13 Telecom Article b 12.2011

IEEE Wireless Communications August 2011 131536-1284/11/$25.00 2011 IEEE

Arrange multipletransmissionscoordinately

Combine multiplereceived signalscoherently

Allocate transmitpower or scheduletransmissionsadaptively

AC C E P T E D F R O M OP E N CALL

INTRODUCTIONAfter more than two decades of rapid develop-ment, wireless communication has become a pil-lar industry of the worlds high tech sector.However, existing and upcoming systems are stillunable to mitigate the contradiction betweenlimited spectrum resources and ever-increasinguser demands, which has been regarded as thebottleneck of wireless communication ever since.

Traditional wireless communication systemsare likely designed mainly based on independentoptimization of utilization of radio resources. Asa result, their capacities are mostly subject to thelaw of diminishing returns, meaning that thecapacity increment becomes smaller and smallerwith the increase of resource of some kind [1].Take a single-input single-output (SISO) withadditive white Gaussian noise (AWGN) channel,for example. Its capacity is determined by theShannon formula, C = Wlog2 [1 + P/(nW)], whereW, P and n are the channel bandwidth, transmitpower, and noise power spectrum density, respec-tively. As shown in Fig. 1, the capacity will reachto a limit as the bandwidth goes to infinity, or

Even though the capacity may increase with-out limitation on the growth of the transmitpower, the rate of increase decreases graduallyand eventually approaches zero. Another exam-ple may be given by cellular networks. Frequen-cy reuse is supposed to provide more availablespectrum to each cell, while intercell interfer-ence becomes more serious in turn; thus, the sys-tem capacity becomes saturated. In fact, in mostpractical systems, the relationship between aresource input and the capacity holds almost thesame as the one depicted in Fig. 1.

In order to break through the bottleneck andimprove system capacity significantly, variousjoint optimizations over multiple domains ofresources were proposed. For example, Foschini[2] developed a novel signal architecture acrossspace and time domains, known as V-BLAST, torealize a large capacity gain. Rhee and Cioffi [3]studied a joint subcarrier and power allocationproblem in multiuser orthogonal frequency-divi-sion multiplexing (OFDM) systems to maximizethe sum capacity. Cai, Shen, and Mark [4] inves-tigated a similar problem with the considerationof heterogeneous traffic. However, rather thanjust focusing on specific models and detailedalgorithms, how and how much in general jointoptimization over multiple domains yields capac-ity gain should be studied so that a guide lightmay illuminate the roadmap of future wirelesssystem development.

This article proposes a new framework ofwireless networks with combined utilization ofmultiple domains, named multidomain collabo-ration (MDC). MDC extends the traditionalconcept of joint optimization to a more generalcase, by exploring and taking advantage of posi-tive interaction among multiple domains of radioresources, such as the time, frequency, space,and power domains. Within this framework, wetry to reveal the underlying rationale of collabo-rative use of multiple domains for increasing sys-tem capacity, while obtaining the fundamentalbounds of improved capacity gains in more gen-eral system models. It is worth noting that theFLoWS project [5], a five-year DefenseAdvanced Research Projects Agency (DARPA)

lim / log .W

C P n e

= 2

JIANHUA LU, YIZHEN JIA, TENGFEI XING, AND XIAOMING TAO, TSINGHUA UNIVERSITY

ABSTRACTThe bottleneck of wireless communication lies

in the contradiction between limited spectrumresources and ever-increasing user demand. Mul-tidomain collaboration (MDC) has emerged as anew framework to solve the problem, to someextent, with a great spectrum efficiency improve-ment. In this article, we introduce the concept ofMDC with the help of some intuitive examples.Specifically, the underlying rationale of MDC forincreasing transmission capacity is revealed fromthe perspective of both multiplexing gain andpower gain. Cases studies of point-to-point,point-to-multipoint, multipoint-to-point, andmultipoint-to-multipoint transmissions are con-ducted as preliminary evaluations of the perfor-mance limits that may be achieved by MDC.

MULTIDOMAIN COLLABORATION:A NEW FRAMEWORK OF WIRELESS NETWORKS

WITH HIGH TRANSMISSION CAPACITY

The bottleneck ofwireless communica-tion lies in the con-tradiction betweenlimited spectrumresources and ever-increasing userdemand. Multido-main collaborationhas emerged as anew framework tosolve the problem,to some extent, with a great spectrum efficiencyimprovement.

LU LAYOUT 8/8/11 12:09 PM Page 13

IEEE Wireless Communications August 201114

program, is striving for similar objectives inmobile ad hoc networks. In fact, recently theendeavor to achieve enormous capacity improve-ment has become a significant trend in theresearch on wireless communication systems.The material in this article was presented in partat IEEE ICWITS 2010.

