CEAR: A cooperation based energy aware reward scheme for next generation green cognitive radio networks

Cognitive Radio (CR) networks are envisioned as a key empowering technology of the fifth-generation (5G) wireless communication networks, which solves the major issues of 5G, like high-speed data transmission, seamless connectivity, and increased demand for mobile data. Another significant characteristic of the 5G network is green communications, as energy consumption from the communication field is predicted to rise remarkably by the year 2030. In this work, we are concerned about energy-related issues and propose a cooperation-based energy-aware reward scheme (CEAR) for next-generation green CR networks. The proposed CEAR scheme is based on the antenna and temporal diversity of the primary users (PUs). For providing the service to the PUs, the users of another network called cognitive users (CUs) work as a cooperative relay node, and, in return, they get more spectrum access opportunities as a reward from the primary network. The CUs with delay-tolerant data packets take a cooperative decision by recognizing the availability and traffic load of PUs, channel state information, and data transmission requirements. We utilize the optimal stopping protocol for solving the decision-making problem and use the backward induction method to obtain the optimal cooperative solution. The simulation results reveal notable enhancements in energy efficiency (EE) of CUs compared with other cooperative schemes. The proposed CEAR scheme is more energy-efficient for ultra-dense network deployment because results show that the CU’s EE, spectral efficiency (SE), and throughput improved with the increase of PUs.     

A survey on UAV placement optimization for UAV-assisted communication in 5G and beyond networks

With the increase in capacity demands and the requirement of ubiquitous coverage in the fifth generation and beyond wireless communications networks, unmanned aerial vehicles (UAVs) have acquired a great attention owing to their outstanding characteristics over traditional base stations and relays. UAVs can be deployed faster and with much lower expenditure than ground base stations. In addition, UAVs can enhance the network performance thanks to their strong line-of-sight link conditions with their associated users and their dynamic nature that adapts to varying network conditions. Optimization of the UAV 3D locations in a UAV-assisted wireless communication network was considered in a large body of research as it is a critical design issue that greatly affects communication performance. Although the topic of UAV placement optimization was considered in few surveys, these surveys reviewed only a small part of the growing literature. In addition, the surveys were brief and did not discuss many important design issues such as the objectives of the optimization problem, the adopted solution techniques, the air-to-ground channel models, the transmission media for access and backhaul links, the limited energy nature of the UAV on-board batteries, co-channel interference and spectrum sharing, the interference management, etc. Motivated by the importance of the topic of UAV placement optimization as well as the need for a detailed review of its recent literature, we survey 100 of the recent research papers and provide in-depth discussion to fill the gaps found in the previous survey papers. The considered research papers are summarized and categorized to highlight the differences in the deployment scenario and system model, the optimization objectives and parameters, the proposed solution techniques, and the decision-making strategies and many other points. We also point to some of the existing challenges and potential research directions that have been considered in the surveyed literature and that requires to be considered     

Characterization of MmWave Full-Duplex Cloud-Radio Access Network (C-RAN) with RRH Selection for 5G and Beyond

In this paper, a millimeter-wave (mmWave) full-duplex (FD) cloud radio access network (C-RAN) for 5G and beyond systems is studied, where the central unit is equipped with multiple antennas, and the spatially distributed remote radio heads (RRHs) operate in FD mode. In particular, we analyze a relay selection method based on end-to-end signal to interference plus noise ratio (SINR) in the proposed system. Distinguishing features of mmWave communications such as Rician small scale fading, path loss, blockage and directivity are taken into account in both fronthaul (FH) and access links. In order to have a comparison basis, the performance of the RRH selection method is also investigated in half-duplex (HD) mmWave C-RAN. Initially, the expression of the end-to-end SINR in the proposed system is derived, and then the cumulative density function (CDF) of the end-to-end SINR is derived in both FD and HD RRHs. Subsequently, we derive performance expressions such as outage probability, average rate and energy efficiency for the RRH selection method in the proposed system in both HD and FD mmWave C-RAN. Finally, the effectiveness of the RRH selection method and the accuracy of the obtained results are verified via Monte Carlo simulation results, which show that the RRH selection method in the mmWave FD C-RAN improves the performance significantly.