Integrating Cognitive Radio MIMO UAVs in Cellular Networks for 5G and Beyond

Lokman Sboui, Hakim Ghazzai, Y. Massoud
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Abstract

In this paper, we study the performance of deploying multiple unlicensed unmanned aerial vehicles (UAV s) to share the spectrum and the base station of an established primary network in Multiple-Input-Multiple-Output (MIMO) communications. We present a novel power allocation scheme based on a combination of underlay cognitive radio with channel precoding and decoding to maximize the UAVs sum-rate. In the proposed scheme, we jointly use space alignment and successive interference cancellation techniques to minimize and avoid the interference caused on the primary communication. Optimal power allocation scheme for the proposed system is devised. In our simulations, we show that the proposed scheme allows the UAV s to achieve a rate that highly depends on the primary power and interference threshold. In addition, a supplementary rate is achieved when the UAVs transmit in the unused parallel channels called free eigenmodes. The impact of the different system parameters including the number of antennas and the 3D position of the UAVs are also evaluated.
在5G及以后的蜂窝网络中集成认知无线电MIMO无人机
本文研究了在多输入多输出(MIMO)通信中部署多架无证无人机(UAV)共享已建立主网络的频谱和基站的性能。提出了一种基于底层认知无线电与信道预编码和解码相结合的功率分配方案,以最大限度地提高无人机的和速率。在该方案中,我们联合使用空间对准和逐次干扰抵消技术来减少和避免对主通信造成的干扰。设计了该系统的最优功率分配方案。在我们的仿真中,我们表明所提出的方案允许无人机实现高度依赖于主功率和干扰阈值的速率。此外,当无人机在未使用的并行信道(称为自由特征模式)中传输时,可以实现补充速率。分析了不同系统参数(包括天线数量和无人机的三维位置)对系统性能的影响。
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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