IEEE TRANSACTIONS ON COMMUNICATIONS 1 Slot Jamming …

IEEE TRANSACTIONS ON COMMUNICATIONS 1

Slot Jamming Effect and Mitigation BetweenLTE-LAA and WLAN Systems With Heterogenous

Slot DurationsYao Ma, Senior Member, IEEE, Daniel G. Kuester, Senior Member, IEEE, Jason Coder, and William Young

Member, IEEE

Abstract—To improve spectrum sharing between long-termevolution (LTE) license assisted access (LAA) and incumbentsystems such as wireless local area networks (WLANs) in unli-censed spectrum, listen before talk (LBT) has been proposed as acandidate for LAA channel access. To allow for a robust spectrumsensing performance, LBT may use a backoff-slot duration thatis substantially larger than its WLAN counterpart. There ispotential for an unknown backoff slot-jamming (SJ) effect, whichmay significantly decrease channel access probability (CAP) andthroughput of LAA-LBT links. In this paper, we study the SJeffect and propose an effective anti-SJ (ASJ) LBT scheme. Togain theoretical insight, we develop a new performance analysisapproach on coexisting systems with different slot durations. Wemodel the LAA backoff process with super-counters, provide anin-depth analysis of the backoff process, and derive key perfor-mance indicator (KPI) statistics. These KPIs include backoff holdtime, successful transmission probability, CAP, and throughput.Simulation results thoroughly validate our analytical results, andshow that the ASJ-LBT scheme is effective in mitigating the SJeffect. These results fill a major technical gap in spectrum sharingresearch and may be extended to support system optimizationand coexistence analysis of other heterogeneous systems.

Index Terms—CSMA/CA; LTE-LAA; MAC-layer PerformanceAnalysis; Wireless Spectrum Sharing; WLAN.

I. INTRODUCTION

A. Background and Motivations

Congestion and scarcity of available spectrum resourcesmotivate research on unlicensed spectrum sharing betweenlong-term evolution license assisted access (LTE-LAA) andthe incumbent systems, such as Institute of Electrical andElectronics Engineers (IEEE) 802.11 wireless local area net-work (WLAN) [1]–[8]. The 3rd Generation Partnership Project(3GPP) has considered the use of listen before talk (LBT)as a possible candidate to enable constructive coexistencebetween LAA and incumbent systems [4], [5]. Besides 3GPP,the European Telecommunications Standards Institute (ETSI)has defined unlicensed spectrum sharing procedures via LBT

Manuscript received June 8, 2018; revised December 6, 2018 and February4, 2019; accepted February 5, 2019. The editor coordinating the review ofthis paper and approving it for publication was Prof. Zaher Dawy.

U.S. Government work not protected by U.S. copyright.This paper was presented in part at the IEEE International Conference on

Communications (ICC), May 2017.Yao Ma, Daniel G. Kuester, and Jason Coder are with Communications

Technology Laboratory, National Institute of Standards and Technology, 325Broadway, Boulder, Colorado, USA.

William Young participated in this work when he was affiliated with NIST,USA. He is now with the MITRE Corporation.

[7], [8]. Various aspects of LTE-LAA and WLAN coexistencehave been extensively studied, including experimental andfield test results [4]–[6], performance analysis [16]–[20], andoptimization methods (e.g., [11]–[13]). WLAN uses carriersense multiple access with collision avoidance (CSMA/CA) inthe medium access control (MAC) layer, whereas load-basedLBT may use a similar CSMA/CA protocol but with differentspecifications.

The WLAN idle slot duration is 9 µs for several popularphysical-layer specifications in the 5 GHz industrial, scientific,and medical (ISM) band [10]. Regarding LAA and WLANcoexistence, their backoff idle slot durations can be eitheridentical or different. In the first setup, the LAA idle slotduration is assumed to be equal to its WLAN counterpart.This is convenient for system design and analysis, but maynot provide adequate time for channel sensing. Typically, alimited portion in an idle slot duration is used for channelsensing, such as the clear channel assessment (CCA) durationin WLAN. When the slot duration is 9 µs, the actual timefor sensing is as low as 4 µs for LAA and WLAN systems[9], [10]. Each LAA node requires adequate channel sensingdurations for the robust and reliable detection of channelactivity. This is even more important when sensing occurs onmultipath fading channels when a low signal to noise ratio(SNR) may be experienced.

In the second setup, the LAA slot duration can be largerthan its WLAN counterpart. Since an LAA small cell typicallyhas a larger coverage area than a WLAN contention zone andalso experiences more mutual interference, there is a practicalneed to consider an LAA slot duration larger than 9 µs toachieve a more reliable channel sensing performance. In 3GPPtechnical reports [4], [5], the LAA backoff idle slot durationcan be up to 20 µs. In the ETSI standards [7], [8] pertaining tounlicensed spectrum sharing in a few 5 GHz frequency bands,the LBT idle slot duration is set to 18 µs in [7] and at least9 µs in [8]. Though the second setup is technically useful,there are two problems: First, heterogeneous slot durationsmay cause a slot jamming (SJ) effect; second, the performanceevaluation is challenging due to the lack of prior art onmodelling and analysis of this setup. The SJ effect has beenoriginally described in our preliminary result [19]. The SJcauses WLAN links to have channel access advantage andsignificantly decreases channel access probability (CAP) andthroughput of LAA-LBT links. A straightforward mitigation ofSJ is to significantly reduce the contention window (CW) size


of LAA links. However, this may cause substantially increasedchance of collisions, and still may not be effective. To treat theroot-cause of the SJ problem, we develop a new LBT schemethat uses variable slot duration to effectively mitigate it.

In general, the backoff-slot durations can be non-identicalin different CSMA/CA-based systems, such as IEEE 802.15,IEEE 802.11, and LTE-LAA LBT systems. Hence, analyzingthe case of heterogeneous backoff-slot durations will haveimportant theoretical and practical value, which is useful forfuture coexistence applications of heterogeneous systems.

In this paper, we address the challenging problem of designand performance analysis of LAA-LBT-based coexistencesystems with heterogeneous slot durations. The contributionsare highlighted as follows:

• We show that with heterogeneous backoff-slot durationsbetween LAA and WLAN systems, there is a previously-unknown backoff-slot jamming effect to LAA nodesbased on an original LBT.1 We propose an anti-SJ (ASJ)-LBT scheme to mitigate this negative effect.

• For both the original-LBT and the proposed ASJ-LBTschemes, we develop a novel analytical tool to modelthe non-identical backoff-slots with super-counters andweighted probability transition paths. Then, we providea thorough performance analysis on key performanceindicators (KPIs), such as the backoff counter holdtime, successful transmission probability (STP), CAP, andthroughput of both LAA and WLAN systems.

• We program the related LBT algorithms and implementextensive Monte Carlo simulations, which validate theaccuracy of all of the analytical results. Select throughputresult is also validated by our software defined radio(SDR) experimental test, which is designed and reportedin [21]. Numerical results show that while the SJ effectis detrimental, the proposed ASJ-LBT scheme can signif-icantly alleviate the SJ effect in terms of throughput andSTP.

The new techniques developed in this paper fill a majorgap in coexistence design and analysis of LAA-LBT-basedspectrum sharing systems, and can be extended to the analysisof other CSMA/CA based heterogeneous wireless systems.The technical insight and method provided by this work maybe used for KPI optimization of coexisting systems, and tosupport flexible slot duration design in future 3GPP and ETSIunlicensed spectrum access standards.

B. Related Work

The impact of heterogeneous slot durations in coexistingLAA-LBT and WLAN systems has not been adequatelystudied. Available methods face formidable challenges toaddress the case of non-equal idle backoff-slot durations. Apopular approach for CSMA/CA performance analysis fora WLAN system is developed in [14], [15], and has beenextended in [16]–[18], [20] to coexistence analysis of LAAand WLAN systems. However, extending this framework tomodel complex system interactions appears intractable when

1Here, the original-LBT refers to the LBT schemes given in [4], [5] withslight revisions, as shown in Fig. 1.

these systems have non-identical slot durations. For example,this method does not provide a clear procedure to model andcompute the backoff wait time per counter reduction (CR).Furthermore, it is not clear how to incorporate the backoff timeinformation (even when available) in this method to analyzethe throughput.

Recently, a more powerful method on CSMA/CA perfor-mance analysis is provided in [22]–[24], in which explicitmodels of the backoff hold time and non-traditional statis-tics are developed to compute the MAC layer throughput.However, the methods in [22]–[24] consider only a WLANsystem, and assume identical backoff idle slot durations amongall links. How to extend this approach to the performanceevaluation of multiple coexistence systems with heterogeneousslot durations is not clear.

Regarding joint optimization LTE-LAA and WLAN sys-tems, several schemes have been proposed in [11]–[13] andaddressed various system and fairness constraints. Yet, theeffect of non-identical backoff slot durations is not modelledor analyzed therein.

Coexistence analysis between IEEE 802.11 WLAN andIEEE 802.15.4 systems has recently been implemented in [25],where the 802.15.4 devices are assumed to have a backoff-slotduration three times as large as their counterpart WLAN nodes.This method, however, cannot be used for the LAA-LBT andWLAN coexistence analysis. Besides differences in the MACprotocols between LTE-LAA and IEEE 802.15.4, a 802.15.4device does not have the backoff-slot frozen requirement asthe LAA node. Thus, we need to develop a new analyticaltechnique to solve the problem at hand.

From the review of the above, there is a significant technicalgap on the modelling and analysis of slot-heterogeneousCSMA/CA systems, especially the case that LAA backoff-slot duration is larger than the WLAN counterpart. In ourpreliminary result [19], an ASJ-LBT scheme is proposedand analyzed, but the SJ effect of the original LBT schemeis not modelled or analyzed. In this paper, we perform athorough performance analysis of both original-LBT and ASJ-LBT schemes, and make extensive comparisons. The obtainedanalytical and simulation results can provide a guideline forperformance optimization of coexistence slot-heterogeneoussystems.

