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Temporal Diversity Coding for Improving the Performanceof Wireless Body Area Networks
Gabriel E. ArroboDepartment of Electrical
EngineeringUniversity of South Florida
Tampa, [email protected]
Zygmunt J. HaasSchool of Electrical andComputer Engineering
Cornell UniversityIthaca, New York
Richard D. GitlinDepartment of Electrical
EngineeringUniversity of South Florida
Tampa, [email protected]
ABSTRACTWireless Body Area Networks (WBANs) promise a signifi-cant improvement in the reliability of monitoring and treat-ing people’s health. A WBAN comprises a number of in-telligent biosensors and actuators that may either be im-planted in vivo or mounted on the surface of the humanbody, and that are capable of wireless communication toone or more external nodes that are in close proximity tothe human body. In this paper, we propose a new and effi-cient feedforward error-control technology, Temporal Diver-sity Coding (TDC), to increase the robustness and reliabilityof Wireless Body Area networks. Temporal Diversity Cod-ing applies Diversity Coding in time and space to improvethe WBAN’s performance. We demonstrate that by im-plementing this novel technique, we can achieve significantimprovement (∼ 50%) in throughput compared to extantWBANs.
Categories and Subject DescriptorsC.2.1 [Computer-Communication Networks]: NetworkArchitecture and Design—Network communications, Wire-less Communication; C.4 [Performance of Systems]: Per-formance attributes, Reliability, availability, and serviceabil-ity.
General TermsPerformance, Reliability.
KeywordsWireless Body Area Networks, Diversity Coding, Perfor-mance, Probability of Success, Reliability.
1. INTRODUCTIONA Wireless Body Area Network (WBAN) is a collection oflow-power, intelligent devices, such as sensors or actuators,which are located in, on, or in close proximity to, the hu-man body and are wirelessly interconnected [1]. As is shown
in [2], typically, the information collected by the sensor (im-planted or body surface node) has to be transmitted overa two-hop network to reach the external node via a bodysurface node.
In this paper, we discuss and analyze the application and ef-fect of Diversity Coding [3] on the performance of WBANs,and propose the Temporal Diversity Coding scheme (TDC),a novel technique that applies Diversity Coding in time anduses multiple paths to enhance the performance of WBANs,especially for emerging real-time in vivo traffic such as (1)streaming real-time video during surgery, and (2) measurement-response applications. The latter application requires feed-back on a small time-scale, such as cardio-feedback applica-tions, where the remote control system needs to react to fastchanges in the biological/physiological parameters and ac-tuate an in vivo mechanism. Because of the nature of thesetime-sensitive applications and the fact that some sensorsmay be able to transmit but not to receive, retransmissionsmay not be possible. Moreover, the throughput is oftenreduced because the tissues and organs within the humanbody affect the signal propagation and integrity from the invivo sensor to the destination/gateway. This was demon-strated in [4] where the channel impulse response and theattenuation change with the location of the receiver. An ex-ample of an implementation of in vivo real-time application,where TDC can improve the communications performance,is the MARVEL (Miniature Anchored Robotic Videoscopefor Expedited Laparoscopy) [5] research platform developedat USF. MARVEL decreases the surgical-tool bottleneck ex-perienced by surgeons in state-of-the-art Laparoscopic En-doscopic Single-Site procedures for minimally invasive ab-dominal surgery.
The paper is organized as follows. In section 2, we presenta summary of Diversity Coding, and an overview of our ap-proach. The Temporal Diversity Coding scheme (TDC) toincrease the performance of WBANs is presented in Section3. Section 4 presents simulation results of the performanceof TDC in WBANs. Finally, in Section 5 we present ourconclusions.
