The LTE Radio Interface - Key Characteristicsand Performance

Anders Furuskar, Tomas Jonsson, and Magnus LundevallEricsson Research, Sweden

Abstract-Mobile broadband usage is taking off, demandingimproved services and increased capacity of mobile networks. Tomeet tbese requirements, 3GPP bas defined LTE (tbe 3GPP LongTerm Evolution). Tbis paper presents some key cbaracteristics oftbe LTE radio interface, including pbysical layer and radio re­source management functions, and evaluates tbeir impact onsystem performance. As compared to a reference system witbmore basic cbaracteristics, represented by Mobile WiMAX, re­sults point to a combined gain in spectrum efficiency of 60% indownlink and 100% in uplink. Cell-edge bitrate gains are about100% in botb downlink and uplink. A closer analysis of tbe indi­vidual system cbaracteristics indicates tbat tbese performancedifferences are due to ratber uniform contributions from a set ofdistinctive features.

Index Terms-LTE, Performance, WiMAX

I. INTRODUCTION

U sage of mobile broadband services, supported by the in­troduction of High Speed Packet Access (HSPA), is tak­

ing off. To meet the future increased demand for such servic­es, corresponding improvements in the supply of services arerequired, including higher bit rates, lower delays, and highercapacity. This is the target of 3GPP's two radio access net­works HSPA and LTE [1], of which the latter is the focus ofthis paper. LTE brings unprecedented performance. Examplesinclude peak data rates exceeding 300Mbps, delays below10ms, and manifold spectrum efficiency gains over early 3Gsystem releases. Further, LTE can be deployed in new andexisting frequency bands, has a flat architecture with fewnodes, and facilitates simple operation and maintenance.While targeting a smooth evolution from legacy 3GPP and3GPP2 systems, LTE also constitutes a major step towardsIMT-Advanced systems. In fact, LTE includes many of thefeatures originally considered for future fourth generation sys­tem.

General LTE concept descriptions are available in [1]. Inthis paper, the focus is on key characteristics of the LTE radiointerface. A set of such key characteristics are both qualita­tively discussed and quantitatively evaluated in terms ofdownlink and uplink user data rates and spectrum efficiencygenerated by means of system level simulations. For refer­ence, the LTE characteristics are compared to more conven­tional solutions. These are represented by corresponding func­tionalities in Mobile WiMAX with Partial Usage of Sub­Channels (PUSC) [2].

978-1-4244-2644-7/08/$25.00 ©2008 IEEE

The paper is outlined as follows: After an introduction tothe basic structure of the LTE radio interface in Section II,Section III provides a qualitative discussion of distinctive fea­tures of the evaluated system concepts, and their impact onperformance. Models and assumptions are summarized in Sec­tion IV, followed by numerical results in Section V. Finally, asummary is provided in Section 6.

II. AN OVERVIEW OF THE LTE RADIO INTERFACE

Comprehensive descriptions of the LTE radio interface areavailable in [1]. In short, LTE is based on Orthogonal Fre­quency Domain Multiplexing (OFDM). The numerology in­cludes a subcarrier spacing of 15kHz, support for bandwidthsup to 20MHz, and resource allocation granularity of 180kHz xIms (a so-called resource block pair). In the uplink, a pre­coder is used to limit peak-to-average power ratios, and there­by reduce terminal complexity. Based on channel quality,modulation (up to 64QAM) and channel coding rates are dy­namically selected. Both FDD, TDD, and half duplex FDD aresupported. A variety of antenna concepts targeting differentscenarios is included: transmit diversity for improved robust­ness of control channels, beamforming for improved channelquality in general, and multi-stream (MIMO) transmission forimproved data rates in scenarios with good channel quality.On the MAC layer, dynamic scheduling is done on a resourceblock pair basis, based on QoS parameters and channel quali­ty. Retransmissions are handled with two loops, a fast innerloop taking care of most errors complemented with a veryrobust outer loop for residual errors.

III. KEy LTE CHARACTERISTICS

Some of the more fundamental features discussed in theprevious section are not unique to LTE. E.g. OFDM, multi­antenna transmission, and adaptive modulation and coding arestandard techniques used by many systems. On a more de­tailed level however, LTE distinguishes itself by using moresophisticated solutions than other systems. A list of such cha­racteristics is presented in Table I. For reference, the corres­ponding solutions used in more basic systems are also listed.This is represented by Mobile WiMAX Wave 2. It should benoted that there are several other features differing betweenthese systems which are not listed, e.g. control signaling ro­bustness, higher layer overhead, and mobility aspects.