There are several metrics of system capacityfor wireless networks. Considering that transmis-sion capacity is basic, this article focuses onincreasing transmission capacity by means ofMDC. For a wireless link connecting one trans-mitter and one receiver, transmission capacityrefers to the (ergodic) channel capacity of thelink; for a network containing multiple pairs oftransmitters and receivers, transmission capacityrefers to the sum capacity of all the links. Sincethe total available spectrum for a network islikely fixed, we do not strictly differentiate trans-mission capacity and spectrum efficiencythroughout the article.

The remainder of this article is organized asfollows. We present an overview of MDC, fromits concept to practice with intuitive examples.We evaluate the transmission capacity gainsobtained by MDC under four typical networktopologies (i.e., point-to-point, point-to-multi-point, multipoint-to-point, and multipoint-to-multipoint). Promising applications of MDC inpractical systems or their evolutions are alsoinvestigated. Finally, concluding remarks with aperspective of future work on MDC are given.

OVERVIEW OF MULTIDOMAINCOLLABORATION

The word collaboration is commonly defined asthe process of coordinating different types ofindividuals to fulfill a certain mission. As such,in this article MDC refers to the process ofexploiting and making use of positive interactionamong multiple domains to significantly improvethe transmission capacity of wireless networks.The domains include the basic radio resourcesutilized for wireless communications (i.e., the

time, frequency, space, and power domains).Below are two intuitive examples of MDC.

Collaboration between time and frequencydomains: Consider a simple case with one serverand three users. Suppose that the availablebandwidth is two units of spectrum, and theachievable spectrum efficiency for each user is 1Mb/s per unit of spectrum. All the users wouldlike to download their own favorite videos storedin the server, while the download data rate foreach user is assumed to be constant during thedownload process, say, 1 Mb/s. The time lengthsof the videos required by users U1, U2, and U3are two units, one unit, and one unit of time,respectively. Furthermore, we assume that allthe users expect to enjoy their videos within twounits of time while ignoring the propagationtime. How do we allocate the radio resources(i.e., available spectrum and time units) amongthese three users? If the resources are assignedto the users in one domain, either time or fre-quency, it is impossible to meet the require-ments of all three users. In other words, neithertime-division multiplexing (TDM) nor frequen-cy-division multiplexing (FDM) can serve thesethree users within two units of spectrum and twounits of time (Fig.s 2a and 2b).

However, combining TDM and FDM togeth-er (i.e., assigning radio resources jointly in timeand frequency domains), one can easily findmore than one feasible resource allocation meet-ing all the users demands, as shown in Fig. 2c asan example. Compared with TDM and FDM,this joint TDM and FDM scheme may improvethe transmission capacity from 33 to 100 per-cent, which embodies the collaboration betweenthe time and frequency domains.

Collaboration among time, space, and powerdomains: Assume a scenario where the usershave no waiting time restriction with sufficientstorage capacity such that the download datarate may be flexible. All users experience differ-ent fading channels which are supposed to beindependent of one another (Fig. 3a). For such asystem, traditional scheduling schemes (e.g.,round robin or polling) arrange transmissions toall the users in a predetermined order regardlessof channel conditions. As a result, for one user,a transmission may happen even when the chan-nel quality is very poor during the scheduledperiod, thus leading to low transmission capacity.Inspired by the idea of MDC, however, one mayemploy opportunistic scheduling [6] by transmit-ting, with all available power, to the user of thebest channel condition, most likely resulting inimproved capacity. This capacity improvementby opportunistic scheduling may be understoodin two aspects. First, for each user, the random-ness of its channel fading in the time domainlikely ensures the emergence of good channelconditions where the channel strength is muchstronger than average. Second, the indepen-dence of the users channel fading in the spacedomain makes it highly probable that there isone user with good channel conditions in eachscheduled period.

An intuitive comparison between opportunis-tic scheduling and round-robin with an order ofU1 U2 U3 U1 is illustrated in Fig. 3b. Itis shown that in the period 1, U2 will have chance

Figure 1. An example of diminishing returns in wireless communication. Usinga fixed transmit power, the capacity of an AWGN channel will reach a limit as the bandwidth goes to infinity.

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IEEE Wireless Communications August 2011 15

to receive data with opportunistic schedulingsince its channel condition is the best, but U1will download data with round robin accordingto the predetermined order. Because U2s chan-nel strength (approximate 5dB) is much higherthan U1s (approximate 15dB), much largerdata rate may be achieved by opportunisticscheduling in this period. This conclusion alsoholds for other periods, implying a significantcapacity gain by the use of the opportunisticscheduling, which may refers to a collaborationamong time, space and power domains.