The remainder of this paper is organized as follows: SectionII presents an LBT-based LAA and WLAN coexistence systemmodel, describes the SJ effect, and presents a new ASJ-LBTscheme. Section III defines a preliminary mathematical modelfor coexistence analysis. Section IV presents a coexistenceperformance analysis for LTE-LAA with original-LBT usinga novel super-counter model assuming heterogeneous slotdurations. Section V presents the analysis of ASJ-LBT schemebased on a more complicated super-counter model. Section VIvalidates all the analytical results via Monte Carlo simulations,as well as an SDR test result, and compares the performance oforiginal and ASJ LBT schemes. Conclusions are provided inSection VII. For ease of reference, some symbols, expressionsand their definitions are listed in Table I.


TABLE I: Definition of select symbols and expressions frequently used in this paper.

Symbol or Expression Definition

TL,0 (or TW,0) Time per counter reduction (CR) in an LAA (or WLAN) link.

TS,L (or TF,L) Time of successful (or failed) transmission in an LAA link.

τLOL (or τGO

L ) Locally (or globally) observed channel access probability (CAP) of an LAA link.

P̂i,L (or Pi,L) Observed LAA channel idle probability by an LAA (or WLAN) link.

P̂S,L (or PS,L) Observed LAA successful transmission probability (STP) by an LAA (or WLAN) link.

πS,L (or πS,W ) State probability of successful transmission of an LAA (or WLAN) link.

πR,L,k (or πF,L,k) State probability of backoff (or failed transmission) at stage k of an LAA link.

II. SYSTEM MODEL

Here, we consider a scenario that several LTE-LAA linksand WLAN links use CSMA/CA schemes (such as LBT) tocoexist in unlicensed bands. The processing flow of an LAACategory 4 LBT scheme is shown in Fig. 1, as adopted from[4], [5] with modifications. In comparison with [4], [5], weswitched the order of the blocks “z > 0" and “extended CCA".This revision lets a transmitter that finishes one transmissionto wait for an additional idle slot before it restarts the backoffprocess. This change makes sure that after a channel busyperiod, the active transmitter that finishes its transmissionopportunity (TXOP) does not have priority over the otherstations in the next channel access competition. It is consistentwith the non-contiguous transmission requirement set by 3GPPand ETSI [4], [7]–[9].

A channel busy duration for basic access scheme is formedby payload duration, TSIFS, TACK, and TDIFS, where TSIFS,TACK, and TDIFS refer to short interframe space (SIFS), ac-knowledgement signal duration, and distributed coordinationfunction (DCF) interframe space (DIFS), respectively. Whenan LAA transmission is over, the receiver waits for a durationof SIFS, and sends back an ACK signal via the reverse link.Then, after a TDefer silent duration, all links resume backoffcountdown.

To facilitate smooth coexistence, we make the followingassumptions:

1) The LAA extended defer period (TDefer) is set equal tothe WLAN DIFS duration (TDIFS).

2) Both LAA-LBT and WLAN systems use a similarCSMA/CA protocol with multistage backoff, but withdifferences on some parameters, such as CW size, max-imum backoff stage, slot duration, and payload duration.The LBT and DCF protocols we consider here followclosely those described in [4], [5], [14], [15], [22].

3) Failed transmissions are caused by either collisions orlow channel SNR. We define packet error rate (PER) tomodel the effect of low SNR on the KPIs. This is moregeneral than the assumption in [14], [15], [22], [24] thatfailed transmissions are only caused by collisions.

When Ns = 1, in an idle slot of 9 µs, there is an overhead ofabout 5 µs which is caused by MAC and physical layer delays,and transmit and receive turn around time, etc. There is about4 µs dedicated for CCA sensing [9], [10]. When Ns = 2 or3, the LAA node has 9× 2− 5 = 13 µs or 9× 3− 5 = 22 µsfor CCA sensing, respectively. The sensing time ratio between

Ns = 2 or 3 vs. Ns = 1 is 13/4 or 22/4, and this brings about5.12 dB or 7.4 dB improvement of SNR for channel detection,respectively. Therefore, the non-equal idle slot setup for theLAA is very useful for a low SNR scenario.

A. Slot-Jamming Effect in LAA-LBT with Heterogeneous SlotDurations

We define δL and δW as the backoff idle slot durations forLAA and WLAN, respectively. In the original-LBT, the idleslot duration δL is fixed at δL = NsδW , where Ns is a positiveinteger.

Fig. 1: Flow diagram of LTE downlink LAA LBT Category-4procedure (aka, an original LBT), adopted from [4], [5] withminor revisions. We mark the backoff SJ effect assuming thatthe LTE-LAA system has a backoff-slot duration larger thanthat of the WLAN system.

We point out that when Ns > 1, the original-LBT schemecan cause a backoff SJ effect which is disadvantageous to theLAA links. This is not investigated in the available literature(except briefly by our preliminary result in [19]). This SJ effectis illustrated for the original-LBT in Fig. 2 which assumesNs = 3. In the example shown in Fig. 2, an LAA CR takes alonger slot duration (NsδW ) than its WLAN counterpart (δW ),


Fig. 2: Backoff counter reduction and transmission process of one LAA link (with original-LBT) and one WLAN link, whenthe LAA has backoff-slot duration three times as large as that of the WLAN system (Ns = 3).

Fig. 3: Backoff counter reduction and transmission process of one LAA link (with the proposed ASJ-LBT) and one WLANlink, when Ns = 3.

and before it reaches a slot boundary, a WLAN counter mayfirst reduce to zero and begin a transmission. After the channelbusy state is over, the LAA node has to reset the countervalue to the state before the WLAN transmission occurs:that is, the reduction can be jammed if there are frequentWLAN transmissions (when Ns > 1). The SJ effect happensin WLAN slots 3-9 in Fig. 2, where the LAA counter valueremains at two, and its reduction is interfered and jammed byWLAN transmissions. When there are an increased numberof WLAN links, the SJ effect will be more severe. Besidesthe case of LAA and WLAN coexistence with different slotdurations, the SJ effect can also happen when two or moreLAA systems coexist and have different slot durations.

B. A Countermeasure Scheme: ASJ-LBT

In the LAA backoff CR scheme, shown in Fig. 1 and Fig.2, an LAA CR occurs in either of the following two cases:

1) when the channel becomes idle for TDIFS+δL right aftera channel-busy state;

2) the channel becomes idle for δL again right after aprevious CR.

The SJ effect reduces the CAP and throughput of LAA nodeswhen Ns > 1. To mitigate this problem, we propose animproved LAA CR scheme, where δL can be a variabledepending on cases 1 and 2 of channel status, and name it theASJ-LBT scheme. Suppose that an LAA node has maximumbackoff stage K (aka. cutoff stage), with CW size Zk at stagek, for k = 0, 1, . . . ,K.

The ASJ-LBT Scheme

1) Initialize to backoff stage 0 (k = 0). Draw counter valueZ ∈ (1, Z0), where Z0 is the LAA initial CW size.

2) Decrease counter Z by 1 in either of the following cases;otherwise, freeze the counter.case 1: Following a channel busy state, if the channelbecomes idle for TDIFS + δW ;case 2: After the previous CR, channel is idle again forδL = NsδW .

3) If Z is reduced to zero, starts a transmission.4) If the transmission is successful, go to step 1);5) If the transmission fails: if k < K, add backoff stage k

by 1, draw counter value Z ∈ (1, Zk), and go to step2); and if k = K, drop the packet and go to Step 1).

In our proposed ASJ-LBT scheme, in step 2) when any nodejust finishes a transmission, the channel will be idle for at leastTDIFS+δW duration. This gives an opportunity for all the nodesto reduce their counters by one. In case 1, each LAA node hasa slot duration δL = δW , so that LAA and WLAN nodes haveequal priority in reducing their counter values. After an LAACR, if the idle period continues (the status becomes case 2),then we still set δL = NsδW , which enables an adequate slotperiod for channel sensing.

The state transition with CR for the proposed scheme isgiven in Fig. 3. In WLAN slot indexes 5 and 9 of Fig. 3,the ASJ-LBT scheme allows the LAA CR after each channelbusy event, and consequently makes an LAA transmission atslot 9. This is in contrast to that shown in Fig. 2 where theoriginal-LBT has a counter value being jammed to two.


The ASJ-LBT scheme has two advantages over the original-LBT: 1) it significantly mitigates the SJ effect, so that itprotects CAP and throughput of LAA links; and 2) it causesonly a small impact on channel sensing accuracy. Althoughthe total idle duration used for channel detection in case 1 isreduced from TDIFS +NsδW to TDIFS + δW , it is still typicallylarger than NsδW (the idle slot duration in case 2). The ASJ-LBT is designed to treat the root cause of the SJ effect,and it may be combined with some CSMA/CA parameteroptimization schemes [23], [24] to further provide target KPIs,such as proportional fairness or maximization of throughput.

III. PRELIMINARY MODELLING AND ANALYSIS FOR THELAA-LBT

To analyze the performance of the original-LBT and ASJ-LBT schemes and make comparisons, we provide a newmathematical modeling of coexistence systems in this section.The results will be used to further analyze both originaland ASJ-LBT schemes. The basic formulas for throughputevaluation developed here are fundamentally different fromthose used in [16]–[18]. Our method has a slight similarityto those given in [22]–[24], but has several major differencesand enhancements in modelling and analytical techniques tocompute STP, CAP, and transmission backoff duration.

