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Paper Abstract and Keywords
Presentation 2018-03-01 09:20
Transmit Power and Beamforming Control Using Neural Networks for MIMO Small Cell Networks with Interference Cancellation
Koi Tou, Yuyuan Chang, Kazuhiko Fukawa (TokyoTech)
Abstract (in Japanese) (See Japanese page) 
(in English) Dense deployment of small cell base stations (BSs) causes the coverage areas of neighboring cells to overlap, which increases inter-cell interference and degrades the system capacity. This report proposes a new inter-cell interference coordination (ICIC) scheme to improve the system capacity in multiple-input multiple-output (MIMO) small cell networks. The proposed ICIC scheme consists of both an interference cancellation (IC) technique on the receiver side, and a power/beamforming control on the transmitter side. The receiver removes interfering signals with high received power by IC, whereas the transmitter searches for a combination that maximizes the system capacity from a predetermined set of precoding matrices and transmit power levels. However, the greedy search has a problem that it requires a large amount of computational complexity. In order to reduce such an amount of complexity, the neural network (NN) is applied, which can greatly reduce the complexity after initial estimation of the weights converges. The NN training consists of two steps. In the first step, unsupervised pre-training has been proposed to reduce the training time. The unsupervised pre-training sets initial values to the NN weights by extracting feature quantities only from the NN inputs. In the second step, supervised training adjusts the NN weights using the inputs and the corresponding ideal outputs, and minimizes the difference between the ideal output and the NN output by the backpropagation algorithm. Computer simulations demonstrate that the proposed NN scheme can obtain the nearly optimum system capacity.
Keyword (in Japanese) (See Japanese page) 
(in English) MIMO / small cells / inter-cell interference coordination / interference canceller / neural network / system capacity / transmit power control / beamforming  
Reference Info. IEICE Tech. Rep., vol. 117, no. 456, RCS2017-347, pp. 173-178, Feb. 2018.
Paper # RCS2017-347 
Date of Issue 2018-02-21 (RCS) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380

Conference Information
Committee RCS SR SRW  
Conference Date 2018-02-28 - 2018-03-02 
Place (in Japanese) (See Japanese page) 
Place (in English) YRP 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Mobile Communication Workshop 
Paper Information
Registration To RCS 
Conference Code 2018-02-RCS-SR-SRW 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Transmit Power and Beamforming Control Using Neural Networks for MIMO Small Cell Networks with Interference Cancellation 
Sub Title (in English)  
Keyword(1) MIMO  
Keyword(2) small cells  
Keyword(3) inter-cell interference coordination  
Keyword(4) interference canceller  
Keyword(5) neural network  
Keyword(6) system capacity  
Keyword(7) transmit power control  
Keyword(8) beamforming  
1st Author's Name Koi Tou  
1st Author's Affiliation Tokyo Institute of Technology (TokyoTech)
2nd Author's Name Yuyuan Chang  
2nd Author's Affiliation Tokyo Institute of Technology (TokyoTech)
3rd Author's Name Kazuhiko Fukawa  
3rd Author's Affiliation Tokyo Institute of Technology (TokyoTech)
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Date Time 2018-03-01 09:20:00 
Presentation Time 20 
Registration for RCS 
Paper # IEICE-RCS2017-347 
Volume (vol) IEICE-117 
Number (no) no.456 
Page pp.173-178 
#Pages IEICE-6 
Date of Issue IEICE-RCS-2018-02-21 

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