2. RELATED WORKDiversity Coding [3] (DC) is an established feedforward spa-tial diversity technology that enables near-instant self-healingand fault-tolerance in the presence of link and node fail-ures. The protection paths (ci) carry information that isthe combination of the uncoded data lines (dj). For exam-
Permission to make digital or hard copies of all or part of this work forpersonal or classroom use is granted without fee provided that copiesare not made or distributed for profit or commercial advantage and thatcopies bear this notice and the full citation on the first page. To copyotherwise, to republish, to post on servers or to redistribute to lists,requires prior specific permission and/or a fee.BODYNETS 2012, September 24-26, Oslo, NorwayCopyright © 2012 ICST 978-1-936968-60-2DOI 10.4108/icst.bodynets.2012.249937
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ple, in a DC system with N data lines (j = 1, 2, . . . , N)and one protection line (i = 1), if any of the data lines fails(e.g., d3), the failure detector detects the problem (e.g., lossof signal) and informs the receiver about the failure of d3.The destination (receiver), through the protection line (c1),can recover the information of the data line that was lost(d3) by taking the mod 2 sum of all of the received signals
(d3 = d1 ⊕ d2 ⊕ . . . ⊕ dN ⊕ c1). This model can be gener-alized as a M− for −N Diversity Coding system as shownin [3]. As we will show later in this paper, Diversity Codingmay also be used to provide time diversity. More generally,we can say that the M protection packets are the combina-tion of data packets {d1, d2, . . . , dN}, where each protectionpacket is calculated as [3]:
ci =∑N
j=1 βijdj i ∈ {1, 2, . . . ,M} (1)
where ci and dj are protection (diversity coded) and data(uncoded) packets, respectively. As in [3], the β coefficients
are given by βij = α(i−1)(j−1) and α is a primitive elementof a Galois Field GF(2q). All the operations in DiversityCoding are performed over a Galois Field GF(2q), whereq ≥ dlog2(N +M + 1)e. The total number of transmittedpackets is equal to the number of data packets plus the num-ber of protection packets (N + M), where the number ofprotection packets is typically less than the number of datapackets (M ≤ N). So, the β matrix for i = {1, 2, . . . ,M}and j = {1, 2, . . . , N} is:
[βij ] =
1 1 1 . . . 1
1 α α2 . . . α(N−1)
1 α2 α4 . . . α2(N−1)
......
.... . .
...
1 αM−1 α(M−1)2 . . . α(M−1)(N−1)
(2)
Notice that (2) represents the Discrete Fourier Transformmatrix on a Galois Field with respect to the primitive ele-ment α.
3. TEMPORAL DIVERSITY CODING FORINCREASING THE PERFORMANCE OFIN VIVO WIRELESS COMMUNICATIONS
Without some form of coding, if a sensor incurs a packetloss, the throughput is always reduced. Moreover, becauseof the real-time nature of these applications, retransmissionis not always feasible. To overcome the effects of packetloss, one can use several schemes. For example: one can usespatial diversity with multiple paths, so the same informa-tion is transmitted to the destination through different nodes(links. Alternatively, one can transmit additional (extra) re-dundant copies of the original (uncoded) packets. However,since there is no a priori knowledge about which packets willbe lost during the transmission, as with classical communi-cations, a coded scheme, such as Diversity Coding, appliedto the additional (extra) packets could be beneficial.With this in mind, we take as a frame of reference theWBAN topology proposed by the IEEE P802.15 WorkingGroup in [2], and we investigate the proposed Temporal Di-versity Coding (TDC − 2) model of Fig. 1, where “2” repre-sents the number of relays that help to transmit the sourcepackets towards the destination. Each sensor transmits in-dependently, but may use the same relays.
Video
capsule
Relay
R1
Destination
Body surface node
External node
Implanted node
Pacemaker
EMG
Relay
R2
In vivo – Body
surface link
Body surface
– External link
Figure 1: Temporal Diversity Coding: NetworkTopology.
The system model, as depicted in Fig. 1, applies Diver-sity Coding only in the time mode. It transmits the samepackets through multiple paths with the aim of enhancingthe throughput and reliability of real-time in vivo applica-tions such as medical imaging and capsule endoscope. Thescheme also increases the energy efficiency of transmitting amessage, while minimizing the delay. Since coding is appliedat the packet level, Diversity Coding provides time diversityinstead of spatial diversity as in [3]. Reliability is increasedby using multiple relays (paths). Because of the complexityand energy constraints of these in vivo sensors, the reliabil-ity should be maximized while the sensor’s energy to trans-mit the message should be minimized. Temporal DiversityCoding promises improvement in these two parameters, in-cluding improved reliability in the presence of link and nodefailures. The throughput is calculated as the sum of all re-ceived packets that add new information at the destination.Additionally, Diversity Coding is a feed-forward technologywhere protection packets are transmitted and no retransmis-sion is required for the destination to be able to decode theinformation.