A. A New Mathematical Modeling of Coexistence System

The backoff-and-transmission state transition model fora Category-4 LBT is described in Fig. 4.(a). At stage k(k = 0, . . . ,K), Rk and Fk are the backoff state and failedtransmission state, respectively, and Pt,L is the conditionalprobability of a successful LAA transmission (conditioned onthat an LAA transmission starts). The state of a successfultransmission is denoted by S. When the transmission in stageK fails, the counter moves to stage 0.

Some detail about one backoff stage (stage k) with Ns > 1is described in Fig. 4.(b), where one LBT idle slot duration isNs times as large as a WLAN idle slot duration (Ns > 1). Thissignificantly changes the interactions between LAA-LBT andWLAN systems in terms of CAP, STP, and throughput, com-pared to the case of Ns = 1. Available analytical approachesare not flexible enough to analyze coexistence performance inthis scenario.

Based on the LAA-LBT Markov model of Fig. 4, someCSMA/CA parameters related to LTE and WLAN coex-istence are defined here. In this paper, we use subscriptsL,W, p, i, S, F to denote LAA, WLAN, payload, idle slot,successful transmission, and failed transmission, respectively.

We define TP,L (and TP,W ) as payload duration, TS,L (andTS,W ) as channel access duration caused by a successfultransmission (which includes payload, TSIFS, ACK and TDefer),TF,L (and TF,W ) as channel access duration caused by a failedtransmission, and TR,L (and TR,W ) as total backoff durationfor an LAA (and WLAN) node, respectively. Furthermore, foran LAA (and WLAN) node, we define πS,L (and πS,W ) as theprobability of a successful transmission, πF,L (and πF,W ) asthe probability of a failed transmission, and πR,L (and πR,W )as the probability of staying in a backoff stage, respectively.

For the basic access schemes in the LAA-LBT system, wedefine TS,L = TP,L + TSIFS + TL,ACK + TDIFS + δL, andTF,L = TS,L, where the purpose of δL is to remove thechannel access priority of the LAA node which just finishes asuccessful transmission. For the RTS/CTS-type access in theLAA system, we define

TS,L = TRTS + TSIFS + TCTS + TSIFS + TP,L

+TSIFS + TL,ACK + TDIFS + δL, (1)TF,L = TRTS + TSIFS + TL,ACK + TDIFS + δL. (2)

The TS,W , TF,W for WLAN with RTS/CTS access can beobtained, similar to (1)-(2). The time-efficiency throughputsof an LAA link and a WLAN link are, respectively, given by:

SL = πS,LTP,L/Tave,L (3)SW = πS,WTP,W /Tave,W , (4)

where Tave,L (and Tave,W ) is the average total duration causedby one successful LAA (and WLAN) transmission. The time-efficiency throughput for (3) and (4) refers to the time propor-tion of successful payload transmission of that link dividedby the total observation duration. The payload throughputsin physical layer (which models the losses caused by backoffwait and failed transmissions) are given by SLRL and SWRW ,respectively, where RL and RW are the channel bit rate (CBR)of LAA and WLAN links.

The Tave,L involved in (3) can be computed from

Tave,L = πS,LTS,L +K∑

k=0

[πR,L,kTR,L,k + πF,L,kTF,L],

(5)

where πR,L,k and TR,L,k represent the probability of backoffstage k and the incurred hold time, respectively, and πF,L,k isthe failed transmission probability at stage k. Define πF,L,k

and πR,L,k as the probabilities for failed transmission andbackoff at stage k, respectively. Given that the total probabilityof Markov chain states is unity, we have πS,L+

∑Kk=0[πR,L,k+

πF,L,k] = 1. Based on the model of Fig. 4(a), we can solvefor the state probabilities as:

πS,L = Pt,L/2, (6a)

πR,L,0 =0.5Pt,L

1− (1− Pt,L)K+1, (6b)

πR,L,k = πR,L,0(1− Pt,L)k, (6c)

πF,L,k = πR,L,0(1− Pt,L)k+1, (6d)

for k = 0, . . . ,K. For a Category-3 LBT (when K = 0), wehave πS,L = 0.5Pt,L, πF,L = 0.5(1− Pt,L), and πR,L = 0.5.Using a similar procedure, we can obtain Tave,W as

Tave,W =

M∑m=0

[πR,W,mTR,W,m + πF,W,mTF,W ]

+πS,WTS,W , (7)

where πS,W , {πF,W,m}m=0,...,M , and {πR,W,m}m=0,...,M canbe computed using equations similar to (6a)-(6d), replacingk,K and Pt,L by m,M and Pt,W , respectively. Pt,W is


Fig. 4: Markov model for the LTE-LAA category-4 LBT procedure in coexistence with WLAN, when overall state transitionhas K + 1 stages, and backoff stage k (state Rk) is illustrated (with Ns > 1).

the conditional STP of a WLAN node given that it starts atransmission.

We define the CAPs of an LAA node and a WLAN nodeas τL and τW , respectively, and their expressions are providedby (33) and (34) in Appendix A. We can solve for Pt,L, Pt,W ,τL, and τW jointly by expressing Pt,L and Pt,W as functionsof τL and τW and other parameters.

To compute throughput, we still need to find backoff du-rations TR,L,k (for LAA) and TR,W,m (for WLAN). Theiranalytical formulas will be developed in Sections IV and Vfor the original-LBT and ASJ-LBT schemes, respectively.

B. Equal Slot Duration (Ns = 1)

For Ns = 1 we develop a new method which explicitlycomputes backoff time based on enumerating all the probabil-ity paths of one CR. This probability path enumeration methodis also partially described in our preliminary result [20]. Thisfeature allows us to more conveniently analyze the backoffprocess for Ns > 1. Here, we try to develop an approach thatexplicitly calculates the durations spent on the backoff stagefor both LAA and WLAN nodes. Our method uses multiplefeedforward probability paths to compute a CR time. It isdifferent than [22], [23], which use a feedback probability pathmethod.

When Ns = 1, it follows that

Pt,L = (1− τW )nW (1− τL)nL−1(1− PPE,L), (8)

Pt,W = (1− τW )nW−1(1− τL)nL(1− PPE,W ), (9)

where PPE,L and PPE,W are the transmission PERs due to thelow SNR, in the LTE-LAA and WLAN systems, respectively.When the backoff moves to stage k for an LAA node (or m fora WLAN node), the initial counter may take values uniformlyfrom (1, ZK) and (1,Wm), respectively. We assume that alltransmitting and listening nodes have one idle slot, right afterthe transmission and TDIFS silent duration. So, all nodes mayuse this idle slot of duration δW to reduce counter value by onewhen Ns = 1. Consequently, after finishing a transmission,an LAA (or WLAN) node has equivalently an initial countervalue which is uniformly distributed in range (0, ZK − 1) (or

(0,Wm − 1)) at stage k (or m) when Ns = 1. It follows thatTR,W,m = Wm−1

2 TW,0, and

TR,L,k =Zk − 1

2TL,0, (10)

where TL,0 and TW,0 are the hold-time per CR at LAA andWLAN nodes, respectively. Their expressions are derived inAppendix B and are given by (35) and (36), respectively. Ourmethod of computing TL,0 and TW,0 is accurate and new,and uses only feedforward probability paths when Ns = 1.A comparison with a recent of method on analyzing TW,0 in[22] is given in Appendix C.

Eq. (10) holds for Ns = 1, and the ASJ-LBT scheme whenNs ≥ 1. Note that, however, (10) is slightly different forthe original-LBT scheme when Ns > 1, which is providedby (16) in Section IV. By applying results in (5)–(10), (35),and (36) into (3) and (4), the throughput of the coexistingLAA and WLAN links with Ns = 1 can be readily evaluated.The purpose of showing the case of Ns = 1 is to set upa benchmark to compare with available methods, and definesome variables that will be used for the case Ns > 1 for boththe original-LBT and ASJ-LBT schemes.

IV. COEXISTENCE PERFORMANCE ANALYSIS FOR THEORIGINAL-LBT (Ns > 1)

Based on results in Section III, we now proceed to analyzethe performance of the original-LBT scheme, assuming Ns >1.

A. Modeling of LAA Backoff Process

To address the complicated interaction between LAA andWLAN nodes in the backoff countdown process, we developa new approach that is significantly different than those in theavailable literature [14]–[18], [22], [23], [25].

Refer to super-counter n in Fig. 5, where the stage index kis suppressed for brevity. In Fig. 5, the detail of LAA CR ismodeled by assuming Ns > 1 and Ns is an integer. At countervalue n, the slot duration δL is split into Ns sub-counters, eachwith duration δW , and denoted as (n, 0), (n, 1), . . . , (n,Ns −


Fig. 5: Proposed super-counter model for the original LTE-LAA LBT procedure in coexistence with WLAN (when Ns > 1).

1), respectively. At sub-counter (n,Ns − 1), when no WLANnode transmits (with probability Pi,W ), the process movesto sub-counter (n,Ns − 2); otherwise, when any WLANnode transmits (with probability 1−Pi,W ), the process resetsand restarts from sub-counter (n,Ns − 1). This phenomenonholds until sub-counter (n, 1). At sub-counter (n, 0), the LAAcounter finishes its CR, and the transition time to next LAAsub-counter (n − 1, Ns − 1) can be computed based on sixevents illustrated in Fig. 15.

B. Successful Transmission Probabilities

We define PW (WCR) as the probability that only WLANcounter reduction (WCR) can happen in an idle slot of durationδW , and PW (JCR) as the probability that LTE-LAA andWLAN joint counter reduction (JCR) may happen, respec-tively, as observed by a WLAN node. Similarly, we definePL(WCR) and PL(JCR) as the corresponding probabilities ofWCR and JCR, as observed by an LAA node.

