IEEE Communications Magazine November 201454 0163-6804/14/$25.00 2014 IEEE

Fuad M. Abinader, Jr.,Erika P. L. Almeida,Fabiano S. Chaves, AndrM. Cavalcante, RobsonD. Vieira, Rafael C. D.Paiva, and Angilberto M.Sobrinho are with NokiaInstitute of Technology.

Sayantan Choudhury, EsaTuomaala, and KlausDoppler are with NokiaResearch Center.

Vicente A. Sousa Jr. iswith Federal University ofRio Grande do Norte.

INTRODUCTIONWireless communication infrastructure is facing agreat challenge with the expanding demand forwireless broadband access to Internet. A recentforecast study [1] indicates that a traffic growthbeyond 500-fold is expected between 2010 and2020, assuming the same increase in data usage ismaintained. In order to improve the capacity, theThird Generation Partnership Project (3GPP)standards group has been investigating the per-formance gains obtained by small cell deploy-ment in Long Term Evolution (LTE) Release 12and beyond. On the other hand, the IEEE 802.11Working Group (WG) just ratified a new IEEE802.11ax Task Group (TGax) primarily focusedon enhancing the system performance of Wi-Fiin dense deployment scenarios [2].

However, some practical issues impose limita-tions on large-scale small cell deployments. First,there are increased costs for deploying andmaintaining the required infrastructure. Cus-tomers are increasingly seeing wireless Internetaccess as a utility, and premium taxation onfaster connections becomes less of an option

since the introduction of flat rate tariffs. So, asrevenue is not increasing at the same pace asexpenditures [1], capacity expansion requiringlarger capital expenditures (CAPEX), such asacquisition and installation of cells, and operat-ing expenditures (OPEX) (e.g., backbone main-tenance) becomes an economic challenge. Thesecond issue relates to the diminishing availabili-ty of radio spectrum, a fundamental resourcethat is both finite and expensive. Modern wire-less technologies like orthogonal frequency-divi-sion multiplexing (OFDM), relaying, and spatialmultiplexing allow high spectrum usage efficien-cy to be achieved, and some researchers arguethat spectrum scarcity is a non-issue due to avail-able technology [3]. Nonetheless, a bandwidthshortage of 275 MHz in the United States aloneis foreseen by the end of 2014 [4].

To face these challenges, cellular operatorsare deploying complementary network infra-structure for data delivery, a technique known asmobile traffic offloading [5]. The two main tech-nological advances to enable mobile trafficoffloading are the introduction of small cell net-works and the development of dynamic spectrumaccess techniques for operation in license-exemptradio bands.

The concept of small cells, as proposed forheterogeneous networks (HetNets), is two-fold.In the data plane, the goal is enabling the densedeployment of cells with smaller coverage areas,but capable of serving high traffic loads. On theother hand, in the control plane, the main goal isdiminishing the dependence on an operatorsbackbone by implementing concepts like self-organization and self-adaptation. These require-ments led 3GPP to standardize LTE small cellsfor operation on licensed spectrum in Release12. 3GPP also foresees the adoption of enhancedIEEE 802.11 WLANs in unlicensed spectrum asa complementary solution. In this sense, IEEE802.11ac networks with Wi-Fi Passpoint are agood starting point, while the IEEE 802.11axstandard (currently under development) is beingconsidered for dense deployment scenarios. It isforeseen that by 2016, up to 30 percent of broad-band access in cellular networks will be attainedover traffic offloading networks [1].

ABSTRACTThe expansion of wireless broadband access

network deployments is resulting in increasedscarcity of available radio spectrum. It is verylikely that in the near future, cellular technolo-gies and wireless local area networks will need tocoexist in the same unlicensed bands. However,the two most prominent technologies, LTE andWi-Fi, were designed to work in different bandsand not to coexist in a shared band. In this arti-cle, we discuss the issues that arise from the con-current operation of LTE and Wi-Fi in the sameunlicensed bands from the point of view of radioresource management. We show that Wi-Fi isseverely impacted by LTE transmissions; hence,the coexistence of LTE and Wi-Fi needs to becarefully investigated. We discuss some possiblecoexistence mechanisms and future researchdirections that may lead to successful jointdeployment of LTE and Wi-Fi in the same unli-censed band.

FUTURE OF WI-FI

Fuad M. Abinader, Jr., Erika P. L. Almeida, Fabiano S. Chaves, Andr M. Cavalcante, Robson D. Vieira,

Rafael C. D. Paiva, Angilberto M. Sobrinho, Sayantan Choudhury, Esa Tuomaala, Klaus Doppler,

and Vicente A. Sousa, Jr.

