Air-Ground Collaborative Resource Optimization in UAV Empowered Cell-Free Massive MIMO Systems

Linlin Xu, Qi Zhu, Wenchao Xia, Tony Q.S. Quek, Hongbo Zhu

研究成果: Article同行評審


Cell-free massive multiple-input-multiple-out (CF-mMIMO) systems provide limited coverage because of expensive wired fronthaul between access points (APs) and central processing unit (CPU). To address this challenge, we propose a novel framework where an unmanned aerial vehicle (UAV), acting as an aerial AP, works coherently with the ground APs to expand the coverage of conventional CF-mMIMO system. To fully utilize the spectrum resource, the wireless fronthaul between the CPU and UAV shares the total bandwidth with the radio access networks. Considering limited power supply of the UAV and for the goal of green communications, we formulate a weighted sum power minimization problem to jointly optimize downlink beamforming and fronthaul compression, as well as UAV placement. The formulated problem is a mixed timescale problem, thus we propose a two-timescale optimization framework in which the UAV placement is optimized in each long timescale based on statistical channel state information (CSI), then the downlink beamforming and fronthaul compression are optimized in each short timescale based on instantaneous CSI. Specifically, uplink-downlink duality and semidefinite relaxation (SDR) based alternating optimization techniques are introduced to find solutions to the short timescale issue, while successive convex approximation and SDR methods are invoked to find solutions to the long timescale issue. Finally, simulation results corroborate the performance of the proposed algorithm.

頁(從 - 到)2485-2499
期刊IEEE Transactions on Communications
出版狀態Published - 2024 4月 1

All Science Journal Classification (ASJC) codes

  • 電氣與電子工程


深入研究「Air-Ground Collaborative Resource Optimization in UAV Empowered Cell-Free Massive MIMO Systems」主題。共同形成了獨特的指紋。