Iterative Detection for Overloaded Multiuser MIMO OFDM Systems

Inspired by multiuser detection (MUD) and the ‘Turbo principle’, this thesis deals with iterative interference cancellation (IIC) in overloaded multiuser multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems. Linear detection schemes, such as zero forcing (ZF) and minimum mean square error (MMSE) cannot be used for the overloaded system because of the rank deficiency of channel matrix, while the optimal approach, the maximum likelihood (ML) detection has high computational complexity. In this thesis, an iterative interference cancellation (IIC) multiuser detection scheme with matched filter and convolutional codes is considered. The main idea of this combination is a low complexity receiver. Parallel interference cancellation (PIC) is employed to improve the multiuser receiver performance for overloaded systems. A log-likelihood ratio (LLR) converter is proposed to further improve the reliability of the soft value converted from the output of the matched filter. Simulation results show that the bit error rate (BER) performance of this method is close to the optimal approach for a two user system. However, for the four user or more user system, it has an error floor of the BER performance. For this case, a channel selection scheme is proposed to distinguish whether the channel is good or bad by using the mutual information based on the extrinsic information transfer (EXIT) chart. The mutual information can be predicted in a look-up table which greatly reduces the complexity. For those ‘bad’ channels identified by the channel selection, we introduce two adaptive transmission methods to deal with such channels: one uses a lower code rate, and the other is multiple transmissions. The use of an IIC receiver with the interleave-division multiple access (IDMA) to further improve the BER performance without any channel selection is also investigated. It has been shown that this approach can remove the error floor. Finally, the influence of channel accuracy on the IIC is investigated. Pilot-based Wiener filter channel estimation is used to test and verify how much the IIC is influenced by the channel accuracy

MIMO Systems

In recent years, it was realized that the MIMO communication systems seems to be inevitable in accelerated evolution of high data rates applications due to their potential to dramatically increase the spectral efficiency and simultaneously sending individual information to the corresponding users in wireless systems. This book, intends to provide highlights of the current research topics in the field of MIMO system, to offer a snapshot of the recent advances and major issues faced today by the researchers in the MIMO related areas. The book is written by specialists working in universities and research centers all over the world to cover the fundamental principles and main advanced topics on high data rates wireless communications systems over MIMO channels. Moreover, the book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity

Algorithms for channel impairment mitigation in broadband wireless communications

Ph.DDOCTOR OF PHILOSOPH

Adaptive implementation of turbo multi-user detection architecture

MULTI-access techniques have been adopted widely for communications in underwater acoustic channels, which present many challenges to the development of reliable and practical systems. In such an environment, the unpredictable and complex ocean conditions cause the acoustic waves to be affected by many factors such as limited bandwidth, large propagation losses, time variations and long latency, which limit the usefulness of such techniques. Additionally, multiple access interference (MAI) signals and poor estimation of the unknown channel parameters in the presence of limited training sequences are two of the major problems that degrade the performance of such technologies. In this thesis, two different single-element multi-access schemes, interleave division multiple access (IDMA) and code division multiple access (CDMA), employing decision feedback equalization (DFE) and soft Rake-based architectures, are proposed for multi-user underwater communication applications. By using either multiplexing pilots or continuous pilots, these adaptive turbo architectures with carrier phase tracking are jointly optimized based on the minimum mean square error (MMSE) criterion and adapted iteratively by exchanging soft information in terms of Log-Likelihood Ratio (LLR) estimates with the single-user’s channel decoders. The soft-Rake receivers utilize developed channel estimation and the detection is implemented using parallel interference cancellation (PIC) to remove MAI effects between users. These architectures are investigated and applied to simulated data and data obtained from realistic underwater communication trials using off-line processing of signals acquired during sea-trials in the North Sea. The results of different scenarios demonstrate the penalty in performance as the fading induces irreducible error rates that increase with channel delay spread and emphasize the benefits of using coherent direct adaptive receivers in such reverberant channels. The convergence behaviour of the detectors is evaluated using EXIT chart analyses and issues such as the adaptation parameters and their effects on the performance are also investigated. However, in some cases the receivers with partial knowledge of the interleavers’ patterns or codes can still achieve performance comparable to those with full knowledge. Furthermore, the thesis describes implementation issues of these algorithms using digital signal processors (DSPs), such as computational complexity and provides valuable guidelines for the design of real time underwater communication systems.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Adaptive implementation of turbo multi-user detection architecture

