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Joint Subchannel Pairing and Power Control for Cognitive Radio Networks with Amplify-and-Forward Relaying

机译:具有放大和前进中继的认知无线电网络的联合子信道配对和功率控制

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Dynamic spectrum sharing has drawn intensive attention in cognitive radio networks. The secondary users are allowed to use the available spectrum to transmit data if the interference to the primary users is maintained at a low level. Cooperative transmission for secondary users can reduce the transmission power and thus improve the performance further. We study the joint subchannel pairing and power allocation problem in relay-based cognitive radio networks. The objective is to maximize the sum rate of the secondary user that is helped by an amplify-and-forward relay. The individual power constraints at the source and the relay, the subchannel pairing constraints, and the interference power constraints are considered. The problem under consideration is formulated as a mixed integer programming problem. By the dual decomposition method, a joint optimal subchannel pairing and power allocation algorithm is proposed. To reduce the computational complexity, two suboptimal algorithms are developed. Simulations have been conducted to verify the performance of the proposed algorithms in terms of sum rate and average running time under different conditions.
机译:动态频谱共享在认知无线电网络中绘制了密集的关注。如果对主用户的干扰保持在低电平,则允许辅助用户使用可用频谱来传输数据。辅助用户的合作传输可以降低传输功率,从而进一步提高性能。我们研究了基于继电器的认知无线电网络的联合子信道配对和功率分配问题。目标是最大化由扩增和前进继电器帮助的辅助用户的总和率。考虑来自源和继电器的各个功率约束,子信道配对约束和干扰功率约束。正在考虑的问题被制定为混合整数编程问题。通过双分解方法,提出了一种联合最优子信道配对和功率分配算法。为了降低计算复杂性,开发了两个次优算法。已经进行了模拟以验证所提出的算法在不同条件下的总和率和平均运行时间方面的性能。

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