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Convex optimization-based beamforming in cognitive radio multicast transmission

机译:认知无线电多播传输中基于凸优化的波束成形

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A novel algorithm for transmit beamforming to single cochannel multicast group is presented in this paper. We consider the max-min fairness (MMF) based beamforming problem where the maximization of the smallest receiver signal-to-noise ratio (SNR) over the secondary users subject to constraints on the transmit power and interference caused to the primary users. It is shown that this problem, which is nonconvex NP-hard, can be approximated by a convex second-order cone programming (SOCP) problem. Then, an iterative algorithm which successively improves the SOCP approximation is presented. Simulation results show the superior performance of the proposed approach, together with a reduced computational complexity, as compared to the state-of-the-art approach.
机译:提出了一种向单个同信道组播组发送波束成形的新算法。我们考虑基于最大-最小公平性(MMF)的波束成形问题,其中,次要用户上最小接收器信噪比(SNR)的最大值受到发射功率和对主要用户造成的干扰的限制。结果表明,非凸NP困难的问题可以通过凸二阶锥规划(SOCP)问题来近似。然后,提出了一种迭代算法,该算法不断提高了SOCP逼近度。仿真结果表明,与最新方法相比,该方法具有优越的性能,并降低了计算复杂度。

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