MULTI-access techniques have been adopted widely for communications in underwater acoustic channels, which present many challenges to the development of reliable and practical systems. In such an environment, the unpredictable and complex ocean conditions cause the acoustic waves to be affected by many factors such as limited bandwidth, large propagation losses, time variations and long latency, which limit the usefulness of such techniques. Additionally, multiple access interference (MAI) signals and poor estimation of the unknown channel parameters in the presence of limited training sequences are two of the major problems that degrade the performance of such technologies. In this thesis, two different single-element multi-access schemes, interleave division multiple access (IDMA) and code division multiple access (CDMA), employing decision feedback equalization (DFE) and soft Rake-based architectures, are proposed for multi-user underwater communication applications. By using either multiplexing pilots or continuous pilots, these adaptive turbo architectures with carrier phase tracking are jointly optimized based on the minimum mean square error (MMSE) criterion and adapted iteratively by exchanging soft information in terms of Log-Likelihood Ratio (LLR) estimates with the single-user’s channel decoders. The soft-Rake receivers utilize developed channel estimation and the detection is implemented using parallel interference cancellation (PIC) to remove MAI effects between users. These architectures are investigated and applied to simulated data and data obtained from realistic underwater communication trials using off-line processing of signals acquired during sea-trials in the North Sea. The results of different scenarios demonstrate the penalty in performance as the fading induces irreducible error rates that increase with channel delay spread and emphasize the benefits of using coherent direct adaptive receivers in such reverberant channels. The convergence behaviour of the detectors is evaluated using EXIT chart analyses and issues such as the adaptation parameters and their effects on the performance are also investigated. However, in some cases the receivers with partial knowledge of the interleavers’ patterns or codes can still achieve performance comparable to those with full knowledge. Furthermore, the thesis describes implementation issues of these algorithms using digital signal processors (DSPs), such as computational complexity and provides valuable guidelines for the design of real time underwater communication systems.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Distortion-Tolerant Communications with Correlated Information

This dissertation is devoted to the development of distortion-tolerant communication techniques by exploiting the spatial and/or temporal correlation in a broad range of wireless communication systems under various system configurations. Signals observed in wireless communication systems are often correlated in the spatial and/or temporal domains, and the correlation can be used to facilitate system designs and to improve system performance. First, the optimum node density, i.e., the optimum number of nodes in a unit area, is identified by utilizing the spatial data correlation in the one- and two-dimensional wireless sensor networks (WSNs), under the constraint of fixed power per unit area. The WSNs distortion is quantized as the mean square error between the original and the reconstructed signals. Then we extend the analysis into WSNs with spatial-temporally correlated data. The optimum sampling in the space and time domains is derived. The analytical optimum results can provide insights and guidelines on the design of practical WSNs. Second, distributed source coding schemes are developed by exploiting the data correlation in a wireless network with spatially distributed sources. A new symmetric distributed joint source-channel coding scheme (DJSCC) is proposed by utilizing the spatial source correlation. Then the DJSCC code is applied to spatial-temporally correlated sources. The temporal correlated data is modeled as the Markov chain. Correspondingly, two decoding algorithms are proposed. The first multi-codeword message passing algorithm (MCMP) is designed for spatially correlated memoryless sources. In the second algorithm, a hidden Markov decoding process is added to the MCMP decoder to effectively exploit the data correlation in both the space and time domains. Third, we develop distortion-tolerant high mobility wireless communication systems by considering correlated channel state information (CSI) in the time domain, and study the optimum designs with imperfect CSI. The pilot-assisted channel estimation mean square error is expressed as a closed-form expression of various system parameters through asymptotic analysis. Based on the statistical properties of the channel estimation error, we quantify the impacts of imperfect CSI on system performance by developing the analytical symbol error rate and a spectral efficiency lower bound of the communication system

Journal of Telecommunications and Information Technology, 2006, nr 1

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