论文标题
低海拔3-D覆盖范围性能分析，无单元的分布式协作大规模MIMO系统
Low Altitude 3-D Coverage Performance Analysis in Cell-Free Distributed Collaborative Massive MIMO Systems
论文作者
论文摘要
To improve the poor performance of distributed operation and non-scalability of centralized operation in traditional cell-free massive MIMO, we propose a cell-free distributed collaborative (CFDC) massive multiple-input multiple-output (MIMO) system based on a novel two-layer model to take advantages of the distributed cloud-edge-end collaborative architecture in beyond 5G (B5G) internet of things (IoT) environment to provide strong flexibility and scalability.我们进一步使用拟议的CFDC大规模MIMO系统来支持低海拔的三维（3-D）覆盖范围，并使用无人机（UAVS）（无人机），同时考虑3-D RICIAN渠道估计，用户中心的关联协会和不同的可扩展接收方案。由于共存的无人机和地面用户（GUE）会引起更大的干扰，因此我们使用以用户为中心的关联策略和最小均值平方错误（MMSE）渠道状态信息（CSI）估计，以获得无人机和GUE的估计CSI。在CFDC方案下，可扩展接收方案作为最大比率梳理（MRC），部分零型（P-ZF）和部分最小值均值误差（P-MMSE）可以在边缘服务器上进行，并为上链接频谱效率（SE）进行封闭形式的表达式。基于派生的表达式，我们通过在最大化无人机的平均SE和GU与深Q-NETWORK（DQN）同时提出多目标优化问题（MOOP）来提出有效的功率控制算法。数值结果验证了CFDC大型MIMO系统中衍生的封闭形式表达式的准确性以及共存无人机和GUES传输方案的有效性。各种系统参数下的SE分析为系统优化提供了许多灵活性。
To improve the poor performance of distributed operation and non-scalability of centralized operation in traditional cell-free massive MIMO, we propose a cell-free distributed collaborative (CFDC) massive multiple-input multiple-output (MIMO) system based on a novel two-layer model to take advantages of the distributed cloud-edge-end collaborative architecture in beyond 5G (B5G) internet of things (IoT) environment to provide strong flexibility and scalability. We further ultilize the proposed CFDC massive MIMO system to support the low altitude three-dimensional (3-D) coverage scenario with unmanned aerial vehicles (UAVs), while accounting for 3-D Rician channel estimation, user-centric association and different scalable receiving schemes. Since coexisted UAVs and ground users (GUEs) cause greater interference, we ultilize user-centric association strategy and minimum-mean-square error (MMSE) channel state information (CSI) estimation to obtain the estimated CSI of UAVs and GUEs. Under the CFDC scenarios, scalable receiving schemes as maximum ratio combing (MRC), partial zero-forcing (P-ZF) and partial minimum-mean-square error (P-MMSE) can be performed at edge servers and the closed-form expressions for uplink spectral efficiency (SE) are derived. Based on the derived expressions, we propose an efficient power control algorithm by solving a multi-objective optimization problem (MOOP) between maximizing the average SE of UAVs and GUEs simultaneously with Deep Q-Network (DQN). Numerical results verify the accuracy of the derived closed-form expressions and the effectiveness of the coexisted UAVs and GUEs transmission scheme in CFDC massive MIMO systems. The SE analysis under various system parameters offers numerous flexibilities for system optimization.
