Multipath Wave Propagation Effects on the Performance of OFDM UMTS-LTE

Communications System

Ammar Osmana, Abbas Mohammedb and Zhe Yangb

aEricsson AB (Branch Sudan), Market Unit North Africa, Riad, Kartoum, Sudan

bSchool of Engineering, Blekinge Institute of Technology, 37225 Ronneby, Sweden

Abstract. Future generation mobile telecommunication systems are expected to provide high data rate services and improved system performance. Long Term Evolution (LTE) is a project within the Third Generation Partnership Project (3GPP) that aims at improving the current 3G UMTS (Universal Mobile Telecommunications System) standard to cope with future requirements and to maintain competitiveness in the long term. This paper analyzes the requirements for this evolution and evaluates the performance of the Orthogonal Frequency Division Multiplexing (OFDM) UMTS-LTE system under different propagation impairments (AWGN, Pedestrian and Vehicular multipath fading channels of different speeds) in terms of bit and symbol error rates (BER and SER) for different modulation formats.

Keywords: LTE, radio wave propagation, OFDM.PACS: 41.20.Jb

INTRODUCTION

The increasing demands for higher data rates nowadays for mobile wireless communication systems for supporting the wide range of multimedia and internet services has gained a significant interest around the globe from academic researchers and mobile industries. The third Generation Partnership Project (3GPP) organization, as an international collaboration project, has been working on evolving the current third generation (3G) mobile telecommunication systems towards the future fourth generation (4G) systems. This has led to the birth of an evolution to the current 3G systems known as 3GPP LTE (Long Term Evolution). LTE aims to ensure 3G UMTS competitiveness in the long term and to improve 3G UMTS standard and performance to cope with future requirements [1]. Hence, the important goals of LTE include achieving higher data rates, reducing latency, improving efficiency, enhancing services, exploitation of new spectrum opportunities, improving system capacity and coverage, lowering costs and better integration with other standards. 3GPP LTE will gain momentum in the coming year and is expected to be an important player in the 4G constellation along with other emerging techniques such as mobile WiMAX (IEEE 802.11e).

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In order to achieve these ambitious requirements Orthogonal Frequency Division Multiplexing (OFDM) was proposed as the multiple access scheme in the physical layer downlink specifications of LTE system [1]. The use OFDM on the downlink was specified to provide UMTS-LTE more robustness and flexibility in its use of the proposed spectrum allocations than the current 3G systems. OFDM has gained a tremendous interest in recent years because of its robustness in the presence of severe multipath channel conditions with simple equalization, robustness against Inter-symbol Interference (ISI), multipath fading, and its high spectral efficiency.

References [3, 7, 5, 11] all deal with the Orthogonal Frequency Division Multiplexing (OFDM) based systems but they did not consider the features and requirements of LTE. Many technical requirements with the consideration of MIMO solution are addressed in [8]. In [11], research on Physical Random Access Channel (RACH), an analysis of the proposed new air interface for the LTE UL with several channel models has been studied. However, downlink is not considered. The choice of an appropriate MIMO scheme is still an important research topic in the standardizations bodies [14].

In light of the above, this paper is focused on studying the performance of the downlink OFDM UMTS-LTE system with appropriate parameters selected according to the standards [1]. This physical layer aspect feasibility study has been carried out by means of software simulations using Matlab. The simulated OFDM UMTS-LTE system operates over a 20 MHz frequency-band. However, it can be easily modified and reconfigured to be used with other spectrum bands specified in the standards [1].

The organization of this paper is as follows: First, the transmitter design is outlined. Then, the OFDM UMTS-LTE receiver design structure is discussed. Next, we briefly present the ITU frequency-selective, time-variant channel models used in the simulations. Simulation results showing the BER and SER performance curves are then presented and compared. Finally, we conclude the paper.

Serial Data Source

Generator

Serial to Parallel

Converter

Parallel To Serial Converter

Signal Mapper QPSK,

16QAM, and

64QAM

LTE Pilot Insertion Zero

Padding IFFT

Parallel to Serial

Converter

SER/ BER Computation

QPSK, 16QAM,

and 64QAM

Demapper

Cyclic Prefix

Insertion

Serial to Parallel

Con. FFT

LMMSE Channel

Estimation

FDE-Zero

Forcing Equa.

Cyclic Prefix

Extraction

Multipath Channel

Mod.

AWGN

FIGURE 1. Block diagram of the implemented OFDM UMTS-LTE system.

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THE OFDM UMTS-LTE TRANSMITTER STRUCTURE

The block diagram of the UMTS-LTE transmitter structure is illustrated in figure 1. In particular the transmitter is based on the popular Orthogonal Frequency Division Multiplexing (OFDM) scheme. The OFDM based transmitter part [2, 3] contains the following blocks: source generator, modulation schemes [4], the proposed LTE pilot insertion [1], Zero padding, IFFT, and the cyclic prefix insertion.