We define τLOL and τGO

L as the locally observed (LO) andglobally observed (GO) CAPs of an LAA node, respectively.τLOL is the LAA CAP when an idle LAA slot of duration δL

(= NsδW ) is observed, and τGOL is the LAA CAP based on a

δW -duration idle slot. When Ns = 1, τLOL = τGO

L = τL. Butwhen Ns > 1, τGO

L ≤ τLOL due to an SJ effect. Since a WLAN

node uses a fixed δW -duration idle slot, its CAP τW is thesame based on either local or global observations.

Define the probabilities of sub-counters (n, 0), (n, 1),. . . , (n,Ns− 1) as P0, P1, . . . , PNs−1, respectively. Note that∑Ns−1

k=0 Pk = 1 holds. At sub-counters (n, 1) . . . , (n,Ns − 1)only a WLAN node can reduce its counter value, and JCR canhappen only at sub-counter (n, 0). Therefore, PW (JCR) = P0

and PW (WCR) = 1− PW (JCR) =∑Ns−1

k=1 Pk.Furthermore, since Pk−1 = PkPi,W , for k = 1, · · · , Ns −

1 (a homogeneous Markov chain), we can determineP0, P1, . . . , PNs−1 uniquely. After some manipulations, weobtain PNs−1 =

1−Pi,W

1−PNsi,W

, and P0 = PNs−1PNs−1i,W . Thus,

PW (JCR) =(1− Pi,W )PNs−1

i,W

1− PNs

i,W

. (11)

Note that in Fig. 5 and deriving (11), we assume a homo-geneous Markov for sub-counter state transitions. A moreaccurate model may be obtained by using a non-homogeneousMarkov chain, omitted here for brevity.

For Ns > 1, the conditional LAA STP Pt,L is observedonly at a JCR event. So,

Pt,L = (1− τLOL )nL−1(1− τW )nW (1− PPE,L). (12)

In comparison, the conditional WLAN STP Pt,W is observedat both WCR and JCR events. Thus, we obtain

Pt,W = (1− PPE,W )[PW (WCR)(1− τW )nW−1

+ PW (JCR)(1− τW )nW−1(1− τLOL )nL

]. (13)

At a WCR event, an LAA transmission cannot happen, andhence the term (1 − τW )nW−1 in (13) denotes the channel-busy probability caused by the other nW − 1 WLAN nodes.Based on the JCR and WCR concept, τGO

L is given by:

τGOL = τLO

L PL(JCR).

The average STPs for each LAA and WLAN link based onthe original-LBT scheme are, respectively, given by:

POrgtxS,L = τGO

L Pt,L, (14)

POrgtxS,W = τWPt,W . (15)

For Ns > 1, the LAA hold time TR,L,k at stage k is relatedto TL,0 by

TR,L,k =Zk + 1

2TL,0, (16)

which is different than (10). We explain this as follows: afteran LAA transmission and TDIFS + δW silent period, the LAAnode that just finishes a transmission will draw an initial valueZ ∈ (1, . . . , Zk). Note that when Ns = 1, the δW idle slotcauses the counter to be reduced immediately and so Z ∈(0, 1, . . . , Zk−1). However, when Ns > 1, the LAA node stillneeds to wait for additional (Ns−1)δW idle period to finish aCR (refer to Fig. 5). Thus, we obtain its initial counter valueZ ∈ (1, . . . , Zk) instead of (0, 1, . . . , Zk−1). This causes theaverage value of Z to be E[Z] = Zk+1

2 instead of Zk−12 . In


comparison, TR,W,m = Wm−12 TW,0 holds for Ns > 1 as well,

since WLAN links are not subject to the SJ effect. Analyticalexpressions of TL,0 and TW,0 for Ns > 1 are studied next.

C. Backoff Counter Hold Duration and Throughput

Based on an assumption of independent transitions in thefirst Ns − 1 sub-counters in Fig. 5, we list the probabilityand duration pairs in Table II. The probability for sub-counter(n, j) is the chance that the LAA sensing process goes to theend of (n, j), but is reset due to a channel-busy event causedby a WLAN transmission.

In Table II, TL,WCR is the average sub-counter hold duration(normalized by its probability) when only WCR occurs. Thishappens when the LAA backoff is in any of the sub-counters(n, 1), · · · , (n,Ns − 1). WLAN transmissions can cause afeedback path with probability (1− Pi,W ). Thus,

TL,WCR =1

(1− Pi,W )[PS,WTS,W + PF,WTF,W ]. (17)

The TL,JCR is the average sub-counter hold duration for LAAin (n, 0), for a JCR event, and its expression is the same as(35).

The first to (Ns − 1)th terms in Table II correspond toall the feedback paths with a total probability PB. WhenTL,WCR ≫ δW , we can group all feedback paths with anoverall probability PB, and average feedback duration of TB.The last term (n, 0) in Table II corresponds to the directfeedforward path (without any feedback) with probability PFand duration TF. We have:

TF = TL,JCR + (Ns − 1)δW , (18)TB ≃ TL,WCR + (Ns/2− 1)δW . (19)

We derive the per CR hold durations for LAA and WLANnodes in Appendix D, and the results are provided by (41)and (42), respectively. By substituting results given by (5)–(7), (12)–(16), (41), and (42) into (3) and (4), the throughputperformance of LAA and WLAN systems with the original-LBT and Ns > 1 can be computed analytically.

TABLE II: Probability and duration pairs to compute LAAcounter hold time of the original-LBT.

Index Probability Duration

(n,Ns − 1) 1− Pi,W TL,WCR

(n,Ns − 2) Pi,W (1− Pi,W ) δW + TL,WCR

· · · · · · · · ·(n, 1) PNs−2

i,W (1− Pi,W ) (Ns − 2)δW + TL,WCR

(n, 0) PNs−1i,W (Ns − 1)δW + TL,JCR

V. COEXISTENCE PERFORMANCE ANALYSIS FOR THEPROPOSED ANTI-SJ LBT (Ns > 1)

The analysis of the proposed ASJ-LBT scheme is morechallenging than the original-LBT (Assume Ns > 1). TheASJ-LBT involves two cases of CRs:

1) C1: Channel is idle for TDIFS + δW following a trans-mission (channel busy); and

2) C2: Channel is idle for δL = NsδW right after a previousCR.

We model the transition paths between the two cases during anLAA CR in Fig. 6. An LAA counter is decomposed into Ns

sub-counters, and the paths of current CR depend on the statusof the previous CR. Thus, we model cases 1 and 2 explicitlyin Fig. 6, and list all the involved probability-duration pairs inTable III.

We explain each path next. Define the probabilities of cases1 and 2 in Fig. 6 as Pr(C1) and Pr(C2). It follows that

Pr(C1) = Pr(C1)(1− P̂i,LPi,W ) + [Pr(C1) + Pr(C2)]

·P̂i,LPi,W [1− P̂i,LPNs

i,W ], (20)

Pr(C2) = [Pr(C1) + Pr(C2)]P̂i,LPi,WPNs−1i,W . (21)

We can verify that equations (20) and (21) are equivalent, asexpected. To determine Pr(C1) and Pr(C2), we need one moreequality. The sum probability of all sub-counter states withinone CR in Fig. 6 is equal to unity. Thus,

Pr(C1) + [Pr(C1) + Pr(C2)]P̂i,LPi,W

·(1 + Pi,W + . . .+ PNs−1i,W ) = 1. (22)

Based on (21) and (22), we derive:

Pr(C2) =

(1− P̂i,LP

Ns

i,W

P̂i,LPNs

i,W

+1− PNs

i,W

PNs−1i,W − PNs

i,W

)−1

=P̂i,LP

Ns

i,W (1− Pi,W )

1− Pi,W − P̂i,LPNs

i,W + P̂i,LPi,W

,

Pr(C1) = Pr(C2)1− P̂i,LP

Ns

i,W

P̂i,LPNs

i,W

.

When Ns = 1, (20) and (21) reduce to

Pr(C1|Ns = 1) = (1− P̂i,LPi,W ),

Pr(C2|Ns = 1) = P̂i,LPi,W ,

as expected. This means that when Ns = 1, case 1 correspondsto a channel busy event, which is always followed by DIFSand an idle slot δW , and case 2 corresponds to a channel idleevent, where all LAA and WLAN nodes stay idle.

A. Successful Transmission Probabilities

We define P̃W (WCR) as the probability that only WLANnodes may reduce counter, and P̃W (JCR) as the probabil-ity that all LAA and WLAN nodes may reduce counter,respectively, after a δW idle slot, observed by the WLANsystem. Here, superscript ˜ on P refers to the case of ASJ-LBT. P̃W (WCR) is the sum probability the Ns − 1 subcellsin the right side of the super-counter. When Ns ≥ 2, we haveP̃W (JCR) = 1− P̃W (WCR), and

P̃W (WCR) = [Pr(C̃1) + Pr(C̃2)]Pi,LP̂i,W

·(1 + P̂i,W + . . .+ P̂Ns−2i,W )

=P̂i,WPi,L(1− P̂Ns−1

i,W )

1− P̂i,W − Pi,LP̂Ns

i,W + Pi,LP̂i,W

,


Fig. 6: Proposed backoff model on probability paths for the LAA with ASJ-LBT.

where Pr(C̃1) and Pr(C̃2) are obtained from Pr(C1) andPr(C2) by replacing P̂i,L and Pi,W with Pi,L and P̂i,W

therein, respectively. With probability P̃W (WCR), all LAAnodes stay silent. Thus, the conditional STP of a WLAN nodeis given by:

Pt,W = (1− PPE,W )[P̃W (WCR)(1− τW )nW−1

+P̃W (JCR)(1− τW )nW−1(1− τLOL )nL ]. (23)

The conditional STP of an LAA node is given by:

Pt,L = (1− τLOL )nL−1(1− τW )nW (1− PPE,L). (24)

In (23) and (24), τLOL is given by (33). The LAA CAP, based

on total number of available idle slots of δW durations, isgiven by:

τGOL = τLO

L PL(JCR)

= τLOL

1− Pi,W

1− Pi,W − PNs

i,WPi,L + Pi,WPi,L

. (25)

The average STPs of each LAA link and WLAN link basedon the ASJ-LBT scheme are, respectively, given by:

PASJtxS,L = Pt,Lτ

GOL = Pt,Lτ

LOL PL(JCR), (26)

PASJtxS,W = Pt,W τW . (27)

Note that τLOL and Pt,L are based on LAA local observation

of idle slots, and are independent of Ns. But τGOL and PASJ

txS,L(based on global observation) are functions of Ns, and providea clearer illustration of LAA performance when in coexistencewith WLAN.

