Inter?WBAN Coexistence and Interference Mitigation

Bin Liu，Xiaosong Zhao，Lei Zou，and Chang Wen Chen

（1.Key Laboratory of Electromagnetic Space Information，Chinese Academy of Sciences，University of Science and Technology of China，Hefei 230027，China；2.Dept.of Computer Science and Engineering，The State University of New York at Buffalo，NY 14260?1604，USA）

Inter?WBAN Coexistence and Interference Mitigation

Bin Liu1，Xiaosong Zhao1，Lei Zou1，and Chang Wen Chen2

（1.Key Laboratory of Electromagnetic Space Information，Chinese Academy of Sciences，University of Science and Technology of China，Hefei 230027，China；2.Dept.of Computer Science and Engineering，The State University of New York at Buffalo，NY 14260?1604，USA）

With promising applications in e?health and entertainment，wireless body area networks（WBANs）have attracted the in?terest of both academia and industry.If WBANs are densely deployed within a small area，serious problems may arise be?tween the WBANs.In this paper，we discuss issues related to the coexistence of WBANs and investigate the main fac?tors that cause inter?WBAN interference.We survey inter?WBAN interference mitigation strategies and track recent re?search developments.We also discuss unresolved issues re?lated to inter?WBAN interference mitigation and propose fu?ture research directions.

wireless body area network（WBAN）；inter?WBAN interfer?ence mitigation；e?health

1 Introduction

T he world’s population is aging，and increased health care expenses are affecting the quality of life of elderly people.Thus，inexpensive health care solutions are urgently needed.Recently，wire?less body area networking（WBAN）has been proposed as one such solution.Physiological information，such as electrocardi?ography（ECG）signals，blood pressure readings，and body pos?ture signals，can be acquired by a WBAN and sent to a remote medical center for analysis and treatment［1］.This has the po?tential to relieve the pressure on public medical resources and increase convenience for patients.A WBAN could reduce the number of times a patient with a chronic disease needs to visit the hospital.

A WBAN also has other applications，such as somatic and virtual reality［2］，sports training and fitness analysis，and mili?tary applications［3］，［4］.

A WBAN comprises a coordinator node and several sensor nodes deployed on the body，within the body，or around the body.These nodes usually form a network with a star topology and single?hop communication.Sensor nodes collect informa?tion from the human body and transmit it to the coordinator node for processing.A typical WBAN architecture is shown in Fig.1.

The body?centric，health?related，mobile nature of WBANmeans there are some special requirements that need to be con?sidered when designing a WBAN system.First，energy efficien?cy needs to be reflected in the system design because sensor nodes only have limited?capacity batteries that are often incon?venient to recharge or replace（especially for implanted sen?sors）.Second，traffic in a WBAN primarily comprises vital signs；therefore，latency and throughput need to be guaranteed. Finally，a WBAN is heterogeneous because there are diverse nodes located in different positions，and these nodes have dif?ferent QoS requirements.There are also the differences be?tween WBAN users.Therefore，is necessary to design proto?cols that enable the data rate to be scaled and services to be differentiated for different sensor nodes and WBANs.

Common wireless technologies may not be suitable for use in a WBAN.For example，Bluetooth［5］only supports a limitednumber of terminal nodes and single?hop communication.It al?so consumes a lot of power［6］.Zigbee［7］does not sufficiently guarantee QoS or mobility［6］.The IEEE 802.15.6 Task Group published the WBAN standard in 2012.The purpose of this Task Group was to establish a communication standard opti?mized for sensors operating on，in or around both human and animal bodies.The standard ensures reliability，QoS，energy ef?ficiency，high data rate，and no interference in a variety of WBAN applications［1］.Many researchers have also investigat?ed WBAN?related topics，including model architecture［8］，PHY and MAC layer design［9］，［10］，adaptive route protocol［11］，and interference mitigation［12］，［13］.

