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An online algorithm of energy-efficient and interference suppression beamforming for cognitive MISO-OFDM interference channels

机译:认知MISO-OFDM干扰信道的高效节能和干扰抑制波束形成在线算法

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Minimization of the sum power of secondary users (SUs) equipped with multi-antenna is considered in the context of OFDM cognitive radio (CR) networks with coexisting primary users (PUs). The aggregated interference generated by SUs is constrained under a tolerable level so as to maintain reliable communication for PUs. Meanwhile, the quality of service (QoS) in terms of sum rate for SUs should be guaranteed as well. Sufficient conditions for the feasibility of this problem are provided for the facilitation of admission control. A novel on-line implementation algorithm is developed based on network duality and geometric programs (GPs) power control. This algorithm is proved to be convergent and the converged solution is locally optimal. Simulations results show that this algorithm is converged within several iterations and significant power savings can be achieved by the proposed algorithm compared with other relevant schemes.
机译:在具有共存主要用户(PU)的OFDM认知无线电(CR)网络的背景下,考虑了配备多天线的辅助用户(SU)的总功率的最小化。 SU产生的聚集干扰被限制在可容忍的水平上,以便维持PU的可靠通信。同时,还应保证SU的总速率方面的服务质量(QoS)。提供了该问题的可行性的充分条件,以促进准入控制。基于网络对偶和几何程序(GPs)功率控制,开发了一种新颖的在线实现算法。证明该算法是收敛的,并且收敛解是局部最优的。仿真结果表明,该算法在多次迭代中收敛,与其他相关方案相比,该算法可以节省大量功率。

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