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Enhancement of Emergency TelemedicineDiagnosis Using 3G+ Mobile Systems

Venkatapathy Prithiviraj, Bharani Kumar Gnanasekaran,Mohan Kumar Murthy and Mohan Devanathan

Department of Electronics and Communication Engineering, PondicherryEngineering College, Puducherry 605014, India;e-mail: {principal, bharaniece07, mohankumarece07, mohanece07}@pec.edu

Received 3 October 2011; Accepted: 30 November 2011

Abstract

Mobile telemedicine is used in cases of emergency when an ambulance needsto communicate with an expert doctor present at a distant location. With thepresent day telemedicine systems lacking a framework that can handle allthe types of data like real time video, audio and heavy data like MagneticResonance Image (MRI), X-ray scans, live cardiograms, and other types ofmedical data, it becomes necessary to design a telemedicine system that cantackle all the problems and provide a robust telemedicine system. This pa-per focuses on providing an efficient mobile wireless telemedicine systemusing 3G+ mobile systems based on High Speed Downlink Packet Access(HSDPA) technology. The telemedicine system can handle real time audio,video streaming, interactive data and background traffic which are essentialdata traffic involved in a telemedicine system. The latency, jitter associatedwith the network is reduced without affecting the throughput by analyzingthe packet scheduler available at the network layer of the UMTS-HSDPAnetwork and various packet scheduling algorithms are tested. The mobiletelemedicine system along with real time channel conditions and backgroundtraffic has been simulated in QualNet Developer Network Simulator.

Keywords: HSDPA, jitter, latency, packet scheduler, wireless.

Journal of Green Engineering, Vol. 2, 139–154.c© 2012 River Publishers. All rights reserved.

140 V. Prithiviraj et al.

1 Introduction

Telemedicine is a rapidly growing application of clinical medicine that en-ables the transfer of medical information through an interactive audio-visualmedia for the purpose of consulting and for remote examinational proced-ures. Existing telemedicine systems which use fiber optic broadband systemslack mobility to the patient or the user and satellite communication basedsystems exhibit large latency. One major constraint for telemedicine systemsis the latency when a real time video or real time audio is transmitted, whichneeds to be maintained well below the threshold levels to provide satisfactorycommunication link between the patient and the doctor.

The wireless communication system can solve the mobility issues of thetelemedicine system while bandwidth offered by wireless systems is restric-ted and also has drawbacks like packet loss, high latency, and jitter. To solvesuch issues an efficient telemedicine system using the High Speed DownlinkPacket Access (HSDPA) system based on the 3rd Generation PartnershipProject (3GPP) has been proposed which provides high data rates of the orderof up to 14.4 Mbps on the downlink.

The cause for the latency is the management of queue present betweenthe MAC layer and the network layer in the core UMTS network. The goal ofthe packet scheduler is to maximize the network throughput while satisfyingthe Quality of Service (QoS) of the users. The latency and jitter of severalof types of data over the telemedicine link has been reduced using proper IPPacket scheduling algorithms in the UMTS core network.

In the proposed system in this paper, the QoS classes are mentioned fordifferent types of flows of data in the telemedicine link and priority bits areattached to their IP headers and weights are assigned to each type of flow. Thescenario of a moving ambulance with Rayleigh physical channel conditionscommunicating with a doctor available on the IP network is considered in theproposed system. The proposed telemedicine system is shown in Figure 1.

2 Packet Scheduling Algorithms

The HSDPA scheduler, which resides in Node B, is the key to resourcemanagement in the UTRAN downlink because it decides which user is to bescheduled in each transmission time interval (TTI). The scheduling decisiondoes not take into account only the channel conditions, but additional factorssuch as fairness between users, cell throughput, and QoS parameters aretypically considered in the scheduling mechanism. The goal of the HSDPA

141

Figure 1 Proposed telemedicine system.

scheduler is to maximize the spectrum efficiency of the cell while maintainingthe QoS requirements for different data services. It is a fast scheduler whichcan make decisions on per TTI (2 ms) basis.

2.1 Slow Scheduling Methods

In Slow Scheduling Methods, the scheduling decisions rely on the averageuser’s signal quality (or they do not use any user’s performance metric at all).

2.1.1 Round Robin SchedulingThe Round Robin (RR) packet scheduler algorithm is the simplest one whichdistributes the scheduling turns equally among all active HSDPA users, re-gardless of the radio channel condition and the QoS requirements of theapplication running on the mobile devices. The fairness in time sharing ofthe system resource creates unfairness to those UEs which are under goodradio conditions and starving for throughput.