The above examples may help to illustratethe concept and advantage of MDC. The ratio-nale for capacity improvement by MDC may berevealed from the Shannon formula, whichexpresses mathematically the dependence of thecapacity of an AWGN channel on the bandwidthand the signal-to-noise ratio (SNR). Furtherconsidering a network as a virtual giant link, onemay declare that the transmission capacity of thenetwork is determined by the effective bandwidth,WE and effective SNR, E, and WE = KMW0, E= KP 0 = KPP0/N0, with W0, P0 being the givenspectrum bandwidth and total transmit power ofthe network, respectively, and N0 the noisepower. KM and KP are defined as multiplexinggain and power gain, respectively, which dependon the way of utilization of resources. Since W0,P0, and N0 are fixed, one may improve the trans-mission capacity by increasing KM and/or KP,which is de facto the goal of MDC. Specifically,note that in the first example presented above,the joint TDM and FDM may increase the mul-tiplexing gain up to two fold compared with theTDM. While in the second one, the power gainof opportunistic scheduling is nearly 100 times(i.e., 20 dB) that of round-robin.

From the perspective of multiplexing gainand power gain, a conceptual diagram of MDCis depicted in Fig. 4. MDC actually serves as amethodology of utilization of resources, accord-ing to which the transmitters (labeled T1, T2, )and receivers (labeled R1, R2, ) make collabo-rative use of radio resources in time, frequency,space, and power domains so as to increase themultiplexing gain and/or power gain, and eventu-ally the transmission capacity gain. Specifically,at the transmitter side, the transmission of multi-ple data streams may be arranged coordinatelyin time, frequency, or space domains, with prop-er power planning if needed, so that the assignedspectrum may be reused as aggressively as possi-ble without interference or under a tolerableinterference level. As such, a multiplexing gain isobtained. Second, the transmit power or trans-mission opportunity may be adaptively allocatedaccording to the fluctuating channel characteris-tic. As a result, the signal-to-noise ratio (SNR)of the received signal is increased and a powergain is achieved. Third, at the receiver side, themultiple copies of received signals possibly avail-able in time, frequency, and space domains maybe combined coherently, which also yields apower gain. Both the multiplexing gain andpower gain may be translated into transmissioncapacity gain.

Below, we study some typical cases of wirelessnetwork topologies, analyzing and evaluating thecapacity gains of MDC with achievable limits.

Figure 2. An example of collaboration between time and frequency domains.Three users (U1, U2 and U3) apply for 1 unit of spectrum each, and a continu-ous period of 2 units, 1 unit, and 1 unit of time, respectively, while the availableresources include 2 units of spectrum and 2 units of time. Thereby, neither a)TDM, which requires 4 units of time, nor b) FDM, which requires 3 units ofspectrum, can serve these three users. However, scheme c) with joint TDM andFDM, for example, may assign the basic resource blocks of RB1, RB2, RB3,and RB4 to U1, U1, U2, and U3, respectively, serving all users.

RB4

Basicresource

block

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CASES STUDIES OF MDC WITHPERFORMANCE EVALUATION

Consider a general wireless network composedof Mt transmitters, labeled T1, T2, , TMt, andMr receivers, labeled R1, R2, , RMr. Each ofthese nodes may be equipped with multipleantennas. The channel coefficient from eachtransmit antenna to each receive antenna isassumed to be a zero mean circularly symmetriccomplex Gaussian random variable with unitvariance. We then focus on a symmetric casewhere the path loss from each transmitter toeach receiver is assumed to be the same andnormalized to one. Each of the receive antennassuffers from AWGN. Following the notationfrom earlier, the total transmit power and noisepower are denoted P0 and N0, respectively.Moreover, the available spectrum bandwidth isnormalized to one so that transmission capacity isequal to spectrum efficiency in magnitude.

We now study the performance of MDC underfour cases with typical network topologies: point-to-point, point-to-multipoint, multipoint-to-point,and multipoint-to-multipoint transmissions.Specifically, in the first three cases, the emphasisis put on collaboration between the space andpower domains, while in the last one, the timeand frequency domains are also involved.

POINT-TO-POINTThis case includes only one transmitter and onereceiver (i.e., Mt = Mr = 1). In a single-antennacase, it has been shown above that the capacityimprovement obtained by increasing only thebandwidth or transmit power is eventually limit-ed due to the law of diminishing returns. Byexploiting the additional signal dimensionsreserved in the space domain, on the other hand,multiple-antenna technologies may acquire a sig-

nificant multiplexing gain. Moreover, the trans-mit power may be allocated adaptively accordingto the channel conditions to make full use of thesignal dimensions, achieving a considerablepower gain. Then both the multiplexing gain andpower gain may together improve the transmis-sion capacity.

