Intelligent reflecting surface (IRS) is a promising technology to support high performance wireless communication. By adaptively configuring the reflection amplitude and/or phase of each passive reflecting element on it, the IRS can reshape the electromagnetic environment in favour of signal transmission. This letter advances the existing research by proposing and analyzing a double-IRS aided wireless communication system. Under the reasonable assumption that the reflection channel from IRS 1 to IRS 2 is of rank 1 (e.g., line-of-sight channel), we propose a joint passive beamforming design for the two IRSs. Based on this, we show that deploying two cooperative IRSs with in total K elements can yield a power gain of order O(K 4 ), which greatly outperforms the case of deploying one traditional IRS with a power gain of order O(K 2 ). Our simulation results validate that the performance of deploying two cooperative IRSs is significantly better than that of deploying one IRS given a sufficient total number of IRS elements. We also extend our line-of-sight channel model to show how different channel models affect the performance of the double-IRS aided wireless communication system.

Abstract-Age of information is a newly proposed metric that captures delay from an application layer perspective. The age measures the amount of time that elapsed from the moment the mostly recently received update was generated until the present time. In this paper, we study an age minimization problem over a wireless broadcast network with many users, where only one user can be served at a time. We formulate a Markov decision process (MDP) to find dynamic transmission scheduling schemes, with the purpose of minimizing the long-run average age. While showing that an optimal scheduling algorithm for the MDP is a simple stationary switch-type, we propose a sequence of finitestate approximations for our infinite-state MDP and prove its convergence. We then propose both optimal off-line and online scheduling algorithms for the finite-approximate MDPs, depending on knowledge of time-varying arrivals. I. INTRODUCTIONIdeas of traditional networks have been focused on network throughput or delay. In addition to those concerns, in recent years there has been growing interest in an age of information. The age is defined to capture the freshness of information; more precisely, it is the time elapsed since the generation of the information. This is motivated by a variety of network applications requiring timely information, e.g., traffic, transportation, air quality, and typhoon.While the packet delay is usually referred to as the elapsed time from the generation to its delivery, the age includes not only the packet delay but the inter-delivery time because the age of information increases until the information is updated. We hence need to jointly consider the two parameters so as to design an age-optimal network. Moreover, while traditional relays need to keep all packets that are not served yet, the relays for the timely information only store the latest information, but remove those out-of-date packets, i.e. a new arrival always replaces the old packet in a buffer. Due to the distinctions, we need to re-consider networks for the timely information.In resource-shared networks, the scheduling is a critical issue to optimize network performance. For delivering clean theoretical results and clear engineering insights, we look at the simplest and fundamental problem by considering a

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Age of information is a new network performance metric that captures the freshness of information at end-users. This paper studies the age of information from a scheduling perspective. To that end, we consider a wireless broadcast network where a base-station (BS) is updating many users on random information arrivals under a transmission capacity constraint. For the offline case when the arrival statistics are known to the BS, we develop a structural MDP scheduling algorithm and an index scheduling algorithm, leveraging Markov decision process (MDP) techniques and the Whittle's methodology for restless bandits. By exploring optimal structural results, we not only reduce the computational complexity of the MDP-based algorithm, but also simplify deriving a closed form of the Whittle index. Moreover, for the online case, we develop an MDP-based online scheduling algorithm and an index-based online scheduling algorithm. Both the structural MDP scheduling algorithm and the MDP-based online scheduling algorithm asymptotically minimize the average age, while the index scheduling algorithm minimizes the average age when the information arrival rates for all users are the same. Finally, the algorithms are validated via extensive numerical studies.Index Terms-Age of information, scheduling algorithms, Markov decision processes. ✦ • Y.-P. Hsu is with