No abstract

In this paper, energy efficient uplink communications are investigated for battery-constrained mobile terminals (MTs) with service quality requirements and multi-homing capabilities. A heterogeneous wireless medium is considered, where MTs communicate with base stations (BSs) and access points (APs) of different networks with overlapped coverage. Different from the existing works, we develop a quality of service (QoS)-based optimization framework for joint uplink bandwidth and power allocation to maximize energy efficiency for a set of MTs with multi-homing capabilities. The proposed framework is implemented in a decentralized architecture, through coordination among BSs/APs of different networks and MTs, which is a desirable feature when different networks are operated by different service providers. A suboptimal framework is presented with a reduced computational complexity as compared with the optimal framework. Simulation results demonstrate the improved performance of both the optimal and suboptimal frameworks over a state-of-the-art benchmark.Index Terms-Energy efficient communications, green communications, multi-homing resource allocation, heterogeneous wireless medium.

No abstract

No abstract

This paper investigates energy efficient uplink communications for battery-constrained mobile terminals (MTs). We consider a heterogeneous wireless medium where MTs communicate with base stations (BSs) and access points (APs) of different networks with overlapped coverage. Unlike the existing research, we develop a joint bandwidth and power allocation framework that maximizes energy efficiency for a set of MTs, in different service areas, with best effort service and multi-homing capabilities. The problem formulation captures the heterogeneity of the medium, in terms of different service areas, channel conditions, available resources at BSs/APs of different networks, and different available maximum power at the MTs. In addition, the framework is implemented in a decentralized manner which is desirable in a case that different networks are operated by different service providers. Simulation results are presented to demonstrate the performance of the proposed framework.Index Terms-Energy efficiency, heterogeneous wireless medium, multi-homing resource allocation, joint bandwidth and power allocation, fractional programming.