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Volume 42 Issue 4
Jun.  2020
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Guoquan LI, Yongjun XU, Qianbin CHEN. Interference Efficiency-based Base Station Selection and Power Allocation Algorithm for Multi-cell Heterogeneous Wireless Networks[J]. Journal of Electronics & Information Technology, 2020, 42(4): 957-964. doi: 10.11999/JEIT190419
Citation: Guoquan LI, Yongjun XU, Qianbin CHEN. Interference Efficiency-based Base Station Selection and Power Allocation Algorithm for Multi-cell Heterogeneous Wireless Networks[J]. Journal of Electronics & Information Technology, 2020, 42(4): 957-964. doi: 10.11999/JEIT190419

Interference Efficiency-based Base Station Selection and Power Allocation Algorithm for Multi-cell Heterogeneous Wireless Networks

doi: 10.11999/JEIT190419
Funds:  The National Natural Science Foundation of China (61601071), The Science and Technology Research Program of Chongqing Municipal Education Commission (KJQN201800606), The Natural Science Foundation of Chongqing (cstc2019jcyj-msxmX0666, cstc2019jcyj-xfkxX0002), The Chongqing Science and Technology Innovation Leading Talent Support Program (CSTCCXLJRC201908), The Open Research Fund from Shandong Provincial Key Laboratory of Wireless Communication Technologies (SDKLWCT-2019-04)
  • Received Date: 2019-06-07
  • Rev Recd Date: 2020-01-18
  • Available Online: 2020-02-20
  • Publish Date: 2020-06-04
  • To solve interference management and efficiency improvement of multi-cell multi-user heterogeneous wireless networks, the downlink Base Station (BS)-user matching and power allocation problem are studied to maximize the interference efficiency of femtocells. Firstly, consideration of quality of service of macro cell users and femtocell users, the problem is formulated as a multivariate mixed integer nonlinear programming problem. Secondly, the problem is decomposed into two subproblems. The BS selection problem is solved by convex optimization technique. The power allocation problem is firstly converted into a convex one by using quadratic transformation method and Dinkelbach approach, then the problem is resolved by using Lagrange dual methods and subgradient methods. Simulations results show the effectiveness of the proposed algorithm by comparing with the existing algorithms in terms of interference efficiency and interference management.

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