Attached to the body，a WBAN moves as the hosts does.In a hospital or nursing home，coexistence of WBANs may cause problems.Adjacent WBANs may use the same channel simul?taneously because of limited frequency and dense distribution. Without scheduling or coordination between adjacent WBANs，intra?WBAN packet delivery may suffer.WBANs may also need to compete with other wireless networks for spectrum if both networks use the same spectrum band，e.g.，unlicensed 2.4 GHz ISM.Problems arising from the coexistence of WBANs and other wireless networks can be simplified by re?garding the WBAN as a uniformly distributed disturbance point because a WBAN is much smaller than other wireless networks.Some research on the coexistence of WBANs and other wireless networks has been done recently［14］-［16］. Problems arising from coexisting WBANs are more complex due to the fact that the scale of communication of different WBANs is similar and different inter?and intra?WBANs may have heterogeneous characteristics.Such problems hamper the widespread deployment of WBANs.

In this paper，we focus on problems arising from the coexis?tence of multiple WBANs and discuss related interference?mit?igation solutions.We also discuss research trends and unre?solved issues related to inter?WBAN coexistence.

In section 2，we describe inter?WBAN interference prob?lems in detail.In section 3，we introduce and compare inter?WBAN interference mitigation solutions.In section 4，we dis?cuss related open research issues.In section 5，we summarize and conclude the paper.

2 Problems Arising from the Coexistence of WBANs

Problems with coexisting WBANs occur for three main rea?sons：

1）a large number of WBAN users gathered together.Although WBANs usually only have a short communication range，they may still come close to each other in certain places，such as metro stations，hospitals，nursing homes，or retire?ment villages.If the WBANs are not scheduled properly，transmission collision may occur.

2）limited wireless resources.Most WBANs use the 2.4 GHz ISM band，which is also used by Wi?Fi，Bluetooth，and Zig?bee networks（Fig.2）.The problem is compounded because Wi?Fi APs have been widely deployed both in public places and at home.Therefore，there are insufficient collision?free channel resources to satisfy demand.

3）random mobility.In crowded and resource?limited environ?ments，reuse of frequency channels is inevitable.However，the random mobility of WBAN users breaks down the spatial isolation of co?channel WBANs.

The distance between WBANs and the distribution intensity of WBANs are both important factors affecting the degree of in?terference between two WBANs.In［17］，Muhammad et al.con?ducted experiments on the change in packet loss rate（PLR）in a WBAN in relation to the distance of the WBAN from other in?terfering WBANs.They found that the distance between WBANs noticeably affects the PLR in each WBAN.In［18］，the relationship between the number of interfering WBANs and packet error rate（PER）was analyzed.The authors found that densely distributed interference sources congest the chan?nel and cause high PER.Thus，closer inter?WBAN distance and denser distribution increases interference between WBANs and degrades communication.

Body movements and clothing give rise to a shadowing ef?fect，i.e.，lack of signal reflection，in a WBAN.The antenna an?gle greatly affects the received signal strength（RSS），which is given by the received signal?to?interference?plus?noise ratio（SINR）［19］.An unsuitable transmission angle may create seri?ous interference for other WBANs.In addition，the topology of a WBAN affects the degree of interference for other WBANs. For example，WBAN users form a line when queuing in a sta?tion or a ring when sitting around a table.In［20］，Wang et al. studied WBANs with a hexagonal lattice structure within an in?ter?WBAN mesh structure.Geometric probability was then used to model and analyze interference arising from coexis?tence of WBANs.In［21］，the power?law distribution model of the crowd was introduced to simulate the structure of multiple WBANs，and the distance?based distribution function of inter?ference probability was proposed to estimate the probability of inter?WBAN interference.

Apart from the previously mentioned external factors，there are some factors within a WBAN that significantly affect inter?WBAN interference.In［22］，De Silva et al.investigated the re?lationship between packet delivery rate（PDR），packet trans?mission rate，and number of interfering networks.They found that PDR decreases to as low as 65%for a transmission rate of 100 packets/s in a mission?critical WBAN situation.This re?duced to 60%when there were eight WBANs in the surround?ing environment.In［23］，Sarra et al.investigated transmission power，frequency of data transmission，and packet size in a WBAN when there was both heavy and light interference from the surrounding environment.They found that decreasing the packet size or frequency of data transmission can improve the expected transmission（ETX）and increase PDR.Increasing transmission power also increases the SINR.In［18］，the au?thors investigated SINR，BER，and probability of collision for TDMA，F(xiàn)DMA and CDMA access schemes when there was in?ter?piconet coexistence.The authors confirmed that interfer?ence from coexisting WBANs significantly degrades the perfor?mance of WBANs within the system.The experimental results showed that TDMA and FDMA are better choices than CDMA for mitigating interference when there are coexisting WBANs.

