We consider robust receiver design in uncoded multiple-input multiple-output (MIMO) wireless communication systems. In practical systems, the channel state information (CSI) available at the receiver is often imperfect due to measurement errors, quantization errors and many other sources of errors. Consequently, using the erroneous CSI for decoding the transmitted symbols will significantly degrade the symbol error rate (SER) performance of any decoding schemes. In this paper, we formulate and implement a decoder for MIMO systems with imperfect CSI. The proposed decoder is the maximum likelihood (ML) decoder under imperfect receiver CSI, which is the optimal decoder. This "robust" decoder has exponential complexity; with the goal of reducing its complexity, we propose a recursive search algorithm which is akin to a modified form of sphere decoding. We verify, via numerical simulation, that the recursive search algorithm (termed as robust sphere decoder) achieves performance almost the same as the ML solution, with significantly lower computational complexity.
['Boon Sim Thian', 'Andrea J. Goldsmith']
Decoding for MIMO Systems with Imperfect Channel State Information