B. Backoff Counter Hold Time and Throughput

Refer to Fig. 6 again. The average hold time for an LAAnode TL,0 is obtained by summing the duration of each pathfrom the start states to the end states, weighted by the pathprobability. The probability and duration pair of each path islisted in Table III.

In Table III, the last three columns list each path, and itscorresponding probability and duration. The first row is for the

direct path through the regular counter on the top side, fromcase 1 to case 1 which is a channel busy event. The 2nd to(Ns+1)th rows are for the paths through the super-counter onthe bottom side starting from either case 1 or 2 and ending incase 1. The (Ns+2)th term is for reaching sub-counter (n, 0),from case 2 to case 2. As an example, consider sub-counter(n,Ns − 1) which has probability Pr(C1, C2)(1 − Pi,W ) toexit the counter n. The factor Pr(C1, C2) is the probabilitythat the LAA backoff goes to counter value n from a previouscounter n+ 1 (either case 1 or 2), and is given by:

Pr(C1, C2) = [Pr(C1) + Pr(C2)]Pi,W P̂i,L. (28)

The other factor (1−Pi,W ) is the probability that at the end ofthe first τW duration in super-counter n, at least one WLANtransmissions start and are detected by this LAA node. Afterthis channel busy event is over, the LAA node moves to case1, shortens its slot duration to δW , reduces the counter value ton−1, and thus it exits this counter. The TL,WCR is the averagechannel busy time when the WCR occurs (normalized by itsprobability), given by:

TL,WCR =1

(1− Pi,W )[PS,WTS,W + PF,WTF,W ].

In the last row of Table III, when sub-counter (n, 0) is reached,TL,JCR is the average channel busy duration for a CR. TL,JCRis given by (35), where the involved probabilities of Ns = 1are replaced by those for the case of Ns > 1. TL,0 canbe computed by summing up all the probability-weighteddurations in Table III, resulting in

TL,0 ≃ 1

Pr(C1) + Pr(C2)

Ns+2∑n=1

Pn,LTn,L, (29)

where the normalization by factor Pr(C1) + Pr(C2) is used,because an LAA node transmits only upon the two idle caseswith sum probability Pr(C1)+Pr(C2). The minor approxima-tion in (29) is caused by facts such as that a homogeneousMarkov chain in a super-counter CR is modelled. A better


TABLE III: Probability and duration pairs to compute LAA counter hold time of the ASJ-LBT.

Index Sub-counter index Probability Duration1 C1 → C1 Pr(C1)(1− P̂i,LPi,W ) TL,JCR

2 (n,Ns − 1) Pr(C1, C2)(1− Pi,W ) TL,WCR

3 (n,Ns − 2) Pr(C1, C2)(1− Pi,W )Pi,W TL,WCR + δW· · · · · · · · · · · ·Ns (n, 1) Pr(C1, C2)(1− Pi,W )PNs−2

i,W TL,WCR + (Ns − 2)δW

Ns + 1 (n, 0) Pr(C1, C2)(1− Pi,W P̂i,L)PNs−1i,W TL,JCR + (Ns − 1)δW

Ns + 2 (n, 0) Pr(C1, C2)P̂i,LPNsi,W NsδW

accuracy may be obtained if a non-homogenous model of sub-counter transition is used. The average CR duration can alsobe expressed as

TL,0 =Pr(C1)TL,0|C1

+ Pr(C2)TL,0|C2

Pr(C1) + Pr(C2), (30)

where TL,0|C1and TL,0|C2

are the CR durations conditionedon starting states C1 and C2, respectively. Assuming thatTW ≫ δW and TL,JCR ≫ δW , we have TL,0|C2

≃Pi,W P̂i,L[(1−PNs−1

i,W )TL,WCR+PNs−1i,W (1−P̂i,LPi,W )TL,JCR],

and TL,0|C1≃ TL,0|C2

+(1−Pi,W P̂i,L)TL,JCR. We obtain anapproximate formula for TL,0 as

TL,0 ≃ Pi,W P̂i,L[(1− PNs−1i,W )TL,WCR

+PNs−1i,W (1− P̂i,LPi,W )TL,JCR]

+Pr(C1)(1− P̂i,LPi,W )

Pr(C1) + Pr(C2)TL,JCR. (31)

By use of the concept of JCR and WCR, TW,0 for a WLANnode is derived as

TW,0 ≃ P̃W (WCR)T̃W,WCR + P̃W (JCR)T̃W,JCR, (32)

where

T̃W,WCR = P̂S,WTS,W + P̂F,WTF,W + P̂i,W δW ,

T̃W,JCR = P̂i,WPi,LδW + (P̂S,WTS,W + P̂F,WTF,W )Pi,L

+(PS,LTS,L + PF,LTF,L)P̂i,W

+(1− P̂i,W )(1− Pi,L)TF,M .

By substituting results given by (5)–(7), (10), (23), (24), (31),and (32) into (3) and (4), the throughput performance of LAA-LBT and WLAN systems with the ASJ-LBT and Ns > 1 canbe readily evaluated.

VI. NUMERICAL RESULTS

In this section, we provide both analytical and simulationresults of the spectrum sharing performance of LTE-LAA andWLAN links. Both the original-LBT and the proposed ASJ-LBT schemes are simulated, and the results are comparedwith analytical formulas derived in Sections IV and V. In ourMonte-Carlo computer simulation, we define and track threeglobal events at each slot: channel idle, successful transmis-sion, and failed transmission (caused by either collision or lowreceiver SNR). We also track four local events for every LAAand WLAN link: channel idle, channel busy (counter frozen),successful transmission, and failed transmission. On each

parameter setting, we ran 106 mixed time slots to generatethe simulation results.

Our simulation method and codes, when simplified to thecase of only WLAN links and after minor changes, providenumerical results that fit well to the methods given by [14],[22]. To further validate our simulation method, we providean SDR test result for two CSMA/CA links with different slotdurations. The setup and method of experiment were presentedin detail in [21], where we varied the slot duration ratio(Ns) of two coexistence CSMA/CA links, and recorded thethroughput for the original LBT and the ASJ-LBT schemes.The throughput was normalized by the physical-layer rate,and the payload duration is 3 ms. The simulation and SDRmeasured results are provided in Fig. 7, which shows thatthe ASJ-LBT reduces the SJ effect compared to the originalLBT scheme for link 2 which has a larger slot duration. Inaddition, the simulation result (in lines) matches well withSDR measured result (in markers).

1 2 3 4 5N

s (slot duration ratio of Link 2 vs. Link 1)

10-1

100

Thr

ough

put

Lines: Computer Simu. Markers: SDR measured

Link 1, w/ original-LBTLink 2, w/ original-LBTLink 1, w/ ASJ-LBTLink 2, w/ ASJ-LBT

Fig. 7: Throughput of two CSMA/CA links, when Ns = 1 ∼5. CW = 16 for both links, without retransmission.

From here on, we consider larger link numbers (nL andnW ) and compare analytical and simulation results. We setpayload durations for LAA and WLAN as TP,L = 2 ms andTP,W = 1 ms, Z0 = W0 = 16, and δW = 9 µs. The LAAsuccessful transmission and collision channel-busy durationsin an RTS/CTS mode are given by (1) and (2), respectively. Weassume that the WLAN and LAA systems have channels fullyoverlapped in the 5 GHz ISM band. Every analytical curve in


2 4 6 8 10 12 14

Number of WLAN links

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.1A

vera

ge s

ucce

ssfu

l tra

nsm

issi

on p

roba

bilit

y pe

r lin

k

Solid lines: Ana.Markers: Simu.

WLAN coex w/ original-LBTLAA w/ original-LBT

(a)

2 4 6 8 10 12 14


0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.1

Ave

rage

suc

cess

ful t

rans

mis

sion

pro

babi

lity

per

link


WLAN coex w/ ASJ-LBTLAA w/ ASJ-LBT

(b)

Fig. 8: Average successful transmission probability per link ofthe LAA and WLAN systems vs. nW , when Ns = 2, K = 1,M = 3, Z0 = W0 = 16, nL = nW , and with RTS/CTSschemes. (a) Original LBT and (b) ASJ-LBT.

each figure is accompanied by another curve based on MonteCarlo simulation result. Comparison between analytical andsimulation results illustrates a very close match.

The average STPs for the original-LBT (see (14)) and theASJ-LBT (see (26)) are provided in Fig. 8 (a) and (b), respec-tively, assuming Ns = 2, K = 1, M = 3, Z0 = W0 = 16,and nL = nW . Fig. 8 shows that as nW increases from 2 to14, the STP of the original-LBT scheme reduces from about0.032 to 0.005, but the STP of the ASJ-LBT scheme decreasesonly from about 0.042 to 0.013, which significantly enhancesthe performance compared to the original-LBT.

