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Antenna Selection in RF-Chain-Limited MIMO Interference Networks Under Interference Alignment

机译:干扰对准下射频链受限的MIMO干扰网络中的天线选择

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摘要

In multiple-input multiple-output (MIMO) systems, the deployment of multiple radio-frequency (RF) chains is much more expensive than that of multiple antennas. Antenna selection (AS) is a low-cost low-complexity method to exploit the diversity gain in MIMO systems with sufficient antennas but limited RF chains. Among the AS algorithms, decremental AS has been shown to be near-optimal compared with exhaustive search. In this paper, we study AS in MIMO interference networks applying the interference alignment (IA) scheme. IA aligns and zero-forces the interference via transmitter–receiver beamforming and achieves a maximum degree of freedom. The feasibility and alignment topology of IA is dependent on the active antenna configuration. For users in tightly feasible systems, IA can be resumed after AS by adapting the beamformers locally, and the exact transmission rate can be known. For users in superfeasible systems, we derive the expected rate under IA conditioned on local channel state information (CSI). Adopting the rate or expected rate as selection criterion, we propose the decremental AS algorithms achieving a twofold complexity reduction. Simulation results and complexity analysis show that the algorithms achieve near-optimal performance at low complexity.
机译:在多输入多输出(MIMO)系统中,部署多个射频(RF)链要比部署多个天线贵得多。天线选择(AS)是一种低成本,低复杂度的方法,用于利用天线充足但RF链受限的MIMO系统中的分集增益。在AS算法中,与穷举搜索相比,递减AS已被证明是最佳的。在本文中,我们研究了采用干扰对准(IA)方案的MIMO干扰网络中的AS。 IA通过发射器-接收器波束成形来对干扰进行零位对准并实现最大的自由度。 IA的可行性和对准拓扑取决于有源天线配置。对于严格可行的系统中的用户,可以在AS之后通过局部调整波束形成器来恢复IA,并且可以知道确切的传输速率。对于超可行系统中的用户,我们根据本地信道状态信息(CSI)得出IA下的预期速率。采用速率或期望速率作为选择标准,提出了递减的AS算法,实现了两倍的复杂度降低。仿真结果和复杂度分析表明,该算法在低复杂度下达到了近乎最优的性能。

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