This work focuses on the study of a heterogeneous wireless-powered communication (H-WPCN) system, where a device-to-device (D2D) communication pair is overlaid with a downlink (DL) communication pair. In DL communications, the access point keeps spreading radio frequency (RF) signals to serve the DL user equipment (UE). In addition to being the data source of the UE, DL RF signals are also utilized by the D2D transmitter as the only energy source supporting D2D communications. To capture the impact of limited spectrum resource on the proposed H-WPCN system, co-channel interference is considered. Assuming the Rayleigh block fading channel for signal propagation, a tight lower bound as well as its closed-form approximation are provided for the outage probability of the DL communication link, and an exact expression is derived for the outage probability of the D2D communication link. After that, the throughput of the H-WPCN system is optimized via joint power control and time allocation, where the throughput of the D2D communication link is maximized subject to a required throughput for DL communications. Finally, our theoretical analysis is verified by numerical simulations. The simulation results show that the throughput of the H-WPCN system may not benefit from a high energy conversion efficiency.

The exponential growth in smart devices and mobile data traffic presents significant challenges for Beyond 5G (B5G) networks. The dense deployment of these networks has escalated energy consumption, conflicting with existing goals for energy conservation and emission reduction. Base Station Microgrids (BSMGs), powered by renewable energy, offer a promising solution by alleviating energy pressure on operators due to their economic and environmental advantages. However, recent research on base station deployment has mainly concentrated on performance and coverage, often neglecting the costs to communication operators. Furthermore, the massive increase in device access within heterogeneous networks necessitates urgent improvements in network capacity and the optimization of computing resources using edge computing. This paper proposes a B5G heterogeneous edge BSMG system, comprising macro BSMGs and edge BSMGs. An enhanced K-means algorithm is employed to optimize the deployment of BSMGs, while an adaptive optimization strategy, incorporating edge computing and model predictive control, is designed to maximize green energy utilization. Extensive simulations demonstrate that the proposed system effectively reduces reliance on the traditional power grid and optimizes energy and computing resources compared to other schemes.

In the field of wireless body area networks (WBANs), for solving the complex interference problem of inter-WBANs, a density-based adaptive optimization strategy (DAOS) is proposed in this paper. Firstly, the complex interference problem among WBANs is converted into a distance-based graph coloring model, then time division multiple access and a two-level split clustering methods are adopted to allocate initial time slots for nodes. Secondly, the particle swarm optimization algorithm is used to optimize the time slot of each node for maximizing the throughput. We simulate the scenario on MATLAB simulator. Experimental results show that compared with the traditional scheme in high-density healthcare Internet of Things (IoT) scenarios, DAOS has obvious advantages compared with three comparison strategies of faster convergence rate of 48.94%, 60.76%, and 96.82%, and higher throughput of 5.60%, 8.08%, and 8.05% in traffic priorities 7 to 4.

In this paper, we propose the two-stage constructions for the rate-compatible shortened polar (RCSP) codes. For the Stage-I construction, the shortening pattern and the frozen bit are jointly designed to make the shortened bits be completely known by the decoder. Besides, a distance-greedy algorithm is presented to improve the minimum Hamming distance of the codes. To design the remaining Stage-II frozen bits, three different construction algorithms are further presented, called the Reed-Muller (RM) construction, the Gaussian Approximation (GA) construction, and the RM-GA construction. Then we give the row weight distribution numerical results of the generator matrix after the Stage-I and Stage-II constructions, which shows that the proposed constructions can efficiently increase the minimum Hamming distance. Simulation results show that the proposed RCSP codes have excellent frame error rate (FER) performances at different code lengths and code rates. More specifically, the RM-GA construction performs best and can achieve at most 0.8 dB gain compared to the Wang14 and the quasi-uniform puncturing (QUP) schemes. The RM construction is designed completely by the distance-constraint without channel evaluation thus has the simplest structure. Interestingly, it still has better FER performance than the existing shortening/puncturing schemes, especially at high signal noise ratio (SNR) region.

Unmanned Aerial Vehicle (UAV) communications have recently entered a new period of interest, motivated by technological advances and the gradual emergence of the Space-Air-Ground Integrated Network (SAGIN). The current survey aims to capture the use of UAVs in the SAGIN while highlighting the most promising open research topics. The traditional UAV network architecture is not adequate to meet the challenges presented by the SAGIN, and an effective and secure space-air-ground integrated UAV network needs to be constructed. Given its well-distributed management and consensus mechanism, blockchain technology can make up for the deficiency of the traditional UAV network. In this work, we review the role of UAVs in the SAGIN. Then, three applications of the blockchain-envisioned UAV network are introduced through several classifications. Future challenges and the corresponding open research topics are also described.

With the rapid advancement of the Internet of Things (IoT), the typical application of wireless body area networks (WBANs) based smart healthcare has drawn wide attention from all sectors of society. To alleviate the pressing challenges, such as resource limitations, low-latency service provision, mass data processing, rigid security demands, and the lack of a central entity, the advanced solutions of fog computing, software-defined networking (SDN) and blockchain are leveraged in this work. On the basis of these solutions, a task offloading strategy with a centralized low-latency, secure and reliable decision-making algorithm having powerful emergency handling capacity (LSRDM-EH) is designed to facilitate the resource-constrained edge devices for task offloading. Additionally, to well ensure the security of the entire network, a comprehensive blockchain-based two-layer and multidimensional security strategy is proposed. Furthermore, to tackle the inherent time-inefficiency problem of blockchain, we propose a blockchain sharding scheme to reduce system time latency. Extensive simulation has been conducted to validate the performance of the proposed measures, and numerical results verify the superiority of our methods with lower time-latency, higher reliability and security.