Robust ML Detection Algorithm for MIMO Receivers in Presence of Channel Estimation Error

Capacity of wireless communication systems can be increased enormously using arrays of antenna at transmitter and receiver. However, in these so called multi-input multi-output (MIMO) communication systems, the performance of the signal detection is tightly related to the channel knowledge at the receiver side. Practically, the channel information at the receiver is subject to error because of the outdated data, quantization error, and imperfect channel estimation/measurement. It is known that in the case of imperfect channel knowledge, performance of symbol detection in MIMO communications may severely degrades. The optimum detection method in the sense of symbol error rate in MIMO systems is the maximum likelihood (ME) detection. In this paper, we proposed and studied a couple of robust detection methods that improve the performance of ME detector in MIMO systems in the presence of channel matrix error at the receiver