3 Solutions for Mitigating Interference Caused by Coexisting WBANs

As with intra?WBAN multiple access，inter?WBAN coexis?tence can be achieved by separating WBANs in the frequency，time，or spatial domains.In the following subsections，we dis?cuss frequency allocation，time scheduling and co?channel in?terference mitigation.Some other interference?mitigation strate?gies are also discussed.

3.1 Channel Assignment

In general，each WBAN should choose a wireless channel for intra?WBAN data transmission.Reasonable channel alloca?tion is the most straightforward way of avoiding inter?WBAN interference.A WBAN is assigned a channel that is different from an adjacent conflicting WBAN.In most scenarios，there is no centralized managing entity；therefore，channels need to be assigned in a distributed way.

In［1］，distributed channel?hopping mechanisms were de?scribed.Channel hopping is controlled by the hopping se?quence，which is generated by the generator polynomial based on the Galois linear feedback shift register（LFSR）.The WBAN coordinator may then change its operating channel peri?odically according to the Channel Hopping State and Next Channel Hop fields in its beacons without exchanging informa?tion.In［18］，［24］，［25］，some other random channel?allocation strategies can be found.These random channel hopping or allo?cation schemes are easy to implement and are well suited to an environment with a small number of WBANs.However，when WBANs are densely distributed and channel resources are lim? ited，randomized channel?assignment schemes lead to a high probability of channel conflict and significantly degrade perfor?mance.

Some other channel?assignment solutions use only self?mea?sured interference indicators，such as received signal strength indication（RSSI）and received signal?to?interference ratio（SIR），which can only be regarded as rough indicators of inter?fering WBANs.In［26］，the authors propose an interference?aware channel switching（inter?ACS）algorithm that senses whether WBANs are experiencing interference according to the SIR.Depending on the degree of SIR detected by the coor?dinator，various n?hop channels are assigned to WBANs.This results in better performance than that achieved using uniform or random channel allocation.

SIR?based methods are not well suited to crowd scenarios，in which more information about other interfering WBANs needs to be acquired to better allocate channels.In a distribut?ed situation，messages need to be exchanged between WBANs so that WBANs know the interference information of adjacent WBANs.In［27］，Deylami et al.proposed a distributed dynam?ic coexistence management（DCM）mechanism to improve the performance of coexisting WBANs.In DCM，each WBAN lis?tens the channel and extracts beacon information from other WBANs when it suffers beacon loss.If there is an insufficient gap for coexistence，the WBAN switches to another channel.In［28］and［29］，Movassaghi et al.designed a scheme based on the interference region（IR）for eliminating inter?WBAN inter?ference.In this scheme，each WBAN records the information of interfering nodes in the IR and shares this information with all the other WBANs in its vicinity.A channel?reuse strategy similar to that in cellular networks is then used.With this strat?egy，distant WBANs can use the same channel，and orthogonal sub?channels are assigned to WBANs that are close to each other and experiencing interference.

If more information is exchanged between WBANs，channel assignment can be modeled as a graph coloring problem.Net?work topology is modeled as a graph G=（V，E），where the ver?tex set V represents an individual WBAN，and the edge of set E of G shows that the two connected vertices（WBANs）conflict with each other if allocated the same channel.The colors of the graph show the channel resources.Hence，channel allocation can then be transformed into a graph coloring problem with fastest speed and least colors.In［30］，a Random Incomplete Coloring（RIC）algorithm with low time complexity and high spatial reuse was proposed.In this algorithm，quick inter?WBAN scheduling（IWS）is achieved through random?value coloring，and the reuse efficiency of channel resources is guar?anteed by incomplete coloring.In［31］，a combination of coop?erative scheduling and graph coloring was proposed to elimi?nate inter?WBAN interference.The main idea of this scheme is that adjacent WBAN pairs form a cluster that can allocate channels using the same method as that in［28］and further dis?tribute resources between clusters by using the graph coloringmethod.With graph coloring methods，perfect superframe syn?chronization is assumed.However，such synchronization can?not be guaranteed because of the randomness of WBANs.Fur?thermore，interference should also be detected while building the graph model.

