A Unified Energy Efficiency and Spectral Efficiency Tradeoff Metric in Wireless Networks

• Published in: IEEE communications letters Vol. 17; no. 1; pp. 55 - 58
• Main Authors: Lei Deng, Yun Rui, Peng Cheng, Jun Zhang, Zhang, Q. T., Mingqi Li
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.01.2013; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Applied sciences; Computational efficiency; Computer science; control theory; systems; Computer systems and distributed systems. User interface; Computing time; Downlink; EE and SE tradeoff (EST); Energy efficiency (EE); Exact sciences and technology; Mathematical analysis; Mathematical models; Mathematical programming; Measurement; multi-object optimization (MOO); Networks; Operational research and scientific management; Operational research. Management science; Optimization; Optimized production technology; Pareto optimality; Pareto optimization; Software; Spectra; spectral efficiency (SE); Systems, networks and services of telecommunications; Telecommunications; Telecommunications and information theory; Transmission and modulation (techniques and equipments); Wireless networks; Energy spectrum; Energy consumption; Energy efficiency (EE); Pareto optimum; Multiobjective programming; Scalarization; Distributed system; Energy savings; Efficiency; Optimal solution; spectral efficiency (SE); Wireless network; EE and SE tradeoff (EST); multi-object optimization (MOO); Metric; Objective function; By product; Mathematical programming
• ISSN: 1089-7798; 1558-2558
• DOI: 10.1109/LCOMM.2012.112812.121744

In this letter, we propose a unified metric for energy efficiency (EE) and spectral efficiency (SE) tradeoff design in wireless networks. Different from previous EE-based or SE-based design, we simultaneously optimize both EE and SE. First, we formulate our design problem as a multi-object optimization (MOO) problem, in which the Pareto optimal set is characterized. After normalizing EE and SE to make them comparable, we then convert the MOO problem into a single-object optimization (SOO) problem by the weighted product scalarization method. We further show that the objective function of this SOO problem, i.e., our proposed EE and SE tradeoff (EST) metric, is quasi-concave with the transmit power and a unique globally optimal solution is derived. Numerical results validate the effectiveness of the proposed unified EST metric.