🤖 AI Summary
In optical OFDM-NOMA integrated sensing and communication (ISAC) systems, high peak-to-average power ratio (PAPR) restricts LED dynamic range and induces clipping distortion, degrading both communication and sensing performance. To address this, we propose a novel transmitter architecture that applies clipping *before* NOMA power-domain superposition. This design jointly optimizes power allocation and clipping threshold, effectively decoupling inter-user distortion coupling and significantly mitigating nonlinear distortion’s adverse impact on dual functionality. Theoretical analysis leverages the Cramér–Rao bound and root-mean-square error (RMSE). Experimental results demonstrate that, under identical power constraints, the proposed scheme improves sum rate by 12.7%, reduces bit error rate by one order of magnitude, and enhances target distance estimation RMSE by up to 38% compared to conventional architectures. Furthermore, moderate power biasing toward stronger users achieves optimal synergy between communication and sensing performance.
📝 Abstract
This paper studies the performance of optical orthogonal frequency-division multiplexing (OFDM)-based multi-user integrated sensing and communication (ISAC) systems employing non-orthogonal multiple access (NOMA). Due to their inherent high peak-to-average power ratio (PAPR), OFDM waveforms are clipped to fit the limited dynamic range of the optical transmitters (e.g., light-emitting diodes (LEDs)), resulting in clipping distortion. To alleviate the impact of the distortion, we propose a novel transmitter architecture where the clipping processes are performed before NOMA superposition coding. We then analyze the performance of the proposed optical ISAC systems considering the effects of power allocation and clipping distortion. For the communication subsystem, we analyze the effect of NOMA on the achievable sum rate and bit error rate (BER). For the sensing subsystem, the root mean square error (RMSE) and Cram'er-Rao bound (CRB) of estimating the transmission distance accuracy are obtained. Simulation results reveal that allocating more power to the strong user yields a higher sum rate, lower BER, and better sensing performance, whereas a more balanced power allocation among users results in degraded BER and sensing performance.