Consider a multiple-antenna case where boththe transmitter and receiver are equipped with Nantennas a typical case of multiple-input multi-ple-output (MIMO). When the channel stateinformation (CSI) is only available at the receiv-er side (termed CSIR), the transmit power isequally allocated across the eigenmodes of thechannel matrix H due to lack of CSI at the trans-mitter, and thus the transmission capacity, CP2P,can be expressed as [6]

where Nrank is the rank of H, i is the ith nonze-ro singular value of H, and E[] denotes expecta-tion of random variables. At the high SNRregion, if H is sufficiently random (and thusprobably with full rank) and statistically wellconditioned, the capacity is approximately equalto Nlog2 [1 + P0/(NN0)], indicating an N-foldmultiplexing gain over SISO. However, if H isstatistically rank deficient due to the correlationof the entries, the multiplexing gain decreasesaccordingly. At the low SNR region, whether theentries of H are correlated or not, the capacity isalways approximately equal to NP0/N0log2e, indi-cating an N-fold power gain over SISO. Anyway,under CSIR, the capacity of a sufficiently ran-dom and well conditioned MIMO channelincreases linearly with N.

If the CSI is also available at the transmitterside (termed CSIT) via estimation or feedback,

CP N

Ni

N

iP2P Erank

= +

=

12

2 0

01log

/,

Figure 3. An example of collaboration among time, space and power domains. A server schedules transmissions to three users (U1, U2,and U3), while two scheduling methods, the opportunity scheduling and round robin, are employed for comparison: a) the channelfading of the three users, which is supposed to be independent of each other; b) Scheduling results of the opportunistic scheduling (solidline) and round robin (dashed line), which shows an enormous advantage of opportunistic scheduling.An example of collaborationamong time, space and power domains. A server schedules transmissions to three users (U1, U2 and U3), while two scheduling meth-ods, the opportunity scheduling and round robin, are employed for comparison: a) The channel fading of the three users, which is sup-posed to be independent of each other; and b) Scheduling results of the opportunistic scheduling (solid line) and round robin (dashedline), which shows an enormous advantage of opportunistic scheduling.

Cha

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the transmit power may be allocated in a water-filling manner across the eigenmodes of H, yield-ing an additional power gain [6]. At the highSNR region, this additional power gain producesa limited capacity improvement, especially whenH is sufficiently random and statistically wellconditioned. At the low SNR region, however,this additional power gain may yield consider-able capacity improvement. Specifically, whenSNR is low enough, the water-filling scheme willassign all the available power to the strongesteigenmode corresponding to the largest singularvalue, max. By virtue of

the transmission capacity approximates2maxP0/N0log2e, where 2max locates in the interval[N, N2] with high probability [7]. Therefore, withCSIT, N to N2 times power gain may be obtainedcompared to SISO, which may be translated intothe same amount of capacity gain at the lowSNR region. The upper bound N2 is achievablewhen the entries of H are fully correlated [8].

Figure 5 illustrates the capacity gains ofMIMO over SISO with N = 8. Both cases theentries of H are independent identically dis-tributed (labeled iid) or fully correlated(labeled corr), are considered. At the highSNR region (Fig. 5a), the transmission capacityis mainly increased by the multiplexing gain. Asa result, the capacity gain is nearly N for the iidcase and approximately one for the corr casedue to rank deficiency. Meanwhile, CSIT doeslittle to further increase the capacity. At the lowSNR region (Fig. 5b), the capacity is mainlyincreased by the power gain. Specifically, if thechannel coefficients are fully correlated andknown at the transmitter, N2-fold power gain isachieved, which can be converted into nearly thesame amount of capacity gain.

This case study provides an intuitive interpre-tation of the term positive interaction amongdomains in the concept of MDC. Take the(asymptotic) N2 times of capacity gain as anexample. When SNR is very low, the power

domain sends this piece of SNR information tothe space domain. One can then increase thecorrelation of the transmit and receive antennasin space domain by, for example, reducing thespacial distances among the antennas, therebycreating the condition under which a large capac-ity gain may be achieved.

Take an example of applying MDC in a prac-tical point-to-point network, such as the down-link transmission in a Third GenerationPartnership Project (3GPP) Universal MobileTelecommunications System/Long Term Evolu-tion (UMTS/LTE) network [9], where both thee-NodeB and the user equipment (UE) can beequipped with up to four antennas. The e-NodeBmay use either open-loop, such as multiple-code-word-based transmission, or closed-loop spatialmultiplexing technologies, such as precoding, toachieve times of capacity gain through multiplex-ing gain at the high SNR region. At the lowSNR region, one of the MDC strategies men-tioned above, the antenna correlation alternatingmethod, is a valid option to get additional powergain besides existing diversity techniques, such asspace-time coding.

