Detection for MIMO systems with imprecise channel knowledge

We investigate signal detection for MIMO systems with imprecise channel knowledge. The optimal detector is one which best matches the "total" observation matrix and a "total" signal matrix which has a finite alphabet constraint and a Sylvester structure constraint. An iterative local optimization with interference cancellation (LOIC) algorithm is proposed to achieve low complexity and exploit the finite alphabet constraint. Simulation results show that our proposed algorithms can detect signals with BER close to the case of perfect channel knowledge, if a rough channel estimate is available initially.