Due to global warming, the reduction of energy consumption has become a significantly important issue. According to the international energy agency (IEA), the amount of global $CO_2$ emissions showed the highest increase by 1.0 Gt (3.2% of total 31.6 Gt) recorded in 2011. Unless we keep the annual $CO_2$ emissions lower than 44 Gt until year 2020, the Earth will encounter extensive ecosystem failures. Hence, the energy saving efforts are required in all the industrial and commercial fields including information communication technologies (ICTs). Within the ICT, wireless base stations (BSs) are known to consume approximately 80% of the total energy used in wireless networks.
Moreover, wide penetration of smartphones has drastically increased wireless data traffic. According to Cisco, the compound annual growth rate (CAGR) of the global wireless data traffic is forecasted to be 78%. Particularly, in the United States, wireless data traffic increased 123% from 2010 to 2011 (CTIA). Within five years, wireless data traffic is expected to be approximately 18 times higher than the present traffic. Thus, service providers should increase network capacity by more than 80% each year to resolve such a tremendous traffic growth. Among the solutions for this traffic increment such as installing new bases stations or upgrading the cellular network into a next-generation network, WiFi offloading has been spotlighted with its cheap capital and operation expenditure (CAPEX/ OPEX). With WiFi offloading, users offload the cellular networks using overlapped WiFi networks.
In this dissertation, we focus on the research of energy-efficient BS architectures. First, we propose a practical BS power consumption model and compare the performance of various BS architectures in terms of throughput and energy efficiency. We consider a BS power consumption model with more realistic environments such as walls, temperature, the number of antennas, and behavior of IT components. Moreover, we model various BS architectures such as the conventional macro-cell based BS architecture, a micro-cell based BS architecture, and a distributed remote radio head (RRH)-based BS architecture. Through numerical results, we investigate the effect of the number of transmitters in an area and the active user density on the entire BS power consumption and energy efficiency.
In addition, we focus on the research of an energy-efficient multi-mode integrated BS architecture. In a heterogeneous network which consists of multiple wireless networks (such as cellular and IEEE 802.11-based WiFi networks), mobile terminals with multiple wireless module can simultaneously utilize different networks. Consequently, from the current multi-mode environment, a multi-mode integrated BS architecture can enhance the network performance. In this dissertation, we propose both centralized and decentralized WiFi-offloading models for maximizing throughput in a heterogeneous network. Through numerical results, a user and the heterogeneous network with the proposed models achieve 20% higher throughput than the conventional on-the-spot WiFi-offloading model in a dense traffic environment.