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

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 capacit...

Full description

Saved in:
Bibliographic Details
Main Authors: Yuan Gao, Peng Xue, Yi Li, Hongyi Yu, Xianfeng Wang, Shihai Gao
Format: Article
Language:English
Published: Wiley 2015-08-01
Series:International Journal of Distributed Sensor Networks
Online Access:https://doi.org/10.1155/2015/472169
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1849397498707181568
author Yuan Gao
Peng Xue
Yi Li
Hongyi Yu
Xianfeng Wang
Shihai Gao
author_facet Yuan Gao
Peng Xue
Yi Li
Hongyi Yu
Xianfeng Wang
Shihai Gao
author_sort Yuan Gao
collection DOAJ
description 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.
format Article
id doaj-art-acd7307461824da78c11bfaf2a2fb97c
institution Kabale University
issn 1550-1477
language English
publishDate 2015-08-01
publisher Wiley
record_format Article
series International Journal of Distributed Sensor Networks
spelling doaj-art-acd7307461824da78c11bfaf2a2fb97c2025-08-20T03:38:59ZengWileyInternational Journal of Distributed Sensor Networks1550-14772015-08-011110.1155/2015/472169472169Energy Aware Optimal Resource Allocation in Backhaul Constraint Wireless Networks: A Two Base Stations ScenarioYuan Gao0Peng Xue1Yi Li2Hongyi Yu3Xianfeng Wang4Shihai Gao5 Information Science and Technology Institute, Zhengzhou 450002, China Naval Aeronautical and Astronautical University, Yantai 264000, China The High School Affiliated to Renmin University of China, Beijing 100030, China Information Science and Technology Institute, Zhengzhou 450002, China Information Science and Technology Institute, Zhengzhou 450002, China Information Science and Technology Institute, Zhengzhou 450002, ChinaIn 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.https://doi.org/10.1155/2015/472169
spellingShingle Yuan Gao
Peng Xue
Yi Li
Hongyi Yu
Xianfeng Wang
Shihai Gao
Energy Aware Optimal Resource Allocation in Backhaul Constraint Wireless Networks: A Two Base Stations Scenario
International Journal of Distributed Sensor Networks
title Energy Aware Optimal Resource Allocation in Backhaul Constraint Wireless Networks: A Two Base Stations Scenario
title_full Energy Aware Optimal Resource Allocation in Backhaul Constraint Wireless Networks: A Two Base Stations Scenario
title_fullStr Energy Aware Optimal Resource Allocation in Backhaul Constraint Wireless Networks: A Two Base Stations Scenario
title_full_unstemmed Energy Aware Optimal Resource Allocation in Backhaul Constraint Wireless Networks: A Two Base Stations Scenario
title_short Energy Aware Optimal Resource Allocation in Backhaul Constraint Wireless Networks: A Two Base Stations Scenario
title_sort energy aware optimal resource allocation in backhaul constraint wireless networks a two base stations scenario
url https://doi.org/10.1155/2015/472169
work_keys_str_mv AT yuangao energyawareoptimalresourceallocationinbackhaulconstraintwirelessnetworksatwobasestationsscenario
AT pengxue energyawareoptimalresourceallocationinbackhaulconstraintwirelessnetworksatwobasestationsscenario
AT yili energyawareoptimalresourceallocationinbackhaulconstraintwirelessnetworksatwobasestationsscenario
AT hongyiyu energyawareoptimalresourceallocationinbackhaulconstraintwirelessnetworksatwobasestationsscenario
AT xianfengwang energyawareoptimalresourceallocationinbackhaulconstraintwirelessnetworksatwobasestationsscenario
AT shihaigao energyawareoptimalresourceallocationinbackhaulconstraintwirelessnetworksatwobasestationsscenario