| IEICE Technical Committee Submission System Conference Paper's Information |
Online Proceedings [Sign in] Tech. Rep. Archives |
| Go Top Page | Go Previous | [Japanese] / [English] |
| 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)  RCS2017-347 |
|
| 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 | |
| Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) | |
| Download PDF | RCS2017-347 |
|
| 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) |
| 4th Author's Name | |
| 4th Author's Affiliation | () |
| 5th Author's Name | |
| 5th Author's Affiliation | () |
| 6th Author's Name | |
| 6th Author's Affiliation | () |
| 7th Author's Name | |
| 7th Author's Affiliation | () |
| 8th Author's Name | |
| 8th Author's Affiliation | () |
| 9th Author's Name | |
| 9th Author's Affiliation | () |
| 10th Author's Name | |
| 10th Author's Affiliation | () |
| 11th Author's Name | |
| 11th Author's Affiliation | () |
| 12th Author's Name | |
| 12th Author's Affiliation | () |
| 13th Author's Name | |
| 13th Author's Affiliation | () |
| 14th Author's Name | |
| 14th Author's Affiliation | () |
| 15th Author's Name | |
| 15th Author's Affiliation | () |
| 16th Author's Name | |
| 16th Author's Affiliation | () |
| 17th Author's Name | |
| 17th Author's Affiliation | () |
| 18th Author's Name | |
| 18th Author's Affiliation | () |
| Speaker | Author-1 |
| Date Time | 2018-03-01 09:20:00 |
| Presentation Time | 20 minutes |
| Registration for | RCS |
| Paper # | RCS2017-347 |
| Volume (vol) | vol.117 |
| Number (no) | no.456 |
| Page | pp.173-178 |
| #Pages | 6 |
| Date of Issue | 2018-02-21 (RCS) |
[Return to Top Page]