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TABLE ILTE KEy CHARACTERISTICS

Function LTE Mobile WiMAX wave 2(slogan used in Fig. 1-2)Multiple access OFDMinDL, OFDM in DL and UL(MA) DFT-spread OFDM in UL

Uplink power control Fractional pathloss compensa- Full pathloss compensation(PC) tionScheduling Channel dependent in time Channel dependent in time(Scheduling) and freq~~t.t.~y4~J!l~it.t. domainMIMO scheme Horizontal encoding (multiple Vertical encoding (single(MIMO) codewords), closed loop with codeword)

precodingModulation and cod- Fine granularity Coarse granularitying scheme granulari- (1-2dB apart) (2-3dB apart)ty (MCS)Hybrid ARQ II Incremental redundancy Chase combining(HARQ)

Frame duration Ims subframes 5ms frames(CQI delay)

Overhead / control Relatively low OH (while Relatively high OHchannel efficiency control channels are(OH I CCH eft) robust)

Performance impact

DFT-spread OFDM reduces the peak-to-averagepower ratio and reduces terminal complexity,requires one-tap equalizer in base station receiverFractionafpathfoss-compensation·enables·flexibletrade otr~~~~_e.n ave~a.ge. and cell-edge data ratesAccess to the frequency domain yields largerscheduling gainsHorizontafenco·ding enables per-stream linkadaptation and successive interference cancella­tion (SIC) receiversFiner gianu·iaritY enables better link adaptationprecision

Incremental redundancy is more efficient(lower S~r~quir~~ for given error rate)Shorter subframes yield lower user planedelay and reduced channel quality feedbackdelaysLower overhead improves performance

IV. MODELS AND ASSUMPTIONS

Models and assumptions are aligned with the NGMN re­commendations in [3]. Table II contains a brief summary. Theevaluation methodology is based on time-dynamic, multi-cellsystem simulations.

V. NUMERICAL RESULTS

This section presents downlink and uplink user throughputand spectrum efficiency for a selection of system configura­tions and scenarios. More specifically, the following subsec­tions cover (A) baseline configurations with 2x2 and Ix2 an­tenna configurations, (B) more advanced multi-antenna confi­gurations, and (C) results for file transfer (non-full buffer)traffic models.

A. LTE and Mobile WiMAX - Baseline Scenario

Downlink user throughput and spectrum efficiency figuresfor LTE FDD, LTE TDD, and Mobile WiMAX are summa­rized in Fig. 1. Note that in this special case, as there are 10full-buffer users per sector in average, and the spectrum allo­cation is 1oMHz, the spectrum efficiency, measured inbps/HzJsector, and the average user throughput, measured inMbps, are the same. For the TDD systems, the spectrum effi­ciency is calculated by down-scaling the denominator (systembandwidth) with the relative time utilization in the direction inquestion (measured in data symbols). Distributions of userthroughput normalized with spectrum allocation and TODutilization are also presented.

It is seen that LTE is some 60% better than Mobile WiMAXin the average metrics, and about a factor two better in cell­edge performance. The reasons for these differences are acombination of the distinctive features presented in Table I.

Parameter

Traffic Model

User locationSite-to-site distanceCarrier frequencyCarrier bandwidthDistance-dependentpathlossLognormal shadowing

Channel model

Terminal speedBS I Terminal power

Antenna configura­tionsScheduler

MIMO

Power control

Receiver type

TOD asymmetry

TABLE IIMODELS AND ASSUMPTIONS

Value

a) Full buffer (10 users per sector) orb) File transfer (100KB fixed file size) withvariable loadUniform distribution500m2.0GHzIOMHzL= I+ 37.6·log lO(R) + P, Rin kIn, 1= 128.1 for2GHz, P= 20dB penetration loss8dB std dev, 50m correlation distance, 0.5 corre­lation between sites3GPP SCM, Urban Macro High Spread (15 deg),extended to IOMHz3kmlh46dBm / 23dBm

BS: 2-4 transmit and receiveTerminal: 1transmit, 2-4 receiveLTE: DL: Proportional fair in time and fre­quency, UL: Quality-based FDMWiMAX: DL: Proportional fair in time domain,UL:FDMLTE: Codebook-based pre-coded adaptive rankMIMOWiMAX: Dynamic switching between spatialmu~tiplexing MIMO and STCLTE: Open loop with fractional pathloss com­pensation (a=O.8), SNR target 10dB at cell edgeWiMAX: Open loop, SNR target I5dB (fullpathloss compensation)LTE: MMSE with SIC in DLWiMAX:MMSELTE: 4:3, WiMAX: 22:15

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Downlink Uplink

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Fig. 2. Summary of baseline uplink normalized user throughput and spectrumefficiency results, and feature analysis.

LTE LTE

Scheduling OH/CCH eftI

COl delayI

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WiMAX PUSCI

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Fig. 1. Summary of baseline downlink normalized user throughput and spec­trum efficiency results, and feature analysis.

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The individual impact of each such feature has been assessedby, in the simulations, replacing the LTE functionality withthe corresponding WiMAX functionality. The result is shownin the lower bar graph in Fig. 1. The percentage figure to theleft represents the individual feature impact, and the percen­tage figure to the right the accumulated impact of the featurescombined. It is seen that the total difference is not due to asingle distinctive feature, but rather a combination of distinc­tive features, headed by frequency domain scheduling, faster

channel quality feedback, and control channel efficiency. Notealso that when all distinctive features are replaced, the perfor­mance is the same, confirming that these features are indeedthe reason for the overall difference in performance. A similaranalysis can be made for the cell-edge metric.