POINT-TO-MULTIPOINTA point-to-multipoint transmission is composedof one transmitter and multiple receivers (i.e.,Mt = 1, Mr = M > 1). One typical example isthe downlink transmission that one base station(BS) transmits data to several mobile stations(MSs). Considering that the radio signal to onereceiver may also be received by other receivers,one may combine multiple copies of receivedsignals coherently. Coherent combination meansthat the useful signals are added in phase (i.e., inamplitude), while the noisy signals are added inpower due to their independence. Thereby,power gain is obtained. The coherent combina-tion may be regarded as collaboration betweenthe space and power domains, in the sense thatthe signal energy dispersed in a broad space isefficiently collected.

Consider a simple example where the trans-mitter employs all the available power to trans-

lim log ( ) log ,

+ =0

2 21 e

Figure 4. A conceptual diagram of MDC. MDC is dedicated to increase multiplexing gain by a coordinatearrangement of multiple transmissions, and power gain by adaptive power allocation, scheduling, and/orcoherent combination of multiple received signals. Both the multiplexing gain and power gain may trans-late to a capacity gain.

Time

Space

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Power

Frequency

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Multiplexinggain

Multiplexinggain

Capacity gain

Arrange multipletransmissionscoordinately

Combine multiplereceived signalscoherently

Allocate transmitpower or scheduletransmissionsadaptively

R1

R2

Coherent combina-tion means that the

useful signals areadded in phase, i.e.,

in amplitude, whilethe noisy signals areadded in power due

to their indepen-dence. Thereby, a

power gain isobtained.



mit to one receiver in one time slot by turns, i.e.,in a TDM mode. Each of these nodes is assumedto be equipped with one antenna. The channelcoefficient between the transmitter T1 and thereceiver R j (j = 1, 2, , M), hj, experiencesRayleigh fading as stated above. Without coher-ent combination, the SNR of the received signalof Rj is P0hj2/N0. However, with the optimalcoherent combination, that is, the maximumratio combination (MRC), it is increased to Mj=1P0hj2/N0 [10]. Since all the hj (j = 1, 2, , M)may follow the same distribution, an averagepower gain of M times may be achieved for eachlink.

At the low SNR region, by virtue of

the transmission capacity gain is nearly equal tothe power gain. At the high SNR region, on theother hand, due to

the capacity gain should be much less than thepower gain.

Numerical results for verification are show inFig. 6. In particular, Fig. 6a plots the capacitygains at typical values of average SNR. An M-fold power gain may be obtained using MRC. Atlow SNR region, this power gain is approximate-ly equivalent to the same amount of capacitygain, while at high SNR region, the capacity gainis very small. For clearer explanation in Fig. 6b,at a low SNR, say, 20dB, the capacity gain isincreased linearly as M increases, while at a highSNR, say, 20dB, the capacity gain gets saturatedquickly.

MDC may be implemented and provide ben-efits in practical networks with point-to-multi-point topology, such as the downlink of an IEEE802.16j network [11]. Specifically, the relay sta-tions (RSs) may assist the base station (BS) to

transmit signals to users, increasing the systemcoverage and yielding additional power gains. Ifuser cooperation is allowed in the system, usersmay perform as relays for each other. Then, bycarrying out some multiplexing scheme (such asTDD), each user could receive his own signalwith a significant power gain aided by othercooperative users. Again, note that this powergain may be translated into the capacity gain lin-early at low SNR region.

MULTIPOINT-TO-POINTA multipoint-to-point transmission is of multipletransmitters and one receiver, i.e., Mt = M > 1,Mr = 1. One typical example is the uplink of acellular system where multiple MSs transmittheir data to one BS. The same idea utilized inthe point-to-multipoint case, i.e., coherent com-bination, may also be applied here. In particular,by means of data exchange among the transmit-ters aforehand, the data to be sent from onetransmitter may be transmitted by multipletransmitters, with proper delays and phase-shifts,in order that the multiple transmitted signals areautomatically combined coherently at the receiv-er. Such a technology is much alike joint beam-forming, which serves as an embodiment ofspace domain and power domain collaborationin the sense that the signal energy radiated fromdifferent space locations is focused together.Accordingly, a power gain may be expected.

Without loss of generality, we assume thateach of the nodes is equipped with one antenna.The channel coefficient between the transmitterTi (i = 1, 2, , M) and the receiver R1 is denot-ed hi. The maximum average transmit power ofeach transmitter is P0/M.