By passing messages between WBANs，the channel?assign?ment scheme ensures a higher channel reuse rate.The main problem with this scheme is that effective channel allocation cannot be guaranteed in some scenarios，such as when WBANs are densely distributed or when frequency spectrum is scarce.Furthermore，frequent interference detection and infor?mation exchange consumes wireless resources and energy. Therefore，the channel?assignment scheme is only appropriate when there is a relatively large frequency spectrum to be allo?cated or when there is a relatively small number of coexisting WBANs.

3.2 Time Rescheduling

The TDMA?based scheme is usually used for intra?WBAN communication to avoid sensor collision.In such a scheme，non?overlapping time slots are allocated to different sensors for transmission.Similarly，inter?WBAN interference can also be mitigated by time rescheduling.When an individual WBAN oc?cupies the channel only part of the time，e.g.，during the chan?nel sensing period or inactive period of superframe in［1］，［5］and［7］，the other WBANs can temporarily access the channel to transmit data.This is a more efficient way of utilizing the channel.

In［32］-［37］，the authors use time rescheduling to mitigate inter?WBAN interference.In［32］，the authors propose a BAN?BAN interference mitigation（B2IRS）beacon?enabled strategy in which the coordinator of the WBAN collects information about adjacent WBANs at the end of superframe active time. In this way，multiple WBANs do not access the channel at the same time.In［33］，Kim et al.proposed an asynchronous inter?network interference avoidance scheme called AIIA.This scheme was implemented in the coordinator of the WBAN and maintained a table containing the time scheduling information about adjacent WBANs.Thus，every WBAN could transmit in a conflict?free time slot according to the information table.In［34］，information was exchanged between proximal coordina?tors of WBANs in order to arrange the transmission sequence of WBANs according to application priority.In［35］and［36］，Mahapatro et al.focused on the fairness between WBANs when there was an insufficient number of time slots.If all WBANs accessed the channel in a round?robin way according to their time slot requirements，WBANs with fewer nodes would have a long wait.The authors then proposed a scheme in which WBAN containing fewer nodes could occupy more time slots and found that average wait times between WBANs re?mained the same.In time?rescheduling solutions，complete and up to date information about adjacent WBANs is prerequi?site.In［37］，Wen et al.used a CSMA?like mechanism to trans? mit the beacon without collision caused by an incomplete neighbor list.

Some other contention?based time rescheduling approaches are found in［38］-［42］.In［38］，［39］，the listening strategy is similar to that in［32］；however the channel is sensed when the beacon needs to be sent.A Poisson distribution model is estab?lished to generate the probability of channel sensing.Then，the beacon is sent to reserve the channel once the channel is idle. However，if the channel is busy，there needs to be a wait peri?od before resensing.In［40］-［41］，Dong et al.modified the inter?WBAN time?scheduling scheme to uniformly access the chan?nel when there is no cooperation between WBANs.At the same time，an opportunistic relaying（OR）strategy was intro?duced to select the minimum interference link inside a WBAN.This enhances coexistence between WBANs.Howev?er，this scheme was not practical because links were selected according to channel measurements rather than a prediction scheme，and an increase in the number of relays had the poten?tial to sacrifice system performance.

Time scheduling requires complex arrangement strategies to avoid inter?WBAN interference.With scheduling?based meth?ods of inter?WBAN interference mitigation，frequent coordina?tion consumes a lot of energy.With contention?based methods of inter?WBAN interference mitigation，broadcasting informa?tion before accessing the channel consumes a lot of energy.In addition，it is also a challenge for a WBAN to obtain transmis?sion information about other WBANs in the vicinity in a timely way.The key issue for effective time scheduling is timely up?dating of information.Therefore，time?scheduling methods may be more appropriate when the inter?WBAN topology is chang?ing slowly.