Next, the backoff hold durations per CR of LAA and WLANsystems are illustrated in Fig. 9 for the original-LBT and ASJ-LBT schemes assuming Ns = 3, K = 1, M = 3, Z0 = W0 =16, and nL = nW . As nW increases, the counter hold time ofthe original-LBT scheme increases almost exponentially, fromabout 1 ms to about 3.4 ms. In comparison, the hold timeof the ASJ-LBT scheme varies from about 0.6 ms to about

2 4 6 8 10 12 14


10-4

10-3

10-2

Ave

rage

bac

koff

coun

ter

hold

tim

e (S

ec)


Original LBT

ASJ-LBT

WLAN coex w/ original-LBTLAA w/ original-LBTWLAN coex w/ ASJ-LBTLAA w/ ASJ-LBT

Fig. 9: Backoff counter hold time per reduction of LAA andWLAN systems vs. nW , when Ns = 3, K = 1, M = 3,Z0 = W0 = 16, nL = nW , and with RTS/CTS schemes.

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

Packet error rate

10-1

100

Thr

ough

put



Fig. 10: System throughput of LAA and WLAN vs. PER(PEP,L = PEP,W ), when Ns = 2, K = M = 3, W0 =Z0 = 16, nL = nW = 10, and with basic access schemes.

0.85 ms and then drops to 0.7 ms, and the gap between theWLAN and LAA hold durations decreases as nW increases.The backoff time of the ASJ-LBT is significantly less than thatof the original-LBT, indicating a better CAP performance.

We show the time-efficiency system throughput of the LTE-LAA and WLAN under the effect of PER in Figs. 10 and 11,assuming the basic access and RTS/CTS schemes, respectively.We assume that the RTS/CTS packet experiences the samePER as the payload packet. Figs. 10 shows that when thePER increases from 0 to 0.8, the throughputs of the LAAand WLAN systems decrease significantly. For example, thethroughput of the LAA with original-LBT reduces from about0.17 to about 0.05. In comparison, when the LAA and WLANboth use RTS/CTS schemes, their throughput decreases withPER, but more gracefully. This is because with the RTS/CTShandshaking, the failed packets cause much smaller time lossthan the basic access scheme.


0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

Packet error rate

10-1

100T

hrou

ghpu

t



Fig. 11: System throughput of LAA and WLAN systems vs.PER (PEP,L = PEP,W ), when Ns = 2, K = M = 3, W0 =Z0 = 16, nL = nW = 10, and with RTS/CTS access schemes.

5 10 15 20 25

Number of WLAN links (coexisting with 4 LAA links)

10-2

10-1

100

Thr

ough

put

Original LBT

ASJ-LBT

WLAN, AnalysisWLAN, SimulationLAA, AnalysisLAA, Simulation

Fig. 12: System throughput of LAA and WLAN vs. nW , whenNs = 3, K = 1, M = 3, Z0 = W0 = 16, nL = 4, and withRTS/CTS schemes.

We consider a fixed nL = 4 but an increasing nW in Fig.12. As nW increases from 4 to 28, the system throughputof the LAA system (with the original-LBT) decreases fromabout 0.24 to about 0.02. In comparison, the LAA throughput(with the ASJ-LBT) decreases from about 0.48 to 0.26 whenNs = 3. This greatly mitigates the effect of slot jammingcaused by larger LAA slot durations. In summary, the ASJ-LBT avoids the problem of very low throughput which theoriginal-LBT may suffer from due to the SJ, while maintaininga substantially larger sensing slot duration than its WLANcounterpart (when Ns > 1).

We study the constructive coexistence between WLAN andLAA systems based on different LBT and access schemeswhen nW + nL = 20 and nL increases from 0 to 20. Weconsider 2 cases: (1) WLAN uses basic access and LAA usesRTS/CTS access, and (2) both WLAN and LAA systems useRTS/CTS. The throughput per link is given in Fig. 13 (a) and(b) for the two cases, respectively. For comparison purposes,

0 2 4 6 8 10 12 14 16 18 20

Number of LTE-LAA links (nL)

10-2

10-1

Thr

ough

put p

er li

nk

Solid lines: Ana.Dashed lines: Simu.

Stand-alone WLANWLAN coex w/ original-LBTLAA w/ original-LBTWLAN coex w/ ASJ-LBTLAA w/ ASJ-LBT

(a)

0 2 4 6 8 10 12 14 16 18 20

Number of LTE-LAA links (nL)

10-2

10-1

Thr

ough

put p

er li

nk

Solid lines: Ana.Dashed lines: Simu.

Stand-alone WLANWLAN coex w/ original-LBTLAA w/ original-LBTWLAN coex w/ ASJ-LBTLAA w/ ASJ-LBT

(b)

Fig. 13: Throughput per link in the LAA and WLAN systemsvs. nL, when Ns = 2, K = M = 3, W0 = Z0 = 16, andnW + nL = 20. (a) WLAN basic access and LAA RTS/CTSaccess; (b) Both WLAN and LAA use RTS/CTS.

we also show the performance of a standalone WLAN system(nW = 20 and nL = 0). Fig. 13 shows that the per-link-throughput of standalone WLAN is about 0.028 (case 1) or0.044 (case 2). As nL increases, in case 1 with ASJ-LBTthe throughput of each LAA link changes within about 0.037to 0.045, and the throughput of each WLAN link increasesfrom 0.028 to 0.057. These throughputs are comparable toeach other, and they are higher than the basic-access WLANthroughput of 0.028. In case 2 with ASJ-LBT the per-linkthroughputs of coexisting LAA and WLAN systems are closeto or better than that of the standalone WLAN system, thoughthe relative advantage is reduced because the standaloneWLAN system uses an efficient RTS/CTS scheme.

In comparison, with original-LBT, in case 1 the WLANthroughput per link increases from about 0.028 to 0.12 asnL increases, but the LAA throughput per link stays below0.028 unless nL ≥ 16. In case 2, the per-link-throughput ofLAA with original LBT stays lower than that of a standalone


0 5 10 15 20 25

LAA CW size Z0

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8A

vera

ge S

yste

m T

hrou

ghpu

t


WLAN, Original-LBTLAA, Original-LBTWLAN, ASJ-LBTLAA, ASJ-LBT

Fig. 14: System throughput of LAA and WLAN vs. Z0, whenNs = 2, K = M = 3, W0 = 16, nL = nW = 10, and withRTS/CTS access schemes.

WLAN system for nL ≤ 19. This shows that the LAA withoriginal-LBT suffers from SJ effect and the coexistence cannotbe regarded as constructive. From the result of Fig. 13 we drawobservation that the ASJ-LBT and the use of LAA RTS/CTSscheme can effectively support constructive coexistence for thetwo systems with heterogeneous slot durations.

It is shown in [23], [24] that in a WLAN system withheterogeneous throughput requirements, the target throughputratio of links may be achieved by adjusting the CSMA/CAparameters, such as the CW size. We show that the ASJ-LBT design can support system optimization in Fig. 14, whenNs = 2, K = M = 3, W0 = 16, nL = nW = 10, withRTS/CTS access schemes. As the LAA CW size Z0 increases,there is a cross-over point in the throughput of the LAA andWLAN systems based on the ASJ-LBT. Thus, we can selectproper Z0 to enable the LAA and WLAN systems to achieve alarge range of different throughput ratios (including the case ofequal throughput). But with the original LBT, the throughputof the LAA is much lower than that of the WLAN system forall the considered Z0 ∈ (1, 23). This indicates that the originalLBT cannot effectively support throughput optimization in thiscase.

VII. CONCLUSION

In this paper, we have studied the impact of heterogeneousbackoff-slot durations on the MAC-layer performance of LTE-LAA coexisting with WLAN transmissions. We first pointedout a slot-jamming effect due to differences in backoff idleslot durations among LAA-LBT and WLAN systems, andproposed an anti-SJ LBT scheme to mitigate this problem.We have developed a novel and powerful analytical frameworkwith several new features, such as backoff super-counter, enu-merated probability-duration paths, and different probability-time scales captured by WLAN only CR and joint CR events.Then, we provided analytical results on the backoff counterhold time, successful transmission probability, channel accessprobability (locally and globally observed) and throughput. We

have implemented in-depth programming of LAA-LBT andWLAN schemes and extensive computer simulations, whichhave verified all of the analysis results. We have also providedan SDR experimental result to validate our simulation method.Numerical results confirm that the original-LBT may sufferfrom an SJ effect when Ns > 1, and our proposed ASJ-LBTscheme is effective in mitigating this problem. This resultprovides support for a system design when a larger LAAsensing duration than the WLAN counterpart is necessary(e.g., due to low SNR), and will be useful for the relatedsystem optimization work. The new analytical tool lays asolid theoretical foundation to evaluate effect of heterogeneousslot scales in unlicensed spectrum sharing systems, and maysupport related standardization effort in the 3GPP and ETSI.

APPENDIX ADERIVATION OF CAPS OF LAA AND WLAN NODES

We derive τL using a procedure given in our preliminaryresult [18], where τL is the sum of probabilities at backoffcounters (0, 0), (1, 0), . . . , (K, 0) shown in Fig. 4. The relatedstate transition probabilities are given by:

P (0, k|j, 0) = Pt,L/Z0, for j ∈ [0,K − 1],

P (0, k|K, 0) = (1− Pt,L)/Z0, andP (j, k|j, k + 1) = 1, for j ∈ [0,K], k ∈ [0, Zj − 2].

We define Pj,k as the stationary probability of state (j, k). Itfollows that:

Pj,0 = (1− Pt,L)jP0,0, for j ∈ [0,K], and

Pj,k =Zj − k

ZjPj,0, for k ∈ [0, Zj − 1]; j ∈ [0,K].