In a traditional scheme, time-division multi-ple access (TDMA) is used as a benchmark,where each transmitter occupies only 1/M of thetransmission time. As such, the maximum instan-taneous transmit power can be increased up toP0. Consequently, the instantaneous SNR of thereceived signal transmitted from T i is P0

limlog ( )

log ( ),

++

=0

2

2

1

11

KP

lim log ( ) log ,

+ =0

2 21 e

Figure 5. Capacity gain results of an 8 8 MIMO channel: a) at the high SNR region, the capacity gain is nearly N, the number of anten-nas at the transmitter and the receiver, if the channel coefficients are independent identically distributed (iid), and approaching 1 if thechannel coefficients are fully correlated (corr); b) at the low SNR region, the capacity is mainly increased by the power gain. If thechannel coefficients are fully correlated and known at the transmitter, an N2-fold power gain is achieved.

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hi2/N0. When joint collaboration is employed,all the transmitters exchange the data they wantto transmit first. These data are converted intoone serial stream and transmitted over all Mtransmitters simultaneously. In order to realizecoherent combination at R1 and keep the aver-age transmit power at each transmitter no morethan P0/M, the transmitted signal from Ti, xi, isconstructed as

where s is the transmitted data symbol in theserial stream with unit power [10]. Correspond-ingly, the instantaneous SNR of this virtual linkbecomes P0(Mi=1hi)2/(MN0). Note that

the average power gain with joint collaborationmay be equal to or less than M.

Analogous to the conclusion for the case ofpoint-to-multipoint transmission, the capacitygain is approximate to the power gain under thelow SNR region. As the SNR increases, thetransmission capacity gain diminishes and even-tually approaches one with the SNR going toinfinity. The simulation results are similar tothosee in Fig. 6 and thus are omitted here.

Suppose an application of MDC in the uplinkof an IEEE 802.16j network [11]. When a usersends data to the BS, other users may performas relays and assist its transmission, providingadditional power gain by implementing jointtransmission. This power gain may get the sameamount of capacity gain with low SNR.

MULTIPOINT-TO-MULTIPOINTMultipoint-to-multipoint transmission may beviewed as a combination of the above threetopologies. One typical example is a multicellsystem where multiple BSs communicate withmultiple MSs. Consider a multipoint-to-multi-

point network with M transmitter/receiver pairs(i.e., Mt = Mr = M > 1). Transmitter Ti(i = 1, 2,, M) tries to send data to receiver Ri, whichmay be interfered with by Tj(j i).

Due to the coexistence of multiple transmit-ter/receiver pairs, one of the most challengingtasks is to mitigate potential interlink interfer-ence. To address this issue, traditional methodsbased on orthogonal allocation of radioresources, such as time division and frequencydivision, have been proposed. By applying thesesimple and effective methods, the whole networkis decomposed into a set of point-to-point links,while suffering from inefficiency in terms oftransmission capacity. On the other hand,advanced interference management technologiesmay make more aggressive reuse of radioresources by collaboration among time, frequen-cy, space, and power domains, yielding significantmultiplexing gains and/or power gains, whosemagnitudes depend on the capability of dataexchange among the transmitters or receivers.

First, we consider the case where there is nodata exchange among the transmitters orreceivers. In order to achieve the multiplexinggain, interference alignment was proposedrecently [12]. The idea is to construct the trans-mitting signals in such a manner that theyremain distinguishable at their correspondingreceivers while casting overlapping shadows asinterference at other receivers. At each receiv-er, all the interference from transmitters isaligned on certain resource blocks (e.g., timeslots, subcarriers, space eigenmodes), savingother blocks for interference-free transmission.Therefore, interference alignment may beimplemented in either the time, frequency, orspace domain.

A simple example of interference alignmentin the time domain is presented in [12]. In itsmodel, the propagation delay is assumed to beone symbol duration for desired signal paths andtwo symbol durations for interfering paths, andeach transmitter only transmits in odd time slots.

E iM

ih M=( )1

2 2,

x P M sh hi i i= 0 / / ,*

Figure 6. Capacity gain results for a point-to-multipoint transmission: a) the capacity gain is nearly equal to M, the number of receivers,at the low SNR region, resulting from an M-fold power gain, while it gradually diminishes to 1 as the SNR increases; b) the capacitygain increases almost linearly with M at a low SNR value of 20 dB, while at a high SNR of 20 dB, it gets saturated quickly as Mincreases.

Average SNR: P0/N0 (dB)

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For each receiver, the desired signal is receivedin the even time slots and all the interference isreceived in the odd time slots. Therefore, eachtransmitter/receiver pair equivalently utilizes thewhole spectrum half the time. Compared to thetraditional time-division scheme, an M/2-foldmultiplexing gain is achieved in theory.

