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Single Input Single Output (SISO) Orthogonal Frequency Division Multiplexing (OFDM) systems have been adopted in many of the recent wireless communication standards such as European terrestrial broadcast systems based on DVB-H, DVB-T and DVB-T2. For OFDM systems, cyclic prefix of sufficient length makes the receiver design simple in frequency-selective multipath environments. Wireless communication based on Multiple Input Multiple Output (MIMO) systems has gained popularity due to the potential capacity increases it can provide. MIMO-OFDM based transmission systems can thus provide very high data rates with a relatively simple receiver design and are now adopted widely in recent wireless communication standards such as Long Term Evolution (LTE), WiMAX and WiFi. Modern wireless communication applications, both SISO and MIMO, require high data rates at high carrier frequencies and at high levels of mobility. This results in less intercarrier spacing and severe time-varying frequency-selective multipath fading, which breaks the orthogonality of subcarriers and causes intercarrier interference (ICI) in the received signal thus severely impacting the BER performance of the receiver. Hence, efficient receiver design which is fundamental to any communication system is ever more relevant. Turbo iterative receivers (IR) are based on the observation that performance of the system can be significantly improved if detection and decoding are combined together. They, in general, are found to have superior performance compared to other solutions, however turbo IRs usually suffer from high computational complexity which makes their implementation expensive. Such practical application challenges motivate us to propose a new, low complexity, Turbo IR for SISO and MIMO OFDM systems under time varying frequency selective channel conditions. Motivated by the classical TE, we first propose a sub-optimal, successive interference cancellation and MAP decoding (SIC-MAP) algorithm for SISO systems. In SIC-MAP, copies of the received signal on the same and adjacent subcarriers are carefully combined to take advantage of the frequency diversity (on account of the time variations of the channel) while eliminating the interference from the other transmit symbols leveraging the feedback information from the decoder. The resulting system matrix becomes a single column vector which allows an easy MAP decoding. BER performance, computation complexity, and convergence behavior of the proposed scheme has been contrasted with two other similar schemes. It has been found that SIC-MAP, while having near identical performance to the competing schemes, can be implemented approximately with only a third of their computational complexity. Subsequently, we extend the above detection idea, SIC-MAP, to MIMO systems (SIC-MAP-MIMO). Unlike single antenna systems, even under static multipath channel conditions, the received signal in a MIMO receiver is corrupted by the co-antenna interference (CAI), thus making the detection task more challenging. SIC-MAP-MIMO algorithm achieves comparable BER performance to the competing equalization schemes but with even more computational savings than SISO. A low complexity Least Squares (LS) based iterative channel estimation scheme using soft feedback information has also been proposed. This scheme is especially suitable when the number of significant channel taps is higher than the number of pilots, a phenomenon that is often encountered in practical systems.
This dissertation presents four technical contributions in the theory and practice of low-density parity-check (LDPC) codes and orthogonal frequency division multiplexing (OFDM) systems withtransmission non-linearity and with interference due to high mobility. We first explore the universality of LDPC codes for the binary erasure channel (BEC), the AWGN channel, and the flat Rayleigh fading channel. Using excess mutual information as a performance measure, we demonstrate that an LDPC code designed on a singlechannel can be universally good across the three channels. Thus, a channel for which LDPC code design is simple may be used as a surrogate for channels that are more challenging. Due to fast channel variations, OFDM systems suffer from inter-carrier interference (ICI) in frequency-selective fast fading channels. We propose a novel iterative receiver design that achieves near-optimal performance while maintaining a complexity that grows only linearly with the number of OFDM carriers. Weprove that the matched filter bound for such a channel is also the maximum-likelihood sequence detection (MLSD) bound. Because of the presence of high peaks at OFDM modulator output, amplitude clipping due to amplifier saturation causes performance degradation. We show that existing analyses underestimate the capacity of OFDM systems with clipping, and we analyze thecapacity of clipped OFDM systems with AWGN and frequency-selective Rayleigh fading. We prove that for frequency-selective Rayleigh fading channels, under certain conditions, there exists an SNR threshold, above which the capacity of a clipped system is higherthan that of an unclipped system. We provide upper and lower boundson the channel capacity and closed-form approximations of discrete-input capacities with and without clipping. We also derive tight MLSD lower bounds and propose near-optimal receivers for OFDM systems with clipping. We show that over frequency-selective Rayleigh fading channels, under certain conditions, a clipped system with MLSD can achieve better performance than an unclipped system. We show that the MLSD boundscan be achieved or closely approached by the proposed low complexity receivers in various channel types.
