Random beamforming in correlated MISO channels for multiuser systems

We examine the technique of random beamforming to exploit multiuser diversity in the downlink of a wireless cellular communication system with an antenna array at the basestation. In random beamforming systems, the scalar signal is multiplied by a weight vector and the resulting signal vector is transmitted by the antenna array. By varying the weight vector in time, one can increase the dynamic of the effective channel resulting in faster fading and a larger variance of the effective channel. This can be exploited by a scheduler at the basestation which selects users for transmission that momentarily have a good channel. Our work focusses on the generation of the weight vectors for a uniform linear array in the basestation. We especially consider correlation between the antenna elements, but assume that the correlation matrices for the different users are not known to the basestation. Three random beamforming approaches are compared with the simplest possible case of using equal weights, where the weight vector is a constant which serves only to normalize the radiated power. We derive the mean of the received power for the different beamforming techniques and confirm our results by Monte Carlo simulations, where we evaluate the mean power of the actually scheduled user, if a proportional fair scheduling algorithm is used. One important result is the good performance of the rotating beam approach even in a not fully correlated environment.