Optimal and sub-optimal iterative cross-layer energy efficient schemes for CR MIMO systems with antenna selection

E. M. Okumu, M. Dlodlo
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引用次数: 3

Abstract

In this paper, energy efficient transmit antenna selection in underlay cognitive radio (CR) multiple-input multiple-output (MIMO) systems from a cross layer perspective, is investigated. Conventional energy efficient antenna selection optimizes an energy efficiency (EE) metric defined in terms of the system capacity and energy consumption, making it a physical layer criterion. In this work, we propose an EE metric that is defined in terms of the system throughput and energy consumption. Throughput considers characteristics from the data link and physical layers, making the proposed EE metric a cross layer quantity. The subset of transmit antennas that maximizes the proposed EE criterion, subject to interference constraints at the primary user receiver (PU RX), is selected. Additionally, the proposed algorithm optimizes the EE by adapting the number of active transmit antennas and transmit power, under a spectral efficiency constraint. A sub-optimal reduced complexity iterative algorithm is also developed. Simulation results show that the cross layer approach results in overall improved system performance, measured in terms of throughput, packet error rate and transmit power, as compared to conventional energy efficient antenna selection.
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带天线选择的CR MIMO系统的最优和次最优迭代跨层节能方案
本文从跨层的角度研究了底层认知无线电(CR)多输入多输出(MIMO)系统中节能发射天线的选择问题。传统的节能天线选择优化了根据系统容量和能耗定义的能效(EE)指标,使其成为物理层标准。在这项工作中,我们提出了一个根据系统吞吐量和能耗定义的EE度量。吞吐量考虑了数据链路和物理层的特征,使提议的EE度量成为跨层数量。在受主用户接收机(PU RX)干扰约束的情况下,选择使所提出的EE标准最大化的发射天线子集。此外,该算法在频谱效率约束下,通过调整有源发射天线数和发射功率来优化EE。提出了一种次优降复杂度迭代算法。仿真结果表明,与传统的节能天线选择相比,跨层方法在吞吐量、分组错误率和发射功率方面总体上提高了系统性能。
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