Reduction of Implementation Complexity in MIMO-OFDM Decoding for V-BLAST Architecture
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This dissertation documents alternative designs of the Zero Forcing decoding algorithm with Successive Interference Cancellation (ZF-SIC) for use in Vertical Bell Laboratories Layered Space Time Architecture (V-BLAST) Multiple Input Multiple Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) systems, in an effort to reduce the computational complexity of the receiver. The development of a wireless platform utilizing this architecture intended for use in an indoor wireless multipath environment was created to analyze the multipath environment. This implementation is the result of efforts from several individuals within the CST group. My contributions are documented in this dissertation. In order to obtain channel state information (CSI), a training sequence is sent with each incoming frame. A pseudo-inverse operation is performed on the channel matrix and applied to each OFDM symbol that was received. Performing this operation on each tone and across each OFDM symbol is computationally inefficient in a MIMO configuration. If the number of pseudo-inverses can be reduced while maintaining acceptable levels of bit error, the processing time of each frame can be decreased. Traditionally, tests of the performance of ZF-SIC have been conducted with simulations modelling a multipath channel. In this thesis, CSI is observed using an open loop platform developed for MIMO-OFDM communications. The rate of change of the channel is observed for different multipath environments. The proposed methods of decoding require modifications to ZF-SIC. The suggested changes are only applicable to a MIMO OFDM based method of data transmission. The most effective method of reducing decoding complexity and maintaining an acceptable number of bit errors was observed to occur in the time domain rather than in the frequency domain. For selecting frames and averaging frames in the time domain it was determined that the optimal number of OFDM symbols per frame is 1932 and 174, respectively.