NISTIR 7986

LTE Physical Layer Performance 

Analysis

Wen-Bin Yang

Michael Souryal 

http://dx.doi.org/10.6028/NIST.IR.7986
2

NISTIR 7986 

LTE Physical Layer Performance 

Analysis 

Wen-Bin Yang

Michael Souryal

Advanced Network Technologies Division

Information Technology Laboratory

http://dx.doi.org/10.6028/NIST.IR.7986

May 2014

U.S. Department of Commerce 

Penny Pritzker, Secretary

National Institute of Standards and Technology 

Patrick D. Gallagher, Under Secretary of Commerce for Standards and Technology and Director
1

LTE Physical Layer Performance Analysis

National Institute of Standards and Technology

Wen-Bin Yang and Michael Souryal

December 2013

1 Introduction

The 3GPP Long Term Evolution (LTE) technology exhibits a major advance in wireless 

communication networks to meet increasing demands for high quality multimedia 

services. Orthogonal frequency division multiplexing (OFDM) and multiple inputmultiple output (MIMO) are employed to enhance the performance of current wireless 

systems. With these and other techniques, higher data rates and higher capacity can be 

attained in the LTE network.

Among these techniques, link adaptation is used in LTE to exploit the frequency 

selectivity of the wireless channel to improve spectral efficiency. However, to perform 

link adaptation, certain quality information of the channel is required at the transmitter.

During actual network operation, using the channel quality information, link adaption 

dynamically assigns one of the modulation and coding schemes (MCSs) to each user 

equipment (UE) in order to maintain link quality. However, for network planning, design 

or performance evaluation, the performance characteristics (e.g., block error rate as a 

function of SNR) of each MCS is required. 

In this report, we present results of a physical layer performance study for all MCSs

(from MCS0 to MCS28) in terms of block error rate (BLER) and spectral efficiency. The 

results are obtained by using the Steepest Ascent1 LTE toolbox for MATLAB which 

provides functions for modeling the LTE physical layer based upon 3GPP specifications. 

The performance measures for each MCS are evaluated as a function of signal to noise 

ratio (SNR), MIMO configuration, and 3GPP multipath fading channel. The 3GPP 

channels include models for pedestrian, vehicular, and typical urban environments. The 

results of this study can be used in higher level modeling tools such as cellular network 

planning and network modeling tools that take abstractions of physical layer performance 

as input.

2 LTE Physical Layer

OFDM technology has been incorporated into LTE because it enables high data rates to 

be transmitted efficiently while still providing a high degree of resilience to reflections 

 1 Steepest Ascent Ltd. was acquired by The Mathworks, Inc. in September, 2013. 

Certain commercial equipment, instruments, or materials are identified in this report in order to specify the experimental procedure 

adequately. Such identification is not intended to imply recommendation or endorsement by the National Institute of Standards and 

Technology, nor is it intended to imply that the materials or equipment identified are necessarily the best available for the purpose.
2

and interference. The access schemes differ between the uplink and downlink: OFDMA 

(Orthogonal Frequency Division Multiple) Access is used in the downlink, while SCFDMA (Single Carrier - Frequency Division Multiple Access) is used in the uplink. 

The LTE air interface exploits both time division duplex (TDD) and frequency division 

duplex (FDD) modes to support unpaired and paired spectra. MIMO may also be 

optionally deployed in the eNodeB and/or UE in order to enhance link quality and to 

increase data rates/throughputs. MIMO utilizes multiple antennas at the transmitter 

and/or receiver in combination with adaptive signal processing to provide smart array 

processing, diversity combining or spatial multiplexing capability. A generic frame 

structure for the downlink and uplink is shown in Figure 1. 

Since the capabilities of the eNodeB and UE are quite different, the LTE PHY downlink 

and uplink likewise differ and are documented separately in the 3GPP technical 

specifications. The following two sub-sections briefly describe the technical 

specifications of the downlink and uplink PHY layers.