In TDC−K, the source node (e.g., an implanted node) hasa block of information (e.g., N data packets) to transmitto the destination through each of the K relays. So, thesource (S) starts to transmit the N data packets to the Rk
relays1, where k ∈ {1, 2, . . . ,K}, and simultaneously usesthose data packets to create the M protection packets thatare transmitted to the relays after the N data packets havebeen transmitted. The ci protection packets are created us-ing Eq. (1). The computational complexity needed to createthe protection packets is low since the β coefficients in Eq.(2) are known by the source and the destination nodes, andno randomness is required for choosing the coefficients. Thisis in contrast with the case of Network Coding (Random Lin-ear Network Coding [6]). Moreover, the protection packetslength is the same as the data packets and no extra infor-mation such as the β coefficients needs to be included in thepacket’s header. However, it is necessary to include properlyinclude a sequence number in the identification field (packetheader) for the destination to reassemble the packets intothe original block of information.
The Rk relays regenerate the received signal and transmit
1Because of physical and practical constraints, K should bekept low.
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to the destination only the data and protection packets thatare error free. The packets include a cyclic redundancycheck (CRC) to detect bit errors, and erroneous packets arediscarded. Diversity Coding operations, such as decodingand/or encoding, are not performed at the relays. How-ever, the relays detect and compute the CRC to determinewhich packets are in error and should be discarded. Errorcorrection techniques at the bit level can be combined withTDC −K to improve the network’s performance. However,we have not included any bit level error correction techniquein this study because of the computational complexity, en-ergy consumption, and processing time required to code anddecode the bits at the source, the relay, and the destinationnodes. For instance, each relay would need to decode thereceived bits (including deinterleave them), correct any biterrors (according to its error correction capability), checkthe CRC and, if the packet has no errors, code the bits (in-cluding interleave them) and transmit the packet.
To reassemble the original information, the destination (D)receives data and protection packets from the Rk relays andaccepts all the error-free packets. The number of correctlyreceived data and protection packets depends on the proba-bility p(SRk) of link transmission loss between source S andrelay Rk and the probability p(RkD) of link transmission lossbetween the relay Rk and the destination node D. The prob-ability of link transmission loss p is a function of the trans-mission power, channel conditions, modulation scheme, andpacket’s length.
Let N and M denote the number of correctly received dataand protection packets, respectively, where N ≤ N andM ≤ M. To be able to decode the entire block of informa-tion (N), the destination needs to correctly receive at least
N data and/or protection packets, where N ≤ N + M ; oth-
erwise only N information packets can be recovered. Thatis, the useful information is given by:
I =
{N N ≤ N + M
N o.w.(3)
Although the destination receives data and protection pack-ets, the protection packets provide useful information if andonly if N ≤ N + M . Thus, we define another metric, calledutilization, to find the percentage of useful information thatcan be recovered from the correctly received packets. Theutilization can be calculated as:
ρ =I
N + M(4)
The probability of successful reception at the destination isgiven by the total number of useful data packets received atthe destination to the total number of information packetstransmitted by the source (N + M) ratio. We have math-ematically characterized in Eq. (5) the probability of suc-cessful reception at the destination (Ps), for the TDC − 1scheme, as a function of the probability of link transmissionloss, where pk is the probability of transmission loss of pathk between the source and the destination nodes and for atwo-hop communication path:
Ps =
N−1∑t=1
(t
N +M
)(N +M
t
)pk
t(1− pk)N+M−t
+
N+M∑t=N
(N +M
t
)pk
t(1− pk)N+M−t (5)
where pk is equal to (1− pSRk )(1− pRkD).As we can see, this probability distribution is characterizedby the binomial probability distribution function. The gen-eralization of the probability of successful reception at thedestination for the TDC − K scheme is given by the mul-tivariate binomial distribution, where K is the number ofvariables in the multivariate binomial distribution.