Wireless mobile communications were initially a way for people to communicate through low data rate voice call connections. As data enabled devices allow users the ability to do much more with their mobile devices, so to will the demand for more reliable and pervasive wireless data. This is being addressed by so-called 4th generation wireless systems based on orthogonal frequency division multiplexing (OFDM) and multiple-input multiple-output (MIMO) antenna systems. Mobile wireless customers are becoming more demanding and expecting to have a great user experience over high speed broadband access at any time and anywhere, both indoor and outdoor. However, these promising improvements cannot be realized without an e±cient design of the receiver. Recently, receivers utilizing iterative detection and decoding have changed the fundamental receiver design paradigm from traditional separated parameter estimation and data detection blocks to an integrated iterative parameter estimator and data detection unit. Motivated by this iterative data driven approach, we develop low complexity iterative receivers with improved sensitivity compared to the conventional receivers, this brings potential benefits for the wireless communication system, such as improving the overall system throughput, increasing the macro cell coverage, and reducing the cost of the equipments in both the base station and mobile terminal. It is a challenge to design receivers that have good performance in a highly dynamic mobile wireless environment. One of the challenges is to minimize overhead reference signal energy (preamble, pilot symbols) without compromising the performance. We investigate this problem, and develop an iterative receiver with enhanced data-driven channel estimation. We discuss practical realizations of the iterative receiver for SISO-OFDM system. We utilize the channel estimation from soft decoded data (the a priori information) through frequency-domain combining and time-domain combining strategies in parallel with limited pilot signals. We analyze the performance and complexity of the iterative receiver, and show that the receiver's sensitivity can be improved even with this low complexity solution. Hence, seamless communications can be achieved with better macro cell coverage and mobility without compromising the overall system performance. Another challenge is that a massive amount of interference caused by MIMO transmission (spatial multiplexing MIMO) reduces the performance of the channel estimation, and further degrades data detection performance. We extend the iterative channel estimation from SISO systems to MIMO systems, and work with linear detection methods to perform joint interference mitigation and channel estimation. We further show the robustness of the iterative receivers in both indoor and outdoor environment compared to the conventional receiver approach. Finally, we develop low complexity iterative spatial multiplexed MIMO receivers for nonlinear methods based on two known techniques, that is, the Sphere Decoder (SD) method and the Markov Chain Monte Carlo (MCMC) method. These methods have superior performance, however, they typically demand a substantial increase in computational complexity, which is not favorable in practical realizations. We investigate and show for the first time how to utilize the a priori information in these methods to achieve performance enhancement while simultaneously substantially reducing the computational complexity. In our modified sphere decoder method, we introduce a new accumulated a priori metric in the tree node enumeration process. We show how we can improve the performance by obtaining the reliable tree node candidate from the joint Maximum Likelihood (ML) metric and an approximated a priori metric. We also show how we can improve the convergence speed of the sphere decoder (i.e., reduce the com- plexity) by selecting the node with the highest a priori probability as the starting node in the enumeration process. In our modified MCMC method, the a priori information is utilized for the firrst time to qualify the reliably decoded bits from the entire signal space. Two new robust MCMC methods are developed to deal with the unreliable bits by using the reliably decoded bit information to cancel the interference that they generate. We show through complexity analysis and performance comparison that these new techniques have improved performance compared to the conventional approaches, and further complexity reduction can be obtained with the assistance of the a priori information. Therefore, the complexity and performance tradeoff of these nonlinear methods can be optimized for practical realizations.
The Second Edition of OFDM Baseband Receiver Design for Wirless Communications, this book expands on the earlier edition with enhanced coverage of MIMO techniques, additional baseband algorithms, and more IC design examples. The authors cover the full range of OFDM technology, from theories and algorithms to architectures and circuits. The book gives a concise yet comprehensive look at digital communication fundamentals before explaining signal processing algorithms in receivers. The authors give detailed treatment of hardware issues - from architecture to IC implementation. Links OFDM and MIMO theory with hardware implementation Enables the reader to transfer communication received concepts into hardware; design wireless receivers with acceptable implemntation loss; achieve low-power designs Covers the latest standards, such as DVB-T2, WiMax, LTE and LTE-A Includes more baseband algorithms, like soft-decoding algorithms such as BCJR and SOVA Expanded treatment of channel models, detection algorithms and MIMO techniques Features concrete design examples of WiMAX systems and cognitive radio apllications Companion website with lecture slides for instructors Based on materials developed for a course in digital communication IC design, this book is ideal for graduate students and researchers in VLSI design, wireless communications, and communications signal processing. Practicing engineers working on algorithms or hardware for wireless communications devices will also find this to be a key reference.