Figure 1: LTE Generic Frame Structure [3]

2.1 Downlink physical layer

The LTE downlink PHY is specified for bandwidths from 1.25 MHz to 20 MHz. OFDM 

with a cyclic prefix is the basic modulation scheme selected to combat severe frequencyselective multipath fading. Three different types of physical channels are defined for the 

LTE downlink: physical downlink shared channel (PDSCH), physical downlink control 

channel (PDCCH) and common control physical channel (CCPCH). In this report, the 

focus is on PDSCH performance because it carries user data and is designed for a wide 

range of data rates. Therefore, modulations include QPSK, 16QAM and 64QAM and the

coding rate ranges from 1/6 to 3/4. The downlink uses the generic frame structure shown 

in Fig. 1 in the time domain. In the frequency domain, it uses a subcarrier spacing of 

15 kHz. Time-frequency resources are allocated in units of physical resource blocks

(PRBs) comprised of 12 subcarriers in frequency and 1 sub-frame in time. The detailed 

downlink OFDM modulation parameters may be found in [1]. The block diagram of an 

OFDM transceiver is shown in Figure 2.
3

2.2 Uplink physical layer

The basic transmission scheme for the LTE uplink is Single-Carrier-Frequency Domain 

Multiple Access (SC-FDMA). The major advantage of SC-FDMA over conventional 

OFDM is an approximately 2 dB lower PAPR (peak-to-average power ratio). In FDD 

applications, the uplink uses the same generic frame structure as the downlink. It also 

uses the same subcarrier spacing of 15 kHz and PRB width of 12 subcarriers. Again, only 

physical uplink shared channel (PUSCH) performance is evaluated here. The PUSCH 

employs QPSK, 16QAM or 64QAM modulation. The detailed uplink specifications may 

be found in [8].

The block diagram of the SC-FDMA scheme is also shown in Figure 2. This figure also 

indicates the difference between OFDMA and SC-FDMA.

Figure 2: SC-FDMA and OFDMA signal block diagram [3] (S/P = Serial-to-Parallel, DFT = Discrete 

Fourier Transform, IDFT = Inverse DFT, RFE = RF Front End)

3 Schemes and fading channels for Performance 

Analysis

In this section, MCS and MIMO schemes as well as multipath fading channels and 

channel estimation are addressed.

3.1 Modulation and coding scheme

The modulation and coding scheme (MCS) index value summarizes the modulation type 

and the coding rate that is used in a given PRB. Typically, a higher MCS index offers a 

higher spectral efficiency (which translates to a higher potential data rate) but requires a 

higher SNR to support it. Using our simulation results of BLER vs. SNR, the appropriate 

MCS index value for a particular channel condition can be determined.
4

Annex A of 3GPP technical specifications of Refs. [1] and [8] describes downlink and 

uplink fixed reference channels, respectively, which may be used for modeling any 

modulation and coding scheme (MCS) index in terms of number of allocated resource 

blocks, modulation (QPSK, 16QAM or 64QAM), code rate, and associated transport 

block size (TBS). Parameters for any MCS index for PDSCH or PUSCH may be obtained 

by using Tables 7.1.7.1-1, 8.6.1-1 and 7.1.7.2.1-1 [2]. The three tables are listed in 

Appendix A of this report. Tables A1 and A2 list MCS index vs. TBS index for PDSCH 

and PUSCH, respectively. Table A3 (portion of Table 7.1.7.2.1-1) shows transport block 

size as a function of allocated block size and TBS index.

3.2 MIMO

One of the main problems of previous telecommunications systems is that of multiple 

signals arising from the many reflections that are encountered, which may cause 

interference with one another. By using MIMO, these additional signal paths can be used 

to their advantage and can increase the throughput. 

When using MIMO, it is necessary to use multiple antennas to enable the different paths 

to be distinguished. While it is relatively easy to add more antennas to a base station, the 

same is not true of mobile handsets, where the dimensions of the user equipment limit the 

number of antennas to be placed at least a half wavelength apart. A 1x2 MIMO 

configuration for uplink and 2x2 for downlink are studied. For the downlink, both

transmit diversity and spatial multiplexing are considered in this study.

3.2.1 Transmit diversity

The transmit diversity scheme [6] relies on the use of multiple antennas at the transmitter 

in combination with pre‐coding in order to achieve spatial diversity when transmitting a

single data stream. Usually transmit diversity necessitates the absolute channel 

information at the transmitter, but it becomes feasible to implement transmit diversity 

without the knowledge of the channel with space time block coding [4]. The simplest of 

the diversity techniques is the Alamouti space time coding scheme [5]. The use of 

transmit diversity is common in the downlink of cellular systems because it is cheaper 

and easier to install multiple antennas at the base station than to put multiple antennas on

every handheld device. In transmit diversity, to combat instantaneous fading and to 

achieve considerable gain in instantaneous SNR, the receiver is being provided with 

multiple copies of the transmitted signal. Hence, applying transmit diversity creates 

extended converge and better link quality even when users experience poor channel 

conditions.