The expected number of correctly received information pack-ets at the destination, which is calculated as the productof the number of original packets (N) and the probabil-ity of successful reception at the destination, along withthe utilization and DC coding rate metrics, can be usedto optimize the performance of the network.We define the
“DC code rate” as the ratio of data packets to the numberof transmitted packets (data plus protection packets) i.e.,DCcoderate = N
(N+M). As it is well known, any coding
technique adds overhead into the system and therefore, re-duces the maximum efficiency that a coding technique canachieve, while increasing the goodput of the network. Thatis, the DC code rate is also the maximum efficiency of theTDC −K scheme because it indicates how much overheadhas been added to the system.
In the following section, we present the simulation resultsfor a range of network parameters, such as: the number ofcoded packets, the number of relays, the modulation scheme,and the ratio of the energy per bit to noise power spectraldensity.
4. RESULTSThe results presented here were obtained through averag-ing 1,000 simulation runs. We used the MATLAB commu-nications toolbox for the modulation schemes (4-PSK and16-QAM), the additive white Gaussian noise channel model(AWGN), and the Galois Field operations in our simula-tions. The topologies presented in [2] and Fig. 1 (singlepath and multiple paths topologies, respectively) were con-sidered for comparing network performance. We assumedthat the source node transmits blocks of information of 10packets (N = 10) and the diversity coding operations wereperformed over a Galois field GF(28). Also, we assumed thatall the links have the same average performance (Eb/N0).
We compared the performance of the Temporal DiversityCoding (TDC− 2) scheme with the following other commu-nication models: i) The single path uncoded model, wherethe information is transmitted uncoded with the assistanceof only one relay. The information is transmitted from thesource node (e.g., implant) to the destination (e.g., externalnode) via a relay (e.g., body surface node). This communi-cation mode incurs no additional overhead because no extraredundant packets (coded packets) are transmitted. We re-fer to this model as “U − 1”; ii) The single path DiversityCoded model where the source node uses Diversity Codingto code the packets (as explained in section 2), and trans-mits the data (uncoded) and protection (coded) packets tothe destination via a relay. This communication mode incursoverhead of N
N+M. We refer to this model as “TDC − 1”;
and iii) The multiple relay paths uncoded model is wherethe source transmits its information (uncoded) to the des-tination through spatially different paths with the help oftwo relays as is shown in Fig. 2. No information is coded inthis scheme. We refer to this model as “U − 2”, where 2 is
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7th International Conference on Body Area Networks, BodyNets-2012 Oslo, Norway September 24–26, 2012
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
6.0 6.4 6.8 7.2 7.6 8.0 8.4 8.8 9.2 9.6 10.0
Pro
ba
bil
ity o
f S
ucce
ss (
Ps)
Eb/N0 (dB)
U-1 (10 data packets)U-2 (10 data packets)TDC-1 (5 protection packets)TDC-1 (10 protection packets)TDC-2 (5 protection packets)TDC-2 (10 protection packets)
Figure 2: Comparison of the Probability of successfor Temporal Diversity Coding (TDC − 2) and theother 3 schemes (U − 1, U − 2, TDC − 1).
the number of relays that help to transmit the informationtowards the destination.
