Reduced-rank space-time signature and receiver adaptation

Interference in code-division multiple access (CDMA) or multi-antenna systems can be avoided by choosing a signature (in space and/or time), which lies in the direction of least interference plus noise. If the interference statistics are not known, then the signature can be estimated with a training sequence. We propose an iterative scheme for joint signature-receiver adaptation with an adaptive reduced-rank Multi-Stage Wiener Filter (MSWF) at the receiver, which can reduce the estimation error due to limited training. We establish convergence of the iterative signature-receiver optimization scheme, and show that the performance for the reduced-rank receiver with rank D ≥ 2 is the same as that obtained with a full-rank receiver. Numerical results show that when the receiver and signature are estimated from a short training sequence, the adaptive reduced-rank receiver gives substantially better performance than an adaptive full-rank receiver. To reduce feedback requirements, we also consider joint signature-receiver adaptation with a reduced-rank signature, which is confined to a randomly chosen subspace. Numerical results are presented, which show that joint reduced-rank signature-receiver estimation can achieve near-optimal performance with relative little training and low complexity.