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.

<div>Non-terrestrial networks, including Unmanned Aerial Vehicles (UAVs), High Altitude Platform Station (HAPS) and Low Earth Orbiting (LEO) satellites, are expected to have a pivotal role in the sixth generation wireless networks. With their inherent features such as flexible placement, wide footprint, and preferred channel conditions, they can tackle several challenges in current terrestrial networks. However, their successful and widespread adoption relies on energy-efficient on-board communication systems. In this context, the integration of Reconfigurable Smart Surfaces (RSS) into aerial platforms is envisioned as a key enabler of energy-efficient and cost-effective deployments of aerial platforms. Indeed, RSS consist of low-cost reflectors capable of smartly directing signals in a nearly passive way. We investigate in this paper the link budget of RSS-assisted communications under the two discussed RSS reflection paradigms in the literature, namely the specular and the scattering reflection paradigm types. Specifically, we analyze the characteristics of RSS-equipped aerial platforms and compare their communication performance with that of RSS-assisted terrestrial networks, using standardized channel models. In addition, we derive the optimal aerial platforms placements under both reflection paradigms. The obtained results provide important insights for the design of RSS-assisted communications. For instance, given that a HAPS has a large RSS surface, it provides superior link budget performance in most studied scenarios. In contrast, the limited RSS area on UAVs and the large propagation loss in LEO satellite communications make them unfavorable candidates for supporting terrestrial users. Finally, the optimal location of the RSS-equipped platform may depend on the platform’s altitude, coverage footprint, and type of environment.</div>

Next generation wireless networks are expected to be highly heterogeneous, multi-layered, with embedded intelligence at both the core and edge of the network. In such a context, system-level performance evaluation will be very important to formulate relevant insights into tradeoffs that govern such a complex system. Over the past decade, stochastic geometry (SG) has emerged as a powerful analytical tool to evaluate system-level performance of wireless networks and capture their tendency towards heterogeneity. However, with the imminent onset of this crucial new decade, where global commercialization of fifthgeneration (5G) is expected to emerge and essential research questions related to beyond fifth-generation (B5G) are intended to be identified, we are wondering about the role that a powerful tool like SG should play. In this paper, we first aim to track and summarize the novel SG models and techniques developed during the last decade in the evaluation of wireless networks. Next, we will outline how SG has been used to capture the properties of emerging radio access networks (RANs) for 5G/B5G and quantify the benefits of key enabling technologies. Finally, we will discuss new horizons that will breathe new life into the use of SG in the foreseeable future. For instance, using SG to evaluate performance metrics in the visionary paradigm of molecular communications. Also, we will review how SG is envisioned to cooperate with machine learning seen as a crucial component in the race towards ubiquitous wireless intelligence. Another important insight is Grothendieck toposes considered as a powerful mathematical concept that can help to solve longstanding problems formulated in SG.

The power consumption of future user equipments (UEs) will be affected by the projected growth in their computing capacity, while data throughput may be affected by emerging aerial UEs with specific radio propagation conditions compared to terrestrial UEs. In such a context, this letter evaluates a key metric of interest, namely the probability that the uplink energy efficiency (EE) at a typical ground base station will be higher than a predefined threshold. We first characterize the priority bias of each UE layer as a function of long-term shadowing and systemlevel parameters to assess its penetration rate, i.e., the amount of active UEs from each tier among the total population of active UEs. Next, tractable approximations of the desired signal and the interference distribution are performed, enabling to derive the uplink EE. Our results demonstrate that an aggregation of the system-level parameters through the aerial priority bias needs to meet a given constraint to mitigate interference from aerial UEs and enhance the uplink EE of ground UEs. Monte-Carlo simulations validate the accuracy of our analytical results.

We consider a 3D cellular network in which generalized shadowing and radio network planning and optimisation (RNPO) parameters (e.g., antenna height, antenna tilt/azimuth, power biaising...) are incorporated into the cell-selection model. Using tools from stochastic geometry (SG), we derive an equivalent 2D network in which no shadowing and RNPO parameters are considered. Next, we derive coverage probability for a tractable case-study network, and the regimes where coverage probability is maximized in addition to the interferencelimited one are investigated. An intermediary result is a closedform expression generator encompassing the Q-function basedexpression in [1]. Numerical results confirm the accuracy of our approximations.

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The ecosystem of airborne platforms is maturing rapidly and becoming essential to meeting the communication requirements of modern wireless networks. In such a context, the speed, range, and quality of service are highly dependent on a timely access to the right amount and type of affordable spectrum. In this way, evaluating the statistical properties of the air-to-ground (AtG) channel in different built-up propagation environments with regard to the operating frequency is crucial for performance analysis of airborne platform-assisted communications. In this paper, we construct a framework for the line-of-sight (LoS) probability based on the intrusion ratio of obstacles within the first Fresnel zone, yielding an analytical expression for the LoS probability that is sensitive to the operating frequency, the transmitter and receiver heights, the horizontal distance between them, and three other parameters depicting the statistical properties of the urban environment. The model developed is accurate enough to capture scattering mechanisms such as reflection and diffraction, while being sufficiently flexible mathematically to allow, based for instance on powerful analytical tools such as stochastic geometry, a seamless and physically meaningful system-level performance evaluation of modern wireless networks in the presence of airborne platforms.

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