Enabling the Coexistence ofLTE and Wi-Fi in Unlicensed Bands

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IEEE Communications Magazine November 2014 55

Dynamic spectrum access (DSA) has emergedas an alternative to overcome the increasingdemand for additional capacity in wireless net-works and spectrum scarcity [6]. DSA enablerslike cognitive radio concepts motivated regulato-ry agencies to allow license-exempt operation inlicensed spectrum. For instance, the UnitedStates [7] and Europe [8] recently publishedrules for operation of secondary users (SUs) inthe so-called TV white spaces (TVWS). Anotherinitiative is authorized shared access (ASA) [9],where incumbent spectrum holders negotiatetheir spectrum with SUs in underutilized loca-tions while maintaining acceptable interferencelevels.

Despite small cells and DSA, spectrumdemand is so intense that joint operation of LTEand Wi-Fi in the same license-exempt bands maybe expected [10]. Although current spectrumallocation does not comprise any overlappedspectrum band between both technologies, therehave been recent discussions in 3GPP concern-ing the need for feasibility studies about thedeployment of LTE in unlicensed spectrum [11].The objective of this study is to determine whichenhancements would be needed from LTE tofulfill regulatory requirements to occupy thosebands, for example, the 5.8 GHz industrial, sci-entific, and medical (ISM) band. Figure 1 showsthe LTE and Wi-Fi spectrum allocation in theUnited States, already considering the 5.8 GHzISM as a possibility for LTE deployment.

Coexistence of LTE and Wi-Fi in the sameband poses certain technical challenges, andsome performance degradation can be expected.From the early coexistence results in [12, 13], aseries of questions could be made to directfuture research: What issues arise from simulta-neous operation of LTE and Wi-Fi in the samespectrum bands? What technology is affectedthe most? What can be done to improve perfor-mance of both networks while coexisting? Shouldenhancements be introduced for the physical(PHY) and/or media access control (MAC) lay-ers?

This article discusses the coexistence of LTEand Wi-Fi networks in the same unlicensed spec-trum bands from the radio resource manage-ment (RRM) perspective. We review thedifferences between LTE and Wi-Fi channelaccess mechanisms, and present recent resultsdemonstrating the performance of the two tech-nologies when they coexist in the same unli-censed band. Then we discuss coexistencemechanisms, including the adaptation of featuresin both LTE and Wi-Fi that may act as enablersfor a coexistence scenario. Finally, we presentfuture research trends and conclusions.

CHALLENGES FORLTE/WI-FI COEXISTENCE IN

UNLICENSED BANDSEnabling different networks to operate in thesame shared spectrum requires taking someissues under consideration. One importantaspect is coexistence, which involves the defini-tion of boundaries for the occupation of radioresources (i.e. time and spectrum) by the net-

works, as well as intelligent modifications on theRRM algorithms to take into account coexistingdissimilar access technologies. Another impor-tant aspect is interworking, that is, intelligentmanagement of user allocations among dissimi-lar access technologies, handling ongoing (e.g.,handover) and incoming (e.g., access selection)connections. This work focuses on the coexis-tence aspects. Interworking and network selec-tion are beyond the scope of this article.

The lack of inter-technology coordination andmutual interference management are some ofthe main challenges for the efficient coexistenceof different wireless technologies. Most broad-band wireless access systems have interferencemanagement mechanisms, but these are designedto work properly for terminals of the same tech-nology. These built-in mechanisms become lesseffective in heterogeneous wireless protocols/standards, which adopt asynchronous time slots,different channel access mechanisms, and dis-parate transmission/interference ranges. In fact,two of the most utilized broadband wirelessaccess networks nowadays, LTE and Wi-Fi, arenot only dissimilar but also incompatible whenoperating in the same band.

Wi-Fi employs OFDM for encoding digitaldata on multiple carrier frequencies, groupedwithin subcarriers where OFDM symbols areactually transmitted. In Wi-Fi infrastructuremode, an access point (AP) bridges a basic sub-scriber set (BSS) of wireless stations (STAs) to awired Ethernet network. STAs and APs utilize aWi-Fi default channel access mechanism, thedistributed coordination function (DCF), toexchange data, control, and management frames.DCF uses a contention-based protocol known ascarrier sense multiple access with collision avoid-ance (CSMA/CA), where nodes listen to thechannel prior to transmission in a procedureknown as clear channel assessment (CCA). Anode in CCA may receive transmissions comingfrom other nodes, causing the channel to beseen as occupied, and hence deferring transmis-sion to a random backoff time. CCA and backoffdecrease the probability of transmission colli-sions in Wi-Fi at the cost of lower channel uti-lization.

On the other hand, LTE employs orthogonalfrequency-division multiple access (OFDMA),which is a multi-user version of OFDM. Multipleaccess is achieved in LTE by assigning subsets ofsubcarriers to individual user equipments (UEs)for a specific number of symbol times (i.e., phys-ical resource block, PRB), thus allowing simulta-neous transmissions from several UEs. In

Figure 1. LTE and Wi-Fi spectrum allocation in the United States, consid-ering future LTE deployment at the 5.8 GHz ISM band.

