A computationally efficient node-selection scheme for cooperative beamforming in Cognitive Radio enabled 5G systems

Cooperative transmit beamforming (CTB) is a practical approach for addressing the challenging problem of spectrum scarcity in broadband 5G wireless communication systems. It is a technique that allows a group of secondary users (SUs), each equipped with a single omni-directional antenna, to collaborate and steer the signal towards the intended receiver. CTB allows SUs to co-exist with primary users in the same spectrum, which helps to significantly improve the efficiency of spectrum utilization. One of the key factors that affect the performance of CTB is the selection of participatory nodes. In this paper, we first formulate the CTB as an optimization problem, and then investigate the impact of different node-selection schemes on the performance of CTB. Our findings illustrate that exhaustive search based optimal node-selection scheme is computationally infeasible for real-time systems, while simple random-selection and highest-channel-state based selection often result in poor performance. Motivated by these findings, we propose a computationally efficient node-selection scheme for CTB that achieves a near-optimal performance. The proposed scheme is based on iterative node-replacement and is computationally scalable to large system size. Results from extensive simulations show that the proposed scheme asymptotically approaches the exhaustive search based optimal system performance. In our example, the performance of the proposed scheme is approximately 98.5% of the optimal system performance while limiting the required computations to only 1.67%.