室内毫米波海量MIMO压缩感知研究(特邀论文)

John Franklin, A. Cooper
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引用次数: 1

摘要

在稀疏信道假设下,无需对每个天线采样即可有效估计海量MIMO上行链路的信道状态信息。假设有一个缓慢的平坦衰落多径信道、正交导频信号和均匀的矩形阵列,通过利用空间和导频码域的稀疏性来重建到所有天线的信道来进行信道估计。给出了在上行导频阶段对32 × 64元大规模MIMO阵列进行25%采样的结果。使用压缩感知和稀疏恢复信道估计获得的和速率超过了使用最小二乘信道估计获得的和速率。
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Compressive Sensing for Indoor Millimeter Wave Massive MIMO : (Invited Paper)
Under sparse channel assumptions, channel state information for the massive MIMO uplink can be effectively estimated without sampling every antenna. Assuming a slow flat fading multipath channel, orthogonal pilot signals, and a uniform rectangular array, channel estimation is performed by leveraging sparsity in the spatial and pilot code domains to reconstruct the channel to all antennas. Results of sampling from 25 percent of a 32 by 64 element massive MIMO array during the uplink piloting phase are presented. The sum rate achieved by using compressed sensing and sparse recovery channel estimates exceeds that achieved with the least squares channel estimate for the same number of sampled antennas.
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