Data Communication in Cyber-Physical Systems: An Integrated Approach Using CLDCR and EA-SCMA Protocols

Cyber-physical systems (CPS) require reliable, strong, and energy-efficient data communication systems tosupport everything from environmental monitoring to industrial automation. In this paper, two complementingalgorithms are combined to propose an integrated framework: Dynamic Cross-LayerCLDCR, or compression and routing, and EA-SCMA, or energy-aware sparse code multiple access.While EA-SCMA improves physical-layer resource allocation through dynamic codebook adaptation andgame-theoretic power optimization, CLDCR optimizes data compression and energy-aware routing at thenetwork layer. Synergistic integration mitigates critical CPS concerns such as energy constraints, spectrumefficiency, and data volume minimization. Demonstrations and theoretical studies indicate that the frameworkimproves packet delivery rates, conserves 15% of energy, and reduces network overhead by 40–60%. Hybridprototype and machine learning integration for prediction of sparsity adaptability are future directions.