2.1.2 Strict Priority QueuingStrict priority queuing assumes that types of traffic can be differentiated andtreated preferentially. Separate FIFO queues are created for each defined pri-ority level and the arriving traffic is sorted into its proper queue as it arrives.Thus the first task of configuring strict priority queuing is to determine thetraffic classifications. More queues mean more complexity in running thealgorithm.

At the service side of the queue, the processing rule is simple: higher pri-ority FIFO queues are always processed to completion before lower priorityqueues are processed. For example, in a three-queue system, if the two highestpriority queues had no packets buffered, then the lowest priority queue wouldbe serviced. The moment a higher priority packet arrived in its FIFO queue,

Emergency Telemedicine Diagnosis Using 3G+ Mobile Systems


however, servicing of the lower priority packets would be interrupted in favorof the higher priority queue. Strict priority queuing is the gold standard forhigh priority traffic.

The greatest disadvantage relates to the way strict priority queuingtreats queues. High-priority packets are always processed before those ofless priority. If the amount of high-priority traffic is great, other queuesmight never empty, leading to worse performance for the low-priority andmedium-priority traffic than if a single FIFO queue were used.

2.2 Fast Scheduling Methods

In Fast Scheduling Methods, the scheduling decisions rely on UE channelquality measurements (i.e. executed on a TTI basis) that allow tracking theinstantaneous variations of the user’s supportable data rate. These algorithmshave to be executed in Node B in order to acquire the recent channel qual-ity information. These methods can exploit the multiuser selection diversity,which can provide a significant capacity gain when the number of timemultiplexed users is sufficient.

2.2.1 Weighted Fair QueuingWeighted Fair Queuing (WFQ) is a packet scheduling technique allowingguaranteed bandwidth services. The purpose of WFQ is to let several sessionsshare the same link. WFQ is an approximation of Generalized ProcessorSharing (GPS). It is based on a fluid model, so it assumes that the inputtraffic is infinitely divisible and that all sessions can be served at the sametime. Since each session has its own queue, an ill-behaved session (which issending a lot of data) will only ‘punish’ itself and not other sessions. This is awork-conserving server and it guarantees that each session receives a servicerate gi of at least:

gi = θi∑N

j=1 θj

r

where r is the server rate and θ i is the weight for the ith session. The sched-uler picks a small piece of data from each session and transmits it to theoutput link.

From an implementation point of view, the slow scheduling methods havea lower degree of complexity than fast scheduling ones, because the latterrequire the information of the supportable data rate from the UE channelquality measurements for all the users in the cell, and later compute their

143

Figure 2 Comparison of Round Robin, strict priority and weighted fair scheduling algorithms.

priority on a 2 ms basis. In order to have access to such frequent and recentchannel quality measurements, the Packet Scheduler must be located in NodeB.

The graphs in Figure 2 show the theoretical value of end-to-end delay andthroughput of different scheduling algorithms.

• For weighted fair queuing, the end-to-end delay is less among the threealgorithms and the throughput is comparatively high.

• For strict priority queuing, the throughput is high than WFQ but theend-to-end delay is high than WFQ.

• For Round Robin, the end-to-end delay and the throughput is very highamong the three algorithms.

3 HSDPA Based Mobile Telemedicine System

The High Speed Downlink Packet Access (HSDPA) system based on thepacket data network has the ability to connect with the IP based Local AreaNetwork (LAN) which can be exploited to provide an efficient data con-nectivity between a mobile user and immobile user. The system is designedto handle all types of data real time audio, video, heavy data and backgrounddata for applications like email and the queue management is done by usingthe priority based scheduling algorithm.

The telemedicine system should be fault tolerant and a doctor shouldalways be connected to the patient. In case any failure occurs in the network,



Figure 3 Routing between UMTS and IP network.

then an alternate connection should be provided. Such a system is proposedin this paper.

3.1 Routing between UMTS and IP Networks

Usually, a routing protocol is not needed within the access network. Thenodes in the UTRAN, including UEs, Node B’s and RNCs learn theirconnectivity through UMTS signaling. However, the scenario has to beconfigured to enable routing of packets beyond the UTRAN.

There are two aspects in routing:

• A routing protocol is needed in the backbone core network of UMTSto enable routing between SGSNs, GGSNs, and HLRs, which may beseveral hops away from each other.

• IP Packet Data Networks (PDNs) have their own IP routing architecture.In order to route packets between the UMTS PLMN and IP networks,necessary routing information is needed, especially at the nodes onthe boundary between the PLMN and PDN. These requirements forboundary nodes are described below.

