Spectrum Efficiency and Energy Efficiency in Wireless Communication Networks

Abstract

In the October 2020 issue of IEEE Wireless Communications Magazine, we are pleased to present a special issue on “Spectrum and Energy Efficient Wireless Communications” with a collection of 12 articles. In this issue, we are also very glad to present 12 articles accepted from the open call. Driven by new-generation mobile devices and bandwidth consuming applications such as video streaming, wireless traffic volume is expected to continue expanding tremendously in the next few years. Sustaining this growing trend will in turn require higher spectrum capacity from the network side. Research has shown that capacity demand increases much faster than the current spectrum efficiency improvement, in particular at hot spot areas. From recent data, global mobile data traffic increased nearly 11-fold in the last few years. In contrast, the peak data rate from 3G wireless technology to 4G wireless technology only increased 55 percent in the last decade. Clearly there is a huge gap between the capacity growth of new wireless access technologies and the fast growth of wireless traffic volume for the next-generation wireless networks. In the meantime, energy efficiency, commonly defined as information bits per unit of energy, has become another essential requirement for the design of future wireless communication networks besides spectrum efficiency. Energy efficient communications have attracted great attention due to the ever-increasing demand to preserve energy resources and to protect the environment. Furthermore, mobile devices, such as smart phones and tablets, are widely used to conduct new applications such as video content distribution, location-aware advertisement, video chatting, video streaming, music and movie downloading, etc. In the year 2012, mobile video traffic exceeded 50 percent of the total wireless traffic volume for the first time. Mobile video has increased 14-fold since then, accounting for 69 percent of the total mobile data traffic by the end of last year. How to support energy and bandwidth consuming video applications with high QoE is becoming another challenging issue in future wireless networks. Clearly, there is an urgency for a new disruptive paradigm to bridge the gap between the increasing capacity, energy and QoE demands and the deficiency of radio spectrum resources. As wireless channel efficiency is approaching its fundamental limit, improvements in future wireless system capacity can be alternatively realized by networking technologies such as node density increase through underlay and overlay deployments, or by going to a higher spectrum such as millimeter wave to seek more spectrum bandwidth. In addition to delivering the required network spectrum efficiency, energy efficiency and QoE, the anticipated tremendous proliferation of machine-type devices and consumer-wearable devices also makes the underlay wireless network desirable. These small devices usually have limited onboard processing power and battery size. If they need powerful computing capability to process extensive content information, they will have to heavily rely on their surrounding local networks and computing platforms to facilitate these computing-intensive and thus power consuming applications. Using high performance and very low latency communication links to offload mobile device computing load into nearby powerful computing clouds becomes an essential direction to pursue. This paradigm shift in the next decade also calls for the cluster-based underlay networking technologies, in which a cluster head of a number of underlay devices can be selected as the representative of the entire cluster for both communication and control purposes. Spectrum and energy efficient wireless communications is one of the most important topics today in the next generation wireless networking area, and attracting more and more attention from industry, research, and academia. This special issue focuses on the challenges and novel solutions for spectrum and energy efficient wireless communication networks. Thanks to the guest editors, Q. Liang, T. S. Durrani, J. Koh, Q. Wu, and X. Wang, who did an excellent job in editing this special issue for our readers. Please stay tuned for new developments in the research area of spectrum and energy efficient wireless communications, and read the editorial for more details about the papers in this special issue. In addition to the 12 articles in the special issue, we have also included 12 accepted open call articles. The first article, “Dense Small Satellite Networks for Modern Terrestrial Communication Systems: Benefits, Infrastructure, and Technologies” by N. Hassan et al., demonstrates several components of dense small satellite networks (DSSN) infrastructure, including satellite formations, orbital paths, inter-satellite communication links, and communication architectures for data delivery from source to destination. It also reviews important technologies for DSSN as well as the challenges involved in the use of these technologies in DSSN. Several open research directions to enhance the benefits of DSSN for MTCS are also identified in the article. A case study showing the integration benefits of DSSN in mobile terrestrial communication systems is also included. The second article, “Overcoming the Channel Estimation Barrier in Massive MIMO Communication via Deep Learning” by Z. Liu et al., discusses the application of deep learning (DL) for massive MIMO channel estimation in wireless networks by integrating the underlying characteristics of channels in future high-speed cellular deployment. It develops important insights derived from the physical radio frequency channel properties and presents a comprehensive overview on the application of DL for accurately estimating channel state information (CSI) with low overhead. The article provides examples of successful DL application in CSI estimation for massive MIMO wireless systems and highlights several promising directions for future research. In the third article, “Energy-aware Task Offloading in Internet of Things”, J. Li et al. introduce a new energy-aware task offloading scheme in IoT to determine the optimal offloading strategy. First, they investigate the architecture of mobile edge computing (MEC) in IoT. Second, they discuss the challenges of task offloading in MEC for IoT. Third, they propose the framework of task offloading for MEC, the optimal offloading strategy for computing task is achieved. Finally, the article demonstrates experiment results to show that the proposed scheme can significantly improve the efficiency of task offloading compared with the conventional scheme. Yi Qian