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Age of information (AoI) is a performance metric that measures the timeliness and freshness of information, and is particularly relevant in applications with time-sensitive data. This paper studies average AoI minimization in cognitive radio energy harvesting communications. More specifically, the system studied has a primary user with access rights to spectrum, and a secondary user who can utilize the spectrum only when it is left idle by the primary user. The secondary user is an energy harvesting sensor that harvests ambient energy with which it performs spectrum sensing and status updates of its sensing data to a destination. The status-updates are sent by opportunistically accessing the primary user's spectrum. The secondary user aims to minimize the average AoI by adaptively making sensing and update decisions based on its energy availability and the availability of the primary spectrum with either perfect or imperfect spectrum sensing. The sequential decision problems are formulated as partially observable Markov decision processes and solved by dynamic programming for finite and infinite horizon. The properties of the optimal sensing and updating policies are investigated and shown to have threshold structure. Numerical results are presented to confirm the analytical findings.
Leng et al. (Fri,) studied this question.