3.2.2 Spatial Multiplexing
5

Spatial multiplexing [6] can provide a substantial increase in data rates by transmitting 

different data streams over parallel channels provided by the multiple transmit and 

receive antennas, while using the same bandwidth and with no additional power

expenditure. In MIMO systems, the increase in capacity is linearly related to the number 

of transmit/receive antenna pairs. Consider a MIMO system with M transmit and N

receive antennas; the radio channel for this system will consist of M×N ideally 

uncorrelated paths. This configuration offers min(M,N) parallel channels that permit

simultaneous transmission of data streams. In a 2×2 system, for example, a single bit 

stream is split into two half‐rate bit streams, modulated and transmitted simultaneously 

from both antennas which can cause interference to each other at the receiver. Therefore 

at the receiver, inference cancellation is employed to separate the different transmitted 

signals. For the spatial multiplexing technique, several decoding algorithms are

developed for interference cancellation for the narrowband frequency flat fading case.

The spatial multiplexing may be either open-loop or closed-loop MIMO schemes. Openloop spatial multiplexing uses large cyclic delay diversity to pursue maximum 

multiplexing gain. Closed-loop spatial multiplexing uses pre-coding feedback from the 

UE to improve SNR or capacity.

3.3 3GPP multipath fading channels

The multipath fading channel is defined by a combination of a multipath delay profile 

and a maximum Doppler frequency, which can be 5, 70 or 300 Hz. Annex B of 3GPP 

technical specification [1] describes the multipath fading propagation conditions,

including taps of the Extended Pedestrian A model (EPA), Extended Vehicular A model 

(EVA) and Extended Typical Urban model (ETU) (also shown in Table 1 below) as well 

as classical Doppler spectrum. In this report, we focus on performance analysis for EPA5, 

ETU70 and EVA70 models.

Table 1: 3GPP multipath fading channel models [1]

EPA ETU EVA

Excess tap 

delay [ns]

Relative 

power 

[dB]

Excess tap 

delay [ns]

Relative 

power 

[dB]

Excess tap 

delay [ns]

Relative 

power 

[dB]

0 0.0 0 0.0 0 -1.0

30 -1.0 30 -1.5 50 -1.0

70 -2.0 150 -1.4 120 -1.0

90 -3.0 310 -3.6 200 0.0

110 -8.0 370 -0.6 230 0.0

190 -17.2 710 -9.1 500 0.0

410 -20.8 1090 -7.0 1600 -3.0

1730 -12.0 2300 -5.0

2510 -16.9 5000 -7.0
6

3.4 Channel estimation

A radio propagation channel is time-varying depending upon the propagation 

environment and Doppler effects. Channel estimation is a vital part of a receiver’s design 

as it is used to estimate the time-varying channel condition in wireless systems. As long 

as the time-varying radio propagation channel can be kept track of, the receiver can 

recover precise transmitted information. To facilitate the estimation of channel 

characteristics, LTE uses cell specific reference signals (pilot symbols). The pilot 

symbols provide an estimate of the channel at a given location within a sub-frame [7]. 

Through interpolation, it is possible to estimate the channel across an arbitrary number of 

sub-frames. Implementation of channel estimation and interpolation depends on window 

sizes in time and in frequency domains. Each hardware vendor may implement the 

channel estimator in its own way. Therefore, to minimize the ambiguity of the channel 

estimation implementation, we assume a perfect channel estimator is employed in our 

simulations. The effect of practical estimators can be incorporated by shifting the 

performance curves accordingly (e.g., 1 dB).

4 Simulation Results 

In this study, we assume 5 PRBs are allocated to the link. Although an allocation of 5 

PRBs is assumed, we did not see a significant difference in BLER performance when 

varying the number of allocated PRBs from 1 to 50. The multipath fading channels 

include EPA5, ETU70 and EVA70.2 MIMO configurations are 2x2 and 1x2 for downlink 

and uplink, respectively. The LTE downlink employs OFDMA multiplexing schemes 

including transmit diversity and spatial multiplexing. FDD and hybrid automatic repeat 

request (HARQ) are used in the simulations. PDSCH and PUSCH BLER-vs.-SNR curves 

are shown in the following subsections. Each figure contains BLER curves for all MCSs. 

Also, a combined spectral efficiency curve is included that is based upon the maximum 

spectral efficiency over all MCSs at any SNR value.

4.1 Downlink PDSCH performance using transmit diversity

scheme

4.1.1 Block error rate

Figures 3-5 show downlink PDSCH block error rate vs. SNR for all MCSs (MCS0 –

MCS28) using transmit diversity over EPA5, ETU70 and EVA70 channels, respectively. 

As expected, lower MCS index values result in lower BLER than higher index values (at 

the expense of lower spectral efficiency).

