Energy-optimal base station density in cellular access networks with sleep modes |
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| Affiliation: | 1. Department of Electrical Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong (Special Administrative Region);2. School of Electrical and Electronic Engineering, Engineering Campus, Universiti Sains Malaysia, Penang, Malaysia;3. Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur, Malaysia;4. Department of Electrical and Computer Engineering, Texas A&M University, College Station, Texas, USA;5. Department of Electronic Engineering, University of Science and Technology, Sana''a, Yemen;6. Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong (Special Administrative Region);1. Preventive Medicine Department, Hospital Universitari de Bellvitge, Institut d''Investigació Biomèdica de Bellvitge, L''Hospitalet de Llobregat, Barcelona, Spain;2. Microbiology Department, Hospital Universitari de Bellvitge, Institut d''Investigació Biomèdica de Bellvitge, L''Hospitalet de Llobregat, Barcelona, Spain;3. Intensive Care Department, Hospital Universitari de Bellvitge, Institut d''Investigació Biomèdica de Bellvitge, L''Hospitalet de Llobregat, Barcelona, Spain;4. Infectious Diseases Department, Hospital Universitari de Bellvitge, Institut d''Investigació Biomèdica de Bellvitge, L''Hospitalet de Llobregat, Barcelona, Spain |
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| Abstract: | Sleep modes are widely accepted as an effective technique for energy-efficient networking: by adequately putting to sleep and waking up network resources according to traffic demands, a proportionality between energy consumption and network utilization can be approached, with important reductions in energy consumption. Previous studies have investigated and evaluated sleep modes for wireless access networks, computing variable percentages of energy savings. In this paper we characterize the maximum energy saving that can be achieved in a cellular wireless access network under a given performance constraint. In particular, our approach allows the derivation of realistic estimates of the energy-optimal density of base stations corresponding to a given user density, under a fixed performance constraint. Our results allow different sleep mode proposals to be measured against the maximum theoretically achievable improvement. We show, through numerical evaluation, the possible energy savings in today’s networks, and we further demonstrate that even with the development of highly energy-efficient hardware, a holistic approach incorporating system level techniques is essential to achieving maximum energy efficiency. |
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| Keywords: | Green networking Cellular networks Sleep modes |
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