Multi-antenna systems have been shown to significantly improve channel capacity in wireless environments. The focus of this thesis is on the design of low-complexity multi-antenna receiver architectures for communication networks and their demonstration in a real-time wireless environment. Our practical realization of an orthogonal frequency-division multi-antenna receiver is capable of several forms of linear and iterative detection. Our implementation is based on a division-free reformulation of standard minimum mean-squared-error detection algorithms and uses complex dot-products as the basic building blocks of a folded-pipelined architecture. This folded-pipelined architecture provides significant area savings over non-folded approaches. The demonstration of our receiver architecture is carried out on a rapid-prototyping FPGA communication system. This prototype is used to validate our design and complement theoretical and simulated results with real-time laboratory measurements in a typical office environment.
Wireless Communication Systems: Advanced Techniques for Signal Receptionoffers a unified frameworkfor understanding today's newest techniques for signal processing in communication systems - andusing them to design receivers for emerging wireless systems. Two leading researchers cover a fullrange of physical-layer issues, including multipath, dispersion, interference, dynamism, andmultiple-antenna systems. Topics include blind, group-blind, space-time, and turbo multiuserdetection; narrowband interference suppression; Monte Carlo Bayesian signal processing; fast fadingchannels; advanced signal processing in coded OFDM systems, and more.
This book focuses on the receiver design issue in high spectral efficiency communication systems, which is one of the main research directions in beyond 5G and 6G era. In particular, this book studies two technologies to improve the spectral efficiency, i.e., FTN signaling which transmits more data information in the same time period and NOMA scheme which supports more users with the same resource elements. Different commonly used channel propagation conditions are considered, and advanced signal processing algorithms have been developed for designing receivers, which is suitable for low-complexity receiver design in engineering practice. Moreover, this book discusses possible solutions to further increase spectral efficiency and propose practical receivers in such scenarios. It benefits researchers, engineers, and students in the fields of wireless communications and signal processing.
This monograph focuses on the design of low complexity interference cancellation and channel estimation algorithms for two different space-frequency coded OFDM system configurations. The first of these configurations is space-frequency block coded OFDM (SFBC-OFDM) which yields performance improvement mainly by exploiting spatial diversity. To attain further performance improvement, a concatenated SFBC-OFDM system configuration, which exploits both spatial and frequency diversities inherent in multiple-input multiple-output multi-path channels, is considered next. In addition to presenting computationally efficient receiver designs for the two above-mentioned system configurations, the monograph also investigates the performance of the proposed receivers via accurate analytical and simulation methods under various channel conditions. Furthermore, the performances and complexities associated with the designed receiver structures are quantified and compared with those corresponding to the receivers that already exist in the literature.
This practical book is an accessible introduction to Orthogonal frequency-division multiplexing (OFDM) receiver design, a technology that allows digitized data to be carried by multiple carriers. It offers a detailed simulation study of an OFDM algorithm for Wi-Fi and 4G cellular that can be used to understand other OFDM waveforms. Extensive simulation studies are included using the transmissionwaveform given by the IEEE 802.11 standard. Scrambler, error-correcting codes, interleaver and radio-wave propagation model are included. OFDM waveform characteristics, signal acquisition, synchronization issues, channel estimation and tracking, hard and soft decision decoding are all covered. Detailed derivations leading to the final formula for any algorithm are given, which allows the reader to clearly understand the approximations and conditions behind the formulas and apply them appropriately. The algorithms are selected not just for the best performance from simulation study but also for easy implementation. An example is a unique algorithm for signal acquisition using the principle of maximum likelihood detection.
MIMO-OFDM for LTE, WIFI and WIMAX: Coherent versus Non-Coherent and Cooperative Turbo-Transceivers provides an up-to-date portrayal of wireless transmission based on OFDM techniques augmented with Space-Time Block Codes (STBCs) and Spatial-Division Multiple Access (SDMA). The volume also offers an in-depth treatment of cutting-edge Cooperative Communications. This monograph collates the latest techniques in a number of specific design areas of turbo-detected MIMO-OFDM wireless systems. As a result a wide range of topical subjects are examined, including channel coding and multiuser detection (MUD), with a special emphasis on optimum maximum-likelihood (ML) MUDs, reduced-complexity genetic algorithm aided near-ML MUDs and sphere detection. The benefits of spreading codes as well as joint iterative channel and data estimation are only a few of the radical new features of the book. Also considered are the benefits of turbo and LDPC channel coding, the entire suite of known joint coding and modulation schemes, space-time coding as well as SDM/SDMA MIMOs within the context of various application examples. The book systematically converts the lessons of Shannon's information theory into design principles applicable to practical wireless systems; the depth of discussions increases towards the end of the book. Discusses many state-of-the-art topics important to today's wireless communications engineers. Includes numerous complete system design examples for the industrial practitioner. Offers a detailed portrayal of sphere detection. Based on over twenty years of research into OFDM in the context of various applications, subsequently presenting comprehensive bibliographies.