The digital random data set is generated uniformly. These blocks of digital data set have been paralleled and mapped into complex data blocks using different modulation techniques, i.e. 4QAM, 16QAM, and 64QAM respectively. Each complex data block, also referred to as symbol, of data is attached to an individual sub-carrier.

Since the bandwidth of the transmitted signal is less than the sampling rate of the OFDM modulator, the unused frequency bands are padded with zeros. The inverse DFT is efficiently implemented by means of Inverse Fast Fourier Transform (IFFT) in order to generate the time version of the transmitted signal. The time domain signals corresponding to all sub-carriers are orthogonal to each other; however, their frequency spectrums overlap. Furthermore, to get rid of the inter-symbol interference and the noise distortion, transmitting OFDM symbols into parallel intervals allow signal duration to become large enough to alleviate these effects. Finally, the cyclic prefix is inserted in front of every transmitted OFDM symbol.

UMTS-LTE Pilot Structure

One of the crucial problems in OFDM systems is how to track and estimate the time-varying multipath propagation channel environments. In order to assess the performance of the OFDM UMTS-LTE system presented in this paper, we use the ITU frequency-selective propagation channel models [9, 13].

There are three main general uses for the pilot tones in the proposed LTE downlink reference signal [1]: ) Measuring the channel quality ) Channel estimation for different demodulation and detection at the end user side ) Initial acquisition and cell search

An efficient way of tracking the multipath channel is by transmitting these pilot symbols at instant time intervals of certain locations of the LTE downlink time-frequency lattice. Based on the working assumptions of [1, section 7.1.1.2.2], neither all frequency bins nor all transmitted OFDM symbols contain pilots for UMTS-LTE. However, for the implementation part we considered only the OFDM symbols that contain pilot tones as shown in the time-frequency lattice figure 7.1.1.2.2-1 in [1].

Zero Padding, OFDM Modulation, and Cyclic Prefix Insertion

In order to simplify the realization of the analog filters used for transmission, the sampling rate is higher than the bandwidth of the transmitted signal, and therefore zero padding at the transmitter side is required for our design. It consists of increasing the

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length of the spectrum of the signal with specific number of zeros. However, the extended length should not be an integer multiple of the total length of the signal. Extending the length of the signal is usually done either by extending the time band limits or the frequency band limits of the signal. We used extension in the time domain with zeros to the transmitted signal.

One of the key elements of any OFDM system is the existence of the Fast Fourier transform (FFT). The generated streams from the OFDM modulation are carried out on different sub-carriers [12, 15]. Hence, the transmitter complexity is reduced by the use of the inverse Fast Fourier Transform (IFFT). Similarly, the receiver is implemented as the low-complexity Fast Fourier Transform (FFT) operation to demodulate the OFDM signals. The transmitted data are split into low bit rate streams. However, these low rate streams are subject to individual flat fading due to their transmission over the frequency selective channel model.

Suppose we have Nsc sub-carriers, and that the transmitted OFDM symbols are X(1), X(2), X(3), X(4),…. , X(N). After normalizing all the OFDM IFFT symbols, the mathematical discrete-time representation for these symbols is:

1 2

0

1( ) ( ) 0,......, -1.

knN jN

n

x k X n e k NN

/�

�

� �& (1)

At the receiver side, the received OFDM data symbols converted to the time domain by using the FFT:

1 2

0

( ) ( ) 0,......, -1.knN jN

k

Y n y k e n N/� �

�

� �& (2)

Cyclic prefix is a copy of the last part of the transmitted OFDM symbol which is appended in front of the same symbol for each transmitted OFDM symbol. Inter-symbol interference and inter-carrier interference are the two major consequences of the transmission over time-varying frequency selective channels. Since the cyclic prefix is used in our UMTS-LTE transceiver, the influence of the inter-symbol interference is reduced. However, the length of the cyclic prefix must be at least the same or longer than the length of the channel impulse response, in order to prevent the occurrence of interference.

THE OFDM UMTS-LTE RECEIVER STRUCTURE

The current mobile receivers are small in size and have stringent power consumption constraints, hence the design of the receiver should meet specific requirements to assure low complexity and low cost at the same time. In the first step, the receiver has to remove the guard period (introduced in the transmitter) from the received signals. This operation is called de-cyclic prefix. This is followed by the Fast Fourier

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Transform (FFT) operation in order to recover the modulated symbols for all sub-carriers and to convert them into the frequency-domain.

Due to the propagation of the transmitted signal over the multipath channels, it is subjected to a number of impairments (i.e. attenuation, Doppler shift, and amplitude-phase distortion). Thus, all the received sub-carriers signals experience a complex gain, amplitude and phase distortion. A minimum mean-squares error (MMSE) channel estimator [7, 8, 10] is implemented. Afterwards, soft or hard QAM de-mapping schemes are employed. A fully synchronized OFDM transceiver system is assumed in this paper.