700 MH

z850

MHz

900 MH

z1.7

GHz1.9

GHz2.1

GHz2.4

GHz2.6

GHz3.65

GHz

5.8 GHz

5.9 GHz 60 G

Hz

802.11y 802.11p 802.11ad

IEEE 802.15.4 ZigBeecordless phone

IEEE 802.11 WLANBluetoothIEEE 802.15.4 ZigBee IEEE 802.11 WLANLTE ?

ISM

LTE LTE LTE LTE LTE LTE

ISM ISM

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IEEE Communications Magazine November 201456

comparison with Wi-Fi using DCF, LTE hasmuch more flexibility regarding resource alloca-tion in time and frequency domains. Also, LTEdoes not require carrier sensing prior to trans-mission. Instead, the LTE base station (knownas eNodeB) allocates radio communication sub-channels for channel estimation and equaliza-tion, synchronization, management, control, anddata transmissions. Finally, eNodeB deploymentis usually planned, and inter-eNodeB communi-cation infrastructure may be used for spectrumusage coordination.

Another challenge is the LTE deploymentmodel for unlicensed spectrum bands. The firstlimiting factor is that regulatory agencies restrictthe effective isotropic radiated power (EIRP) inunlicensed spectrum bands to much lower levelsthan typically used in LTE macrocells. Addition-ally, LTE should be able to determine whetherWi-Fi is jointly operating in the same spectrumas well as establishing a coexistence mechanismwith it. From this, LTE small cells appear as anatural deployment model for LTE operation inunlicensed spectrum.

A potential traffic offloading scenario withcoexisting LTE and Wi-Fi deployments is thesingle floor/multi-room indoor environment withLTE small cells and Wi-Fi, illustrated in Fig. 2.This scenario, composed of 2 rows of 10 rooms,each measuring 10 m 10 m 3 m, is adoptedby both 3GPP and IEEE as a realistic scenarioto represent residential and small office uncoor-dinated deployments.

In standalone single-floor/multi-room indoordeployments, it can be expected that LTE out-performs Wi-Fi in terms of average user

throughput due to its more efficient usage ofradio resources. A recent performance study [12]not only confirmed that, but also showed thatwhen nodes of the two technologies coexist inthe same frequency band, LTE interferenceseverely affects Wi-Fi operation (Fig. 3).1 Themain reason is that LTE, in contrast to Wi-Fi,does not sense for channel vacancy prior totransmissions; thus, Wi-Fi nodes have a tendencyto be blocked by LTE transmissions. Hence,while LTE is seldom affected by Wi-Fi interfer-ence, Wi-Fi is almost silenced when coexistingwith LTE. This can be clearly seen on the aver-age user throughput performance of both tech-nologies presented in Fig. 3, especially for thehigh node density case.

The next section explores enabling featuresfor efficient coexistence between LTE and Wi-Fi.

LTE/WI-FI COEXISTENCE ENABLERSCoexistence mechanisms can be broadly classi-fied into collaborative and non-collaborative(autonomous), according to the exchange ofmessages between coexisting systems. Non-col-laborative mechanisms may be usedautonomously to facilitate coexistence with othernetworks and devices, while collaborative mech-anisms require mutual agreement on the param-eters used in each network.

A classic example of a non-collaborativecoexistence mechanism is CSMA/CA with CCAin Wi-Fi, which enables coexistence with otherwireless network technologies in unlicensedbands such as IEEE 802.15.4 (Bluetooth). Onthe other hand, a representative example of astandardized collaborative coexistence mecha-nism is IEEE 802.19.1, which defines a series ofnetwork elements, functions, and interfaces forthe coexistence and coordination of differentnetworks in TVWS bands. Utilization of collabo-rative coexistence mechanisms has greater poten-tial to provide better performance for allcoexisting networks than non-collaborativemechanisms. We describe a generalized proce-dure for collaborative coexistence through theflowchart in Fig. 4.

The generalized collaborative procedureassumes two operation modes: regular mode(RM) and coexistence mode (CM). RM repre-sents standard operation, where no other tech-nology is assumed to be using the spectrum atthe same location and time. Here, the search forcoexisting systems is done periodically, or trig-gered by external events such as the increase ofthe received interference or the detection of abeacon of another technology.

If a coexisting system is detected, the follow-ing actions are expected: identification of coex-isting systems and synchronization with theidentified systems. Synchronization can be doneby reusing synchronization signals of the coexist-ing technology, such as the primary and sec-ondary synchronization signals (PSS and SSS) ofLTE and the preamble of Wi-Fi. Additional syn-chronization information can also be obtained byexploring the cyclic prefix repetitions of thecoexisting technology.

Next, a negotiation phase is started. At thisstage, the systems sharing the spectrum agree on

Figure 2. Single-floor/multi-room indoor scenario composed of 2 rows of 10rooms, each measuring 10 m 10 m 3 m.

