Iterative Channel Estimation For Wireless Communications

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.

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.

As a result of higher frequencies and increased user mobility, researchers and systems designers are shifting their focus from time-invariant models to channels that vary within a block. Wireless Communications Over Rapidly Time-Varying Channels explains the latest theoretical advances and practical methods to give an understanding of rapidly time varying channels, together with performance trade-offs and potential performance gains, providing the expertise to develop future wireless systems technology. As well as an overview of the issues of developing wireless systems using time-varying channels, the book gives extensive coverage to methods for estimating and equalizing rapidly time-varying channels, including a discussion of training data optimization, as well as providing models and transceiver methods for time-varying ultra-wideband channels. An introduction to time-varying channel models gives in a nutshell the important issues of developing wireless systems technology using time-varying channels Extensive coverage of methods for estimating and equalizing rapidly time-varying channels, including a discussion of training data optimization, enables development of high performance wireless systems Chapters on transceiver design for OFDM and receiver algorithms for MIMO communication channels over time-varying channels, with an emphasis on modern iterative turbo-style architectures, demonstrates how these important technologies can optimize future wireless systems

This book presents an algorithm for the detection of an orthogonal frequency division multiplexing (OFDM) signal in a cognitive radio context by means of a joint and iterative channel and noise estimation technique. Based on the minimum mean square criterion, it performs an accurate detection of a user in a frequency band, by achieving a quasi-optimal channel and noise variance estimation if the signal is present, and by estimating the noise level in the band if the signal is absent. Organized into three chapters, the first chapter provides the background against which the system model is presented, as well as some basics concerning the channel statistics and the transmission of an OFDM signal over a multipath channel. In Chapter 2, the proposed iterative algorithm for the noise variance and the channel estimation is detailed, and in Chapter 3, an application of the algorithm for the free-band detection is proposed. In both Chapters 2 and 3, the principle of the algorithm is presented in a simple way, and more elaborate developments are also provided. The different assumptions and assertions in the developments and the performance of the proposed method are validated through simulations, and compared to methods of the scientific literature.

This book introduces the theoretical elements at the basis of various classes of algorithms commonly employed in the physical layer (and, in part, in MAC layer) of wireless communications systems. It focuses on single user systems, so ignoring multiple access techniques. Moreover, emphasis is put on single-input single-output (SISO) systems, although some relevant topics about multiple-input multiple-output (MIMO) systems are also illustrated. Comprehensive wireless specific guide to algorithmic techniques Provides a detailed analysis of channel equalization and channel coding for wireless applications Unique conceptual approach focusing in single user systems Covers algebraic decoding, modulation techniques, channel coding and channel equalisation

Discover cutting-edge research in wireless communications This book presents cutting-edge research in wireless communications, particularly in the fast-growing subject of multiple-input multiple-output (MIMO) wireless communication systems. It begins with an introduction, which includes historical notes and a review of turbo-information processing and MIMO wireless communications, and goes on to cover: MIMO channel capacity BLAST architectures Space-time turbo codes and turbo decoding principles Turbo-BLAST Turbo-MIMO systems The material is complemented with abundant illustrations and computer experiments that are designed to help readers reinforce their understanding of the underlying subject matter. Space-Time Layered Information Processing for Wireless Communications is an ideal resource for researchers in academia and industry and an excellent textbook for related courses at the graduate level.

Optimization of adaptive signal processing algorithms for wireless communications is based on a model of the underlying propagation channel. In practice, this model is never known perfectly. For example, its parameters have to be estimated and are only known with significant errors. In this book, a systematic treatment of this practical design problem is provided.

This dissertation, "An Iterative Receiver With Pilot-aided Kalman Filter Based Channel Estimation for Wireless MC-CDMA Communication Systems" by Tung-man, Law, 羅東文, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: Abstract of the thesis entitled An Iterative Receiver with Pilot-Aided Kalman Filter based Channel Estimation for Wireless MC- CDMA Communication Systems submitted by Law Tung Man for the degree of Master of Philosophy at the University of Hong Kong in July 2007 Efficient channel estimation and multiuser detection techniques are required to overcome the deficiencies due to the multipath fading and multiuser access interference (MAI) in multicarrier code-division multiple-access (MC-CDMA) systems. In order to obtain further improvement, a turbo receiver using maximum a posteriori expectation-maximization (MAP-EM) demodulator with a soft low-density parity-check (LDPC) decoder is considered. In this thesis, we consider two main streams of channel estimation and multiuser detection for wireless MC-CDMA communications. First, a turbo receiver with pilot-aided Kalman filter-based channel tracking is developed to investigate the iiimportant role of channel estimation. The pilot-aided Kalman filter considerably simplifies the tracking of the time-varying channel, which helps to improve the performance of the MAP-EM demodulator and LDPC decoder in fast fading channels. Simulation results show that the proposed system gives a better BER performance than conventional turbo receiver, at the expense of a slightly lower data rate due to the use of pilot symbols. It is therefore an useful alternative to conventional approaches providing a different tradeoff between BER performance, implementation complexity, and transmission bandwidth. When some subcarriers in MC-CDMA system are contaminated by narrowband interfering signals, it was found that the performances of conventional least-squares (LS) channel estimators and multiuser detectors, and even the Kalman filter-based channel estimator, were significantly degraded. Therefore a turbo receiver with pilot- aided robust channel tracking and multiuser detection under time-varying narrowband interference (NBI) is developed. A new weighted least M-estimate (WLM) multiuser detector based on the M-estimation and weighted least square (WLS) algorithm is proposed to jointly suppress the MAI and time-varying NBI. To provide reliable channel estimation in NBI, a weighted recursive least M-estimate (WRLM) channel estimator is also employed to estimate time-varying frequency- selective fading channels. Simulation results show that the proposed WRLM channel estimator and WLM multiuser detector significantly outperform the conventional RLS channel estimator and linear decorrelator under NBI respectively. An abstract of exactly 307 words iii DOI: 10.5353/th_b3858166 Subjects: Signal detection Code division multiple access Wireless communication systems