 2 Because of the longer coherence time of the EPA5 channel model, statistically significant results with this 

channel model requires the simulation of substantially more frames than with the other channel models.
7

Figure 3: Downlink transmit diversity block error rate over EPA5 channel for all MCSs

Figure 4: Downlink transmit diversity block error rate over ETU70 channel for all MCSs

-15 -10 -5 0 5 10 15 20 25 30

10-4

10-3

10-2

10-1

100

SNR (dB)

BLER

MCS0 MCS28

-15 -10 -5 0 5 10 15 20 25 30

10-3

10-2

10-1

100

SNR (dB)

BLER

MCS28

MCS0
8

Figure 5: Downlink transmit diversity block error rate over EVA70 channel for all MCSs

4.1.2 Spectral efficiency

Figure 6 shows spectral efficiency when transmit diversity is employed. There is no 

significant difference among the three fading channels except in the range of 10-23dB of 

SNR.

Figure 6: Downlink spectral efficiency using transmit diversity scheme

-15 -10 -5 0 5 10 15 20 25 30

10-3

10-2

10-1

100

SNR (dB)

BLER

MCS0 MCS28

-15 -10 -5 0 5 10 15 20 25 30 35

0

1

2

3

4

5

6

SNR (dB)

Spectral Efficiency (Bits/Symbol)

EPA5

ETU70

EVA70
9

4.2 Downlink PDSCH performance using open-loop spatial 

multiplexing scheme

4.2.1 Block error rate

Figures 7-9 show downlink PDSCH block error rate vs. SNR over EPA5, ETU70 and 

EVA70 channels, respectively, when open-loop spatial multiplexing scheme is employed.

Figure 7: Downlink spatial multiplexing block error rate over EPA5 channel for all MCSs

Figure 8: Downlink spatial multiplexing block error rate over ETU70 channel for all MCSs

-10 0 10 20 30 40 50

10-3

10-2

10-1

100

SNR (dB)

BLER

MCS0 MCS28

-10 -5 0 5 10 15 20 25 30 35 40

10-3

10-2

10-1

100

SNR (dB)

BLER

MCS28 MCS0
10

Figure 9: Downlink spatial multiplexing block error rate over EVA70 channel for all MCSs

4.2.2 Spectral efficiency

Spectral efficiency curves for the three fading channels are shown in Fig. 10 when openloop spatial multiplexing is employed. In contrast to transmit diversity, spatial 

multiplexing shows spectral efficiency differentiation in the higher SNR range of 25-

40dB. Furthermore, the peak spectral efficiency is roughly twice that when transmit 

diversity is employed because of the use of two spatial streams.

Figure 10: Downlink spectral efficiency using spatial multiplexing scheme

-10 -5 0 5 10 15 20 25 30 35 40

10-3

10-2

10-1

100

SNR (dB)

BLER

MCS0 MCS28

-15 -10 -5 0 5 10 15 20 25 30 0

1

2

3

4

5

6

SNR (dB)

Spectral Efficiency (Bits/Symbol)

EPA5

ETU70

EVA70
11

4.3 Uplink PUSCH performance

4.3.1 Block error rate

Figures 11-13 show uplink PUSCH block error rate vs. SNR over EPA5, ETU70 and 

EVA70 channels, respectively.

Figure 11: Uplink block error rate over EPA5 channel for all MCSs

Figure 12: Uplink block error rate over ETU70 channel for all MCSs

-15 -10 -5 0 5 10 15 20 25 30

10-3

10-2

10-1

100

SNR (dB)

BLER

MCS28

MCS0

-15 -10 -5 0 5 10 15 20 25

10-3

10-2

10-1

100

SNR (dB)

BLER

MCS0

MCS28
12

Figure 13: Uplink block error rate over EVA70 channel for all MCSs

4.3.2 Spectral efficiency

PUSCH spectral efficiency curves for the three fading channels are shown in Figure 14.

Figure 14: Uplink spectral efficiency 

-15 -10 -5 0 5 10 15 20 25 30

10-3

10-2

10-1

100

SNR (dB)

BLER

MCS28 MCS0

-15 -10 -5 0 5 10 15 20 25 30 0

1

2

3

4

5

6

SNR (dB)

Spectrum Efficiency (Bits/Symbol)

EPA5

ETU70

EVA70
13

5 Summary

PDSCH and PUSCH performance was evaluated over 3GPP multipath fading channels 

for all MCS index values (MCS0 to MCS28). The performance measures included block 

error rate and spectral efficiency. The 3GPP multipath channels were EPA5, ETU70, and 

EVA70. Transmit diversity and spatial multiplexing schemes for downlink performance 

were evaluated.

