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Power and Time Slot Allocation in Cognitive Relay Networks Using Particle Swarm Optimization

机译:基于粒子群算法的认知中继网络功率和时隙分配

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摘要

The two main problems in cognitive radio networks are power and time slot allocation problems which require a precise analysis and guarantee the quality of service in both the primary and secondary users. In this paper, these two problems are considered and a method is proposed to solve the resulting optimization problem. Our proposed method provides an improved performance in solving the constrained nonlinear multiobject optimization for the power control and beamforming in order to reach the maximum capacity and proper adaption of time slots, and as a result a new scheme for joint power and time slot allocation in cognitive relay networks is proposed. We adopt space diversity access as the secondary users access scheme and divide the time between multiple secondary users according to their contribution to primary user's transmission. Helping primary users provides more opportunities for secondary users to access the channel since the primary users can release the channel sooner. In contrast, primary network leases portion of channel access time to the secondary users for their transmission using particle swarm optimization (PSO). Numerical studies show good performance of the proposed scheme with a dynamic cost function in a nonstationary environment.
机译:认知无线电网络中的两个主要问题是功率和时隙分配问题,这需要精确的分析并保证主要和次要用户的服务质量。本文考虑了这两个问题,并提出了一种解决最终优化问题的方法。我们提出的方法在解决功率控制和波束成形的约束非线性多目标优化问题上提供了改进的性能,以达到最大容量和时隙的适当适应,结果是在认知中联合了功率和时隙分配的新方案提出了中继网络。我们采用空间分集访问作为次要用户访问方案,并根据多个次要用户对主要用户传输的贡献来划分时间。因为主要用户可以更快地释放频道,所以帮助主要用户为次要用户提供了更多访问频道的机会。相反,主要网络使用粒子群优化(PSO)将部分信道访问时间租给次要用户进行传输。数值研究表明,该算法在非平稳环境下具有动态成本函数,具有良好的性能。

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