Now let us consider the scenario where thetransmitters can exchange data with one anoth-er. Each transmitter may be viewed as a transmitantenna of a virtual giant transmitter, and thedata for each receiver can be jointly precodedbefore transmission. From the perspective ofinformation theory, the network turns into abroadcast channel whose spatial degrees of free-dom is M times of an interference channel [13].Therefore, an M-fold multiplexing gain and cer-tain power gain could be obtained comparingwith orthogonal strategy by using well-designedprecoding algorithm.

Furthermore, if both the transmitters andreceivers can exchange data with one another,the network can be viewed as a M M (dis-tributed) MIMO channel. This way, the tech-nologies and conclusions presented in thepoint-to-point case are applicable here, meaningthat an M-fold multiplexing gain or a power gainfrom M to M2 may be obtained.

Applications of MDC in practical multipoint-to-multipoint communication networks may be foundin the study of future wireless systems. In LTE-Advanced, Inter-Node B Coordination has beenproposed to achieve collaboration among e-NodeBs [14], where adjacent e-NodeBs are con-nected by fibers to exchange data with one another.When multiple e-NodeBs are communicating withmultiple users, both uplink and downlink multi-plexing gain may be achieved by employingadvanced joint signal processing of uplink anddownlink signals. By introducing user cooperation,an additional power gain may be achieved and ahigher capacity gain can be expected.

SUMMARY OF IMPORTANT RESULTSThe potent ia l mult ip lex ing ga ins and/orpower gains of MDC with four typical topolo-gies are summarized in Table 1. It is noted

that the power gain, compared to the multi-plexing gain, is expected to be obtained moreeasily or in a larger amount. However, onlyat the low SNR region may the power gainbe translated into nearly the same amount ofcapacity gain.

FUTURE PERSPECTIVE OF MDCIt has been shown that MDC will be an impor-tant technical paradigm to advance transmissioncapacities of wireless networks. However, theexciting capacity gains evaluated above are basedon some conditions which may not be supportedin current systems. For example, in the point-to-multipoint case, maximum radio combination isimplemented on the basis of data exchangeamong the receivers; in the multipoint-to-pointand multipoint-to-multipoint cases, the imple-mentation of joint beamforming or networkMIMO has to rely on data exchange among thetransmitters. Such functions are not available incurrent cellular systems or wireless local areanetworks (WLANs). Moreover, technicalprogress in synchronization, demodulation, andso on are necessary to realize the promisedtransmission capacity gains at the low SNRregion in practice. Although relevant researchhas been launched from both the theoretical [15]and standardization perspectives [14], a greatdeal of future work is desirable to address theseproblems.

CONCLUSIONSThis article introduces the concept of multido-main collaboration and reveals its rationale forimproving transmission capacity of wireless net-works from the perspective of both multiplexingand power gains. The capacity gains achievedby MDC are evaluated for the cases of point-to-point, point-to-multipoint, multipoint-to-point, and multipoint-to-multipointtransmission. Specifically, the power gain of anN N MIMO point-to-point link may increaseup to N2 with fully correlated channel coeffi-cients using several collaboration techniques,thereby increasing the transmission capacityconsiderably at the low SNR region. Moreover,for a network with M transmitters and Mreceivers, a multiplexing gain of M/2 or M or apower gain with upper bound of M2 may beachieved, depending on the capability of dataexchange, both of which may lead to a largecapacity gain. It turns out that the capacity gainis probably larger at the low SNR region thanthat at the high SNR region. This raises sometechnical challenges such as synchronization,demodulation, equalization, and other signalprocessing technologies at the extremely lowSNR region. Possible technical solutions tothese challenges require comprehensive studyin the future.

ACKNOWLEDGMENTThe authors would like to thank Mr. DanhuaZhang, Ms. Hui Deng, Mr. Weiliang Zeng, andDr. Mai Xu for their helpful discussion, and theanonymous reviewers for their constructive com-ments that helped to improve the presentationof this article.

Table 1. Potential performance gains of MDC with typical network topologies(Mt: number of transmitters, Mr: number of receivers, Na: number of anten-nas at each node).

Multiplexinggain

Powergain

Capacity gain

HighSNR

LowSNR

Point-to-point(Mt = Mr = 1, Na = N)

N N~N2 N N~N2

Point-to-multipoint(Mt = 1, Mr = M, Na = 1)

M 1 M

Multipoint-to-point(Mt = M, Mr = 1, Na = 1)

M 1 M

Multipoint-to-multipoint(Mt = Mr = M, Na = 1)

M/2 or M M~M2 M/2 or M M~M2



REFERENCES[1] K. E. Case and R. C. Fair, Principles of Economics, 5th

ed., Prentice-Hall, 1999.[2] G. Foschini, Layered Space-Time Architecture for Wire-

less Communication in a Fading Environment WhenUsing Multi-Element Antennas, Bell Labs Tech. J., vol.1, no. 2, 1996, pp. 4159.

