Training sequence design for robust joint detection and channel estimation over rank-deficient MIMO links

In this paper, we present a study of optimal training sequences for robust joint channel estimation and signal detection. Particularly, we study the case of virtual MIMO links, where there are more co-channel signals M than receive antennas N, i.e., N <;M. A training sequence based on the one-dimensional chaotic Chebyshev map is presented herein. This sequence delivers robust performance in terms of Bit Error rate (BER), Normalized Mean-Squared-Error (NMSE) of the estimation and computation complexity. The proposed sequence exhibits an optimal performance by spanning only a minimal number of training symbols, i.e., L=M. The proposed chaotic-based training sequence performs adequatly on both i.i.d. and correlated Rayleigh Fading Channels without the need for a priori statistics of the channel.