Query Age of Information Analysis in STAR-RIS-Assisted PQ and QAPA Systems

Time-sensitive applications such as internet of things (IoT) depend on the timely delivery of fresh data. Thus, the age of information (AoI) metric is defined to measure the freshness of data available for remote monitoring in future networks. However, its definition indirectly assumes that new information is utilized at all times, which isn't always the case. The literature introduces the query age of information (QAoI) to measure AoI at query instants when information is needed. This is particularly relevant in resource-constrained contexts since for many IoT use cases, the best use of the available transmissions requires exact timing. In this paper, energy signals are transmitted to two sensors on either side of a simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) by a multi-antenna power station. Energy signals are harvested by sensors, then start transmission to the monitor when they are scheduled and ready to start transmission. Moreover, sensors deliver data packets to the monitor under two scenarios: permanent query (PQ), in which sensors send data packets at any time regardless of when the monitor needs them, and query arrival process aware (QAPA), which aims to provide fresh data at queries. The optimization problem is analyzed afterward using an alternating optimization approach, and the problem's non-convexity is addressed by applying the successive convex approximation approach. The average sum-QAoI of PQ and QAPA is investigated in numerical results versus various parameters, to demonstrate how employing STAR-RIS may enhance system performance in comparison to the conventional RIS structure.