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Max-Min Power Control in Downlink Massive MIMO with Distributed Antenna Arrays
IEEE Transactions on Communications ( IF 7.2 ) Pub Date : 2020-01-01 , DOI: 10.1109/tcomm.2020.3033018
Noman Akbar 1 , Emil Bjornson 2 , Nan Yang 1 , Erik G. Larsson 1
Affiliation  

In this paper, we investigate optimal downlink power allocation in massive multiple-input multiple-output (MIMO) networks with distributed antenna arrays (DAAs) under correlated and uncorrelated channel fading. In DAA massive MIMO, the base station (BS) consists of multiple antenna sub-arrays. Notably, the antenna sub-arrays are deployed in arbitrary locations within a DAA massive MIMO cell. Consequently, the distance-dependent large-scale propagation coefficients are different from a user to these different antenna sub-arrays, which makes power control a challenging problem. We assume that the network operates in time-division duplex mode, where each BS obtains the channel estimates via uplink pilots. Based on the channel estimates, the BSs perform maximum-ratio transmission in the downlink. We then derive a closed-form signal-to-interference-plus-noise ratio (SINR) expression, where the channels are subject to correlated fading. Based on the SINR expression, we propose a networkwide max-min power control algorithm to ensure that each user in the network receives a uniform quality of service. Numerical results demonstrate the performance advantages offered by DAA massive MIMO. For some specific scenarios, DAA massive MIMO can improve the average per-user throughput up to 55%. Furthermore, we demonstrate that channel fading covariance is an important factor in determining the performance of DAA massive MIMO.

中文翻译:

具有分布式天线阵列的下行链路大规模 MIMO 中的最大-最小功率控制

在本文中,我们研究了在相关和不相关信道衰落下具有分布式天线阵列 (DAA) 的大规模多输入多输出 (MIMO) 网络中的最佳下行链路功率分配。在 DAA 大规模 MIMO 中,基站 (BS) 由多个天线子阵列组成。值得注意的是,天线子阵列部署在 DAA 大规模 MIMO 小区内的任意位置。因此,从用户到这些不同天线子阵列的距离相关的大规模传播系数是不同的,这使得功率控制成为一个具有挑战性的问题。我们假设网络在时分双工模式下运行,其中每个 BS 通过上行链路导频获得信道估计。基于信道估计,BS 在下行链路中执行最大比率传输。然后我们推导出封闭形式的信干噪比 (SINR) 表达式,其中信道受到相关衰落的影响。基于SINR表达式,我们提出了全网最大-最小功率控制算法,以确保网络中的每个用户都能获得统一的服务质量。数值结果证明了 DAA 大规模 MIMO 提供的性能优势。对于某些特定场景,DAA 大规模 MIMO 可以将平均每用户吞吐量提高 55%。此外,我们证明了信道衰落协方差是决定 DAA 大规模 MIMO 性能的重要因素。我们提出了全网最大-最小功率控制算法,以确保网络中的每个用户都能获得统一的服务质量。数值结果证明了 DAA 大规模 MIMO 提供的性能优势。对于某些特定场景,DAA 大规模 MIMO 可以将平均每用户吞吐量提高 55%。此外,我们证明了信道衰落协方差是决定 DAA 大规模 MIMO 性能的重要因素。我们提出了全网最大-最小功率控制算法,以确保网络中的每个用户都能获得统一的服务质量。数值结果证明了 DAA 大规模 MIMO 提供的性能优势。对于某些特定场景,DAA 大规模 MIMO 可以将平均每用户吞吐量提高 55%。此外,我们证明了信道衰落协方差是决定 DAA 大规模 MIMO 性能的重要因素。
更新日期:2020-01-01
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