Similar results for the uplink are summarized in Fig. 2. Inthis direction, it is seen that LTE is more than a factor twobetter than Mobile WiMAX in both average and cell-edgemetrics. Also here, the distinctive features jointly make up the

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Fig. 3. Summary ofdownlink results with additional antenna concepts.

total performance difference, lead by control channel efficien­cy (OR), faster channel quality feedback, and more flexiblepower control.

The small difference between LTE FDD and TDD dependson the TDD guard period and differences in channel qualityfeedback delays.

B. Results with Additional Antenna Concepts

In this section results with more advanced antenna conceptsare presented. Downlink results are summarized in Fig. 3. It isseen that both average and cell-edge performance are im­proved by using 4x2 and 4x4 MIMO solutions.

For the uplink, results with four receive antennas are pre­sented in Fig. 4. In addition to receive diversity results, resultsfor multi-user MIMO, with 2 users multiplexed, are shown. Asignificant performance increase is achieved already using 4­branch receive diversity. The additional gain provided by MU­MIMO is smaller. With two receive antennas the MU-MIMOgains are even smaller.

C. Results for File Transfer Traffic Models

In addition to the full buffer traffic model, for LTE, evalua­tions with a file transfer traffic model have also been per­formed. For simplicity, a fixed file size of IOOKB is assumed.

Although simple, this model captures a number of realisticphenomena not covered by the full buffer model. These in­clude the 'equal buffer' effect of users with low data rates do­minating the link usage, and the effect of interference varia­tions caused by transmitters switching on and off. The filetransfer model also enables the possibility to study achievableuser data rates under varying load conditions.

A number of traffic load levels, realized by different sessionarrival intensities, are evaluated and user bitrates are logged.The user bitrate is measured as the file size divided by thetime between arrival in the system and successful reception.Queuing delays are hence included. The baseline system con­figurations are assumed (2x2 DL and 1x2 UL).

Results in the form of 5th, 50t

\ and 95th percentile user bit­rates as a function of served traffic per sector are presented inFig. 5. It is seen that very high user bitrates are achieved. At'low' load (1-2Mbps/sector), the cell edge bitrate exceeds20Mbps in downlink, and is almost IOMbps in UL. Averagevalues are about a factor two higher, and the 95th percentilevalues are not far from the theoretical peak data rates (72Mbpsin DL and 26Mbps in UL with the overhead assumptionsmade). Further, the capacity, here measured as the maximumsector throughput for a certain 5th percentile bitrate (e.g.IMbps), is not very much lower than in the full buffer case.

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VI. SUMMARY

The results presented indicate that in normalized metricsLTE, with its more sophisticated radio interface, outperformsthe more basic Mobile WiMAX Wave 2 in both downlink anduplink and for both FDD and TDD operation. In the downlink,LTE is about 60% better in spectrum efficiency and averageuser throughput, and 100% better in cell-edge user throughput.In the uplink, LTE is 100% better in both average and cell­edge performance. Utilizing the full LTE potential (4x4MIMO, 20MHz carriers, FDD), the differences are even great­er. The large gains for LTE can not be attributed to a singlefeature, but are rather the effect of a number of distinctivecharacteristics, each contributing to the overall gain.

With non-full buffer traffic, very high user bitrates areachieved for LTE. In low to moderate load scenarios, bitratesof tens ofMbps are achievable at the cell-edge, and theoreticalpeak data rates are approached closer to the base station.

In general, absolute performance values depend largely onthe scenario, models, and assumptions used, here aligned withthe NGMN recommendations. Although relevant and well­designed, different results are achieved in other scenarios andunder different assumptions. For example, refined base stationantenna models, based on realistic antenna patterns and mod­eling vertical antenna diagrams, typically yield improved ab­solute spectrum efficiency and user throughput values [4].

The above file transfer results, especially the bitratesachieved at low to moderate load where file transfers are com­pleted in tens of ms, depend on the initial selection of modula­tion, coding and MIMO scheme. These settings have not beenoptimized. Further, the control channel overhead assumptionsare pessimistic for scenarios with low to moderate load, astypically quite few users are scheduled in the same frame.

87

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Fig. 5. Downlink and uplink bitrate percentiles v traffic load for file transfertraffic

The small difference indicates a fair system. It may be notedthat, in theory, with a resource fair scheduler, the 'full buffer'capacity is determined by the average of the user bitrates R,here denoted mean(R). The 'equal buffer' capacity on the oth­er hand may be estimated by the inverse of the average norma­lized delay (D=l/R), and is hence given by l/mean(l/R),which is less than or equal to mean(R).

REFERENCES

[1] E. Dahlman et aI, "3G Evolution: HSPA and LTE for Mobile Broad­band", Academic Press, Oxford, UK, 2007

[2] WiMAX Forum, "Mobile System Profile", Release 1.0 Approved Speci­fication, Revision 1.4.0.

[3] NGMN, "NGMN Radio Access Performance Evaluation Methodology",Version 1.2, June 2007, www.ngmn.org.

[4] F. Gunnarsson et aI., "Downtilted Base Station Antennas - A SimulationModel Proposal and Impact on HSPA and LTE Performance", in IEEEVTC 2008 fall.

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