3.1.1 Boundary Node RequirementsRouting from UMTS PLMN to IP networks: The GGSN node needs to routepackets to the proper IP gateway node.

Routing from IP networks to UMTS PLMN: The following considera-tions apply for routing packets from IP networks to the UMTS PLMN:

• The IP routers usually do not know the individual IP addresses assignedto UMTS UEs. However, they need to know how to reach the UMTSPLMN network as a whole.

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• The IP address segments allocated to a UMTS PLMN are usuallystatically configured.

• The aggregate routing information for IP address segments of eachUMTS PLMN needs to be advertised to IP networks.

3.2 Inter Domain Routing

Routing by Making GGSN a Part of IP Network: In this configuration, theGGSN node of the UMTS PLMN is also included in the routing domain ofthe IP network. The GGSN node is also configured to be a gateway for theIP network. In order to configure the GGSN node as an IP gateway, it shouldhave at least one interface in each of the routing domains (UMTS and IPnetwork). The GGSN learns the routing information to IP nodes via the dy-namic routing protocol configured for the IP network. This method works forrouting packets from the UMTS PLMN to the IP network. However, packetscannot be routed from the IP network to the UMTS PLMN because the IPnodes do not know that the packets have to be routed to the GGSN node. Inthis case, static or default routes can be used to route packets from IP nodesto the UMTS PLMN.

3.3 Mobile Telemedicine Scenario in Qualnet

A mobile telemedicine system is the system in which the patient is mobileand is connected to the expert doctor at the other and all types of data needsto be transferred to the expert doctor to know the condition of the patient.The scenario considered here is that a patient is moving in an ambulancewhich is present on a HSDPA network and a doctor is available on the LANnetwork. The LAN network is introduced because the usage of the wirelessHSDPA network for the doctor who is immobile is inefficient as there is anincreased packet loss and latency due to the wireless channel conditions. TheIP based LAN network is connected to the UTRAN network using the methoddescribed in Section 5.3.2.

In Figure 4, Node 20 represents the HSDPA UE in the moving ambulanceand Node 26 represents terminal present in LAN network of the hospitalpremises.

3.4 Priority Assignment and Scheduling

The telemedicine system proposed can handle all the types of data that areneeded in a telemedicine system i.e. real time audio, video, heavy data and



Figure 4 Mobile telemedicine scenario using HSDPA and LAN in QualNet simulator.

background data. The problem that is encountered while handling all suchdata is the queue management at the network layer. An improperly managedqueue leads to extremely large latency and low throughput which will makethe system not suitable for operation.

The IP headers of the data packets of the different types of flows areassigned priority as shown in the following table.

The strict priority and weighted fair queue algorithms are the algorithmsthat are based on the priority which are used in the network for the purposeof packet scheduling.

3.5 Fault Tolerant System

The telemedicine system is a very crucial system and should be kept awayfrom failures. But there are chances that the data network may fail in the UT-RAN or in LAN system. In such cases the doctor should not lose connectivitywith the patient. For this purpose, if the telemedicine data system fails at anytime the system should at least have a circuit switched voice call between the

147

Figure 5 Flow diagram of the proposed telemedicine system.

doctor and user for immediate necessary communication. The flow diagrambelow summarizes the proposed telemedicine system.

4 Results and Simulations

The simulation commences with the setting up of the backbone UMTS net-work enabled with HSDPA capability. It is followed by the configuring of theNode B’s attached to the Radio Network Controller (RNC) for the handling



Table 1 Handover parameters.Parameter DescriptionMinimum cell selection RX level –95 dBmCell search threshold –80 dBmCell reselection hysteretic (dB) 3.0

Figure 6 Mobile telemedicine scenario.

of the soft handover. The HSDPA UE is attached to the respective Node B’s.The wireless channel is configured to be a Raleigh’s fading channel. TheLocal Area Network (LAN) is connected to the HSDPA backbone networkby configuring the GGSN as the default gateway and by making it as a partof the IP network. The simulation parameters are listed in Table 1.

Figure 6 shows a snapshot of the QualNet scenario of the mobiletelemedicine system simulated for a dimension of 1500 m × 1500 m. Tointroduce congestion two UMTS phone calls and one streaming CBR ap-plication were configured in the network between the rest of the users inthe network. The UE (mobile ambulance) is allowed to move with vary-ing velocity in the path shown in figure below with an average velocity of

149

Table 2 Telemedicine data traffic.S. No Type of data Data rate (Kbps) TTI (ms) Priority1 Conversational audio 14 10 6–72 Streaming video 128 10 4–53 Heavy data 47 10 1–34 Background data 47 10 0

Figure 7 Average end-to-end delay in the network.

