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Research On MIMO Channel Modeling And Channel Estimation For New Generation Wireless Communication Systems

Posted on:2008-01-26Degree:DoctorType:Dissertation
Country:ChinaCandidate:H L XiaoFull Text:PDF
GTID:1118360215450400Subject:Information and Communication Engineering
Abstract/Summary:PDF Full Text Request
It is believed that the wireless MIMO technology will be one of the key ones that realize the high speed broadband wireless internet access networks in the future and has wide application prospect in the third generation (3G) or beyond third generation (B3G) mobile communication. However, the implementation of this unprecedented target is not so easy, and the traditional communication systems using single-antenna transmitting and receiving are confronted with a stiff challenge to achieve this target. The demands of both high capacity and high reliability in the new generation wireless communication systems are not enough to be met even though one of the traditional improved measures, such as the traditional transmit diversity, receive diversity and smart antenna technology, is used. In the next generation of wireless communication, the application of MIMO technologies increases the system capacity linearly with the minimum number of transmit and receive antennas. However, many more problems are emerging and urgently wanted to be solved in MIMO communication systems due to introducing the multiple-antenna comparing with the traditional single-antenna systems.This dissertation, sponsored by the project of the Novel types of antennas and diversity technology which is one part of the National High Technology Research and Development Program (863 program), focuses on the MIMO channel modeling and channel estimation for new generation wireless communication systems, It has mainly made further research on the related theories about four main aspects: channel modeling, signal correlation analysis, channel capacity and channel estimation on the basis of other's research work.The major innovations in this dissertation include five, levels.The first part is mainly concerned with a new study method of binary symmetric discrete channel average mutual information. We adopt the Synergetics to study the binary symmetric discrete channel how to allocate input probability in order to maximize average mutual information under memoryless and memory channel with interference.In the second part, we analyze the signal correlation in MIMO channels. Research signal low spatial correlation on the effects of the performance of MIMO channels establishes the solid theoretical basis both for MIMO channel modeling and MIMO antenna designing, and provide important insights into the analyses of capacity and Bit-Error-Ratio (BER) of MIMO channels. First, presents a spatial channel propagation model. Consider a uniform linear antenna (ULA) at the base station (BS) and narrowband signals transmitted at the mobile. In two types of propagating environments: indoor and outdoor, performance of low spatial correlation is investigated. Secondly, The optimum channel capacity for using diversity technique in the Nakagami fading or Weibull fading channels has been derived, based on the optimum capacity of multi-antenna Gaussian channel model. Optimized switch threshold was obtained in the Weibull fading channel by using switch stay combining technology. Thirdly, presents the novel closed-form expressions for the average channel capacity of dual selection diversity, as well as the bit-error rate (BER) of coherent frequency shift keying (CFSK) and non-coherent M-ary frequency shift keying (NMFSK) digital modulation schemes in correlated Weibull fading channels with nonidentical statistics.In the third part, present a new model and its performance prediction for multiple input multiple output (MIMO) indoor wireless fading channels, including the effect of small-scale fading, the relative path loss and shadowing fading.In the four part, A MIMO channel estimation model using superimposed training sequence method is extended in this paper. By exploiting least square method, a closed-form solution for the estimation of variance and Cramer-Rao bound are derived, as well as the lower bound of channel capacity.In the five part, We adopt space time spreading, superimposed training and space-time coding to obtain a closed-form of average error probability upper bound and maximum likelihood estimation expression for correlated frequency-selective multiple input and multiple output (MIMO) channel in the presence of interference.In this dissertation, the explorative studies on MIMO channel modeling and multiple-antenna designing for new generation wireless communication systems show that they are vital to the implementation of the wireless transmission both with high capacity and high reliability.
Keywords/Search Tags:Self-organizing, MIMO channel modeling, channel capacity, antenna diversity, space time spreading (STS), space time coding (STC)
PDF Full Text Request
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