gain due to the massive amount of 
 data . to achieve a decent time ( in the range of 4 - 5 minutes ) , the 
 equivalent speed would rise above 1.5 mbps , which is rather inapplicable , at 
 least for the time being in a real enhanced uplink platform .
conclusively , although 
 the system under examination was able to serve this scenario , the time needed 
 was impractical .
considering the low qos demanded by background services , one 
 may either compromise with this feature , or try a different angle of approach 
 by selecting another system for the massive transmission of background data . 

wimax or wilan platforms are ideal candidates in order to cooperate with enhanced 
 uplink and solve this issue .
in the present paper , a high - speed 3.5 g 
 simulation scheme for serving mobile healthcare applications is studied .
the 
 paper demonstrates the feasibility of utilizing a realistic enhanced uplink network 
 for such applications on a number of test cases , that is , emergency health 
 services , teleconsultation collaborative sessions between moving physicians , and 
 mobile access to electronic health records .
transmission of voice , real - time 
 video , biosignals and transfer of files has been taken into account .
the performance 
 of the proposed scheme has been evaluated mainly in terms of delay under 
 different load and services requirements .
the simulation campaign proved that a 
 careful system design is indispensable in order the system to have the ability 
 to sufficiently cope with the supplied load . summarizing the provided results
, it was evident 
 that enhanced uplink successfully coped with all the test cases examined .
the end - to - end 
 delays in all cases were quite satisfactory , apart from the first test case of 
 the first scenario .
this particular simulation run proved that assigning high bit 
 rate to a single session leads to a deterioration of the overall system 's 
 performance . to face this issue and to optimally
manage the network 's 
 resources , the maximum allocated bit rate per session was bounded to 768 kbps 
 and the maximum proposed video bit rate was 512 kbps , unless better quality may 
 be explicitly required .
derived by the second scenario and driven by the fact 
 that ehr transaction services need to be served within a reasonable amount of 
 time , the necessity of a separate session to be occupied by this kind of 
 services was obvious .
finally , although enhanced uplink was able to serve all 
 types of file transfers , massive file transfers induce significant delays for 
 their accomplishment .
this remark reinforces the prospect of a collaboration of 
 enhanced uplink with another platform , such as wimax , to achieve the 
 improvement of the provided quality of service . conclusively ,
enhanced uplink managed to meet 
 the requirements for remote healthcare applications , serving adequately the 
 generated load .
consequently , it can serve as a new generation technology for mobile 
 health systems providing immediate and ubiquitous health care in a range of 
 different circumstances , as it may handle a variety of telemedicine needs , 
 especially in the fields of emergency health care provision in ambulances , 
 rural hospital centers or any other remote and dispersed located health center , 
 and intensive care patients monitoring .
as a future work , the proposed scheme could be evaluated in a more 
 real - life experimental scenario , where an adequate number of users can access 
 the hsupa network .
the above scenario incorporates multicell planning , where 
 the location of the users can be chosen so as to evaluate the effect of mutual 
 interference , handover , and power control problems .
part of future investigation as well could be 
 the integration of the standard h.264/mpeg-4 avc in the simulation procedure , which 
 achieves significantly higher compression and may partly alleviate some of the 
 described problems .
furthermore , 
 in order the results to be more reasonable for the forthcoming networks , we 
 would like to provide further experimentation facts considering medical data 
 provision over heterogeneous access networks like 802.16 .
 the present paper studies the prospective and the performance of a forthcoming high - speed third generation ( 3.5 g ) networking technology , called enhanced uplink , for delivering mobile health ( m - health ) applications . 
 the performance of 3.5 g networks is a critical factor for successful development of m - health services perceived by end users . in this paper 
 , we propose a methodology for performance assessment based on the joint uplink transmission of voice , real - time video , biological data ( such as electrocardiogram , vital signals , and heart sounds ) , and healthcare records file transfer . 
 various scenarios were concerned in terms of real - time , nonreal - time , and emergency applications in random locations , where no other system but 3.5 g is available . 
 the accomplishment of quality of service ( qos ) was explored through a step - by - step improvement of enhanced uplink system 's parameters , attributing the network system for the best performance in the context of the desired m - health services . 
1. INTRODUCTION
2. NEXT GENERATION WIRELESS
TELEMEDICINE TECHNOLOGY AND REMOTE
HEALTHCARE REQUIREMENTS
3. 3.5G m-HEALTH SCENARIOS
4. DESCRIPTION OF THE SIMULATION MODEL
5. SIMULATION RESULTS AND
NETWORK EVALUATION
6. CONCLUSIONS