Showing papers by "Congzheng Han published in 2011"
TL;DR: The technical background to the VCE Green Radio project is discussed, models of current energy consumption in base station devices are discussed and some of the most promising research directions in reducing the energy consumption of future base stations are described.
Abstract: Recent analysis by manufacturers and network operators has shown that current wireless networks are not very energy efficient, particularly the base stations by which terminals access services from the network. In response to this observation the Mobile Virtual Centre of Excellence (VCE) Green Radio project was established in 2009 to establish how significant energy savings may be obtained in future wireless systems. This article discusses the technical background to the project and discusses models of current energy consumption in base station devices. It also describes some of the most promising research directions in reducing the energy consumption of future base stations.
793 citations
TL;DR: This study addresses a number of key radio resource management strategies across PHY and MAC layers for reducing base station energy consumption, as measured by a ‘Joules per bit’ metric.
Abstract: Mobile communication industries are increasingly contributing to the worldwide energy consumption and CO2 emission. This study addresses a number of key radio resource management (RRM) strategies across PHY and MAC layers for reducing base station energy consumption, as measured by a ‘Joules per bit’ metric. These strategies including power efficient link adaptation, exploitation of multi-user diversity and trading bandwidth for energy efficiency. By collectively taking advantage of those RRM strategies, a multi-user adaptive power and resource allocation algorithm is proposed to ease the power requirements of a base station, while maintaining the same levels of service to the user. The scheduling algorithm is applied to an LTE downlink simulator and its performance is evaluated for various traffic load conditions. The results show that the proposed algorithm achieves a significant energy saving (up to 86%) over a conventional non-energy aware resource allocation scheme. Furthermore, the energy efficiency performance of various multiple antenna techniques is evaluated along with the impact of control signalling overhead. These multiple antenna schemes are then incorporated into the proposed scheduling algorithm and the additional achievable energy savings are quantified.
38 citations
01 Dec 2011
TL;DR: This paper presents a number of key radio resource management strategies across physical and medium access control layers for reducing base station energy consumption including power efficient link adaptation (LA), exploitation of multi-user diversity and trading bandwidth for energy efficiency.
Abstract: This paper presents a number of key radio resource management strategies across physical (PHY) and medium access control (MAC) layers for reducing base station energy consumption including power efficient link adaptation (LA), exploitation of multi-user diversity and trading bandwidth for energy efficiency. By collectively taking advantage of these radio resource management strategies, a multi-user adaptive power and resource allocation algorithm is proposed to ease the power requirements of a base station, whilst maintaining the same levels of service. The scheduling algorithm is evaluated within a LTE downlink simulator for various traffic load conditions. The results show that the proposed algorithm achieves a significant energy saving over a conventional non-energy aware resource allocation scheme.
20 citations