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Volume 43 Issue 9
Sep.  2021
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Hong ZHANG, Xiao HAN, Ruyan WANG, Zhidu LI, Min ZHOU. Load Balancing User Association and Resource Allocation Strategy in Time and Wavelength Division Multiplexed Passive Optical Network and Cloud Radio Access Network Joint Architecture[J]. Journal of Electronics & Information Technology, 2021, 43(9): 2672-2679. doi: 10.11999/JEIT200849
Citation: Hong ZHANG, Xiao HAN, Ruyan WANG, Zhidu LI, Min ZHOU. Load Balancing User Association and Resource Allocation Strategy in Time and Wavelength Division Multiplexed Passive Optical Network and Cloud Radio Access Network Joint Architecture[J]. Journal of Electronics & Information Technology, 2021, 43(9): 2672-2679. doi: 10.11999/JEIT200849

Load Balancing User Association and Resource Allocation Strategy in Time and Wavelength Division Multiplexed Passive Optical Network and Cloud Radio Access Network Joint Architecture

doi: 10.11999/JEIT200849
Funds:  The National Natural Science Foundation of China (61771082, 61871062), The University Innovation Research Group of Chongqing (CXQT20017), The Science and Technology Research Program of Chongqing Municipal Education Commission (KJQN201900609, KJQN202000626), The Natural Science Foundation of Chongqing (cstc2020jcyj-zdxmX0024)
  • Received Date: 2020-09-30
  • Rev Recd Date: 2021-01-29
  • Available Online: 2021-03-02
  • Publish Date: 2021-09-16
  • The load imbalance in the wireless domain limits the overall transmission efficiency of the network in the joint architecture of Time and Wavelength Division Multiplexed Passive Optical Network (TWDM-PON) and Cloud Radio Access Network (C-RAN). A Load Balancing User Association and Resource Allocation (LBUARA) algorithm is proposed to ensure the Quality of Service(QoS) of users, and make full use of network resources TWDM-PON jointly with C-RAN architecture. Firstly, the user revenue function is constructed according to the service quality requirements of different users and the impact of Remote Radio Head (RRH) load on users. Furthermore, a random game model is established according to the network state, under the premise of ensuring the quality of user service. A user association and resource allocation algorithm based on multi-agent Q-learning load balancing is proposed to obtain the optimal user association and resource allocation plan. The simulation results show that users association and resource allocation strategies mentioned can achieve load balancing network to ensure quality of service users, and improve network throughput.
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