Joint rate allocation and power control for RSMA-based communication and radar coexistence systems

We consider a rate-splitting multiple access (RSMA)-based communication and radar coexistence (CRC) system. The proposed system allows an RSMA-based communication system to share spectrum with multiple radars, which significantly improves spectral efficiency, energy efficiency and quality of service (QoS) of communication users (CUs). Due to the spectrum sharing, the communication network and the radars cause interference to each other, which reduces the signal-to-interference-plus-noise ratio (SINR) of the radars as well as the data rate of the CUs. Therefore, a major problem is to maximize the sum rate of the CUs while guaranteeing their QoS requirements of data transmissions and the SINR requirements of multiple radars. To achieve the objective, we formulate a new problem that optimizes i) common rates of the CUs, ii) transmit power of the common message of the CUs, iii) transmit power of the private messages for the intended CUs, and iv) transmit power of the radar systems. The problem is non-convex, and thus we propose two algorithms. The first sequential quadratic programming (SQP) as the state-of-the-art in nonlinear programming method can quickly return a local optimal solution. The second is an additive approximation scheme (AAS) which solves the problem globally in a reasonable amount of time. Simulation results show the significant improvement of the AAS compared with the SQP in terms of sum rate. Furthermore, with the AAS, the sum rate of the CUs only slightly decreases when the radars' SINR is significantly increased. This implies that the AAS supports the RSMA-based communication system which allows to well coexist with the radars.Info-communications Media Development Authority (IMDA)Ministry of Education (MOE)National Research Foundation (NRF)This research was supported in part by the National Research Foundation of Korea (NRF) Grant funded by the Korean Government (MSIT) under Grant 2021R1A2C2007638 and in part by MOE Tier 1 (RG87/22), the National Research Foundation (NRF), Singapore and Infocomm Media Development Authority under the Future Communications Research Development Programme (FCP), and DSO National Laboratories under the AI Singapore Programme (AISG Award No: AISG2-RP-2020-019), under Energy Research Test-Bed and Industry Partnership Funding Initiative, part of the Energy Grid (EG) 2.0 programme, and under DesCartes and the Campus for Research Excellence and Technological Enterprise (CREATE) programme