Society has grown increasingly aware of the need to reduce CO2 emissions in order to mitigate consequential environmental effects. The primary contributors to CO2 emissions are electric power generation, transport, and manufacturing. Information and Communications Technology (ICT) at present contributes a non-negligible 3% of world-wide energy consumption, which in turn causes about 2% of the world-wide CO2 emissions. The dramatic growth in Internet traffics and the growing pervasive use of mobile and wireless technologies to support this are likely to increase CO2 emissions in the future unless greater energy efficiency can be achieved in networking technologies. Thus, thedevelopment of wireless networks that require lower energy consumption is desirable. In addition to this key driver of reducing CO2 emissions, the cost of energy has increased substantially and this is a significant proportion of the costs of any wireless access infrastructure company. These issues have resulted in an increased interest in “green radio” networks that reduce the energy requirements for wireless communications, and can thus contribute not only to goals for sustainable development, but also to the profitability of the telecommunication industry. Although green radio can be justified in the context of energy consumption as noted above, it also can be viewed in a wider sense, such as in the optimization of spectrum usage to reduce electromagnetic radiation levels in order to enable coexistence of multiple wireless systems (i.e., less interference) as well as to reduce human exposure to radiation, in the recycling and reuse of ICT equipment, and in many other related contexts. There are 17 papers in this special issue. It is difficult to classify these papers into distinct categories, as many of them deal with several aspects of green radio. Nevertheless, the classification proposed by Luis Suarez, Loutfi Nuaymi, and Jean-Marie Bonnin in their overview paper (see below) seems very appropriate for classifying these papers and, referring to Figure 1, we can make use of this classification as follows. In particular, this special issue has assembled papers dealing with network considerations at large (both indoor and outdoor networks), with the cell layout adaptation (CLA) level (six papers), and with efficient techniques for the radio resource management and optimal transmission (EE-RRM-OT) layer (seven papers). Moreover, three papers deal with cognitive radio networks, belonging to the environment learning & information exchange (EL-IE) layer, while two others deal specifically with component optimization aspects, pertaining to the component baseline layer, and one provides a tutorial on some green radio topics. The paper providing an overview of green radio is “An overview and classification of research approaches in green wireless networks” by Luis Suarez, Loutfi Nuaymi, and Jean-Marie Bonnin. It provides an overview of research directions, both at the component level and at the network level. This overview provides an interesting classification, as noted above, and in addition describes major projects dedicated to green radio. It incorporates 76 references, which provide resources for further reading on all aspects of the subject. Among the six papers dealing with the CLA layer, the paper entitled “Mobile operators have set ambitious targets—is it possible to boost network capacity while reducing its energy consumption?” by Gilbert Micallef, Preben Mogensen, and Hans-Otto Scheck, deals with the challenges faced by telecommunication operators. It quantifies, through a number of case studies, the impact of specific solutions and how the energy consumption trend can be expected to develop over the next decade. It shows that a hybrid macrocell-picocell upgrade is more energy-efficient than a macrocell or picocell only solution. Results show that network operators can get relatively close to their targets, with energy reductions of up to 40%. The next paper, entitled “Evaluation of the potential for energy saving in macrocell and femtocell networks using a heuristic introducing sleep modes in base stations” by Willem Vereecken, Margot Deruyck, Didier Colle, Wout Joseph, Mario Pickavet, Luc Martens, and Piet Demeester, deals with sleep modes for base stations. It derives a heuristic that can serve as a design tool for establishing a baseline. The authors demonstrate * Correspondence: jacques.palicot@supelec.fr SUPELEC/IETR Avenue de la Boulais, CS 47601, Cesson-Sevigne Cedex 35576, France Full list of author information is available at the end of the article
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Open Access
Jan 1, 2024
Yuval Cohen + 1