3.3 Co-Channel Interference Mitigation

Generally speaking，resource management strategies，such as channel assignment and time rescheduling，are the most straightforward ways of reducing interference between coexist?ing WBANs.Each WBAN can work in an orderly manner based on the established resource allocation strategy.Howev?er，sometimes there may be problems with resource manage?ment because WBANs are densely deployed and the inter?WBAN topology changes quickly.In this case，we can only ad?just the transmission power to improve the performance of co?existing densely distributed WBANs.Interference between WBANs may still exist，and a proper method should be used to mitigate it.

Adjusting the transmission power is a natural way of improv?ing the performance of coexisting densely distributed WBANs. However，although decreasing the transmission power of one WBAN mitigates the interference experienced by that WBAN，it also degrades the performance of that WBAN.Game theory is usually introduced to trade off performance for energy con?sumption in a cooperative or non?cooperative manner.The im?portance of performance or energy consumption can be adjust?ed by setting the fixed or adaptive weighting factor in the appli?cation?based utility function.According to Nash Equilibrium（NE），anyone who changes their strategy alone without consid?eration of the strategies of other participants will benefit less［43］.That is，each rational participant is not motivated to change their strategy unilaterally if they seek the maximum possible benefit.

In［21］and［43］-［46］，the authors describe power?control game for inter?WBAN interference mitigation.In［21］，［43］，［45］，and［46］，a power control game involving a trade?off be?tween throughput and power consumption was proposed to miti?gate interference arising from coexisting WBANs.The exis?tence of and uniqueness of the NE solution was discussed.Fast?convergence algorithms such as Harmonic Mean（HM）［43］；Proactive Power Update（PAPU）［46］；and Best Response Itera?tion［21］，［45］have been proposed to converge to the unique NE.In［44］，Wu et al.created a decentralized inter?user inter?ference suppression（DISG）algorithm for a WBAN.They pro?posed a power?control game based on the SINR and power use to choose a suitable channel and transmission power.After proving the existence of the NE，the authors derived the condi?tion that would guarantee the uniqueness of the NE and intro?duced the No?Regret Learning algorithm to optimize the NE.

Most of works referring to the power?control game for WABNs only consider the single link inside the WBAN，which is impractical because a WBAN comprises many sensors with various QoS requirements，link gains，etc.The convergence speed of the power?updating algorithm must keep up with any change in the inter?WBAN topology；otherwise，the solution ob?tained in the current iteration is only optimal for the earlier pe?riod，not the current period.

In［47］，Kazemi et al.do not use game theory to mitigate in?terference arising from coexistence of WBANs.Instead，they propose a power controller based on reinforcement learning（RL）that exploits environmental information such as received interference，previous transmission power，and SINR.In［48］，the authors propose a fuzzy power controller（FPC）that ex?ploits the SINR，transmission power，and interference power level.An FPC uses genetic algorithms（GAs）to optimize pa?rameters and can maximize throughput and minimize power consumption by updating the optimal transmission power ac?cording to the current environment.

As well as power?adjustment strategies，adaptive strategies can be used to mitigate inter?WBAN interference.In［13］，Yang et al.proposed a scheme that included adaptive modula?tion，adaptive data rate，and adaptive duty cycle.They also in?troduced the interference mitigation factor（IMF），which is used to quantitatively analyze the effectiveness of their pro?posed scheme.

Co?channel interference?suppression methods such as power control based on game theory，power controller，and adaptive schemes are passive ways of mitigating inter?WBAN interfer?ence.Passively mitigating inter?WBAN interference involves constantly adjusting the transmission strategy according to the communication environment rather than actively altering the communication environment.This means compromising on per?formance when there is severe interference.In such situations，resource allocation strategies are ineffective.

3.4 Other Strategies

There are also other strategies for mitigating inter?WBAN in?terference［1］，［21］，［22］.In［1］，beacon?shifting strategies are introduced to protect the most important part of intra?WBAN communication，i.e.，transmission of the beacon，and make it easier for WBANs to coexist.The coordinator of a WBAN can transmit its beacon at different offsets relative to the start of the beacon periods in order to avoid repeated beacon colli?sions.The coordinator can also schedule allocation conflicts that occur as a result of coexistence.The offsets are decided by the unique beacon shifting sequence chosen by the coordinator.

