Cross layer optimization for efficient spectrum utilization in cognitive radios

Ali H. Mahdi, M. Kalil, A. Mitschele-Thiel
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引用次数: 4

Abstract

Cognitive Radio (CR) systems are smart systems capable of sensing the surrounding radio environment and adapting their operating parameters for efficient utilization of the available radio spectrum. To reach this goal, different operating parameters across the OSI layers of a device should be optimized such as transmit power, modulation scheme and packet length etc. In this paper, we propose an efficient algorithm for optimizing and adapting CR operating parameters from physical, MAC and network layers for better utilization of radio spectrum. We include Automatic Repeat reQuest (ARQ) inside our proposed algorithm to check the validity of best parameters at the receiver side under specific link state. The proposed algorithm is called ARQ-Adaptive Discrete Particle Swarm Optimization (ARQ-ADPSO). The simulation results show an improvement by ARQ-ADPSO compared to the well-known genetic algorithm.
认知无线电频谱高效利用的跨层优化
认知无线电(CR)系统是一种智能系统,能够感知周围的无线电环境,并调整其运行参数,以有效利用可用的无线电频谱。为了达到这一目标,应该优化设备的OSI层之间的不同操作参数,如传输功率、调制方案和数据包长度等。在本文中,我们提出了一种有效的算法来优化和适应物理层、MAC层和网络层的CR操作参数,以更好地利用无线电频谱。我们将自动重复请求(ARQ)包含在我们提出的算法中,以检查在特定链路状态下接收端最佳参数的有效性。该算法被称为ARQ-Adaptive Discrete Particle Swarm Optimization (ARQ-ADPSO)。仿真结果表明,ARQ-ADPSO算法比传统的遗传算法有很大的改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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