Efficient Scalar Quantization for MIMO Spatial Multiplexing Receivers

The maximum likelihood detection of multiple input multiple output (MIMO) spatial multiplexing systems is strongly limited by its complexity. We propose that a quantized version of this problem permits the multiplications involved in the numerous calculations of Euclidean distances to be replaced by the use of a small look-up table storing all the exact possible distance components in each dimension of the quantized receive space. The number of pre-stored elements is as small as the number of quantization levels per dimension. This paper presents an approximate analysis of the quantization error which allows us to understand the results from simulations performed over fast flat fading channels for different MIMO systems.