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A Full-Space Spectrum-Sharing Strategy for Massive MIMO Cognitive Radio Systems

机译:大规模MIMO认知无线电系统的全空间频谱共享策略

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In this paper, we introduce a new spatial spectrum-sharing strategy for massive multiple-input multiple-output (MIMO) cognitive radio (CR) systems. Different from the conventional MIMO CR system, CR terminals can be discriminated by their angular information with the help of high spatial resolution of massive antennas at CR base station (CBS). Moreover, the discrete Fourier transform can be applied to efficiently obtain such angular information thanks to the massive antennas, again. We then formulate a 2-D spatial basis expansion model to represent the uplink/downlink channels of CRs with reduced parameter dimensions, which immediately alleviates the general headaches of massive MIMO systems, such as uplink pilot contamination and downlink training overhead. Moreover, we present a full-space coverage concept by employing two CBSs at the adjacent sides of each cell, which diminishes the sheltering effect from the primary radio. We also design two greedy CR scheduling algorithms for the dual CBSs to improve the spectral efficiency and enhance the scheduling probability of CRs. Since the proposed strategy exploits angular information and since the angle reciprocity holds for two frequency carriers with moderate distance, the proposed strategy is applied for both time division duplex and frequency division duplex systems.
机译:在本文中,我们为大规模多输入多输出(MIMO)认知无线电(CR)系统引入了一种新的空间频谱共享策略。与传统的MIMO CR系统不同,CR终端可以借助CR基站(CBS)上大型天线的高空间分辨率,通过角度信息来区分它们。而且,由于有大量天线,离散傅里叶变换可以被应用以有效地获得这种角度信息。然后,我们制定一个二维空间基础扩展模型来表示具有减小的参数尺寸的CR的上行/下行信道,这立即减轻了大规模MIMO系统的普遍麻烦,例如上行链路导频污染和下行链路训练开销。此外,我们通过在每个小区的相邻侧采用两个CBS来呈现全空间覆盖的概念,从而减少了主无线电的遮挡效果。我们还为双CBS设计了两种贪婪的CR调度算法,以提高频谱效率并提高CR的调度概率。由于所提出的策略利用角度信息,并且由于角度互易性适用于具有中等距离的两个频率载波,因此所提出的策略适用于时分双工和频分双工系统。

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