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[Truncated abstract] The transmission of digital information over a wireless communication channel gives rise to a number of issues which can detract from the system performance. Propagation effects such as multipath fading and intersymbol interference (ISI) can result in significant performance degradation. Recent developments in the field of iterative detection have led to a number of powerful strategies that can be effective in mitigating the detrimental effects of wireless channels. In this thesis, iterative detection is considered for use in two distinct areas of wireless communications. The first considers the iterative decoding of concatenated block codes over slow flat fading wireless channels, while the second considers the problem of detection for a coded communications system transmitting over highly-dispersive frequency-selective wireless channels. The iterative decoding of concatenated codes over slow flat fading channels with coherent signalling requires knowledge of the fading amplitudes, known as the channel state information (CSI). The CSI is combined with statistical knowledge of the channel to form channel reliability metrics for use in the iterative decoding algorithm. When the CSI is unknown to the receiver, the existing literature suggests the use of simple approximations to the channel reliability metric. However, these works generally consider low rate concatenated codes with strong error correcting capabilities. In some situations, the error correcting capability of the channel code must be traded for other requirements, such as higher spectral efficiency, lower end-to-end latency and lower hardware cost. ... In particular, when the error correcting capabilities of the concatenated code is weak, the conventional metrics are observed to fail, whereas the proposed metrics are shown to perform well regardless of the error correcting capabilities of the code. The effects of ISI caused by a frequency-selective wireless channel environment can also be mitigated using iterative detection. When the channel can be viewed as a finite impulse response (FIR) filter, the state-of-the-art iterative receiver is the maximum a posteriori probability (MAP) based turbo equaliser. However, the complexity of this receiver's MAP equaliser increases exponentially with the length of the FIR channel. Consequently, this scheme is restricted for use in systems where the channel length is relatively short. In this thesis, the use of a channel shortening prefilter in conjunction with the MAP-based turbo equaliser is considered in order to allow its use with arbitrarily long channels. The prefilter shortens the effective channel, thereby reducing the number of equaliser states. A consequence of channel shortening is that residual ISI appears at the input to the turbo equaliser and the noise becomes coloured. In order to account for the ensuing performance loss, two simple enhancements to the scheme are proposed. The first is a feedback path which is used to cancel residual ISI, based on decisions from past iterations. The second is the use of a carefully selected value for the variance of the noise assumed by the MAP-based turbo equaliser. Simulations are performed over a number of highly dispersive channels and it is shown that the proposed enhancements result in considerable performance improvements. Moreover, these performance benefits are achieved with very little additional complexity with respect to the unmodified channel shortened turbo equaliser.
Wireless channels are becoming more and more important, with the future development of wireless ad-hoc networks and the integration of mobile and satellite communications. To this end, algorithmic detection aspects (involved in the physical layer) will become fundamental in the design of a communication system. This book proposes a unified approach to detection for stochastic channels, with particular attention to wireless channels. The core idea is to show that the three main criteria of sequence detection, symbol detection and graph-based detection, can all be described within a general framework. This implies that a detection algorithm based on one criterion can be extended to the other criteria in a systematic manner. Presents a detailed analysis of statistical signal detection for digital signals transmitted over wireless communications Provides a unifying framework for different signal detection algorithms, such as sequence detection, symbol detection and graph-based detection, important for the design of modern digital receivers operating over mobile channels Features the hot topic of graph-based detection Detection Algorithms for Wireless Communications represents a novel contribution with respect to the current literature, with a unique focus on detection algorithms, as such it will prove invaluable to researchers working in academia and industry and in the field of wireless communications, as well as postgraduate students attending advanced courses on mobile communications.
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.
Iterative Detection: Adaptivity, Complexity Reduction, and Applications is a primary resource for both researchers and teachers in the field of communication. Unlike other books in the area, it presents a general view of iterative detection that does not rely heavily on coding theory or graph theory. The features of the text include: Both theoretical background and numerous real-world applications. Over 70 detailed examples, 100 problems, 180 illustrations, tables of notation and acronyms, and an extensive bibliography and subject index. A whole chapter devoted to a case study on turbo decoder design. Receiver design guidelines, rules and suggestions. The most advanced view of iterative (turbo) detection based only on block diagrams and standard detection and estimation theory. Development of adaptive iterative detection theory. Application of adaptive iterative detection to phase and channel tracking in turbo coded systems and systems representative of digital mobile radio designs. An entire chapter dedicated to complexity reduction. Numerous recent research results. Discussion of open problems at the end of each chapter. Among the applications considered in this book are joint equalization and decoding, turbo codes, multiuser detection and decoding, broadband wireless channel equalization, and applications to two-dimensional storage and imaging systems. Audience: Iterative Detection: Adaptivity, Complexity Reduction, and Applications provides an accessible and detailed reference for researchers, practicing engineers, and students working in the field of detection and estimation. It will be of particular interest to those who would like to learn how iterative detection can be applied to equalization, interference mitigation, and general signal processing tasks. Researchers and practicing engineers interested in learning the turbo decoding algorithm should also have this book.
Finally, for vertical Bell Laboratories layered space-time OFDM systems, we propose an iterative channel estimator based on a PSAM structure for time-varying multipath fading channels. By exploiting the statistical properties of a wireless channel, we also develop a method to suppress intercarrier interference due to the channel time selectivity, and propose a low-complexity iterative channel estimator that exploits a priori information in an efficient manner.
