Abstract
The authors present a maximum likelihood (ML) detector for multiple-input multiple-output (MIMO) wireless communication systems. The ML detector has been specifically designed to reduce the implementation complexity without significant degradation in bit error rate (BER) performance. In order to identify the optimized fixed-point representation, the ML detector has been simulated with various representations for the received data. The computation process of the channel matrix and constellation symbols in ML detector is simplified by using normalized symbols. Simulation results are provided showing 42% saving in area usage and 68% saving in power consumption compared to a conventional architecture.
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