Optimizing Spectrum-Energy Efficiency in Downlink Cellular Networks

The popularity of smart mobile devices has brought significant growth of data services for mobile service providers. Mobile users of data services are charged based on the amount of data used. Raising served data amount seemingly increases the profit; energy consumption rises correspondingly. Beside...

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Bibliographic Details
Published in:IEEE transactions on mobile computing 2014-09, Vol.13 (9), p.2100-2112
Main Authors: Chan-Ching Hsu, Chang, J. Morris, Zi-Tsan Chou, Abichar, Zakhia
Format: Magazinearticle
Language:English
Subjects:
Computation
Computational efficiency
Computing time
Cost engineering
Economics
Energy consumption
Energy efficiency
energy saving
Heuristic
integer linear programming
Mobile communication
Mobile computing
network optimization
NIST
Operators
Optimization
Profits
revenue-cost ratio
spectrum efficiency
Switches
Wireless networks
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Summary:The popularity of smart mobile devices has brought significant growth of data services for mobile service providers. Mobile users of data services are charged based on the amount of data used. Raising served data amount seemingly increases the profit; energy consumption rises correspondingly. Besides, spectral resources are licensed and limited for mobile operators to allocate. Increasing data services over the spectrum for the profit does not count the cost of energy. To assess the profitability, considered is the revenue-to-cost ratio. Optimizing the ratio is an economic incentive for mobile operators. Revenue is regarded as efficiency in spectrum use, the cost as energy consumption; therefore we interpret the revenue-to-cost ratio as spectrum-energy efficiency. In this paper, we study the spectrum-energy efficiency optimization problem where BSs are with the ability to perform cell zooming, sleep mode, and user migration. We formulate the problem into an integer linear program which is solvable by CPLEX to maximize spectrum-energy efficiency; meanwhile traffic demands by associated users in multicell/multiuser networks are met. To avoid high computation time, a heuristic algorithm is proposed to efficiently solve the formulated problem. Numerical analysis through case studies demonstrates energy consumption and efficiency improvements, and comparisons between near-optimal solutions against optimality.
ISSN:1536-1233
1558-0660
DOI:10.1109/TMC.2013.99