Performance Analysis and Optimal Resource Allocation for Large Scale Joint Sensing and Communication

Joint sensing and communication (JSAC) is regarded as a promising technology for future networks, which can reuse most devices of the systems in sensing and communication (S&C) and reduces the cost in terms of power and spectrum (P&S) critically. The current research considers the P&S allocation of S&C separately and then discusses the performance from different aspects. However, as an integrated system, the allocation strategy of P&S allocation affects the joint performance significantly. In this article, we use tools from stochastic geometry to study the coverage performance considering the trade-off of P&S allocation for JSAC with the principle requirements of small distance resolution (SDR) in sensing and high data rate (HDR) in communication. In particular, we model the locations of user equipment (UE) and base stations (BSs) as two different Poisson Point Processes and allocate P&S at BSs with two independent ratios. The sensing system will detect the surrounding environment and obtain UE positions. After that, an adaptive beamwidth for beamforming technology is applied in communication, which can save energy effectively. First, we introduce the distance resolution in sensing and special channel models in S&C with a high frequency. Then, considering the proposed system model, we separately model the interference in S&C. Further, the joint coverage probability (CP) of JSAC is derived as a function of densities of UE and BSs, required HDR and SDR, and allocation ratios of P&S. Finally, We draw multiple valuable system-level insights from the proposed analysis. For instance, we show that the SDR and HDR are the two main constraints to the maximum achievable CP with optimized allocations of P&S. Furthermore, we show that different densities of BSs should be considered in various scenarios. The revealed relationship between the densities of UE and BSs can be taken as a reference in practical applications.