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.