10 m

10 m

10 rooms

3 m2 rows

Figure 3. LTE and Wi-Fi average user throughput relative to Wi-Fi low APdensity for indoor scenario. Deployments: low AP density (4 APs pertechnology) and high AP density (10 APs per technology) with an averageSTA density of 2.5 per AP for both cases. LTE and Wi-Fi evaluations: iso-lated (LTE, Wi-Fi) and in coexistence (LTE (Coex) and Wi-Fi (Coex)).

4.36x

LTE

4.13x

LTE (Coex)

1.00x

Wi-Fi

0.39x

Wi-Fi(Coex)

2.78x

LTE

2.73x

LTE (Coex)

0.44x

Wi-Fi

0.04x

Wi-Fi(Coex)

Low AP density High AP density

Relative average user throughput

1 Network performanceassessed by system-levelsimulations modelingmulti-cell and multi-userstandard-complianttime-division duplexingLTE (TDD-LTE) andIEEE 802.11 (Wi-Fi). Asdetailed in [12, 14], thesesimulations include mod-eling of network layout,nodes distribution, radioenvironment, mutualinterference, PHY andMAC layer, and trafficgeneration.

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system parameters for a fair coexistence. Eachsystem is expected to renounce some resources(e.g., time or frequency) it would use if operat-ing in RM. However, minimum operationalrequirements of individual systems must be satis-fied. If there are no mechanisms for communica-tion between the coexisting technologies, eachsystem should trigger coexistence techniques thatavoid channel access domination by any of thecoexisting radio access technologies.

Finally, each system reconfigures to agreedparameters, thus switching to CM. Once in CM,the systems monitor the shared resources inorder to check whether there is effective opera-tion of the coexisting systems. The system shouldalso check for new secondary users, and returnto the negotiation phase when necessary. Whenno coexisting system activity is detected, theoperation is switched back to RM.

A number of enabling features can help withimplementing collaborative coexistence mecha-nisms for LTE and Wi-Fi. For once, new spec-trum utilization opportunities for both LTE andWi-Fi can be created by allowing spectrumincumbents to grant access to subutilizedlicensed spectrum portions for secondary users,known as flexible spectrum access (FSA). Inaddition, given a specific spectrum portion, theselected spectrum sharing technique may operateon distinct dimensions (time, frequency, andspace). Some LTE mechanisms for interferencemanagement can be adapted to enable coexis-tence with Wi-Fi STAs. On the other hand, sinceLTE interference has the potential to block Wi-Fi STAs using DCF, some features can improveWi-Fi performance in coexistence with LTE,such as channel selection and contention-freeoperation. Table 1 presents a brief taxonomy ofthese enabling mechanisms for LTE/Wi-Fi coex-istence according to the radio access technology.

Mechanisms listed in Table 1 can be used inCM operation within the general collaborativecoexistence procedure illustrated in Fig. 4. Suchcoexistence enablers are described below.

FLEXIBLE SPECTRUM ACCESSTwo opposite spectrum licensing models regu-late the operation of wireless broadband accesssystems. In the licensed model, a spectrum

incumbent acquires exclusive utilization rightsfrom governmental regulatory agencies via, forexample, auctions. On the unlicensed model,spectrum portions are specifically allocated fornon-exclusive utilization, and specific rules areset to ensure coexistence. DSA techniques havebeen considered as alternatives for improvingutilization of spectrum portions. However, DSAefficiency in ensuring primary user rights, as wellas the economic viability of systems operatingunder unpredictable portions of the spectrum,are aspects still under evaluation.

An alternative spectrum allocation model,FSA, has been recently proposed in the litera-ture. One major example of FSA is authorizedshared access (ASA) [9], where the spectrumincumbent economically explores its underuti-lized spectrum assets by granting exclusive accessrights to third-party small cell systems, whichalso brings a number of complementary benefits.FSA grants can be constrained in frequency,time, and space, which ensures protection ofincumbents and increases predictability for long-term investments in both the spectrum incum-bent and the leasing third-party system. Inaddition, since small cells have a diminished cov-erage radius, they can be located nearer to thespectrum incumbent than conventional macro-cells. The ASA approach takes advantage ofexisting products and standards such as LTE sys-tems. As such, ASA has potential for being costeffective by reusing the available LTE infra-structure for complementary wireless service.Also, due to the opportunity for wider spectrum

Figure 4. Generalized collaborative coexistence algorithm.

Coexistingsystem Coexisting

systemdetected

Coexistence modeNegotiation phaseRegular mode

Coexistingsystem detected

Coexistencenot detected

Coexistencedetection

Coexistencedetection

Coexistence not detected

Wait coexistencedetection period

Wait coexistencedetection period

Negotiate coexistenceparameters/synchronize

Table 1. Taxonomy for LTE/Wi-Fi coexistenceenablers.

