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Cross-Layer Optimization for Congestion and Power Control in OFDM-Based Multi-Hop Cognitive Radio Networks

机译:基于OFDM的多跳认知无线电网络中拥塞和功率控制的跨层优化

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Efficient and fair power allocation associated with congestion control in orthogonal frequency division multiplexing (OFDM)-based multi-hop cognitive radio networks (CRNs) is a challenging and complicated problem. In this paper, we consider their mutual relationship through a cross-layer optimization design that addresses both aggregate utility maximization and energy consumption minimization. By introducing the unique outage constraint of primary user (PU) protection, the joint congestion control and power control (JCPC) formulation is shown to be a nonlinear non-convex optimization problem. Using dual decomposition approach, we first propose a distributed algorithm that can attain the optimal solution via message passing while maintaining the architectural modularity between the layers. Next, we develop a suboptimal algorithm using a new heuristic method to alleviate the overhead burden of the first solution. Finally, the numerical results confirm that the OFDM-based multi-hop CRNs can optimally exploit the spectrum opportunity if the PU outage probability is kept below the target.
机译:与基于正交频分复用(OFDM)的多跳认知无线电网络(CRN)中的拥塞控制相关的高效且公平的功率分配是一个充满挑战且复杂的问题。在本文中,我们通过跨层优化设计考虑了它们之间的相互关系,该设计解决了总效用最大化和能耗最小化的问题。通过引入主要用户(PU)保护的独特中断约束,联合拥塞控制和功率控制(JCPC)公式被证明是非线性非凸优化问题。使用双重分解方法,我们首先提出一种分布式算法,该算法可以通过消息传递获得最佳解决方案,同时保持各层之间的体系结构模块化。接下来,我们使用新的启发式方法开发次优算法,以减轻第一个解决方案的开销负担。最后,数值结果证实,如果将PU中断概率保持在目标以下,则基于OFDM的多跳CRN可以最佳地利用频谱机会。

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