Maximizing Energy Efficiency of Cognitive Wireless Sensor Networks With Constrained Age of Information

A cognitive wireless sensor network is considered, where a cluster of secondary sensors utilize channel vacancies of a primary network and transmit their measurement samples to a common sink node. We propose a joint framing and scheduling policy that optimizes energy efficiency of communication system under strict constraints on the expected age of information. The age of information is defined as the timespan from the sampling epoch to the successful delivery of the samples to the sink node including framing time, queuing time, waiting time for channel vacancies, and transmission time. First, we develop a number-based framing policy to determine the number of samples bundled into data packets with constant header sizes. Then, we quantify the impact of this policy on the age of information and communication energy efficiency by characterizing the utilized queuing dynamics, packet discard rate, and retransmission probability. The derived closed-form expressions for the age of information and energy efficiency are used to regularize packet lengths based on the current sampling rate, channel quality, and channel utilization rate by primary users. The proposed method can be used to develop low-cost and energy-efficient network of unlicensed sensors for delay sensitive applications such as body area sensor networks.