OFDM Demodulation and Channel Estimation

The received time-domain signal is converted back to the frequency-domain (demodulated) by the Fast Fourier Transform (FFT). Equation (2) illustrates the mathematical representation of the FFT algorithm. The FFT demodulates the N sub-carriers OFDM signals. The complex output signal then contain N different complex QAM symbols.

The reference frequencies that were used for the estimation of the multipath channel realizations, i.e. pilot tones, placed at certain positions in the time-frequency grid as shown in figure 7.1.1.2.2-1 in [1], are used to track the multipath channel effects. The pilot-tones are found only every six symbols in the frequency-domain. In addition to that, the pilot-tones are found only in OFDM symbols number one and Nsc - 2 in the time-domain (where Nsc = 6, 7, 8, or 9) according to table 5.1 and 7.1.1-2 in [1], respectively. The LTE pilot-tones are generated randomly by the simulator.

MMSE Equalization

A frequency-domain equalizer (FDE) was implemented in this simulation, in the form of a linear MMSE equalizer. The simplicity of the implemented frequency-domain equalizer leads to cheap hardware implementation. Then the equalized signal is applied to the M-QAM demodulator block to retrieve the binary information.

THE ITU CHANNEL MODELS

The simplest form of the wireless propagation channel used as a reference in the design of the UMTS-LTE transceiver is the Additive White Gaussian Noise (AWGN) channel model. A more complicated but realistic model is the frequency-selective, time-variant channel models, which specifies the typical multipath effects associated with real-world propagation environments experienced by this wireless system.

The frequency-selective, time-variant channel models that used for designing the UMTS-LTE transceiver in this simulator are based on the ITU channel models [9, 13]. The ITU channel models are divided into two categories: Pedestrian and Vehicular. Pedestrian-A at 3 km/h (“PA3”), Vehicular-A at 120 km/h (“VA120”) and Vehicular-

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A at 350 km/h channel models are used in this paper. The last model with speed of 350 km/h is considered in this study to deal with situations such as high speed trains. Each of these channel models has different number of delay taps which represents the respective delay and power of each signal path. These channel power delay profilesare presented in [13].

SIMULATION RESULTS

In this section we present simulation results to evaluate the performance of the considered UMTS-LTE transceiver under different ITU multipath fading propagation channel models. Perfect synchronization between the transmitter and receiver is assumed in the simulations. The measure used to assess and evaluate the performance is the achieved bit and symbol error rates (BER and SER) for the different proposed QAM modulation formats. The theoretical performance over AWGN is also presented as a reference. The designed transceiver is considered operating with a bandwidth of 20 MHz.

Figures (2-7) show the OFDM UMTS-LTE system performance in terms of bit error rate (BER) and symbol error rate (SER) versus signal-to-noise ratio (SNR) for 4-QAM, 16-QAM and 64-QAM modulation formats, respectively. The figures clearly show the adverse effect of channel selectivity due to the severe multipath fading propagation conditions on the performance as is evident by comparing the vehicular 120 and 350 km/h plots together, and with the performance of the pedestrian plot at 3 km/h. It is also apparent that as the number of transmitted QAM symbols increases, higher data rates are achieved at the expense of higher energy resources needed for satisfactory operation.

The results presented here would be very useful for evaluating and comparing the system performance when using other advanced receiver structures, spectrum allocations, the upcoming LTE-advanced system and other emerging techniques such as mobile WiMAX (IEEE 802.11e).

CONCLUSIONS

Research towards meeting the increasing demands for higher data rates was a major reason for the birth of an evolution technology towards the future fourth generation mobile telecommunication systems. The evolution of the current 3G UMTS system was given the name LTE by 3GPP, where higher data rates are key objective and OFDM is utilized as the multiple access technique in the downlink. In this paper we presented a Matlab simulator of OFDM UMTS-LTE system and highlighted the design and operation of the different system blocks. In addition, we investigated the performance of the system under different multipath propagation environments and modulation formats. These performance results can be used as a benchmark platform for future reference and comparison purposes. For example, the simulator parameters can be adjusted to evaluate the coded performance of the system, the performance over different spectrum allocations and advanced receiver structures.

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FIGURE 2. BER versus SNR using 4-QAM modulation format over various channel models.

FIGURE 3. BER versus SNR using 16-QAM modulation format over various channel models.

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FIGURE 4. BER versus SNR using 64-QAM modulation format over various channel models.

FIGURE 5. SER versus SNR using 4-QAM modulation format over various channel models.

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FIGURE 6. SER versus SNR using 16-QAM modulation format over various channel models.

FIGURE 7. SER versus SNR, using 64-QAM modulation format over various channel models.

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