Some auxiliary information can also be used to mitigate inter?WBAN interference.In［21］，the authors use social interaction detection to estimate the distance of interference.In［22］，De Silva et al.designed a fixed sensor network to predict potential interference.An interference prediction module was used to obtain the location of WBANs and RSSI，and the likelihood of interference was predicted according to the distance and RSSI level.Finally，a resource arbitrator was assigned channels that were different to those of the relevant WBANs in order to avoid potential interference.

3.5 Summary and Discussion

Tables 1 and 2 summarize different inter?WBAN interfer?ence mitigation solutions.These proposed solutions are all de?signed for different particular scenarios.When there are suffi?cient resources and a slowly changing network topology，re?source?allocation methods such as channel assignment and time rescheduling are the most straightforward methods for mit?igating inter?WBAN interference.However，in some scenarios，such as densely deployed WBANs，limited frequency resourceand frequently changing network topology，resource allocation may not be appropriate because of the lack of channels and in?sufficient assigning time.Co?channel interference mitigation is suitable in such scenarios.With co?channel interference miti?gation，the transmission strategy is adjusted according to the environment so that performance degradation is minimized. The density of WBAN deployment，rate of topology change，and number of time and frequency resources all affect the choice of inter?WBAN interference mitigation solution.Al?though we have classified these solutions as channel assign?ment，time rescheduling，and co?channel interference mitiga?tion，they are not mutually exclusive.Co?channel interference mitigation solutions can complement resources?allocation solu?tions.To further improve existing solutions，there are some un?resolved issues that need to be addressed.

▼Table 1.Summary of solutions for inter?WBANs coexistence and interference mitigation problem

▼Table 2.Comparison of solutions for inter?WBANs coexistence and interference mitigation problem

4 Open Research Issues

4.1 Link Diversity

In［21］，［44］-［46］，intra?WBAN communication is modeled as a single link for simplified analysis.However，the links from intra?WBAN sensors to the coordinator are different because sensors are positioned differently and the body is moving. Hence，link diversity inside the WBAN needs to be considered when dealing with inter?WBAN interference.

4.2 Unequal QoS Requirements

Another aspect that is often overlooked is varied QoS re?quirements for sensors inside the WBAN and for different WBAN users.Intra?WBAN sensors may have different require?ments in terms of transmission latency，data rate，priority and PLR，and the amount of interference they experience.Thus，the WBAN should not be regarded as a homogeneous network when designing an interference?mitigation solution.There are also personalized WBANs to serve individual needs，and these tend to have different performance demands.These different demands should not be ignored as well.

4.3 Mobility

A characteristic of a WBAN is random mobility.This is the combination of sensor mobility，due to body movements，and WBAN mobility，due to daily activities.Sensor mobility results in a change of intra?WBAN topology and internal link gain，which may lead to a failure of convergence of the power control game in a co?channel interference mitigation solution.Uncon?scious movements change the inter?WBAN topology and cause problems with the resource management strategy for inter?WBAN coexistence.For example，two WBAN users who are initially far apart may be assigned the same channel according to a certain resource?allocation strategy.When the users move close to each other，a collision occurs.Mobility creates some serious challenges for current interference mitigation solutions. However，in order to make the deployment of WBANs more widespread，more attention has to be paid to mobility.In［1］，［40］，［49］，［50］，the authors have made some preliminary at?tempts to analyze mobility in relation to mitigation of inter?WBAN interference.

4.4 Auxiliary Information

A WBAN is a body?centric network and the human behavior and neighboring environment would affect inter?WBAN coexis?tence.For example，the density of WBANs is very different in a coffee shop or subway station.The social relations between WBAN users may also affect the distance between WBANs. Though some efforts made in［21］，［22］have considered the en?vironmental support，the social attributes of WBAN are still not be utilized sufficiently and need further investigated.

