Providing ubiquitous connectivity to diverse device types is the key challenge for 5G and beyond 5G (B5G). Unmanned aerial vehicles (UAVs) are expected to be an important component of the upcoming wireless networks that can potentially facilitate wireless broadcast and support high rate transmissions. Compared to the communications with fixed infrastructure, UAV has salient attributes, such as flexible deployment, strong line-of-sight (LoS) connection links, and additional design degrees of freedom with the controlled mobility. In this paper, a comprehensive survey on UAV communication towards 5G/B5G wireless networks is presented. We first briefly introduce essential background and the space-air-ground integrated networks, as well as discuss related research challenges faced by the emerging integrated network architecture. We then provide an exhaustive review of various 5G techniques based on UAV platforms, which we categorize by different domains including physical layer, network layer, and joint communication, computing and caching. In addition, a great number of open research problems are outlined and identified as possible future research directions.

Low earth orbit (LEO) satellite networks can break through geographical restrictions and achieve global wireless coverage, which is an indispensable choice for future mobile communication systems. In this article, we present a hybrid cloud and edge computing LEO satellite (CECLS) network with a three-tier computation architecture, which can provide ground users with heterogeneous computation resources and enable ground users to obtain computation services around the world. With the CECLS architecture, we investigate the computation offloading decisions to minimize the sum energy consumption of ground users, while satisfying the constraints in terms of the coverage time and the computation capability of each LEO satellite. The considered problem leads to a discrete and nonconvex since the objective function and constraints contain binary variables, which makes it difficult to solve. To address this challenging problem, we convert the original nonconvex problem into a linear programming problem by using the binary variables relaxation method. Then, we propose a distributed algorithm by leveraging the alternating direction method of multipliers (ADMMs) to approximate the optimal solution with low computational complexity. Simulation results show that the proposed algorithm can effectively reduce the total energy consumption of ground users.

Integrated sensing and communication (ISAC) technique has been viewed as a promising component in future network. A major challenge for ISAC systems is that the constraint introduced by sensing functionality will constrain the degrees of freedom in waveform design and results in large multi-user interference (MUI), thus degrading the communication performance. In this paper, we study the employment of RIS in mitigating MUI in ISAC systems. For practical consideration, we investigate joint constant-modulus waveform and discrete RIS phase shift design, with the aim of minimizing MUI under the Cramer-Rao bound (CRB) constraint for direction of arrival (DOA) estimation. An alternating optimization algorithm is proposed to solve the formulated problem, and two schemes are proposed to deal with the discrete RIS phase shifts. Simulation results show that the proposed algorithm can dramatically improve the sum rate, and the performance under moderate phase shift quantization level is close to that under continuous phase shifts.

Dual-functional radar-communication (DFRC) technique has been viewed as a promising component in the emerging platforms. When synthesizing the desired transmit beampattern, the degrees of freedom of waveform design is limited, which introduces high multi-user interference (MUI), thus degrading the communication performance. Inspired by the applications of the Reconfigurable Intelligent Surface (RIS) in mitigating MUI, in this paper, we investigate joint waveform design and passive beamforming in RIS-assisted DFRC system. We first study the minimization of MUI under the strict beampattern constraint by jointly optimizing DFRC waveform and RIS phase shift matrix. To deal with the coupled variables, we propose an alternating algorithm based on manifold optimization. Subsequently, the trade-off between radar and communication performances is investigated. Simulation results show that for both cases of strict beampattern and trade-off design, with the help of RIS, the system throughput can be significantly improved. Moreover, compared with the scenario where no RIS is employed, the obtained beampattern matches with the target transmit beampattern better.

Research and processing development on the satellite communications has strongly reemerged in recent years. Following the prosperity of various wireless services provided by satellite communications, security issue has raised growing concerns since the space information network is susceptible to be eavesdropped by illegal adversaries in such large-scale wireless network. Recently, physical-layer security (PLS) has emerged as an alternative security paradigm that explores the randomness of the wireless channel to achieve confidentiality and authentication. The success story of PLS technique now spans a decade and thrives to provide a layer of defence in satellite communications. With this position, a comprehensive survey of satellite communications is conducted in this paper with an emphasis on PLS. We first briefly introduce essential background and the view of satellite Internet of Things (IoT), as well as discuss related research challenges faced by the emerging integrated network architecture. Then, we revisit the most popular satellite channel model influenced by many factors and list the commonly used secrecy performance metrics. Also, we provide an exhaustive review of state-of-the-art research activity on PLS in satellite communications, which we categorize by different architectures including land mobile satellite communication networks, hybrid satellite-terrestrial relay networks, and satellite-terrestrial integrated networks. In addition, a number of open research problems are identified as possible future research directions.

In this paper, we investigate the network utility maximization problem in a dual-functional radar-communication multi-unmanned aerial vehicle (multi-UAV) network where multiple UAVs serve a group of communication users and cooperatively sense the target simultaneously. To balance the communication and sensing performance, we formulate a joint UAV location, user association, and UAV transmission power control problem to maximize the total network utility under the constraint of localization accuracy. We then propose a computationally practical method to solve this NP-hard problem by decomposing it into three sub-problems, i.e., UAV location optimization, user association and transmission power control. Three mechanisms are then introduced to solve the three sub-problems based on spectral clustering, coalition game, and successive convex approximation, respectively. The spectral clustering result provides an initial solution for user association. Based on the three mechanisms, an overall algorithm is proposed to iteratively solve the whole problem. We demonstrate that the proposed algorithm improves the minimum user data rate significantly, as well as the fairness of the network. Moreover, the proposed algorithm increases the network utility with a lower power consumption and similar localization accuracy, compared to conventional techniques.