The standardization activities of the fifth generation communications are clearly over and deployment has commenced globally. To sustain the competitive edge of wireless networks, industrial and academia synergy have begun to conceptualize the next generation of wireless communication systems (namely, sixth generation, (6G)) aimed at laying the foundation for the stratification of the communication needs of the 2030s. In support of this vision, this study highlights the most promising lines of research from the recent literature in common directions for the 6G project. Its core contribution involves exploring the critical issues and key potential features of 6G communications, including: (i) vision and key features; (ii) challenges and potential solutions; and (iii) research activities. These controversial research topics were profoundly examined in relation to the motivation of their various sub-domains to achieve a precise, concrete, and concise conclusion. Thus, this article will contribute significantly to opening new horizons for future research directions.

Energy efficiency in cellular networks has increasingly become important to the cellular network operators due to its significant economic and ecological influence in the forthcoming generation of wireless networks, ie, the fifth-generation (5G) network. To pursue a vision of green communication, this study presents a comprehensive overview and discusses how the key physical layer techniques that will be adopted in the 5G technology can improve energy efficiency to achieve a sustainable wireless network. Among the key 5G technologies discussed are massive multiple-input multiple-output, green heterogeneous networks, green millimeter wave, green 5G device-to-device communication, green machine-to-machine communication, and energy-efficient 5G architecture. The review concludes that the 5G technology will soon fulfill the critical requirements of low-energy network while maintaining services with high performance. Potential research opportunities related to green 5G are also highlighted at the end of the article.

Machine learning techniques will contribution towards making Internet of Things (IoT) symmetric applications among the most significant sources of new data in the future. In this context, network systems are endowed with the capacity to access varieties of experimental symmetric data across a plethora of network devices, study the data information, obtain knowledge, and make informed decisions based on the dataset at its disposal. This study is limited to supervised and unsupervised machine learning (ML) techniques, regarded as the bedrock of the IoT smart data analysis. This study includes reviews and discussions of substantial issues related to supervised and unsupervised machine learning techniques, highlighting the advantages and limitations of each algorithm, and discusses the research trends and recommendations for further study.

Recently, cellular networks’ energy efficiency has garnered research interest from academia and industry because of its considerable economic and ecological effects in the near future. This study proposes an approach to cooperation between the Long-Term Evolution (LTE) and next-generation wireless networks. The fifth-generation (5G) wireless network aims to negotiate a trade-off between wireless network performance (sustaining the demand for high speed packet rates during busy traffic periods) and energy efficiency (EE) by alternating 5G base stations’ (BSs) switching off/on based on the traffic instantaneous load condition and, at the same time, guaranteeing network coverage for mobile subscribers by the remaining active LTE BSs. The particle swarm optimization (PSO) algorithm was used to determine the optimum criteria of the active LTE BSs (transmission power, total antenna gain, spectrum/channel bandwidth, and signal-to-interference-noise ratio) that achieves maximum coverage for the entire area during the switch-off session of 5G BSs. Simulation results indicate that the energy savings can reach 3.52 kW per day, with a maximum data rate of up to 22.4 Gbps at peak traffic hours and 80.64 Mbps during a 5G BS switched-off session along with guaranteed full coverage over the entire region by the remaining active LTE BSs.

The success of a rural wireless monitoring system depends on establishing a reliable wireless link over the TCP/IP communication protocol in a challenging terrain and elevation profile. Several studies have shown that link reliability in a rural area can neither be predicted with high accuracy nor precisely modeled using existing mathematical channel modeling tools. Hence, the use of the empirical approach to infer wireless link reliability. This work focuses on the revival of a rural hydrological/water monitoring system with emphasis on the wireless link located in Tasik Chini, a lake with UNESCO biosphere status. The contributions of this study include: understudy the link reliability of a centralized wireless sensor network infrastructure system using the 2G and Long Range (LoRa) wireless network, the performance limitation of the low data wireless sensor network in a rural environment, approaches to revive rural water station monitoring center and finally highlight potential opportunities in rural wireless communications. View less Metadata Advertisement