Joint Transmit and Receive Beamforming Optimization for Energy-Efficient NOMA-Integrated Sensing and Communication Systems

This paper investigates an energy-efficient (EE) non-orthogonal multiple access (NOMA) integrated sensing and communication (ISAC) framework. The framework involves joint waveform optimization for simultaneous multi-user communication and target estimation at both the transmitter and receiver, with sensing reflection separated from multi-user interference using successive interference cancellation (SIC). Our objective is to maximize the system's EE subject to constraints such as the maximum transmission power budget and the minimum signal-to-interference-plus-noise ratio (SINR) for both communication and target estimation. This problem presents a complex non-convex fractional programming challenge. By employing Dinkelbach's method for reformulation, alongside successive convex approximation (SCA) and semidefinite relaxation (SDR) techniques, we propose an iterative algorithm to address this complexity. Numerical results illustrate that the proposed NOMA-ISAC system outperforms traditional ISAC systems, highlighting a trade-off between communication-centric EE and sensing-centric EE.