Energy Aware Optimal Resource Allocation in Backhaul Constraint Wireless Networks: A Two Base Stations Scenario

Yuan Gao,Hongyi Yu,Xianfeng Wang,Peng Xue,Shihai Gao,Yi Li

doi:10.1155/2015/472169

Abstract

In future wireless communication systems, the capacity constrained backhaul gradually becomes bottleneck both in spectrum efficiency and energy efficiency, especially in joint processing of LTE-Advanced. This paper addresses the issue of energy aware resource allocation with limited backhaul capacity in uplink cooperative reception, where two base stations (BSs) equipped with single-antenna each serving multiple users with single-antenna via multicarrier are considered. We propose a novel energy efficient cooperative scheme based on compress-and-forward and user pairing to solve the problem in two base stations scenario. In order to maximize system throughput and increase energy efficiency under the limited backhaul capacity constraint, we formulate the joint optimization problem of user pairing, subcarrier mapping, and backhaul capacity sharing between different pairs (subcarriers). An energy efficient algorithm based on alternating optimization strategy and perfect mapping is proposed to solve this mixed integer programming problem. Simulations show that this allocation algorithm can improve the system capacity and energy efficiency significantly compared with the blind alternatives.

Highlights

With the increasing demand of higher transmission rate and more reliable QoS in wireless personal communications, cooperative schemes are in great need to meet the demand of users, including the cell-edge user with poor performance
We evaluate the performance of our algorithm on the MALAB platform
We have evaluated the sum rate of users in both cells achieved by our algorithm under different backhaul capacity

Summary

Introduction

With the increasing demand of higher transmission rate and more reliable QoS in wireless personal communications, cooperative schemes are in great need to meet the demand of users, including the cell-edge user with poor performance. Base stations are usually in normal load and are not capable for on-off control frequently; on the contrary, in the night time, number of users that require data traffic are far more small than that in the daytime, so there exists the chance to shut down the idle base stations according to the actual status of the data traffic. This is the most effective method to reduce energy consumption due to the architecture of the wireless network [5, 6]. The large amount of cooperative data will cost much resource such as signal processing and transmission, which

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