Since the total probability of all states is 1, i.e.,∑Kj=0

∑Zj−1k=0 Pj,k = 1, we obtain

P0,0 =

0.5 K∑j=0

(1− Pt,L)j(1 + Zj)

−1

.

The CAP of an LAA node is given by:

τL =K∑j=0

Pj,0 = P0,01− (1− Pt,L)

K+1

Pt,L

=2[1− (1− Pt,L)

K+1]

Pt,L

∑Kj=0(1− Pt,L)j(1 + Zj)

. (33)

The CAP for an LAA Category-3 node (when K = 0) isderived as

τL = 2/(1 + Z0).

Using a similar procedure to the above, τW is derived as:

τW =2(1− (1− Pt,W )M+1)

Pt,W

∑Mm=0(1− Pt,W )m(1 +Wm)

. (34)


APPENDIX BDERIVATION OF CR DURATIONS TL,0 AND TW,0 WHEN

Ns = 1

Let P̂ and P denote probabilities observed by a node whenobserving its own system (e.g., state of LAA system observedby an LAA node), and the other system (e.g., state of LAAsystem observed by a WLAN node), respectively. Observedby an LAA node, the probabilities of LAA channel idle,successful transmission, and failed transmission states are,respectively, given by:

P̂i,L = (1− τL)nL−1,

P̂S,L =

{(nL − 1)τL(1− τL)

nL−2, when nL ≥ 2;0, when nL ≤ 1,

,

P̂F,L = 1− P̂i,L − P̂S,L.

However, observed by a WLAN node, the probabilities ofthese LAA states are given by

Pi,L = (1− τL)nL ,

PS,L = nLτL(1− τL)nL−1,

PF,L = 1− Pi,L − PS,L.

Similarly, observed by a WLAN node, probabilities of WLANchannel idle, successful transmission, and failed transmissionstates are, respectively, given by P̂i,W = (1 − τW )nW−1,

P̂S,W =

{(nW − 1)τW (1− τW )nW−2, when nW ≥ 2;

0, when nW ≤ 1,,

and P̂F,W = 1 − P̂i,W − P̂S,W . Furthermore, observed byan LAA node, the corresponding WLAN states are Pi,W =(1 − τW )nW , PS,W = nW τW (1 − τW )nW−1, and PF,W =1− Pi,W − PS,W . Referring to Fig. 15: in an LAA CR thereare 6 mutually-exclusive events, and their probability pathsand durations are listed below:

1) All LAA and WLAN links are idle (with probabilityP̂i,LPi,W and duration δL),

2) successful transmission of an LAA link (with probabilityP̂S,LPi,W and duration TS,L),

3) collision of LAA links while WLAN is idle (withprobability P̂F,LPi,W and duration TF,L),

4) successful transmission of a WLAN link (with probabil-ity PS,W P̂i,L and duration TS,W ),

5) collision of WLAN links while LAA is idle (withprobability PF,W P̂i,L and duration TF,W ),

6) LAA-WLAN inter-system collision of transmissions(with probability (1 − Pi,W )(1 − P̂i,L) and durationTF,M ), where TF,M = max(TF,L, TF,W ).

We can verify that the probability mass function (PMF)shown in Fig. 15 sums up to unity and is valid, as shownby

P̂i,LPi,W + P̂S,LPi,W + P̂F,LPi,W + PS,W P̂i,L

+ PF,W P̂i,L + (1− P̂i,L)(1− Pi,W ) = 1.

When Ns = 1, all LAA and WLAN links have a JCRopportunity at the end of each idle slot. Defining TL,JCR (andTW,JCR) as the duration per CR with JCR at each LAA (and

, ,

( , )( , )

, ,

, ,

, ,

, ,

, ,

Fig. 15: Illustration of Markov model for the LAA CR whenNs = 1.

WLAN) link, respectively, we have:

TL,0 = TL,JCR

= P̂i,LPi,W δW + (P̂S,LTS,L + P̂F,LTF,L)Pi,W

+(PS,WTS,W + PF,WTF,W )P̂i,L

+(1− Pi,W )(1− P̂i,L)TF,M , (35)TW,0 = TW,JCR

= Pi,LP̂i,W δW + (PS,LTS,L + PF,LTF,L)P̂i,W

+(P̂S,WTS,W + P̂F,WTF,W )Pi,L

+(1− P̂i,W )(1− Pi,L)TF,M . (36)

APPENDIX CCOMPARISON WITH A RECENT METHOD ON THE

COMPUTATION OF TW,0 (WHEN Ns = 1)

The techniques developed in this paper explicitly computethe backoff CR time based on a novel probability path method.Below, we simplify our method to the case of a single WLANsystem, and compare it with a recent WLAN analysis method[22] on the computation of TW,0. For this special case (36) issimplified to

TW,0 = P̂i,W δW + P̂S,WTS,W + P̂F,WTF,W . (37)

We can easily verify that P̂i,W + P̂S,W + P̂F,W = 1. Basedon Appendix B in an online material of [22], the hold timeper WLAN CR is given by (6) of [22], which involves anapproximation that Pt,W = (1 − τW )nW−1 ≈ exp(−nτW ),valid when nW ≫ 1. Here, we try to re-derive TW,0 usingthe approach in [22] but with a more strict procedure shownnext (such as without using the large-nW assumption), andcompare it with our special-case result in (37).

In [22], the CR probability at any slot t is given by αt,and the feedback probability is 1 − αt, where t representsa time index normalized by δW . We define the normalizedhold time per CR as TW,0 = TW,0/δW , which is derived asTW,0 = 1/αt, where αt = P{idle at t} is the probability thatthe considered node senses the channel to be idle at time t. Letωt, τT , and τF in [22] be replaced by τW , T s = TS,W /δW ,and TF = TF,W /δW respectively. It is shown in [22] that

αt+1 = P{idle at t+ 1 | idle at t}P{idle at t}+ P{idle at t+ 1 | success at t}P{success at t}+ P{idle at t+ 1 | collision at t}P{collision at t},


where

P{idle at t+ 1 | success at t} = 1/TS ,

P{idle at t+ 1 | collision at t} = 1/TF ,

P{idle at t+ 1 | idle at t} = Pt,W = (1− τW )nW−1,

P{success at t} = TS(nW − 1)τW

·(1− τW )nW−2,

P{idle at t} = αt,

and

P{collision at t} = 1− P{idle at t} − P{success at t}.

In a stationary state (as t becomes large), αt+1 = αt = αholds. We have

α = α(1− τW )nW−1 + α(nW − 1)τW (1− τW )nW−2

+1

TF

[1− α− T s(nW − 1)τW (1− τW )nW−2α].

After some manipulations, we obtain

TW,0 = 1/α = 1 + P̂S,WTS + P̂F,WTF ,

which leads to

TW,0 = δW + P̂S,WTS,W + P̂F,WTF,W . (38)

Since typically either TS,W ≫ δW or TF,W ≫ δW holds, orboth hold, the CR time in (38) is very close to our strict resultgiven in (37), for Ns = 1, though they are based on differentmodelling methods. In comparison, our method for deriving(37) and (36) is more concise and involves no feedback pathsfor Ns = 1. Thus, our method of probability paths is bothconvenient and precise, and is used as a preliminary buildingblock in our super-counter based performance analysis for bothoriginal and ASJ-LBT schemes (when Ns > 1).

APPENDIX DDERIVATION OF CR DURATIONS TL,0 AND TW,0 OF THE

ORIGINAL-LBT (WHEN Ns > 1)

Please refer to the lower portion of Fig. 5. We combine theNs − 1 feedback paths as one path with probability PB, andthis involves a minor approximation. Note that PF + PB = 1.If we assume that the reduction of the first Ns − 1 sub-counters are independent and homogeneous, we obtain PF ≃PNs−1i,W = (1 − τW )(Ns−1)nW , as shown by the index (n, 0)

in Table II. However, the assumption of homogeneous sub-counter transitions may involve a major approximation whenτW ≪ 1 does not hold. We relax this assumption and developa more accurate result next. The PF is equal to the probabilitythat none of the nW WLAN nodes transmits during the first(Ns−1) sub-counters in super-counter n. The probability thata WLAN node does not transmit in this duration is given by(1−(Ns−1)τW ), and the nW WLAN nodes have independentbackoff processes. Tight approximations of PF and PB areobtained as

PF ≃ (1− (Ns − 1)τW )nW , (39)PB = 1− PF ≃ 1− (1− (Ns − 1)τW )nW . (40)

We derive the LAA counter hold time per CR as

TL,0 ≃ PF {TF + (1− PF)(TF + TB) + · · ·+ (1− PF)

k(TF + kTB) + · · ·}

= PFTF[1 + (1− PF) + · · ·+ (1− PF)k + · · · ]

+PF[(1− PF)TB + · · ·+ (1− PF)kkTB + · · · ]

= TF + TB(1− PF)/PF. (41)

In the first two lines of (41), factors (1−PF) and (1−PF)k refer

to one-time feedback and k-time feedback paths, respectively.When 0 < PF ≤ 1, the following equality holds

[(1− PF)TB + · · ·+ (1− PF)kkTB + · · · ] = TB(1− PF)/P

2F .

In the case of WCR (with probability PW (WCR)), eachWLAN node has average counter hold time

TW,WCR = P̂i,W δW + P̂S,WTS,W + P̂F,WTF,W .

In the other case of JCR with probability PW (JCR), thecounter hold time TW,JCR has the same form as (36). Thus,the average counter hold time for a WLAN node is

TW,0 ≃ PW (WCR)TW,WCR + PW (JCR)TW,JCR. (42)

ACKNOWLEDGMENT

The authors thank the Editor and reviewers for some techni-cal comments which helped improve the quality of this paper.They also thank Duncan McGillivray, Eric Anderson, RyanJacobs, and Michael Janezic for some helpful feedback duringthe preparation of this paper.