Enabling mechanism Technology

Flexible spectrum access LTE/Wi-Fi

Channel selection Wi-Fi

Blank subframes LTE

Transmit power control LTE

Non-collaborative

mechanisms may be

used autonomously

to facilitate

coexistence with

other networks and

devices, while

collaborative

mechanisms require

mutual agreement

on the parameters

used in each

network.

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IEEE Communications Magazine November 201458

aggregation, it enables further performanceimprovements.

CHANNEL SELECTIONTwo major differences between Wi-Fi and LTEtechnologies are channel allocation and networkdeployment. While Wi-Fi was developed to beused in unlicensed bands with uncoordinateddeployments, LTE was meant to be used inlicensed spectrum bands and planned deploy-ments. When both of them share the same fre-quency band, Wi-Fi performance is severelydegraded by LTE transmissions, as discussedpreviously. Therefore, channel selection seemsto be an important enabler for LTE/Wi-Fi coex-istence.

The uncoordinated nature of Wi-Fi deploy-ments and the limitation of non-overlappingchannels in the ISM bands have motivated sever-al studies about channel selection for Wi-Fi net-works, which could also be exploited incoexistence with LTE. Some Wi-Fi access points(APs), for example, already implement simplechannel selection techniques, such as least con-gested channel search (LCCS), in which the APmonitors its own channel, also searching forincoming packets from other APs, and selectsthe least congested one.

As a refinement, the subcarrier allocationflexibility provided by OFDM and OFDMAtechniques can also be exploited in coexistencescenarios. Instead of fixed bandwidth channels,adaptive bandwidth channels could be definedand selected in coexistence scenarios.

Since Wi-Fi can be blocked by LTE whencoexisting, it is in Wi-Fis best interest to selectthe least congested channel for operation. In thiscase, some coordination between Wi-Fi APs andLTE eNodeBs for channel selection could easethe task of channel selection. This is an issuesince exchange of information between nodesexperiencing interference relies on a commonintertechnology communication framework, whichis currently unavailable for LTE and Wi-Fi.

BLANK SUBFRAMESAn intuitive way to share the spectrum is avoid-ing technologies to access the channel at thesame time. According to the discussion above,the probability of Wi-Fi being blocked whencoexisting with LTE is high, and since regulatory

rules usually mandate that technologies shouldshare channel access in unlicensed spectrum, atime-sharing coexistence technique wouldrequire LTE silent periods. For this, a key LTEfeature introduced in Release 10, the almostblank subframe (ABS), can be exploited. ABSsare LTE subframes with reduced downlink trans-mission power or activity, intended to coordinatetransmission of macro and pico eNodeBs in het-erogeneous deployments. During an ABS, LTEmacro eNodeBs cause less interference to picoeNodeBs.

A modified version of ABS, where uplink(UL) and/or downlink (DL) subframes can besilenced, and no LTE common reference signalsare included, is proposed in [14] as null-sub-frames to support coexistence with Wi-Fi. It isshown that Wi-Fi is able to reuse the blank sub-frames ceded by LTE, and that throughputincreases with the number of null-subframes.Table 2 shows an example of null-subframe allo-cation inside an LTE frame. However, sinceLTE throughput decreases almost proportionallyto the number of ceded blank subframes, atrade-off is established. Additional LTE perfor-mance degradation may be observed if blanksubframes are nonadjacent, since Wi-Fi trans-missions are not completely confined withinLTE silent periods. This is illustrated in Fig. 5a,which summarizes the main results in [14]. How-ever, if the duration and occurrence of LTEblank subframes is reported to Wi-Fi during thenegotiation phase (Fig. 4), Wi-Fi nodes might beable to conveniently confine their transmissionswithin blank subframes and thus avoid interfer-ing with LTE.

TRANSMIT POWER CONTROLLTE UL transmit power control is an alternativeto the LTE blank subframes time-sharingapproach for LTE/Wi-Fi coexistence. Here, acontrolled decrease of LTE UEs transmit pow-ers diminishes the interference caused to neigh-boring Wi-Fi nodes, thus creating Wi-Fitransmission opportunities as Wi-Fi nodes detectthe channel as vacant. Conventional LTE ULpower control compensates only a fraction of thepath loss. This effectively reduces LTE intercellinterference, as UEs experiencing high path loss,usually in the cell edge, have their UL transmitpower diminished. However, LTE power control

Table 2. Examples of null-subframe allocation considering LTE TDD. The coexistence time denotesthe amount of time given for coexistence with Wi-Fi. D and U denote regular DL and UL subframes,respectively. S denotes a special subframe for signaling. C denotes coexistence subframes (with noLTE transmissions).

