Aerial platforms are expected to deliver enhanced and seamless connectivity in the fifth generation (5G) wireless networks and beyond (B5G). This is generally achievable by supporting advanced onboard communication features embedded in heavy and energy-intensive equipment. Alternatively, reconfigurable smart surfaces (RSS), which smartly exploit/recycle signal reflections in the environment, are increasingly being recognized as a new wireless communication paradigm to improve communication links. In fact, their reduced cost, low power use, light weight, and flexible deployment make them an attractive candidate for integration with 5G/B5G technologies. In this article, we discuss comprehensive approaches to the integration of RSS in aerial platforms. First, we present a review of RSS technology, its operations and types of communication. Next, we describe how RSS can be used in aerial platforms, and we propose a control architecture workflow. Then, several potential use cases are presented and discussed. Finally, associated research challenges are identified.

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In this paper, we propose a framework design for wireless sensor networks based on multiple unmanned aerial vehicles (UAVs). Specifically, we aim to minimize deployment and operational costs, with respect to budget and power constraints. To this end, we first optimize the number and locations of cluster heads (CHs) guaranteeing data collection from all sensors. Then, to minimize the data collection flight time, we optimize the number and trajectories of UAVs. Accordingly, we distinguish two trajectory approaches: 1) where a UAV hovers exactly above the visited CH; and 2) where a UAV hovers within a range of the CH. The results of this include guidelines for data collection design. The characteristics of sensor nodes' K-means clustering are then discussed. Next, we illustrate the performance of optimal and heuristic solutions for trajectory planning. The genetic algorithm is shown to be near-optimal with only 3.5% degradation. The impacts of the trajectory approach, environment, and UAVs' altitude are investigated. Finally, fairness of UAVs trajectories is discussed.

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To solve the spectrum scarcity problem caused by the high number of wireless applications and users, the concept of cognitive radio (CR) was proposed in the past few years. Cognitive radio networks (CRNs) provide dynamic spectrum access (DSA), where the unlicensed users can access the spectrum without causing unacceptable level of interference to the primary user (PU). DSA was based on conventional spectrum sensing information or geolocation databases. Later, radio environment map (REM) as an improved geolocation database was introduced to enhance the DSA process. It is a comprehensive map consists of different integrated databases, and the interference field information is one of its databases.

<p> The ever-increasing number of users and new services in urban regions can lead terrestrial base stations (BSs) to become overloaded and, consequently, some users to go unserved. Compounding this, users in urban areas can face severe shadowing and blockages, which means that some users do not receive a desired quality of service (QoS). Motivated by the energy and cost benefits of reconfigurable intelligent surfaces (RIS) and the advantages of high altitude platform stations (HAPS), including their wide footprint and strong line-of-sight (LoS) links, we propose a solution to service the stranded users using the RISaided HAPS. More specifically, we propose to service the stranded users by a dedicated control station (CS) via a HAPS equipped with RIS (HAPS-RIS). Through this approach, users are not restricted from being serviced by the cell they belong to; hence, we refer to this approach as beyond-cell communication. As we demonstrate in this paper, beyond-cell communication works in tandem with legacy terrestrial networks to support uncovered or unserved users. Optimal transmit power and RIS unit assignment strategies for the users based on different network objectives are introduced. Numerical results demonstrate the benefits of the proposed beyond-cell communication approach. Moreover, the results provide insights into the different optimization objectives and their interplay with minimum quality-of-service (QoS) and network resources, such as transmit power and the number of reflectors. </p>

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