The ubiquitous wireless networks in the next generation of communication systems have motivated advanced techniques with diverse ranges of connectivity, coverage, reliability, and throughput. The massive connectivity in the context of the heterogenous networks has conveyed to different sorts of challenges including inter-cell and intra-cell originated interferences. The complications aggravate due to the sporadic nature of the traffic generated by large-scale and low-powered networks over limited spectrum resources. In this thesis, different techniques in enhancing the reliability, as well as spectral and power efficiency in the future generations of the multi-point communication networks have been investigated. Our proposed schemes are based on the coordination of the transmitters in sharing the source information followed by the joint transmission and the iterative detection. in the context of the cooperative source and channel coding. The Non-Orthogonal Multiple Access (NOMA), Coordinated Multi-Point (CoMP) transmission and the Iterative Joint Detection and Decoding (IJDD) receivers are the frameworks that we have used to validate our proposed improvements. We have initially investigated the cooperative NOMA as the physical layer network coding scheme in the downlink of wireless communication systems. It is proposed to benefit from the so-called interference received from adjacent cells instead of ignoring or cancelling them, as in the state-of-the-art systems. The application of cooperative NOMA is evaluated in a system-level information theoretic framework to optimize the user-pairing strategy. The results show the cell edges with the strongest interference are the optimal vicinity for the NOMA applications. Further, we have evaluated the NOMA for the uplink in the dense Internet of Things (IoT) systems, where the sensor elements observe the correlated sources. Realizing that the separation of source coding from channel coding in NOMA systems with correlated sources is suboptimal, we propose our scheme based on the cooperative source and channel coding. The transmitters are assumed to be privy to the whole data through a high-rate and low-latency background connection. The cooperative source coding is then followed by the transmission over the non-orthogonal multiple access (NOMA) channel. As the transmit signals experience different delay-spreads through the channel, the data streams are received asynchronously, resulting in inter-symbol interference (ISI) at the receiver. We show that the correlated nature of the asynchronous channels can be exploited as the extra source of information, provided that a proper detection technique is adopted. The capacity region is developed, where the sum-rate exceeds that of the synchronous NOMA. The potency of the successive interference cancellation (SIC) receivers, as the main block in NOMA receivers, is investigated. By applying water-filling and geometric power allocation, we show that the NOMA performance degradation in asynchronous channels is caused by the nature of SIC. We have proposed our iterative joint detection and decoding (IJDD) receiver that outperforms SIC in asynchronous NOMA receivers. Moreover, we have addressed two key challenges in Coordinated Multi-point (CoMP) networks. The asynchronous downlink and imperfect channel state information (CSI) are jointly considered in an information theoretical framework. We assume delays from the Transmission and Reception Points (TRP) to the target user, in general, may exceed cyclic prefix (CP) length, causing symbol-asynchronous reception at the receiver. We characterize an accurate mathematical model for the asynchronous Rayleigh fading channel with imperfect CSI for multi-TRP schemes. We have derived the capacity region for asynchronous CoMP systems and have generalized it to the multi-TRP schemes. We propose a low-complexity iterative detection scheme targeting minimizing the mean square error (MMSE) in our asynchronous fading channel model. Finally, we have associated the coordinated multi-point transmission with NOMA methodology. We have considered the downlink CoMP in a Single-Frequency Network (SFN) of Digital Terrestrial Television (DTT) broadcasting network. The coordinated transmit signals are assumed to have embedded Layered-Division Multiplexing (LDM) to enhance the coverage, reliability, and spectral efficiency in multi-content broadcasting. We have extended the MMSE-IJDD receiver to higher order modulation formats and have evaluated the order of the computational complexity for our proposed receiver to be in a decent range. Our extensive simulations validate the proposed scheme providing a considerable boost in the channel reliability, while enhancing the spectral and power efficiency, even as the number of TRPs increases.
The objective of the proposed research is to devise high-performance and low-complexity signal-detection algorithms for communication systems over fading channels. They include channel equalization to combat intersymbol interference (ISI) and multiple input multiple output (MIMO) signal detection to deal with multiple access interference (MAI) from other transmit antennas. As the demand for higher data-rate and more efficiency wireless communications increases, signal detection becomes more challenging. We propose novel transmission and iterative signal-detection techniques based on energy spreading transform (EST). Different from the existing iterative methods based on the turbo principle, the proposed schemes are independent of channel coding. EST is an orthonormal that spreads a symbol energy over the symbol block in time and frequency for channel equalization; space and time for MIMO signal detection with flat fading channels; and space, time, and frequency for MIMO signal detection with frequency-selective fading channels. Due to the spreading, EST obtains diversity in the available domains for the specific application and increases the reliability of the feedback signal. Moreover, it enables iterative signal detection that has near interference-free performance only at the complexity of linear detectors. Either a hard or soft decision can be fed back to the interference-cancellation stage at the subsequent iteration. The soft-decision scheme prevents error propagation of the hard-decision scheme for a low SNR and improves the performance. We analyze the performance of the proposed techniques. Analytical and simulation results show that these schemes perform very close to the interference-free systems.
The Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC) is one of the premier conferences in the wireless research arena and has a long history of bringing together academia, industry and regulatory bodies Today, it has become one of the IEEE Communication Society s major conferences in wireless communications and networks The topics cover the physical layer (PHY) and fundamentals of wireless communications, medium access control (MAC) and cross layer design, mobile and wireless networks, as well as services, applications, and business