Unmanned aerial vehicles (UAVs) have been widely used in both military and civilian applications. Equipped with diverse communication payloads, UAVs cooperating with satellites and base stations (BSs) constitute a space-air-ground three-tier heterogeneous network, which are beneficial in terms of both providing the seamless coverage as well as of improving the capacity for increasingly prosperous Internet of Things (IoT) networks. However, cross-tier interference may be inevitable among these tightly embraced heterogeneous networks when sharing the same spectrum. The power association problem in satellite, UAV and macrocell three-tier networks becomes a critical issue. In our paper, we propose a two-stage joint hovering altitude and power control solution for the resource allocation problem in UAV networks considering the inevitable cross-tier interference from space-air-ground heterogeneous networks. Furthermore, Lagrange dual decomposition and concave-convex procedure (CCP) method are used to solve this problem, followed by a low-complexity greedy search algorithm. Finally, simulation results show the effectiveness of our proposed two-stage joint optimization algorithm in terms of UAV network’s total throughput.

In this paper, a novel reconfigurable intelligent surface (RIS)-assisted HAP-UAV secure multi-user mixed radio frequency (RF)/free space optical (FSO) system is proposed. Specifically, the Gamma-Gamma distribution is utilized to characterize the atmospheric turbulence effect for the FSO link from UAV to HAP, while the Rayleigh and Nakagami- m distribution fading are applied to simulate the legitimate and wiretap RF links, respectively. We present the closed-form expressions for the probability density functions, the cumulative distribution functions, and the secrecy outage probability (SOP) of the end-to-end signal-to-noise ratio (SNR) in terms of Meijer’s G-function. To gain more insight into secrecy performance, we further obtain the closed-form expressions for the asymptotic SOP, the asymptotic probability of positive secrecy capacity (PPSC), the diversity gain, and the coding gain at high SNR regions. We can observe that the secrecy performance depends on the weaker channel between the RF and FSO, and is closely related to the number of RIS elements, the number of terrestrial users, the atmospheric turbulence factor, pointing error parameters, and the fading parameter of Nakagami- m distributed wiretap link. Finally, numerical results validate the derived results and demonstrate that the proposed design achieves superior secrecy performance over the benchmarks.

This paper proposes an innovative Integrated Sensing and Communication (ISAC) framework for moving target detection by leveraging beyond-diagonal RIS (BD-RIS) to improve beamforming performance and control wireless propagation. In this framework, we first design a novel target-tracking method for moving target detection based on Extended Kalman Filtering (EKF) with accurate cooperative localization. In addition, to further improve the sensing accuracy, we minimize the joint posterior Cramér-Rao bound (PCRB) for both target position and velocity constrained by the communication performance requirements, and maintain the orthogonality and symmetry constraints of BD-RIS. Given the non-convex nature of the problem, we break it into two subproblems, which are solved iteratively using the proposed alternating optimization (AO) algorithm. The AO algorithm incorporates a semidefinite relaxation (SDR) method for beamforming and a penalty dual decomposition (PDD) approach for BD-RIS optimization. The simulation results demonstrate that: (1) the proposed prediction method accurately tracks the position and velocity of the target in dynamic environments; (2) the proposed AO algorithm is efficient and effective, exhibiting fast convergence and achieving a performance improvement of 6.7 % compared to conventional diagonal RIS.

Full-duplex (FD) relaying is a promising solution for fifth generation (5G) wireless communications due to its potential to provide high spectral efficiency (SE) transmission. However, FD relay nodes consume much higher power than half-duplex relay nodes, especially in millimeter (mm)-wave band. Therefore, energy-efficiency (EE) is an important issue to address for mm-wave FD relaying systems, which highlights the green evolution of 5G wireless communications. Existing FD relaying related research is SE-oriented, which is not efficient in cutting carbon footprint. This particle is different in that it addresses the critical EE challenges in implementing FD relaying in mm-wave systems, including low drain efficiency of power amplifier, high circuit power consumption, and additional power required by FD relays to mitigate self-interference. Based on the features of mm-wave communications, we outline a number of promising EE-oriented solutions for designing FD relaying enabled systems, including adaptive self-interference cancellation, transmission power adaptation, hybrid relaying mode selection, multi-input-multi-output (MIMO), and massive MIMO FD relaying. Some EE-oriented future research is also envisaged for mm-wave FD relaying systems.

To address the challenges of information leakage, low energy efficiency, and the Doppler effect in mobile Internet of Vehicles (IoV), this paper proposes an enhanced IoV cooperation framework, where privacy information is forwarded by the untrusted relay assisted by unmanned aerial vehicle (UAV) and reconfigurable intelligent surface (RIS), which can improve security and energy efficiency. To meet the requirements of green communication, we formulate a secrecy energy efficiency maximization problem by jointly optimizing the transmit power allocation, the relay’s amplification factor, the two-hop RIS phase shift matrices, and the UAV trajectory. Given the non-convex nature of this problem, we introduce an iterative algorithm based on the convex-concave procedure and Dinkelbach’s method to optimize the transmit power and amplification factor. Additionally, we conceive the majorization-minimization (MM) algorithm to optimize the two-hop RIS phase shift matrices, and a designed firefly algorithm-deep deterministic policy gradient (FA-DDPG) algorithm is proposed to obtain the UAV trajectory. Simulation results demonstrate the effectiveness of the proposed scheme in enhancing secrecy energy efficiency. Specifically, compared to the DDPG-only and FA-based schemes, the proposed scheme achieves an improvement of 33.3% and 64.2%, respectively, in secrecy energy efficiency.