SPHERE DECODING FOR MIMO-OFDM

Abstract

Multiple-input Multiple-Output (MIMO) transmission has become a popular technique to increase spectral efficiency. The increase in spectral efficiency offered by MIMO systems is based on the utilization of space diversity at both the transmitter and the receiver. With MIMO transmission scheme, there is a linear increase in spectral efficiency compared to a logarithmic in more traditional systems utilizing no diversity. The wideband wireless communication channels are frequency selective. OFDM is an attractive modulation scheme for broadband wireless systems which encounter large delay spread (frequency selective channels). OFDM converts a frequency-selective channel into a parallel collection of frequency flat sub-channels, Hence OFDM increases robustness against frequency selective fading and narrowband interference. Further, the combination MIMO and OFDM . i.e. MIMO-OFDM has recently generated significant research interest for high data rate wireless communication systems. In this work different detection schemes such as Zero forcing detection (ZF), Minimum mean-square error (MMSE) detection, Successive interference cancellation (SIC) and Maximum likelihood (ML) detection are considered for the detection of transmitted signal in MIMO environment. ZF detector is simplest but the drawback of the ZF detector is that perfect separation of the transmitted data streams entails an enhancement of the additive noise. The objective in MMSE detection is to minimize the expected mean-square error between the receiver's estimate and the transmitted symbol, but it results in residual interference. In SIC a nonlinear interference cancellation stage partially exploits the knowledge that the entries of the transmitted vector s have been chosen from a finite set of constellation points but it can suffer from error-propagation. ML detector is the optimal detector in terms of bit error rate performance. In this thesis work, the implementation of different detection schemes and their BER performance evaluation for MJMO and MIMO-OFDM systems are given. The design of cost effective receivers for MIMO channels remains a challenging task. Maximum-Likelihood (ML) detector can achieve optimum performance, yet the computational complexity is enormously high. Receivers based on sphere decoding (SD) approach the performance of the ideal ML detector and offer the potential to save a great deal of computational cost. In sphere detection, the search for the most probable transmitted signal vector is limited to a set of points that lie within a hyper sphere of fixed radius centred on the received signal vector. We consider next in this dissertation, implementation of SD, SE and Zero forcing algorithm and their bit error rate performance comparison for MIMO and MIMO-OFDM systems.