[3] W. Rhee and J. Cioffi, Increase in Capacity of MultiuserOFDM System Using Dynamic Subchannel Allocation,Proc. VTC 2000-Spring, Tokyo, Japan, vol. 2, 2002, pp.108589.

[4] J. Cai, X. Shen, and J. Mark, Downlink Resource Man-agement for Packet Transmission in OFDM WirelessCommunication Systems, IEEE Trans. Wireless Com-mun., vol. 4, no. 4, July 2005, pp. 16881703.

[5] A. Goldsmith et al., Beyond Shannon: The Quest forFundamental Performance Limits of Wireless Ad HocNetworks, IEEE Commun. Mag., Jan. 2011.

[6] D. Tse and P. Viswanath, Fundamentals of WirelessCommunication, Cambridge Univ. Press, 2005.

[7] A. Zanella, M. Chiani, and M. Win, Performance ofMIMO MRC in correlated Rayleigh Fading Environ-ments, Proc. VTC-Spring 2005, vol. 3, Stockholm, Swe-den, May 2005, pp. 163337.

[8] X. Wu and R. Srikant, MIMO Channels in the Low-SNRRegime: Communication Rate, Error Exponent, and Sig-nal Peakiness, IEEE Trans. Info. Theory, vol. 53, no. 4,Apr. 2007, pp. 12901309.

[9] 3GPP R1-050766, Multiple Antenna Solutions for E-UTRA, Aug. 2005.

[10] A. Goldsmith, Wireless Communications, CambridgeUniv. Press, 2005.

[11] W. Ni, G. Shen, and S. Jin, Cooperative RelayApproaches in IEEE 802.16j, IEEE C802.16j-07/258r1,IEEE 802.16 Broadband Wireless Access WorkingGroup, Apr. 2007.

[12] V. Cadambe and S. Jafar, Interference Alignment andDegrees of Freedom of the K-User Interference Chan-nel, IEEE Trans. Info. Theory, vol. 54, no. 8, Aug.2008, pp. 342541.

[13] J. Zhang et al., Networked MIMO with Clustered Lin-ear Precoding, IEEE Trans. Wireless Commun., vol. 8,no. 4, Apr. 2009, pp. 191021.

[14] M. Sawahashi et al., Coordinated Multipoint Trans-mission/Reception Techniques for LTE-Advanced, IEEEWireless Commun., vol. 17, no. 3, June 2010, pp.2634.

[15] P. Cuff, H. Permuter, and T. Cover, CoordinationCapacity, IEEE Trans. Info. Theory, vol. 56, no. 9, Sept.2010, pp. 4181206.

BIOGRAPHIESJ IANHUA LU [SM08] ( [email protected])received B.S.E.E. and M.S.E.E. degrees from Tsinghua Uni-versity, Beijing, China, in 1986 and 1989, respectively, andhis Ph.D. degree in electrical and electronic engineeringfrom Hong Kong University of Science and Technology,Kowloon. Since 1989 he has been with the Department ofElectronic Engineering, Tsinghua University, where he iscurrently a professor. His research interests include broad-band wireless communication, multimedia signal process-ing, satellite communication, and wireless networking. Hehas published more than 180 technical papers in interna-tional journals and conference proceedings. He has beenan active member of professional societies. He was one ofthe recipients of best paper awards at the InternationalConference on Communications, Circuits and Systems2002 and ChinaCom 2006, and was awarded the NationalDistinguished Young Scholar Fund by the NSF committeeof China in 2006. He has served in numerous IEEE confer-ences as a member of Technical Program Committees andserved as Lead Chair of the General Symposium of IEEEICC 2008, as well as a Program Committee Co-Chair of the9th IEEE International Conference on Cognitive Informat-ics. He is currently a chief scientist of the National BasicResearch Program, China. He is a Senior Member of theIEEE Signal Processing Society.

YIZHEN JIA [S08, M11] ([email protected])received his B.E. degree from the Department of ElectronicEngineering, Tsinghua University, Beijing, China, in 2005,where he is currently working toward a Ph.D. degree. Hisresearch interests include cooperative communications,wireless resource management, and satellite communica-tions.

TENGFEI XING [S08, M11] ([email protected])received his B.E. degree from the Department of ElectronicEngineering, Tsinghua University, Beijing, China, in 2005,where he is currently working toward a Ph.D. degree. Hisresearch interests include cooperative communications,delay tolerant networks, and space-time coding.

This will raise sometechnical challengessuch as synchroniza-tion, demodulation,

equalization andother signal process-ing technologies atextremely low SNR

region. Possible technical solutions to

these challengesrequire a comprehen-

sive study in thefuture.


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