REFERENCES

[1] R. Zhang, M. Wang, L. X. Cai, Z. Zheng, and X. Shen, “LTE-unlicensed: the future of spectrum aggregation for cellular networks,”IEEE Wireless Commun., vol. 22, no. 3, pp. 150–159, Jun. 2015.

[2] F. M. Abinader, et. al. “Enabling the coexistence of LTE and Wi-Fi inunlicensed bands,” IEEE Commun. Mag., vol. 52, no. 11, pp. 54–61,Nov. 2014.

[3] A. Mukherjee et al., “Licensed-assisted access LTE: coexistence withIEEE 802.11 and the evolution toward 5G,” IEEE Commun. Mag., vol.54, no. 6, pp. 50-57, Jun. 2016.

[4] 3GPP TSG RAN, “Study On Licensed-Assisted Access To UnlicensedSpectrum”, 3GPP TR 36.889 V13.0.0, Jun. 2015.

[5] Ericsson, “Discussion on LBT protocols,” 3GPP Tech. Rep. R1-151996,Apr. 2015.

[6] B. Chen, J. Chen, Y. Gao, and J. Zhang, “Coexistence of LTE-LAA andWi-Fi on 5 GHz with corresponding deployment scenarios: A survey,”IEEE Commun. Surveys Tuts., vol. 19, no. 1, pp. 7–32, 1st Quart., 2017.

[7] ETSI EN 301 893 V1.8.1 (2015-03), “Broadband Radio Access Net-works (BRAN); 5 GHz high performance RLAN; Harmonized EN cov-ering the essential requirements of article 3.2 of the R&TTE Directive”,March 2015.

[8] ETSI EN 301 893 V2.1.1 (2017-05), “5 GHz RLAN; HarmonisedStandard covering the essential requirements of article 3.2 of Directive2014/53/EU,” May 2017.

[9] 3GPP TS RAN, “E-UTRA Physical layer procedures (Release 14)”,3GPP TS 36.213 V14.4.0, Sept. 2017.

[10] IEEE LAN/MAN Standards Committee, IEEE Std 802.11-2012, Part11: Wireless LAN Medium Access Control (MAC) and Physical Layer(PHY) Specifications, Feb. 2012.

[11] V. Valls, A. Garcia-Saavedra, X. Costa and D. J. Leith, “MaximizingLTE capacity in unlicensed bands (LTE-U/LAA) while fairly coexistingwith 802.11 WLANs,” in IEEE Commun. Lett., vol. 20, no. 6, pp. 1219–1222, Jun. 2016.

[12] R. Yin, G. Yu, A. Maaref, and G. Li, “A framework for co-channelinterference and collision probability tradeoff in LTE licensed-assistedaccess networks,” IEEE Trans. Wireless Commun., vol. 15, no. 9, pp.6078–6090, Sept. 2016.


[13] S. Han, Y. C. Liang, Q. Chen and B. H. Soong, “Licensed-assisted accessfor LTE in unlicensed spectrum: A MAC protocol design,” IEEE J. Sel.Areas Commun., vol. 34, no. 10, pp. 2550–2561, Oct. 2016.

[14] G. Bianchi, “Performance analysis of the IEEE 802.11 distributedcoordination function,” IEEE J. Sel. Areas Commun., vol. 18, no. 3,pp. 535–547, Mar. 2000.

[15] I. Tinnirello, G. Bianchi, and X. Yang, “Refinements on IEEE 802.11distributed coordination function modeling approaches,” IEEE Trans.Veh. Technol., vol.59, no.3, pp.1055–1067, Mar. 2010.

[16] C. Chen, R. Ratasuk, and A. Ghosh, “Downlink performance analysisof LTE and WiFi coexistence in unlicensed bands with a simple listen-before-talk scheme,” Proc. IEEE VTC, pp. 1–5, May 2015.

[17] Y. Song, K. W. Sung, and Y. Han, “Coexistence of Wi-Fi and cellularwith listen-before-talk in unlicensed spectrum,” IEEE Commun. Lett.,vol. 20, no. 1, pp. 161–164, Jan. 2016.

[18] Y. Ma and D. G. Kuester, “MAC-layer coexistence analysis of LTEand WLAN systems via listen-before-talk,” in Proc. 14th IEEE AnnualConsumer Communications & Networking Conference (CCNC), LasVegas, NV, 2017, pp. 534-541.

[19] Y. Ma, D. G. Kuester, J. Coder, and W. F. Young, “Coexistence analysisof LTE and WLAN systems with heterogenous backoff slot durations,”in Proc. IEEE Int. Conf. Commun (ICC), Paris, 2017, pp. 1-7.

[20] Y. Ma, W. Young, E. Anderson, and J. Coder, “Probability of coexistenceof LTE-LAA and WLAN systems based on delay constraints”,in Proc.27th ICCCN, July 30 -August 2, 2018, Hangzhou, China, pp. 1-9.

[21] Y. Ma, R. Jacobs, D. G. Kuester, J. Coder, and W. F. Young, “SDR-Basedexperiments for LTE-LAA based coexistence systems with improveddesign,” in Proc. IEEE GlobeCom, Singapore, Dec. 2017.

[22] L. Dai and X. Sun, “A unified analysis of IEEE 802.11 DCF networks:stability, throughput, and delay,” IEEE Trans. Mobile Comput., vol.12,no.8, pp.1558–1572, Aug. 2013.

[23] Y. Gao, X. Sun and L. Dai, “IEEE 802.11e Std EDCA networks: mod-eling, differentiation and optimization,” IEEE Trans. Wireless Commun.,vol. 13, no. 7, pp. 3863–3879, July 2014.

[24] Y. Gao and L. Dai, “Optimal downlink/uplink throughput allocation forIEEE 802.11 DCF networks,” IEEE Wireless Commun. Lett., vol. 2, no.6, pp. 627-630, Dec. 2013.

[25] W. Zhang, M. A. Suresh, R. Stoleru and H. Chenji, “On modeling thecoexistence of 802.11 and 802.15.4 networks for performance tuning,”IEEE Trans. Wireless Commun., vol. 13, no. 10, pp. 5855-5866, Oct.2014.

Yao Ma (S’98-M’01-SM’08) received the B.Eng.degree from Anhui University, in 1993, the M.Sc.degree from the University of Science and Tech-nology of China (USTC), in 1996, and the Ph.D.degree in electrical engineering from the NationalUniversity of Singapore, in 2000. From 2002 to2009, he was an Assistant Professor at the ECEdepartment, Iowa State University, Ames IA, USA.From 2009 to 2011, he was with the EE department,Wright State University. From 2011 to 2014, he waswith the Air Force Research Laboratory, Sensors

Directorate. He was later with the Infoscitex Inc. Dayton, OH, USA. SinceJuly 2015, he has been with National Institute of Standards and Technology,Boulder CO, USA.

His research interests lie in wireless communication, networking, and signalprocessing. His recent research topics include spectrum sharing, wirelesscoexistence and uncertainty evaluation, radio resource allocation, hardwareprogramming and experiments, and machine learning. He has been anassociate editor for the IEEE Transactions on Vehicular Technology sinceAugust 2004. He was a former editor for the IEEE Transactions on WirelessCommunications.

Daniel G. Kuester (S’11-M’12-SM’16) receivedB.S. and B.M. degrees in E.E. and music per-formance (2007), then M.S.E.E. (2010) and Ph.D.degrees (2012) with advisor Zoya Popovi, from theUniversity of Colorado, Boulder. He is with theCommunications Technology Laboratory at the Na-tional Institute of Standards and Technology in Boul-der, CO, USA. His professional interests focus onconnecting robust physical layer metrology to user-visible wireless and spectrum sharing performance.His work has been awarded the U.S. Department of

Commerce Gold Medal (2017), the "Most Innovative Use of RFID" by RFIDJournal (2015), and Best Paper Award by the IEEE Conf. on Wireless PowerTransfer (2013).

Jason Coder received his B.S.E.E. and M.S.E.Edegrees from the University of Colorado Denverin 2008 and 2010, respectively. As a graduatestudent his research focused on signal processingand electromagnetics. Mr. Coder currently worksin the Shared Spectrum Metrology Group as partof the National Institute of Standards and Technol-ogy’s Communications Technology Laboratory. Hisresearch focuses on developing new measurementmethods for spectrum sharing, wireless coexistence,and interference. This work has produced more than

45 publications in a variety of subject areas. Mr. Coder currently serves asthe Chair of the ANSI C63.27 working group.

William F. Young (M’04) received the PhD degreefrom the University of Colorado, Boulder in Elec-trical Engineering in 2006.

At Sandia National Laboratories from 1998 to2010, Dr. William Young’s contributions includedthe information security design and assessmentsof Critical Infrastructure and DoD communicationsystems. His research included optimizing RF prop-agation from ad hoc wireless arrays, RF penetra-tion of large buildings, electromagnetic interferenceon wireless, space-borne telemetry, and the use of

MIMO channels for perimeter intrusion detection. He was with the NationalInstitute of Standards and Technology from 2010 to 2018, where he developedRF performance test methodologies for wireless communication devices forthe National Fire Protection Association (NFPA) and the ANSI C63.27 -Standard for Evaluation of Wireless Coexistence. From 2016 to 2018, hewas Group Leader of Shared Spectrum Metrology and served as the technicallead for the National Advanced Spectrum and Communication Test Network(NASCTN) project investigating LTE impacts on GPS L1 Band receivers.He joined MITRE in 2018 as a subject matter expert in test and evaluationof spectrum sharing and wireless technologies. Since 2015, Dr. Young alsoserves as a part-time instructor at the University of Colorado, Denver.

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