Subframe number

Coexistence time 0 1 2 3 4 5 6 7 8 9

0 ms D S U U D D S U U D

2 1 ms D S C U D D S U U C

4 ms D C C C C D S U U D

2 2 ms D S C C U U S C C D

The uncoordinated

nature of Wi-Fi

deployments and the

limitation of non-

overlapping channels

in the ISM bands

have motivated

several studies about

channel selection for

Wi-Fi networks,

which could also be

exploited in coexis-

tence with LTE.

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based on path loss is not effective for Wi-Ficoexistence, which requires transmit powerreduction of UEs causing high interference toWi-Fi nodes.

An LTE UL power control with an interfer-ence-aware power operating point is proposed in[15] for enabling coexistence with Wi-Fi. Interfer-ence measurements performed at LTE eNodeBsand/or UEs allow estimating the presence andproximity of Wi-Fi nodes. UEs measuring highinterference are more likely to cause high inter-ference, so UL transmit power is reduced accord-ing to a fractional compensation of the measuredinterference. LTE UL power control defines UEtransmit powers so that path loss and interferenceare compensated and a given signal quality (i.e., atarget signal-to-interference-plus-noise ratio,SINR), is achieved at the LTE eNodeB receiver.This fractional compensation of the measuredinterference corresponds to decreasing the targetSINR when high interference is observed. Assuch, LTE UE throughput is decreased accord-ingly. As seen in Fig. 5b, the reduction of keyLTE UEs transmit powers indeed allows neigh-boring Wi-Fi transmissions at the cost of decreas-ing LTE throughput.

Simulated throughput results in Fig. 5 actual-ly demonstrate that LTE blank subframes andUL transmit power control define differenttrade-off configurations for LTE and Wi-Fi incoexistence. While Fig. 5a shows the simultane-ous Wi-Fi throughput increase and LTEthroughput decrease with the number of blanksubframes allocated, in Fig. 5b the decrease inthe fraction of interference compensated by LTE

UL transmit power control also decreases LTEthroughput in favor of Wi-Fi throughputincrease.

LTE/WI-FI STANDARDIZATION FORCOEXISTENCE IN

UNLICENSED BANDSStudies undertaken so far clearly reveal that

some challenges need to be addressed for thecoexistence of LTE and Wi-Fi in the same unli-censed band. Standardization bodies (i.e., 3GPPand IEEE) are addressing some of these chal-lenges.

From the perspective of LTE, 3GPP hasrecently started discussion on operation in unli-censed bands. A Study Item was created fordefining modifications necessary to LTE radiofor deployment in unlicensed spectrum [11]. Onthe other hand, with Wi-Fi conventionally oper-ating in unlicensed bands, IEEE has worked onstandardized mechanisms for allowing efficientcoexistence among heterogeneous wireless broad-band access technologies within TVWS bands.One major example of IEEE initiatives for oper-ation in TVWS is the IEEE 802.19 WorkingGroup (WG) [16], where a task group named802.19 TG1 addresses coexistence for IEEE 802networks and devices. These studies can also beuseful for non-IEEE 802 networks and TV banddevices (TVBDs). Another initiative is the IEEE802.11af standard, published in February 2014,which covers Wi-Fi operation in the VHF andUHF bands between 54 and 790 MHz.

Figure 5. LTE and Wi-Fi average user throughput performance in coexistence with a deployment of 10APs/25 STAs per technology in a 20-room single-floor indoor scenario, relative to Wi-Fi with noblank subframe. a) blank subframes allocation; b) LTE UL power control with an interference-awareoperating point.

Ordinary LTE frame(no blank subframes)

14.45x

7.51x

1.00x

1 blank subframe

14.73x

4.48x

1.53x

2 blank subframes

(a)

14.71x

3.05x1.89x

4 blank subframes

12.98x

0.84x

3.08x

Ordinary LTE power control(full interf. compensation)

14.45x

7.51x

1.00x

50% interferencecompensation

14.53x

6.46x

1.14x

10% interferencecompensation

(b)

14.44x

4.26x

1.60x

No interferencecompensation

13.04x

0.29x

2.97x

LTE DL LTE UL Wi-Fi

LTE DL LTE UL Wi-Fi

Studies undertaken

so far clearly reveal

that some challenges

need to be

addressed for the

coexistence of LTE

and Wi-Fi in the

same unlicensed

band. Standardiza-

tion bodies

(i.e., 3GPP and IEEE)

are addressing some

of these challenges.

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With the increasing relevance of Wi-Fi fortraffic offloading in cellular networks, improvingWi-Fi efficiency in terms of end-user perfor-mance in the presence of dense deployment ofAPs and STAs has become more important.Recognizing this, IEEE 802 WG created theIEEE 802.11 High Efficiency WLAN (HEW)Study Group (SG) [2] in May 2013, aiming toenhance the quality of experience (QoE) ofwireless users in everyday high-density scenarios.As a result of the discussions in HEW SG, theIEEE 802.11ax Task Group (TGax) was recentlyestablished to substantially increase userthroughput in dense networks with a large num-ber of users and devices, dense heterogeneousnetworks, and outdoor deployments. TGaxincludes improvements to cellular offloading asone of its major requirements, and is also inves-tigating mechanisms to increase spatial capacitywith PHY-MAC enhancements to the existingIEEE 802.11 standard in the 2.4 GHz and 5GHz radio frequency bands. A first draft ofTGax amendments to IEEE 802.11 is expectedto be concluded by 2016.

