Near optimal multipoint receive beamforming with finite samples

Receive beamfoming techniques play an important role in MIMO communications systems as means to mitigate interference and enhance the link quality. Multipoint receive beamforming methods are expected to provide additional gains in systems employing advanced coordinated multipoint processing. Due to its importance, receive beamforming has been studied extensively in the literature. The optimal detection schemes are well known in the case of perfect channel knowledge at the receiver. The more realistic case, where the beamformer is constructed using a finite training sequence transmitted by the desired transmitter has also been addressed. The study of the latter case, known as finite sample beamforming, focused on linear detection. In this paper we propose new nonlinear finite sample detection schemes for the case of multiple spatial streams. We show that the proposed schemes significantly outperform the known linear detectors and exhibit near optimal performance. We also show that the complexity of the proposed schemes is very similar to that of standard multi stream MIMO detectors, which makes them ideal for real life systems. We apply the new schemes to uplink space division multiple access and demonstrate the implementation and respective performance gains over standard detectors. Finally, we apply our approach to the case of coordinated multipoint reception where multiple base stations jointly decode multiple spatial streams. We study the tradeoff between performance and backhaul capacity and suggest near optimal finite sample schemes.