Device-to-device (D2D) technology enables direct communication between adjacent devices within cellular networks. Due to its high data rate, low latency, and performance improvement in spectrum and energy efficiency, it has been widely investigated and applied as a critical technology in 5G New Radio (NR). Cooperative D2D communication can achieve a win-win situation between cellular users (CUs) and D2D users (DUs) through cooperative relaying techniques. In addition to conventional overlay and underlay D2D communications, it has attracted extensive attention from academic and industrial circles in the past decade. This paper delves into optimizing joint spectrum allocation, power control, and link-matching between multiple CUs and DUs for cooperative D2D communications. Weighted sum energy efficiency (WSEE) is used as the performance metric to address the challenges of green communication and sustainable development. This mixed-integer fractional programming (MIFP) problem can be decomposed into: 1. a classic weighted bipartite graph matching; 2. a series of nonconvex spectrum allocation and power control problems between potentially matched cellular and D2D link pairs. To address this issue, we propose a hybrid centralized-distributed scheme based on deep reinforcement learning (DRL) and the Kuhn-Munkres (KM) algorithm. Leveraging the former, the CUs and DUs autonomously optimize spectrum allocation and power control by only utilizing local information. Then, the base station (BS) determines the link matching utilizing the latter. Simulation results reveal that it achieves more than 96% WSEE of the optimal scheme and 98% WSEE of the centralized DRL-based scheme. It significantly enhances the network convergence speed with low centralized computational overheads. In addition, we also propose and utilize cooperative link sets for corresponding D2D links to accelerate the proposed scheme and reduce signaling exchange further: an average of about 85% WSEE of the optimal scheme is achieved, while more than 50% of signaling and distributed computing overheads are reduced.

This letter introduces weighted sum power (WSP), a new performance metric for wireless resource allocation during cooperative spectrum sharing in cognitive radio networks, where the primary and secondary nodes have different priorities and quality of service (QoS) requirements. Compared to using energy efficiency (EE) and weighted sum energy efficiency (WSEE) as performance metrics and optimization objectives of wireless resource allocation towards green communication, the linear character of WSP can reduce the complexity of optimization problems. Meanwhile, the weights assigned to different nodes are beneficial for managing their power budget. Using WSP as the optimization objective, a suboptimal resource allocation scheme is proposed, leveraging linear programming and Newton’s method. Simulations verify that the proposed scheme provides near-optimal performance with low computation time. Furthermore, the initial approximate value selection in Newton’s method is also optimized to accelerate the proposed scheme.

Wireless temperature measurement, compared with traditional temperature measurement methods, can not only offer lower costs and higher convenience but also measure the temperature of the target object in real time and continuously. However, current mainstream-based wireless temperature measurement schemes still face issues, such as low-accuracy, high-power consumption and limited data transmission distance. To this end, this article proposes a novel ultrahigh frequency (UHF) battery-free wireless temperature sensing system. The system utilizes the radio frequency (RF) electromagnetic wave signals in the surrounding environment for energy supply, employs a self-compensating temperature sensor to accurately measure the temperature, and achieves data communication by modulating the electromagnetic wave signals through backscattering. This system is characterized by its low-power consumption, long working distance, broad temperature measurement scope and high accuracy. The chip is fabricated in Huahong 0.18× m 1P6M BCD technology, with a tag chip area of 0.097 mm2. Operating at the frequency of 915 MHz, the RF energy harvesting sensitivity is −17 dBm, and the effective distance of RF energy harvesting can be up to 10 m at the equivalent isotropically radiated power (EIRP) of 36 dBm. With a two-point calibration, the measurement covers a range from 0°C to 100°C with a mean error of +0.47/- 0.79.°C The average power consumption of the chip is as low as 0.97×W.

With the accelerate growth of mobile communication technology, 5G emerges at a historic moment, has been developing at high speed and devotes itself to open the curtain of the information age. This paper summarizes the wireless key technologies of 5G including technology trials. Finally, progress on implementation issue of these techniques are also reviewed.

This paper considers device-to-device (D2D) communications overlaying cellular networks. Combined with cooperative relay technology, a D2D user can serve as a relay for a cellular link and gain the opportunity to access the corresponding cellular spectrum. Considering mobile terminals’ limited battery capacity and motivated by green communication, we propose a resource scheduling scheme, which comprises joint power and spectrum allocation, mode selection, and link matching. Unlike previous works, to balance energy utilization and extend the network lifetime, this scheme sets a price for each node and minimizes the system cost during each frame instead of energy efficiency (EE). Specifically, we investigate the power and spectrum allocation problem to characterize the minimum cost of matched links. We prove it to be nonconvex and obtain the optimal solution by the graphic method and Newton’s method with a small number of iterations. We also discuss the energy pricing strategy. In order to reduce communication and computation overhead, we propose a heuristic pricing strategy that involves no iteration and supposes nodes’ energy prices are inversely proportional to their residual energy. Through simulations under various cases, we verify that the proposed scheme significantly improves network lifetime and suits real-time operations while guaranteeing the quality of service (QoS) requirement. Moreover, the simulation results demonstrate that the proposed scheme performs the same as the maximum EE scheme if the energy prices are equal at each node.

This paper investigates a simultaneous wireless information and power transfer (SWIPT) decode-and-forward (DF) relay network, where a source node transmits data to a destination node through the assistance of multi-hop passive relays. We employ the time-switching (TS) protocol, enabling the relays to harvest energy from the received previous hop signal to support data forwarding. We first prove that the system throughput monotonically increases with the transmit power of the source node. Next, by employing logarithmic transformations, we convert the non-convex problem of obtaining optimal TS ratios at each relay to maximize the system throughput into a convex optimization problem. Comprehensively taking into account the convergence rate, computational complexity per iteration, and robustness, we selected the log barrier method—a type of interior point method—to address this convex optimization problem, along with providing a detailed implementation procedure. The simulation results validate the optimality of the proposed method and demonstrate its applicability to practical communication systems. For instance, the proposed scheme achieves 1437.3 bps throughput at 40 dBm maximum source power in a 2-relay network—278.6% higher than that of the scheme with TS ratio fixed at 0.75 (379.68 bps). On the other hand, it converges within a 1.36 ms computation time for 5 relays, 6 orders of magnitude faster than exhaustive search (1730 s).