CONCLUSIONS

The wireless communications community hasbeen searching for solutions to handle theincreasing demand for wireless broadbandaccess. In this context of spectrum scarcity, therehas been recent discussion about allowing wire-less network technologies like LTE and Wi-Fi tocoexist in the same unlicensed bands. In thisarticle, we show that Wi-Fi is severely affectedby concurrent operation of LTE in the sameband. This indicates a serious need for coexis-tence mechanisms to improve the performanceof both systems. The applicability of some coex-istence enabling features for both LTE and Wi-Fi are discussed, and research directions forfurther development of inter-technology coexis-tence are presented. We also propose coexis-tence mechanisms by reusing the blank subframeapproach and the UL transmit power used inLTE, and show that it can significantly improveWi-Fi performance when coexisting with LTE inthe same unlicensed bands.

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[3] G. Staple and K. Werbach, The End of Spectrum Scarcity,IEEE Spectrum, vol. 41, no. 3, Mar. 2004, pp. 4852.

[4] Deloitte, Airwave Overload? Addressing SpectrumStrategy Issues that Jeopardize U.S. Mobile BroadbandLeadership, Deloitte Development LLC, White Paper,Sept. 2012.

[5] C. Sankaran, Data Offloading Techniques in 3GPP Rel-10 Networks: A Tutorial, IEEE Commun. Mag., vol. 50,no. 6, 2012, pp. 4653.

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[7] FCC 10-198 Notice of Inquiry, Nov. 2010, ET Docketno. 10-237.

[8] ECC, Technical and Operational Requirements for theOperation of White Space Devices under Geo-LocationApproach, Report 186, Jan. 2013.

[9] M. Matinmikko et al., Cognitive Radio Trial Environ-ment: First Live Authorized Shared Access-Based Spec-trum-Sharing Demonstration, IEEE Vehic. Tech. Mag.,vol. 8, no. 3, Sept. 2013, pp. 3037.

[10] M. I. Rahman et al., License-Exempt LTE Systems forSecondary Spectrum Usage: Scenarios and First Assess-ment, IEEE Symp. New Frontiers in Dynamic SpectrumAccess Networks, DySPAN, 2011, pp. 34958.

[11] Q. Ericsson, Study on LTE Evolution for UnlicensedSpectrum Deployments, 3GPP TSG RAN Meeting 62,3GPP TSG RAN Std. RP-131 788, Dec. 2013; http://www.3gpp.org/ftp/tsg ran/TSG RAN/TSGR 62/Docs/RP-131788.zip

[12] A. M. Cavalcante et al., Performance Evaluation of LTEand Wi-Fi Coexistence in Unlicensed Bands, Proc. IEEE77th VTC 2013-Spring, Dresden, Germany, June 2013.

[13] T. Nihtil et al., System Performance of LTE and IEEE802.11 Coexisting on a Shared Frequency Band, IEEEWireless Commun. and Networking Conf. 2013, Apr. 2013.

[14] E. P. L. Almeida et al., Enabling LTE/Wi-Fi Coexistence byLTE Blank Subframe Allocation, Proc. IEEE ICC 13, 2013.

[15] F. S. Chaves et al., LTE UL Power Control for theImprovement of LTE/Wi-Fi Coexistence, Proc. IEEE VTC2013-Fall, Las Vegas, NV, Sept. 2013.

[16] T. Baykas, M. Kasslin, and S. Shellhammer, IEEE802.19.1 System Design Document, IEEE 802 WG,Mar. 2010.

BIOGRAPHIESFUAD M. ABINADER, JR. (fuad.abinader@indt.org.br) receivedhis B.Sc. in computer science from Federal University ofAmazonas (UFAM) in 2003, and his M.Sc. in informaticsfrom UFAM in 2006. He is currently a doctoral student inelectrical engineering at Federal University of Rio Grandedo Norte (UFRN) and a researcher at Nokia Institute ofTechnology (INdT). His current interests include mobileInternet protocols, Wi-Fi, LTE, and WiMAX, and standard-ization in IEEE, 3GPP, and IETF.

ERIKA P. L. ALMEIDA (erika.almeida@indt.org.br) received herB.Sc. in telecommunications engineering and M.Sc. degreesfrom the University of Brasilia (UnB), Brazil, in 2007 and2010, respectively. She has been a researcher at INdT since2011, where she has worked on LTE, white space conceptsand coexistence issues in TV white spaces. Her currentresearch topics include Wi-Fi evolution and cognitive radionetworks.

