Owing to the superior performance in spectral efficiency, connectivity, and flexibility, nonorthogonal multiple access (NOMA) is recognized as the promising access protocol and is now undergoing the standardization process in 5G. Specifically, dozens of NOMA schemes have been proposed and discussed as the candidate multiple access technologies for the future radio access networks. This paper aims to make a comprehensive overview about the promising NOMA schemes. First of all, we analyze the state‐of‐the‐art NOMA schemes by comparing the operations applied at the transmitter. Typical multiuser detection algorithms corresponding to these NOMA schemes are then introduced. Next, we focus on grant‐free NOMA, which incorporates the NOMA techniques with uplink uncoordinated access and is expected to address the massive connectivity requirement of 5G. We present the motivation of applying grant‐free NOMA, as well as the typical grant‐free NOMA schemes and the detection techniques. In addition, this paper discusses the implementation issues of NOMA for practical deployment. Finally, we envision the future research challenges deduced from the recently proposed NOMA technologies.

Due to the characteristic of wide coverage, flexible deployment, and low cost, unmanned aerial vehicles (UAVs) have been employed to provide mobile crowd sensing and edge computing. However, the limited computation and on-board battery capacities of UAVs impose a changeling for timely computation and endurance. In this paper, we consider an aerial edge computing system where multiple cellular-connected (UAVs) are employed to perform sensing and computation tasks over target subregions, and the UAVs can offload their computation tasks to the ground base station (BS) with binary offloading scheme. We aim to minimize the maximum energy consumption of all UAVs by optimizing three-dimensional (3D) UAV trajectories jointly with the binary offloading indicator as well as computation resource allocation, subject to the target sensing constraints and the computation completion time constraints. The optimization problem we formulated is non-convex and involves binary design variables, making it difficult to find the optimal solution. To address this challenge, we propose an efficient alternating optimization algorithm that can obtain a high-quality suboptimal solution, where exact penalty method with equilibrium constraints is adopted to tackle the binary constraints. To tackle the non-convexity of the optimization subproblems, we utilize the successive convex approximation approach to obtain suboptimal solution. Extensive simulations are conducted and the results demonstrate that the proposed design significantly reduces the energy consumption of the UAVs over several baseline methods.

In this article, a slot array with double-layered full-corporate-fed distribution network by ridge gap waveguide (RGW) in the G-band is presented. The array antenna proposed in this article contains 16×16-element radiation slots fed by air-filled ridge gap waveguide distribution network that achieves high-efficiency. Gap waveguide technology avoids the demand for perfect electrical contact in millimeter waves, therefore the expensive diffusion bonding and the laser welding processes are not demanded. Moreover, the high-accurate Computerized Numerical Control (CNC) machining is applied for the fabrication. Due to the limited layout space for the distribution network, two types of universal stepped cavity power dividers are presented in this article. The proposed array antenna is fed by a standard WR-5 waveguide at the bottom. Furthermore, the tested outcomes show that the proposed 16×16-element array has a gain larger than 30 dBi with over 50% antenna efficiency in the frequency range of 155-171 GHz.

Due to influence of COVID-19, telemedicine is becoming more and more important. High-quality medical videos can provide a physician with a better visual experience and increase the accuracy of disease diagnosis, but this requires a dramatic increase in bandwidth compared to that required by regular videos. Existing adaptive video-streaming approaches cannot successfully provide high-resolution video-streaming services under poor or fluctuating network conditions with limited bandwidth. In this paper, we propose a super-resolution-empowered adaptive medical video streaming in telemedicine system (named SR-Telemedicine) to provide high quality of experience (QoE) videos for the physician while saving the network bandwidth. In SR-Telemedicine, very low-resolution video chunks are first transmitted from the patient to an edge computing node near the physician. Then, a video super-resolution (VSR) model is employed at the edge to reconstruct the low-resolution video chunks into high-resolution ones with an appropriate high-resolution level (such as 720p or 1080p). Furthermore, the neural network of VSR model is designed to be scalable and can be determined dynamically. Based on the time-varying computational capability of the edge computing node and the network condition, a double deep Q-Network (DDQN)-based algorithm is proposed to jointly select the optimal reconstructed high-resolution level and the scale of the VSR model. Finally, extensive experiments based on real-world traces are carried out, and the experimental results illustrate that the proposed SR-Telemedicine system can improve the QoE of medical videos by 17–79% compared to three baseline algorithms.

To foster the rollout of 5G in unserved areas, 3GPP has kicked off a study item on new radio to support nonterrestrial networks (NTNs). Due to ultra‐wideband of laser, laser communication is very promising for the feeder links of NTNs; however, imprecise temporal synchronization hinders its deployment, which results from a combination of propagation delay, velocity, acceleration, and jerk of NTN platform. The prior synchronization algorithms are inapplicable to the temporal synchronization in laser communications due to the extremely high data rate and Doppler shift. This paper is devoted to addressing the temporal synchronization problem in laser communications. In particular, we first observe the sparsity of laser signal in time‐frequency domain. On top of this observation, we propose a new sparsity‐aware algorithm for temporal synchronization without carrier aid through sparse discrete polynomial‐phase transform and sparse discrete fractional Fourier transform. Subsequently, we implement the proposed algorithm via designing a hardware prototype. To further evaluate its performance, we conduct extensive simulations, and the results demonstrate the effectiveness of the proposed algorithm in terms of good accuracy, low power consumption, and low computational complexity, suggesting its attractiveness for the feeder links of 5G NTNs.