Bandwidth-Constrained Sensor Scheduling: A Trade-off between Fairness and Efficiency

We address fair sensor scheduling over bandwidth-constrained communication channels. While existing literature on fair scheduling overlooks overall system efficiency, we introduce a novel $q$-fairness framework to balance efficiency and fairness by adjusting the parameter $q$. Specifically, for two communication scenarios, we: (i) derive the optimal schedule under limited communication rates, and (ii) propose two suboptimal algorithms under limited simultaneous sensor transmissions and analyze their performance gaps relative to the optimal strategy. Simulations demonstrate that our algorithms effectively balance efficiency and fairness in both cases.