Performance of Cellular-Connected UAV in Cell-Free Radio Access Network With Network-Assisted Full-Duplex

被引:2
作者
Wan, Ziqian [1 ]
Li, Jiamin [1 ,2 ]
Zhu, Pengcheng [1 ]
Wang, Dongming [1 ,2 ]
Zhang, Hongbiao [3 ]
Liu, Feiyang [4 ]
You, Xiaohu [1 ,2 ]
机构
[1] Southeast Univ, Natl Mobile Commun Res Lab, Nanjing 210096, Peoples R China
[2] Purple Mt Labs, Nanjing 211111, Peoples R China
[3] China Mobile Res Inst, Beijing 100033, Peoples R China
[4] Elect Technol Grp Corp, Res Inst 54th, Shijiazhuang 050081, Peoples R China
基金
中国国家自然科学基金;
关键词
Network-assisted full-duplex; cell-free RAN; cellular-connected UAV; multi-objective optimization; deep Q-network; FREE MASSIVE MIMO; SPECTRAL EFFICIENCY ANALYSIS; POWER-CONTROL; SYSTEMS;
D O I
10.1109/TWC.2024.3419850
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Cellular-connected unmanned aerial vehicles (UAVs) is considered as integral components for sixth generation (6G) cellular networks. Cell-free radio access network (CF-RAN) with network-assisted fullduplex (NAFD) possesses global collaborative capabilities and enable uplink and downlink transmission simultaneously, which can be considered as a potential technology for supporting air-ground communication. In this paper, we investigate the performance of cellular-connected UAV in CF-RAN with NAFD. We propose a modified beamforming training scheme to mitigate cross-link interference (CLI) and a location-aware access point (AP) clustering strategy to reduce fronthaul overhead. We derive closed-form expressions for uplink and downlink achievable rates of GUEs and UAVs, respectively. Based on these expressions, we propose an efficient global spectral efficiency optimization scheme by solving a multi-objective optimization problem (MOOP) aiming to maximize the uplink sum rates and downlink sum rates simultaneously with deep Q-network (DQN). Numerical results verify the accuracy of the derived closed-form expressions. The effectiveness of the modified beamforming training scheme and location-aware AP clustering strategy are proved. In addition, the impact of system parameters and the advantages of NAFD system are analyzed. We also illustrate the convergence and benefits of DQN-based optimization scheme on different type of users.
引用
收藏
页码:14848 / 14863
页数:16
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