Energy efficient power allocation strategy for 5G carrier aggregation scenario
Abstract Carrier aggregation (CA) is considered to be a potential technology in next generation wireless communications. While boosting system throughput, CA has also put forward challenges to the resource allocation problems. In this paper, we firstly construct the energy efficiency optimization pr...
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Online Access: | http://link.springer.com/article/10.1186/s13638-017-0924-1 |
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doaj-b9a97c529a76498e958a8d539db083242020-11-24T21:08:05ZengSpringerOpenEURASIP Journal on Wireless Communications and Networking1687-14992017-08-012017111010.1186/s13638-017-0924-1Energy efficient power allocation strategy for 5G carrier aggregation scenarioWeidong Gao0Lin Ma1Gang Chuai2Beijing University of Posts and TelecommunicationsBeijing University of Posts and TelecommunicationsBeijing University of Posts and TelecommunicationsAbstract Carrier aggregation (CA) is considered to be a potential technology in next generation wireless communications. While boosting system throughput, CA has also put forward challenges to the resource allocation problems. In this paper, we firstly construct the energy efficiency optimization problem and prove that the function is strictly quasi concave. Then we propose a binary search-based power allocation algorithm to solve the strictly quasi concave optimization problem. Simulation results show that the proposed algorithm can greatly improve the system energy efficiency while keeping low computation complexity.http://link.springer.com/article/10.1186/s13638-017-0924-1Carrier aggregationPower allocationBinary searchStrictly quasi concaveOptimization |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Weidong Gao Lin Ma Gang Chuai |
spellingShingle |
Weidong Gao Lin Ma Gang Chuai Energy efficient power allocation strategy for 5G carrier aggregation scenario EURASIP Journal on Wireless Communications and Networking Carrier aggregation Power allocation Binary search Strictly quasi concave Optimization |
author_facet |
Weidong Gao Lin Ma Gang Chuai |
author_sort |
Weidong Gao |
title |
Energy efficient power allocation strategy for 5G carrier aggregation scenario |
title_short |
Energy efficient power allocation strategy for 5G carrier aggregation scenario |
title_full |
Energy efficient power allocation strategy for 5G carrier aggregation scenario |
title_fullStr |
Energy efficient power allocation strategy for 5G carrier aggregation scenario |
title_full_unstemmed |
Energy efficient power allocation strategy for 5G carrier aggregation scenario |
title_sort |
energy efficient power allocation strategy for 5g carrier aggregation scenario |
publisher |
SpringerOpen |
series |
EURASIP Journal on Wireless Communications and Networking |
issn |
1687-1499 |
publishDate |
2017-08-01 |
description |
Abstract Carrier aggregation (CA) is considered to be a potential technology in next generation wireless communications. While boosting system throughput, CA has also put forward challenges to the resource allocation problems. In this paper, we firstly construct the energy efficiency optimization problem and prove that the function is strictly quasi concave. Then we propose a binary search-based power allocation algorithm to solve the strictly quasi concave optimization problem. Simulation results show that the proposed algorithm can greatly improve the system energy efficiency while keeping low computation complexity. |
topic |
Carrier aggregation Power allocation Binary search Strictly quasi concave Optimization |
url |
http://link.springer.com/article/10.1186/s13638-017-0924-1 |
work_keys_str_mv |
AT weidonggao energyefficientpowerallocationstrategyfor5gcarrieraggregationscenario AT linma energyefficientpowerallocationstrategyfor5gcarrieraggregationscenario AT gangchuai energyefficientpowerallocationstrategyfor5gcarrieraggregationscenario |
_version_ |
1716760896746815488 |