Opportunistic distributed beamforming in cognitive radio networks with limited feedback

While a cognitive radio network sharing the spectrum with a primary network, one of the major concerns is that harmful interference to the primary users should be avoided. In this paper, we propose three low-complexity algorithms for distributed beamforming in cognitive radio networks which opportunistically select a subset of cognitive source nodes whose phases may be compensated, so that the received signals in cognitive destination can combine in a quasi-coherent manner and the interference to the primary users is not destructive. Only a few bits feedback from cognitive destination is required per cognitive source node. Simulation results demonstrate the good performance of the proposed algorithms.