An End-to-End Sensor-Aware Optical Camera Communication Simulator with Application to Intra-Satellite Links

This work presents a modular, sensor-aware, end-to-end simulation framework for optical camera communication (OCC). The framework combines modified Monte Carlo ray tracing with pixel-level camera modeling, including optical blur, shutter timing, noise, digitization, and modulation-aware signal processing. It produces physically consistent synthetic images from simulated optical propagation and enables communication performance to be estimated through image-domain signal-to-noise ratio (SNR) and theoretical bit-error-rate (BER) calculations. The simulator is applied to intra-satellite optical links as a representative case study involving confined three-dimensional geometries, line-of-sight (LOS) visibility, partial occlusion, and rolling-shutter image formation. Experimental validation under LOS conditions shows good agreement in the dominant spatial-temporal characteristics of rolling-shutter imagery, with a structural similarity index measure (SSIM) of approximately 0.80. Simulated SNR values range from approximately 20.5 to 22.6 dB, compared with measured values between 20.8 and 24.4 dB. No bit errors are observed in the experimental sequences, corresponding to finite-length BER upper confidence bounds, while the BER values derived from the simulated images are theoretical estimates obtained from the image-domain SNR under ideal receiver assumptions. Additional simulations using a detailed 12U CubeSat model demonstrate the capability to assess emitter–receiver placement and partial geometric occlusion, including cases in which the visible portion of the source remains sufficient for bitstream decoding. By jointly modeling optical propagation, camera acquisition, and communication metrics, the proposed framework supports early-stage OCC system analysis and configuration trade-offs without requiring immediate hardware implementation. The approach is applicable to other OCC scenarios in which spatial image formation and sensor dynamics influence communication performance.