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Joint optimization for downlink resource allocation in cognitive radio cellular networks

机译:认知无线电蜂窝网络中的下行链路资源分配联合优化

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This paper takes into account the uncertainty of the primary users' locations and transmission power in designing an optimal downlink scheduling scheme for cognitive radio cellular networks (CogCells). Localization technique is exploited to estimate the position and transmission power of the primary user (PU) transmitting on specific channel. The objective of our scheduling scheme is to maximize the downlink average throughput for CogCells without causing harmful interference to PUs. This paper models the problem as a mixed integer nonlinear programming (MINLP) problem, which has exponential complexity by traditional direct search method. An efficient joint channel assignment and power control scheme based on dual decomposition method is proposed. Firstly, the dual optimization problem is decomposed into K independent subproblems of channel assignment. Karush-Kuhn-Tucker (KKT) conditions are then applied to find the optimal user for a specific channel. Secondly, ellipsoid method is applied to update the dual variables and find the optimal solution for the primal problem. Numerical results demonstrate the effectiveness of the proposed scheme.
机译:本文考虑了主要用户位置和传输功率在设计认知无线电蜂窝网络(Cogcells)的最佳下行链路调度方案时的不确定性。利用本地化技术来估计在特定信道上发送的主要用户(PU)的位置和传输功率。我们的调度方案的目的是最大化Cogcells的下行链路平均吞吐量,而不会对脓液造成有害干扰。本文将问题模拟为混合整数非线性编程(MINLP)问题,这是通过传统直接搜索方法的指数复杂性。提出了一种基于双分解方法的高效联合通道分配和功率控制方案。首先,双重优化问题被分解为频道分配的K独立子问题。然后应用Karush-Kuhn-Tucker(KKT)条件以查找特定通道的最佳用户。其次,应用椭圆体方法以更新双变量,并找到原始问题的最佳解决方案。数值结果证明了提出方案的有效性。

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