Author: Yihai Zhang

Publisher:

Published: 2011

Total Pages:

ISBN-13:

With the increasing demand for more wireless multimedia applications, it is desired to design a wireless system with higher data rate. Furthermore, the frequency spectrum has becomea limited and valuable resource, making it necessary to utilize the available spectrum efficiently and coexist with other wireless systems. Orthogonal frequency division multiplexing (OFDM)modulation is widely used in communication systems to meet the demand for ever increasing data rates. The major advantage of OFDM over single-carrier transmission is its ability to deal with severe channel conditions without complex equalization. However, OFDM systems suffer from a high peak to average power ratio, and they are sensitive to carrier frequency offset and Doppler spread. This dissertation first focuses on the development of intercarrier interference (ICI) reduction and signal detection algorithms for OFDM systems over time-varying channels. Several ICI reduction algorithms are proposed for OFDM systems over doubly-selective channels. The OFDM ICI reduction problem over time-varying channels is formulated as a combinatorial optimization problem based on the maximum likelihood (ML)criterion. First, two relaxation methods are utilized to convert the ICI reduction problem into convex quadratic programming (QP) problems. Next, a low complexity ICI reduction algorithm applicable to $M$-QAM signal constellations for OFDM systems is proposed. This formulates the ICI reduction problem as a QP problem with non-convex constraints. A successive method is then utilized to deduce a sequence ofreduced-size QP problems. For the proposed algorithms, the QPproblems are solved by limiting the search in the 2-dimensional subspace spanned by its steepest-descent and Newton directions to reduce the computational complexity. Furthermore, a low-bit descent search (LBDS) is employed to improve the system performance. Performance results are given to demonstrate that the proposed ICI reduction algorithms provide excellent performance with reasonable computational complexity. A low complexity joint semiblind detection algorithm based on the channel correlation and noisevariance is proposed which does not require channel state information. The detection problem is relaxed to a continuous non-convex quadratic programming problem. Then an iterative method is utilized to deduce a sequence of reduced-size quadratic programming problems. A LBDS method is also employed to improve the solution of the derived QP problems. Results are given which demonstrate that the proposed algorithm provides similar performance with lower computational complexity compared to that of a sphere decoder. A major challenge to OFDM systems is how to obtain accurate channel state information for coherent detection of the transmitted signals. Thus several channel estimation algorithms are proposed for OFDM systems over time-invariant channels. A channel estimation method is developed to utilize the noncircularity of the input signals to obtain an estimate of the channel coefficients ...