Integrated sensing and communication enabled multiple beamwidth and power allocation for connected automated vehicles

• Published in: China communications Vol. 20; no. 9; pp. 46 - 58
• Main Authors: Liu, Shengnan, Hao, Qianyi, Zhang, Qixun, Liu, Jiaxiang, Jiang, Zheng
• Format: Journal Article
• Language: English
• Published: China Institute of Communications 01.09.2023; China Telecom Corporation Limited Beijing Research Institute,Beijing 102209,China%School of Information and Communication Engineering,Beijing University of Posts and Telecommunications,Beijing 100876,China
• Subjects: connected automated vehicles; integrated sensing and communication; Interference; Millimeter wave communication; resource allocation in wireless networks; Resource management; Sensors; Symbols; Vehicle dynamics; connected automated vehicles; resource allocation in wireless networks; integrated sensing and communication
• ISSN: 1673-5447
• DOI: 10.23919/JCC.fa.2023-0144.202309

Connected autonomous vehicles (CAVs) are a promising paradigm for implementing intelligent transportation systems. However, in CAVs scenarios, the sensing blind areas cause serious safety hazards. Existing vehicle-to-vehicle (V2V) technology is difficult to break through the sensing blind area and ensure reliable sensing information. To overcome these problems, considering infrastructures as a means to extend the sensing range is feasible based on the integrated sensing and communication (ISAC) technology. The mmWave base station (mmBS) transmits multiple beams consisting of communication beams and sensing beams. The sensing beams are responsible for sensing objects within the CAVs blind area, while the communication beams are responsible for transmitting the sensed information to the CAVs. To reduce the impact of inter-beam interference, a joint multiple beamwidth and power allocation (JMBPA) algorithm is proposed. By maximizing the communication transmission rate under the sensing constraints. The proposed non-convex optimization problem is transformed into a standard difference of two convex functions (D.C.) problem. Finally, the superiority of the proposed JMBPA algorithm is verified by iterative solutions. The average transmission rate of communication beams remains over 3.4 Gbps, showcasing a significant improvement compared to other algorithms. Moreover, the satisfaction of sensing services remains steady.