A further simulation study may be performed, if interested, by minor modification from 

current simulation setups (for example, different fading channel models, different MIMO 

configurations, or control channel performance study.)

6 References

[1] “3GPP TS 36.101 V11.0.0”, March 2012.

[2] “3GPP TS 36.213 V10.5.0”, March 2012.

[3] Jim Zyren, “Overview of the 3GPP Long Term Evolution Physical Layer”, 

Freescale semiconductor, July 2007.

[4] Mohinder Jankiraman, Space‐Time Codes and MIMO Systems, published by Artech 

House Boston , London, 2004.

[5] S.M. Alamouti, ‘‘A Simple Transmit Diversity Technique for Wireless Comm.,’’IEEE 

Journal Select. Areas Communications, pp. 1451–1458, Vol. 16, No. 8, October 1998.

[6] “3GPP TS 36.211 V11.0.0”, September 2012.

[7] Annex F of “3GPP TS 36.141 V11.0.0”, March 2012.

[8] “3GPP TS 36.104 V11.0.0”, March 2013.
14

Appendix A

Table A1: Modulation and TBS index table for PDSCH [2]

MCS Index

MCS I

Modulation Order

Qm

TBS Index

TBS I

0 2 0

1 2 1

2 2 2

3 2 3

4 2 4

5 2 5

6 2 6

7 2 7

8 2 8

9 2 9

10 4 9

11 4 10

12 4 11

13 4 12

14 4 13

15 4 14

16 4 15

17 6 15

18 6 16

19 6 17

20 6 18

21 6 19

22 6 20

23 6 21

24 6 22

25 6 23

26 6 24

27 6 25

28 6 26

29 2

30 4 reserved

31 6
15

Table A2: Modulation, TBS index and redundancy version table for PUSCH [2]

MCS Index

MCS I

Modulation Order

' Qm

TBS Index

TBS I

Redundancy 

Version

rvidx

0 2 0 0

1 2 1 0

2 2 2 0

3 2 3 0

4 2 4 0

5 2 5 0

6 2 6 0

7 2 7 0

8 2 8 0

9 2 9 0

10 2 10 0

11 4 10 0

12 4 11 0

13 4 12 0

14 4 13 0

15 4 14 0

16 4 15 0

17 4 16 0

18 4 17 0

19 4 18 0

20 4 19 0

21 6 19 0

22 6 20 0

23 6 21 0

24 6 22 0

25 6 23 0

26 6 24 0

27 6 25 0

28 6 26 0

29

reserved

1

30 2

31 3
16

Table A3: Transport block size table [2]

TBS I NPRB

1 2 3 4 5 6 7 8 9 10

0 16 32 56 88 120 152 176 208 224 256

1 24 56 88 144 176 208 224 256 328 344

2 32 72 144 176 208 256 296 328 376 424

3 40 104 176 208 256 328 392 440 504 568

4 56 120 208 256 328 408 488 552 632 696

5 72 144 224 328 424 504 600 680 776 872

6 88 176 256 392 504 600 712 808 936 1032

7 104 224 328 472 584 712 840 968 1096 1224

8 120 256 392 536 680 808 968 1096 1256 1384

9 136 296 456 616 776 936 1096 1256 1416 1544

10 144 328 504 680 872 1032 1224 1384 1544 1736

11 176 376 584 776 1000 1192 1384 1608 1800 2024

12 208 440 680 904 1128 1352 1608 1800 2024 2280

13 224 488 744 1000 1256 1544 1800 2024 2280 2536

14 256 552 840 1128 1416 1736 1992 2280 2600 2856

15 280 600 904 1224 1544 1800 2152 2472 2728 3112

16 328 632 968 1288 1608 1928 2280 2600 2984 3240

17 336 696 1064 1416 1800 2152 2536 2856 3240 3624

18 376 776 1160 1544 1992 2344 2792 3112 3624 4008

19 408 840 1288 1736 2152 2600 2984 3496 3880 4264

20 440 904 1384 1864 2344 2792 3240 3752 4136 4584

21 488 1000 1480 1992 2472 2984 3496 4008 4584 4968

22 520 1064 1608 2152 2664 3240 3752 4264 4776 5352

23 552 1128 1736 2280 2856 3496 4008 4584 5160 5736

24 584 1192 1800 2408 2984 3624 4264 4968 5544 5992

25 616 1256 1864 2536 3112 3752 4392 5160 5736 6200

26 712 1480 2216 2984 3752 4392 5160 5992 6712 7480