First, we compare the performance of the 4 schemes (U − 1,U −2, TDC−1, TDC−2) as a function of the Eb/N0 (Fig.2). Temporal Diversity Coding (TDC − 2) outperforms theother three schemes. TDC − 2 requires about 3.6 dB lessEb/N0 than the single path uncoded scheme to receive theentire message. In other words, with the same Eb/N0, e.g.,7.6 dB, TDC − 2 achieves full throughput and maximumefficiency at a 1/2 DC code rate. Also, we can see that bytransmitting the packets through multiple paths about 12%improvement in throughput is achieved, Temporal DiversityCoding TDC − 1 (1/2 DC code rate) provides about 18%improvement in throughput, and the combination of thesetwo techniques [TDC−2 (1/2 DC code rate)] provides a 43%improvement in throughput. As expected, we can see in Fig.2 that there are regions where TDC − 1 outperforms U − 2.That is the case when the Eb/N0 is greater than 7.5 dB.Therefore, it is preferable to use Temporal Diversity Coding(TDC − 1) instead of two paths (U − 2). Figure 3 showsthe performance, in terms of efficiency and utilization, ofU − 2 and TDC − 2 schemes. As we can see, the efficiencyof both schemes (U−2 and TDC−2) increases with the en-ergy per bit to noise power spectral density (Eb/N0). How-ever, for Eb/N0 larger than a certain value, the efficiencyof TDC − 2 remains constant. For example, for Eb/N0 of7.2 dB or larger, TDC − 2 1/2 achieves its maximum effi-ciency (50%). For the U − 2 scheme, 100% efficiency can beachieved for Eb/N0 of 9 dB or larger because all the packetstransmitted by the source contain useful information (datapackets). However, the U − 2 scheme requires larger Eb/N0
than TDC − 2 to improve the performance of the system.
5. CONCLUSIONSIn this paper, we proposed the Temporal Diversity Coding(TDC − K) scheme, a novel technique that utilizes Diver-sity Coding in time through K spatially independent pathsto achieve improved network performance by increasing thenetwork’s reliability and minimizing the delay. Wirelessbody area networks (WBANs) are an attractive applicationfor Temporal Network Coding because of the requirement for
0%
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50%
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100%
0% 10% 20% 30% 40% 50% 60%
Eff
icie
ncy
Utilization
U-2 (10 data packets)
TDC-2 (1 protection packet)
TDC-2 (2 protection packets)
TDC-2 (5 protection packets)
TDC-2 (10 protection packets)
Eb/N0=7.2 dB
Eb/N0=7.4 dB
Eb/N0=7.6 dB
Eb/N07.9 dB
Eb/N08.2 dB
Figure 3: Efficiency vs. Utilization for an uncoded(U) and Temporal Diversity Coding (TDC) schemesfor a 2-path system.
low complexity, limited power, and high reliability that thistype of networks in real-time applications such as capsule en-doscopy and video/medical imaging where retransmissionsare not a good alternative.
The Temporal Diversity Coding scheme features: 1) lowcomplexity because the Diversity Coding coefficients implic-itly known to the source and destination nodes; 2) limitedpower consumption because smaller Eb/N0 is required to re-cover the entire message; 3) better reliability because of theuse of a cooperative relays that help to transmit the pack-ets from the source to the destination node; and 4) real-time transmission because of the reduced complexity of thescheme, allowing processing on low-power nodes.
6. REFERENCES[1] IEEE 802.15 WPANTM task group 6 (TG6) body area
networks. http://www.ieee802.org/15/pub/TG6.html.
[2] IEEE P802.15 Working Group for Wireless PersonalArea Networks (WPANs). Channel model for body areanetwork (BAN). Technical report.
[3] E. Ayanoglu, C. I, R. Gitlin, and J. Mazo. Diversitycoding for transparent self-healing and fault-tolerantcommunication networks. IEEE Transactions onCommunications, 41(11):1677–1686, 1993.
[4] T. Ketterl, G. Arrobo, A. Sahin, T. Tillman, H. Arslan,and R. Gitlin. In Vivo wireless communicationchannels. In 2012 IEEE 13th Annual Wireless andMicrowave Technology Conference (WAMICON), pages1–3, 2012.
[5] C. A. Castro, S. Smith, A. Alqassis, T. Ketterl, YuSun, S. Ross, A. Rosemurgy, P. P. Savage, and R. D.Gitlin. MARVEL: a wireless miniature anchored roboticvideoscope for expedited laparoscopy. In IEEEInternational Conference on Robotics and Automation(ICRA), 2012, pages 1–6, 2012.
[6] T. Ho, M. Medard, R. Koetter, D. Karger, M. Effros,J. Shi, and B. Leong. A random linear network codingapproach to multicast. IEEE Transactions onInformation Theory, 52(10):4413–4430, 2006.
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