FABIANO S. CHAVES (fabiano.chaves@indt.org.br) received hisB.Sc. and M.Sc. degrees in electrical engineering from theFederal University of Cear (UFC), Brazil, and his Ph.D.degree in electrical engineering from the University ofCampinas (UNICAMP), Brazil, and the cole NormaleSuprieure de Cachan, France, in 2010. Since 2010, he hasbeen a research engineer at INdT, Brazil. His research inter-ests include radio resource management, signal processingand game theory for communications, and cognitive radiosystems.

ANDR M. CAVALCANTE (andre.cavalcante@indt.org.br)received his B.Sc., M.Sc., and Ph.D. degrees in electricalengineering from Federal University of Par (UFPA) in 2001,2003, and 2007, respectively. Since 2007 he has worked asa research engineer at INdT on several research projectsand standardization activities (IEEE). His areas of interestare the evolution of Wi-Fi networks, beyond 4G networks,and systems with multiple antennas.

ROBSON D. VIEIRA (robson.d.vieira@indt.org.br) receivedM.Sc. and Ph.D. degrees in electrical engineering fromthe Catholic University of Rio de Janeiro, Brazil, in 2001and 2005, respectively. From 2005 to 2010, he workedwith white space concepts, and supporting some GERANand 802.16m standardization activities focused on sys-tem performance evaluation at INdT. Since 2010, he isan R&D technical manager at INdT. His research interestsinclude Wi-Fi Evolution, B4G, and cognitive radio net-works.

RAFAEL C. D. PAIVA (rcdpaiva@yahoo.com.br) has been aresearcher at INdT since 2008. He obtained his Bachelorsdegree in electrical engineering from Federal University ofSanta Maria (UFSM) in 2005, his Masters degree in signal

With the increasing

relevance of Wi-Fi for

traffic offloading in

cellular networks,

improving Wi-Fi

efficiency in terms of

end-user perfor-

mance in the

presence of dense

deployment of

APs and STAs

has become more

important.

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processing from the Federal University of Rio de Janeiro(UFRJ) in 2008, and his Doctors degree in acoustics andaudio signal processing from Aalto University in 2013.Among his research interests are digital signal processingand new technologies of wireless networks.

ANGILBERTO M. SOBRINHO (angilberto.m.sobrinho@indt.org.br) received his M.Sc. degree in computer architec-tures from the Industrial Engineering Faculty (FEI) in1984, and his M.Sc. in industrial automation from FederalUniversity of Campina Grande (UFCG) in 2006. He joinedas a professor of the State University of Amazonas (UEA)in 2005, and since 2012 has been working as a researcherat INdT. His main areas of interest are time synchroniza-tion in packet networks, and adaptive and phased arrayantennas.

SAYANTAN CHOUDHURY (sayantan.choudhury@nokia.com)leads the wireless research and standardization activities inNRC-Berkeley. His interests include optimization of PHY andMAC layers focusing on LTE-Advanced and next generationWi-Fi networks. Currently, he is investigating concepts toenable dense deployments of Wi-Fi and also coexistence ofLTE and Wi-Fi systems in unlicensed bands. He is the co-recipient of the 2009-2010 Sharp Labs Inventor of the Yearaward, and the 2010 IEEE Transactions on Multimedia and2012 PIMRC Best Paper awards.

ESA TUOMAALA (esa.tuomaala@nokia.com) received hisM.S.(Tech.) degree in engineering physics and mathematicsfrom Helsinki University of Technology, Espoo, Finland, in2002. He joined Nokia Research Center in 2000. He is cur-rently working as a principal researcher, focusing on sys-tem-level performance evaluation of next generationwireless systems and contributing to the development ofrelevant IEEE standards.

KLAUS DOPPLER (klaus.doppler@nokia.com) received his Ph.D.from Helsinki University of Technology, Finland, in 2010 andhis M.Sc. in electrical engineering from Graz University ofTechnology, Austria, in 2003. He joined Nokia ResearchCenter in 2002 and currently leads the Wireless Systemsteam in Berkeley, California. He has been recognized severaltimes as top inventor in Nokia. He has about 75 pendingand granted patent applications, and published in 30 jour-nals, conference publications, and book chapters.

VICENTE A. DE SOUSA, JR. (vicente.sousa@ct.ufrn.br) receivedhis B.Sc., M.Sc., and Ph.D. degrees in electrical engineeringfrom UFC in 2001, 2002, and 2009, respectively. Between2001 and 2006, he developed solutions to UMTS/WLANinterworking for UFC and Ericsson of Brazil. Between 2006and 2010, he contributed to WIMAX standardization andNokias product as a researcher at INdT. He is now a lectur-er at UFRN, Brazil.

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