A new beamforming design based on random matrix theory for weighted sum-rate maximization in interference channels

In this paper, we propose a new distributed approach for designing the beamforming vectors based on virtual signal-to-interference-plus-noise ratio (VSINR) for weighted sum-rate (WSR) maximization in multiple-input single-output interference channels. Recently, it was shown that by adaptively adjusting parameters which control the leakage interference according to channel realizations and the signal-to-noise ratio (SNR) level, the WSR performance can be improved compared to conventional methods with fixed parameters. However, due to an iterative procedure for each channel realization, this approach requires high computational complexity. To overcome this problem, by utilizing asymptotic results from random matrix theory, we propose a new low-complexity beamforming scheme with constant parameters which depend only on the channel statistics and SNR. Numerical results confirm that the proposed scheme provides the near-optimal WSR performance with much reduced system complexity.