To improve the data rate in OFDMA-based wireless networks, Carrier Aggregation (CA) technology has been included in the LTE-Advanced standard. Different Carrier Component (CC) capacities of users under the same eNodeB (eNB, i.e. Base Station) make it challenging to allocate resources with CA. In this paper, we jointly consider CC and Resource Block (RB) assignments, and power allocation to achieve proportional fairness in the long term. The goal of the problem is to maximize the overall throughput with fairness consideration. We consider a more general CC assignment framework that each User Equipment (UE) (i.e. Mobile Station) can support any number of CCs. Furthermore, we have proved the problem is NP-hard, even if power is equally allocated to RBs. Thus, first an optimal RB assignment and power allocation algorithm is proposed and then a carrier aggregation enabled joint resource allocation algorithm called CARA is proposed. By jointly considering CC and RB assignments, and power allocation, the proposed approach can achieve better performance. Simulation results show the proposed algorithm can significantly improve performance, e.g., total throughput compared with the existing algorithm.
Zanjie HUANG
University of Science and Technology of China
Yusheng JI
National Institute of Informatics
Hao ZHOU
University of Science and Technology of China
Baohua ZHAO
University of Science and Technology of China
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Zanjie HUANG, Yusheng JI, Hao ZHOU, Baohua ZHAO, "Joint Resource Allocation Algorithm in Carrier Aggregation Enabled Future Wireless Networks" in IEICE TRANSACTIONS on Fundamentals,
vol. E97-A, no. 1, pp. 78-85, January 2014, doi: 10.1587/transfun.E97.A.78.
Abstract: To improve the data rate in OFDMA-based wireless networks, Carrier Aggregation (CA) technology has been included in the LTE-Advanced standard. Different Carrier Component (CC) capacities of users under the same eNodeB (eNB, i.e. Base Station) make it challenging to allocate resources with CA. In this paper, we jointly consider CC and Resource Block (RB) assignments, and power allocation to achieve proportional fairness in the long term. The goal of the problem is to maximize the overall throughput with fairness consideration. We consider a more general CC assignment framework that each User Equipment (UE) (i.e. Mobile Station) can support any number of CCs. Furthermore, we have proved the problem is NP-hard, even if power is equally allocated to RBs. Thus, first an optimal RB assignment and power allocation algorithm is proposed and then a carrier aggregation enabled joint resource allocation algorithm called CARA is proposed. By jointly considering CC and RB assignments, and power allocation, the proposed approach can achieve better performance. Simulation results show the proposed algorithm can significantly improve performance, e.g., total throughput compared with the existing algorithm.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E97.A.78/_p
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@ARTICLE{e97-a_1_78,
author={Zanjie HUANG, Yusheng JI, Hao ZHOU, Baohua ZHAO, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Joint Resource Allocation Algorithm in Carrier Aggregation Enabled Future Wireless Networks},
year={2014},
volume={E97-A},
number={1},
pages={78-85},
abstract={To improve the data rate in OFDMA-based wireless networks, Carrier Aggregation (CA) technology has been included in the LTE-Advanced standard. Different Carrier Component (CC) capacities of users under the same eNodeB (eNB, i.e. Base Station) make it challenging to allocate resources with CA. In this paper, we jointly consider CC and Resource Block (RB) assignments, and power allocation to achieve proportional fairness in the long term. The goal of the problem is to maximize the overall throughput with fairness consideration. We consider a more general CC assignment framework that each User Equipment (UE) (i.e. Mobile Station) can support any number of CCs. Furthermore, we have proved the problem is NP-hard, even if power is equally allocated to RBs. Thus, first an optimal RB assignment and power allocation algorithm is proposed and then a carrier aggregation enabled joint resource allocation algorithm called CARA is proposed. By jointly considering CC and RB assignments, and power allocation, the proposed approach can achieve better performance. Simulation results show the proposed algorithm can significantly improve performance, e.g., total throughput compared with the existing algorithm.},
keywords={},
doi={10.1587/transfun.E97.A.78},
ISSN={1745-1337},
month={January},}
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TY - JOUR
TI - Joint Resource Allocation Algorithm in Carrier Aggregation Enabled Future Wireless Networks
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 78
EP - 85
AU - Zanjie HUANG
AU - Yusheng JI
AU - Hao ZHOU
AU - Baohua ZHAO
PY - 2014
DO - 10.1587/transfun.E97.A.78
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E97-A
IS - 1
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - January 2014
AB - To improve the data rate in OFDMA-based wireless networks, Carrier Aggregation (CA) technology has been included in the LTE-Advanced standard. Different Carrier Component (CC) capacities of users under the same eNodeB (eNB, i.e. Base Station) make it challenging to allocate resources with CA. In this paper, we jointly consider CC and Resource Block (RB) assignments, and power allocation to achieve proportional fairness in the long term. The goal of the problem is to maximize the overall throughput with fairness consideration. We consider a more general CC assignment framework that each User Equipment (UE) (i.e. Mobile Station) can support any number of CCs. Furthermore, we have proved the problem is NP-hard, even if power is equally allocated to RBs. Thus, first an optimal RB assignment and power allocation algorithm is proposed and then a carrier aggregation enabled joint resource allocation algorithm called CARA is proposed. By jointly considering CC and RB assignments, and power allocation, the proposed approach can achieve better performance. Simulation results show the proposed algorithm can significantly improve performance, e.g., total throughput compared with the existing algorithm.
ER -