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

Abstract

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.