TY - JOUR
T1 - Inter-Cell Interference Mitigation for Cellular-Connected UAVs Using MOSDS-DQN
AU - Burhanuddin, Liyana Adilla Binti
AU - Liu, Xiaonan
AU - Deng, Yansha
AU - Elkashlan, Maged
AU - Nallanathan, Arumugam
N1 - Funding Information:
This work was supported in part by Engineering and Physical Sciences Research Council (EPSRC), U.K., under Grant EP/W004348/1.
Publisher Copyright:
© 2015 IEEE.
PY - 2023/12/1
Y1 - 2023/12/1
N2 - In 5G and beyond, UAVs are integrated into cellular networks as new aerial mobile users to support many applications and provide higher probability of line-of-sight (LoS) transmission to base stations (BSs). Nevertheless, due to limited frequency bandwidth and spectrum resource reuse when BSs serving terrestrial users (TUEs) and UAVs, it causes severe downlink interference to TUEs, especially when the network has a heavy load. Thus, in this paper, we study the performance of radio connectivity of UAVs and TUEs in an urban area and introduce a downlink inter-cell interference coordination mechanism. Then, we propose adaptive cell muting interference and resource allocation scheduling schemes. A value function approximation solution (VFA), Tabular-Q, and Deep-Q Network (DQN) are proposed to maximize the long-term network throughput of TUEs while guaranteeing the data rate requirements of UAVs. With increasing number of UAVs and TUEs and dynamic wireless environment, we further propose a Muting Optimization Scheme and Dynamic time-frequency Scheduling (MOSDS) algorithm to increase throughput and satisfactory level for both UAVs and TUEs. Simulation results show that the proposed algorithms achieve 80% performance improvement of throughput of UAV and TUE networks and mitigate the interference among them. Also, the proposed MOSDS-DQN shows 18% improvement compared to the DQN algorithm.
AB - In 5G and beyond, UAVs are integrated into cellular networks as new aerial mobile users to support many applications and provide higher probability of line-of-sight (LoS) transmission to base stations (BSs). Nevertheless, due to limited frequency bandwidth and spectrum resource reuse when BSs serving terrestrial users (TUEs) and UAVs, it causes severe downlink interference to TUEs, especially when the network has a heavy load. Thus, in this paper, we study the performance of radio connectivity of UAVs and TUEs in an urban area and introduce a downlink inter-cell interference coordination mechanism. Then, we propose adaptive cell muting interference and resource allocation scheduling schemes. A value function approximation solution (VFA), Tabular-Q, and Deep-Q Network (DQN) are proposed to maximize the long-term network throughput of TUEs while guaranteeing the data rate requirements of UAVs. With increasing number of UAVs and TUEs and dynamic wireless environment, we further propose a Muting Optimization Scheme and Dynamic time-frequency Scheduling (MOSDS) algorithm to increase throughput and satisfactory level for both UAVs and TUEs. Simulation results show that the proposed algorithms achieve 80% performance improvement of throughput of UAV and TUE networks and mitigate the interference among them. Also, the proposed MOSDS-DQN shows 18% improvement compared to the DQN algorithm.
KW - Antennas
KW - Autonomous aerial vehicles
KW - Cellular Networks
KW - Deep Reinforcement Learning
KW - Downlink
KW - Dynamic scheduling
KW - Heuristic algorithms
KW - Interference
KW - Interference Management
KW - Three-dimensional displays
KW - Throughput
KW - UAV
UR - http://www.scopus.com/inward/record.url?scp=85168744832&partnerID=8YFLogxK
U2 - 10.1109/TCCN.2023.3307940
DO - 10.1109/TCCN.2023.3307940
M3 - Article
AN - SCOPUS:85168744832
SN - 2332-7731
VL - 9
SP - 1596
EP - 1609
JO - IEEE Transactions on Cognitive Communications and Networking
JF - IEEE Transactions on Cognitive Communications and Networking
IS - 6
ER -