5 Conclusion

This paper presented a deep analysis of the inter?WBAN co?existence issue and provided a broad overview of the inter?WBAN coexistence and interference mitigation strategies.The solutions to solve the coexistence problem，including channel assignment strategies，time rescheduling strategies，co?channel interference mitigation strategies，etc.，were summarized in this work.Some constructive suggestions were also proposed for the study of inter?WBAN coexistence problem in the future.

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Manuscript received：2015?03?26

Biographiesphies

Bin Liu（flowice@ustc.edu.cn）is an associate professor in the School of Information Science and Technology，University of Science and Technology of China（USTC）. He received his BS and MS degrees in electrical engineering from USTC in 1998 and 2001.He received his PhD degree in electrical engineering from Syracuse Uni?versity，USA in 2006.He was selected in Program for New Century Excellent Tal?ents in Universities of China 2009.His research interests include signal processing and communications in wireless sensor and body area networks.

Xiaosong Zhao（zhaoxiaosong124@sina.com）is a Master’s degree student at the School of Information Science and Technology，USTC.He received his BE degree in electronic information engineering from Chongqing University，China in 2013.His research interests include inter?WBAN interference mitigation and data mining.

Lei Zou（zoulei@mail.ustc.edu.cn）is a doctoral student in information and commu?nication engineering at USTC.He received his BE degree in electronic engineering from USTC in 2011.His research interests include coexistence of wireless devices and interference mitigation，particularly related to WBANs.

Chang Wen Chenis a professor of Computer Science and Engineering at the State University of New York at Buffalo，USA.Previously，he was Allen S.Henry En?dowed Chair Professor at Florida Institute of Technology from 2003 to 2007，a facul?ty member at the University of Missouri?Columbia from 1996 to 2003 and at the University of Rochester，Rochester，NY，from 1992 to 1996.He has been the Editor?in?Chief for IEEE Trans.Multimedia since 2014.He has also served as the Editor?in?Chief for IEEE Trans.Circuits and Systems for Video Technology from January 2006 to December 2009 and an Editor for Proceedings of IEEE，IEEE T?MM，IEEE JSAC，IEEE JETCAS，and IEEE Multimedia Magazine.He is a recipient of Sigma Xi Excellence in Graduate Research Mentoring Award in 2003，Alexander von Humboldt Research Award in 2009，and SUNY?Buffalo Exceptional Scholar—Sus?tained Achievements Award in 2012.He is an IEEE Fellow and an SPIE Fellow.

Roundup Call for Papers ZTE Communications Special Issue on Optical Wireless Communications

Optical wireless communication，which serves as an important alternative to the radio?frequency communication，shows great po?tential to a lot of applications，such as indoor communication，se?cure communication，and battlefield communication.It has at?tracted increasing research interests from both academia and in?dustrial fields.Moreover，optical wireless communication has been applied to the indoor communication and positioning sys?tem.The upcoming special issue of ZTE Communication will fo?cus on the cutting?edge research and application on the communi?cation system and related signal processing in optical wireless communication.The expected publication date will be in Mar. 2016.It includes（but not limited to）the following research direc?tions：

·Coded modulation；

·Channel modeling and estimation；

·Ultra?density transceiver technology；

·Signal detection and estimation in the non?Gaussian noise；

·Design and implementation on the transceiver architecture；

·Interference signal processing；

·Integrated communication and positioning；

·UV optical wireless communications；

·Underwater，free?space，and vehicle?to?vehicle optical wire?less communication；

·Optical wireless communication system optimization.

Paper Submission

Please directly send to cgong821@ustc.edu.cn and copy to all guest editors，and use the email title“ZTE?OWC?Paper?Submis?sion”.

Tentative Schedule

Paper submission due：9/30/2015；Review complete：11/30/2015；

Final manuscript due：12/31/2015.

Guest Editors

Prof.Xiaodong Wang，Columbia University（xw2008@colum?bia.edu）

Prof.Chen Gong，University of Science and Technology of China（cgong821@ustc.edu.cn）

Prof.Xuan Tang，CAS Quanzhou Institute of Equipment Manufacturing（xtang@fjirsm.ac.cn）

This work is supported by the National Natural Science Foundation of China under Grant No.61202406 and the USTC Grand Master Professor Funds under Grant No.ZC9850290097.