Spectrum-energy joint optimization for heterogeneous cognitive UASNs

To address spectrum scarcity and energy consumption constraints in heterogeneous cognitive underwater acoustic sensor networks (CUASNs), an ecologically compliant low-coupling cross-layer framework capable of evaluating and optimizing spectrum allocation protocols to balance quality of service (QoS) of sensor nodes (SNs) and their energy consumption is developed. Leveraging queuing theory and Markov modeling, closed-form expressions for QoS metrics (e.g., throughput distribution, queue length, and packet rejection) are derived to rigorously characterize transmission statistics. Generic node energy consumption models based on throughput probability distributions provide explicit energy analysis. Accordingly, a minimum energy (ME) spectrum allocation protocol is proposed to dynamically select optimal transmission channels. Numerical results demonstrate that ME reduces energy by 53% compared to the maximum-throughput protocol (maintaining 85.55% throughput) and outperforms conventional protocols with 14% energy savings and 31.26% throughput gain. These findings validate the framework’s scalability and analytical utility for resource-constrained marine monitoring systems.