60 km/h. The weighted fair queue algorithm is implemented in the differentstages of the backbone network. The fault tolerant system is simulated withan assumption that the data network fails after 3 seconds of the simulationtime and a voice call is established after the data flow stops.

In Figure 6 Node 20 represents the mobile ambulance and Node 26represent the terminal at the doctor’s end.

Table 2 shows the types of data that flows thorough the network and theirdata rates and their transmit time intervals (TTI).

4.1 Simulation Results of Mobile Telemedicine System

The simulation results of the mobile telemedicine system based on the HS-DPA and IP networks using the weighted fair queue algorithm for the packetscheduling have been shown in following figures. Table 3 shows the notationused in Figures 7–9.

The average end-to-end delay, jitter and the throughput of the networkhas been observed for the proposed telemedicine system.



Table 3 Representation of application.Type of data DescriptionConversational audio 1027Streaming video 1026Heavy data 1025Background data 1024

Figure 8 Average jitter in the network.

Figure 9 Throughput of the network.

4.2 Simulation Results of Fault Tolerant System

Figure 10 shows the snapshot of the fault tolerant system with Node 8 repres-enting the mobile ambulance and Nodes 10 and 14 represents the terminalspresent at the doctor’s end.

Figures 11 and 12 show the results of the fault tolerant system that hasbeen simulated on QualNet simulator.

5 Conclusion

In this paper we have proposed a HSDPA based emergency telemedicinesystem has been proposed with reduced latency and jitter without affectingthe throughput of the network. Simulation Results using Qualnet Simulatorshow that the system fault tolerant, robust and efficient.

We plan to conduct an in-depth analysis by considering two types ofhandoffs: soft (already supported in HSDPA network) and hard handoff (by

151

Figure 10 Fault tolerant telemedicine system.

Figure 11 Total packets received at the doctor’s end.

Figure 12 Establishment of a UMTS phone call.



forcing the radio link cut). With such tests we expect to refine the conclusionsmade in the present paper.

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Emergency Telemedicine Diagnosis Using 3G+ Mobile Systems 153

Biographies

Venkatapathy PrithivirajDr. Prithviraj is the Principal of Pondicherry Engineering College. He

completed his Bachelor of Engineering (Electronics and CommunicationEngineering) in 1972 from the College of Engineering, Guindy Madras Uni-versity, his M.S. by research in 1982 from IIT, Madras, and his Ph.D in 1999from IIT, Kharagpur (research area – Signal Processing Techniques in ArrayAntennas Systems).

He is one of the founding members of Pondicherry Engineering College.At present he is holding the position of Dean-in-charge, School of Engineer-ing, Pondicherry University. He has been teaching for over 28 years and heldthe position of Head of the Electronics and Communications EngineeringDepartment. He has published over 70 technical research papers.

He has also held the position of Director, IT for Government of Pon-dicherry (2002–2005). Currently, he is a Member of Expert Committee formonitoring International Indo-French projects in the field of InformationTechnology as well as Regional Committee of AICTE for Tamil Nadu andPondicherry.

He has a keen interest in research and development projects and providedleadership in many successful projects sponsored by various organiza-tions such as DRDO, ISRO, Department of Electronics and Department ofInformation Technology at IITs and PEC.

He is the recipient of the IEEE International Student Branch Award in1984 and the EDI Award for best technical paper, entitled “COFDM forTelemedicine Applications”, in 2007. He is a Life Member of ISTE andMember of EMC Engineers.

His areas of interest include Broad band and Wireless Communication,Mobile Computing, VLSI for Wireless Applications, Tele Medicine ande-Governance Applications.

Bharani Kumar Gnanasekaran received his B.Tech degree in Electronicsand Communication Engineering from Pondicherry Engineering CollegeAffiliated to Pondicherry University, Puducherry, India in 2011. He iscurrently working on Session Border Controllers in the Research andDevelopment wing of Sonus Networks. His primary research interests are inthe areas of VOIP, Wireless Communications and Networking.


Mohan Kumar Murthy received his B.Tech degree in Electronics andCommunication Engineering from Pondicherry University, Puducherry,India in 2011. He is currently working for Tata Consultancy Servicesas Assistant Systems Engineer. His research interests include areas ofcommunication systems and Networking.

Mohan Devanathan has completed his B.Tech in Electronics and Com-munication at Pondicherry University, India in 2011. His areas of interestsinclude cellular mobile communication, embedded systems and computernetworks.

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