: LICENTIATE T H E SI S Modulation and Channel Effects in Digital Communication Sara Sandberg Luleå University of Technology Department of Computer Science and Electrical Engineering, Division of Signal Processing :|: -|: - -- ⁄ -- Modulation and Channel Effects in Digital Communication Sara Sandberg Dept. of Computer Science and Electrical Engineering Lulea˚ University of Technology Lulea,˚ Sweden Supervisor: James P. LeBlanc ii To Marcus and Miriam iv ABSTRACT This thesis investigates three possible methods to increase the performance of digital communi- cation systems, with focus on wireless systems, by accounting for some of the channel effects that may occur. The modulation scheme plays an important role in the impact of different channel effects on system performance and this work considers both a single-carrier system and orthogonal frequency-division multiplexing (OFDM). The first work investigates effects of the channel estimation errors resulting from blind channel estimation. The performance of a communication system in terms of throughput may be increased by using blind channel estimation instead of non-blind. This will allow more use- ful information to be sent through the system, but the channel estimation will be less reliable. The effects of the channel estimation errors on the performance of separation in a multiple- input multiple-output (MIMO) system are investigated for a specific blind channel estimation method. This work quantifies the expected performance reduction, in terms of cross-channel power, due to channel estimation errors. The second and third work consider the OFDM framework, which enables simple equal- ization and has been adopted in several standards. However, OFDM is sensitive to frequency- selective fading and introduces a large peak-to-average power ratio (PAPR) of the transmitted signal. These problems can be alleviated by pre-multiplying the OFDM block by a spreading matrix, e.g. the Walsh-Hadamard matrix. It is shown that spreading by the Walsh-Hadamard matrix reduces the PAPR of the transmitted signal and increases the frequency diversity. Sur- prisingly, with a joint implementation of the spreading and the OFDM modulation, the spread OFDM system requires less computations than the conventional OFDM system. An alternative to PAPR reduction is to allow clipping of the signal in the transmitter. Clip- ping will however introduce losses due to the clipping distortion of the signal. In the thesis, receiver methods to mitigate such clipping losses are investigated. It is shown that for an OFDM system with low-density parity-check (LDPC) coding, the cost of completely ignoring the clipping effects in the receiver is minimal. v vi CONTENTS INTRODUCTION 1 1 Introduction .................................... 1 2 Low-DensityParity-CheckCodes........................ 3 3 Modulation .................................... 6 4 ChannelEstimation................................ 7 5 SummaryofContributions............................ 10 6 Conclusions.................................... 11 7 FutureWork.................................... 12 PAPER A 19 1 Introduction .................................... 21 2 SystemModel................................... 22 3 SeparationwithKnownMixingMatrix...................... 23 4 BlindIdentificationBasedonCumulantSubspaceDecomposition....... 24 5 Cost of Blindness . ............................. 25 6 SimulationResults................................ 25 7 Conclusions.................................... 28 PAPER B 31 1 Introduction .................................... 33 2 TheOFDMSystem................................ 34 3 LDPCcodesforOFDMandSOFDM...................... 36 4 Results....................................... 39 5 Conclusions.................................... 41 PAPER C 45 1 Introduction .................................... 47 2 SystemDescriptionandChannelModel..................... 48 3 CharacterizationofClippingNoise........................ 50 4 BayesianEstimation............................... 52 5 ResultsandDiscussion.............................. 53 6 Conclusions.................................... 54 viii ACKNOWLEDGMENTS ThefirstpersonIwouldliketoexpressmygratitude to is my supervisor Professor James LeBlanc. Thank you for convincing me that I would find the Ph.D. studies fun and for the guidance and support that you have given me. Because of your enthusiasm and expertise, becoming a Ph.D. student is a choice I have never regretted. Thanks also for always thinking of what is the best for me and my future and giving that the highest priority. Also, many thanks go to my assistant supervisor Professor Bane Vasic from University of Arizona, that has supported me with his coding expertise and interesting ideas. I really look forward to visit you and your group this autumn. I would also like to thank all my colleagues in the signal processing group. All together you make up a friendly and inspiring atmosphere that makes it enjoyable to go to work. Es- pecially, Martin Sehlstedt, that has always taken the time to answer my questions about the life as a Ph.D. student in general and computer problems in particular, deserves extra thanks. Acknowledgments also to the European Commission for co-funding this work, that is part of the FP6/IST project M-Pipe, and to the PCC graduate school. Finally, I would like to express my sincere gratitude to my husband Marcus. Without your encouragement and never ending support at home this thesis would not have been written. Thanks also to my parents for your support and belief in me. Sara Sandberg Lule˚a, August 2005 ix x Part I xii INTRODUCTION 1 Introduction This thesis addresses methods to reduce the impact on system performance of some channel effects that may occur in a digital communication system. To set the stage for the research presentation, this section gives a short introduction to the principles of a digital communication system. This will serve as the overall picture when more details of the communication system and the research are presented in the following sections. There are many textbooks on the subject of digital communication that the reader can refer to for a thorough introduction, see for example [1][2][3]. Figure 1 shows the main elements of a digital communication system. The information source is assumed to be in digital form and possibly encoded by a source encoder which is omitted in this presentation. The information bits (or digits) are fed to the channel encoder, which introduces redundancy in the information sequence. This redundancy can be used by the channel decoder to reduce the impact of channel effects as noise and interference and the result is increased reliability of the received data. One common way of adding redundancy is block coding where information bits at a time are mapped to a unique sequence of bits, called a codeword, with . The amount of redundancy added is found from the relation between the number of information bits and the number of codeword bits and the code rate is defined as the ratio . In this thesis the focus is on one type of block codes called low- density parity-check (LDPC) codes, [4], that have gained much interest in the latest decade. These codes are discussed in more detail in Section 2. The codeword bits from the channel encoder are passed to the digital modulator, which maps the bits to appropriate signal waveforms. The simplest form of modulation is to map each binary zero to one waveform and each binary one to some other waveform that is easy to 1 2INTRODUCTION Information Channel Digital source encoder modulator SISO/MIMO channel Demodulator, Output Channel separator and decoder signal equalizer Channel estimator Figure 1: A basic digital communication system. distinguish from the waveform representing the zero. This is called binary modulation and is one form of single-carrier modulation. In the last decade, multi-carrier systems have become more popular and especially orthogonal frequency-division multiplexing (OFDM) has received much attention. With multiple carriers the superposition of several waveforms representing several bits are transmitted at the same time. Section 3 describes modulation and especially OFDM more. In wireless communication, the modulated waveforms can be transmitted into the com- munication channel by one or several transmitting antennas. A system with one transmitting antenna and one receiving antenna is called a single-input single-output (SISO) system, while systems with several transmitting and receiving antennas are called multiple-input multiple- output (MIMO) systems. Multiple transmitting and/or receiving antennas will increase the spatial diversity and can be used to combat channel effects without increasing the bandwidth of the transmitted signal. The communication channel model represents the physical medium that connects the trans- mitter with the receiver. This medium can be the atmosphere as well as wire lines, optical fibers, etc. All received waveforms will be more or less corrupted due to thermal noise from electronic devices, non-linear distortion in the high power amplifier, interference from other transmissions, atmospheric noise, fading, etc. At the receiver side of the digital communication system, there are one or more receiving antennas. Each antenna receives a weighted and possibly filtered sum of the different transmit- ted waveforms. The digital demodulator processes these signals and produces a binary stream again. In MIMO systems, a separator reconstructs the transmitted signals from the weighted 2. LOW-DENSITY