Channel modeling, estimation and equalization in wireless communication

Abstract

Channel modeling, estimation and equalization are discussed throughout this dissertation. Relevant research topics are first studied at the beginning of each chapter and the new methods are proposed to improve the system performance. MLSE is an optimum equalizer for all the case. However, due to its computational complexity, it is impractical for today technologies in third generation wireless communication. Thus, a suboptimum equalizer so-called perturbation equalizer is proposed, which outperforms the RSSE equalizer in the sense of bit error rate or computational complexity. In order to improve the system performance dramatically, the iterative equalization algorithm is implemented. It has been shown that the turbo equalization using the trellis based Maximum A Posteriori equalizer is a powerful receiver that yielding the optimum system performance. Unfortunately, due to its exhausted computational complexity, a suboptimal equalizer is required. An improved DFE algorithm, which only requires low computational complexity, is proposed for turbo equalization. The promising simulation results indicate that the proposed equalizer provides significant improvement in bit error rate while compared to the conventional DFE algorithm. Prior to channel equalization, channel estimation enable us to extract the necessary channel information from the pilot symbols for equalizers. Least-squares algorithm is a promising estimation algorithm providing the channel is time-invariant in a given period. Based on the derivations, we show that the channel is no longer constant and a new least-squares based algorithm is proposed to estimate the channel accurately. Simulation results convince us that the new algorithm provides the equalizer more reliable information. Besides, antenna diversity is another promising technique implemented practically to improve the system performance provided that the channels of antennas are not correlated. A new three dimensional multiple-input multiple-output abstract model is proposed for the investigation and understanding of the correlation of fading channel. The new model allows us to consider the channel correlation of which the mobile stations receive the incoming waves from any directions and angle spreads. Based on this abstract model, the closed form and mathematical tractable formula is derived for space-time correlation function. The new function can be further simplified other known special cases.