Loading [MathJax]/extensions/MathZoom.js
Energy Efficiency–Spectral Efficiency Tradeoff: A Multiobjective Optimization Approach | IEEE Journals & Magazine | IEEE Xplore

Energy Efficiency–Spectral Efficiency Tradeoff: A Multiobjective Optimization Approach


Abstract:

In this paper, we consider the resource-allocation problem for energy efficiency (EE)-spectral efficiency (SE) tradeoff. Unlike traditional research that uses the EE as a...Show More

Abstract:

In this paper, we consider the resource-allocation problem for energy efficiency (EE)-spectral efficiency (SE) tradeoff. Unlike traditional research that uses the EE as an objective function and imposes constraints either on the SE or on the achievable rate, we propound a multiobjective optimization approach that can flexibly switch between the EE and SE functions or change the priority level of each function using a tradeoff parameter. Our dynamic approach is more tractable than the conventional approaches and more convenient to realistic communication applications and scenarios. We prove that the multiobjective optimization of the EE and SE is equivalent to a simple problem that maximizes the achievable rate/SE and minimizes the total power consumption. Then, we apply the generalized framework of the resource allocation for the EE-SE tradeoff to optimally allocate the subcarriers' power for orthogonal frequency-division multiplexing (OFDM) with imperfect channel estimation. Finally, we use numerical results to discuss the choice of the tradeoff parameter and study the effect of the estimation error, transmission power budget, and channel-to-noise ratio on the multiobjective optimization.
Published in: IEEE Transactions on Vehicular Technology ( Volume: 65, Issue: 4, April 2016)
Page(s): 1975 - 1981
Date of Publication: 23 April 2015

ISSN Information:


I. Introduction

The dramatic growth of wireless communication services and applications represents the main driving force to expand the existing wireless infrastructure and to deploy new systems. Although the communication networks may be able to support the increasing demand of high-data-rate and ubiquitous services, the energy consumption significantly increases, particularly at the base stations. This accounts for most of the energy consumption of cellular networks, which represents an important contribution of the information and communication technology industry to the global CO2 emission [1], [2]. Therefore, wireless communication systems have to be designed based on green metrics that reduce the energy consumption wisely, along with the associated CO2 emission [1], [2]. Energy efficiency (EE) is a widely used green communication metric, which is defined either as the number of successfully delivered bits per unit energy, which we adopt in this paper, or its inverse [3]. Although EE is the major design metric for environment-friendly future wireless communication systems, it conflicts with other traditional metrics such as spectral efficiency (SE) in bits per second per hertz [4]. The tradeoff between EE and SE states that the available system's resources cannot be optimized to improve both EE and SE simultaneously.

References

References is not available for this document.