Unmanned aerial vehicles (UAVs) will be an integral part of the next generation wireless communication networks. Their adoption in various communication-based applications is expected to improve coverage and spectral efficiency, as compared to traditional ground-based solutions. However, this new degree of freedom that will be included in the network will also add new challenges. In this context, the machine-learning (ML) framework is expected to provide solutions for the various problems that have already been identified when UAVs are used for communication purposes. In this article, we provide a detailed survey of all relevant research works, in which ML techniques have been used on UAV-based communications for improving various design and functional aspects such as channel modeling, resource management, positioning, and security.

The performance of digital communication systems over generalized-K (K/sub G/) fading channels is analyzed and evaluated. Novel closed form expressions for the SNR statistics, the average Shannon's channel capacity and the bit error rate (BER) are derived. These expressions are used to study important performance criteria such as the outage performance, the average capacity and the BER for a great variety of modulation formats in K/sub G/ fading channels. The proposed mathematical analysis is accompanied with various performance evaluation results, which demonstrate the usefulness of the proposed approach.

Unmanned aerial vehicle (UAV)-enabled communications have been proposed as a critical part of the beyond fifthgeneration (5G) cellular networks. This type of communications is frequently characterized by line-of-sight (LoS) and dynamic propagation conditions. However, in various scenarios, the presence of large obstacles in the LoS path is unavoidable, resulting in shadowed fading environments. In this paper, a new channel model is proposed, in which the effects of mobility and shadowing are simultaneously considered. In particular, the performance of a UAV-based communication system operating in a shadowed double-scattering channel is analyzed. The new channel model is generic, since it models various fading/shadowing conditions, while it is in terms of easy-to-evaluate mathematical functions. Moreover, a low complexity UAV selection policy is proposed, which exploits shadowing-related information. The proposed scheme offers a reduction of the signal processing complexity, without any important degradation on the performance, as compared to alternatives approaches. In this context, a new analytical framework has been developed for investigating the performance of the new strategy. Finally, the main outcomes of this paper are also validated by empirical data, collected in an air-to-ground measurement campaign.

Maritime activities represent a major domain of economic growth with several emerging maritime Internet of Things use cases, such as smart ports, autonomous navigation, and ocean monitoring systems. The major enabler for this exciting ecosystem is the provision of broadband, low-delay, and reliable wireless coverage to the ever-increasing number of vessels, buoys, platforms, sensors, and actuators. Towards this end, the integration of unmanned aerial vehicles (UAVs) in maritime communications introduces an aerial dimension to wireless connectivity going above and beyond current deployments, which are mainly relying on shore-based base stations with limited coverage and satellite links with high latency. Considering the potential of UAV-aided wireless communications, this survey presents the state-of-the-art in UAV-aided maritime communications, which, in general, are based on both conventional optimization and machine-learning-aided approaches. More specifically, relevant UAV-based network architectures are discussed together with the role of their building blocks. Then, physical-layer, resource management, and cloud/edge computing and caching UAV-aided solutions in maritime environments are discussed and grouped based on their performance targets. Moreover, as UAVs are characterized by flexible deployment with high re-positioning capabilities, studies on UAV trajectory optimization for maritime applications are thoroughly discussed. In addition, aiming at shedding light on the current status of real-world deployments, experimental studies on UAV-aided maritime communications are presented and implementation details are given. Finally, several important open issues in the area of UAV-aided maritime communications are given, related to the integration of sixth generation (6G) advancements. These future challenges include physical-layer aspects, non-orthogonal multiple access schemes, radical learning paradigms for swarms of UAVs and unmanned surface and underwater vehicles, as well as UAV-aided edge computing and caching.

In this work, we investigate a novel covert communication system, where the legitimate transmitter attempts to communicate with a covert user in the presence of a warden and the public user covertly. Specifically, the legitimate transmitter employs non-orthogonal multiple access (NOMA) and rate-splitting (RS) to communicate with users aided by a reconfigurable intelligent surface (RIS). In this context, we investigate key performance indicators of covert communication, namely the detection error probability and the covert communication rate. Meanwhile, we consider the physical layer security (PLS) of the proposed system in the presence of an eavesdropper, and derive the approximate secrecy outage probability (SOP) expression. Also, an asymptotic analysis of the SOP is also carried out. Various numerical results are presented that demonstrate the usefulness of the proposed analysis, which are complemented by simulated ones, verifying the correctness of the theoretical framework. From these results, it becomes evident that the use of RS, NOMA, and RIS can improve the performance of covert communication. Finally, it is also depicted that under the condition of high signal-to-noise ratio, the SOP of the system tends to be a constant value.

The Weibull-gamma (WG) distribution, which is appropriate for modelling fading environments when multipath is superimposed on shadowing, is introduced and studied. For this composite distribution the probability density, cumulative distribution, characteristic functions and the moments are derived in closed form. Furthermore, the average bit error and outage probabilities of a receiver operating over WG fading channels are assessed and compared with the corresponding performances obtained using other composite distributions.