講演抄録/キーワード |
講演名 |
2019-03-09 14:00
A Deep Learning Based Spatial Spectrum Reuse Approach in Multiple Dense WLAN Scenarios ○Jin Liu・Masahide Hatanaka・Takao Onoye(Osaka Univ.) CAS2018-153 CS2018-121 |
抄録 |
(和) |
Recently, with the development of wireless local area network (WLAN) applications, a considerable expansion of wireless devices has resulted in dense WLANs. However, due to the limited resource such as spectrum, an increasing number of these wireless devices are working on the same channel. This dense deployment may incur co-channel interference and lead to the degradation of the overall network performance. To solve this problem, IEEE 802.11ax task group (IEEE 802.11 TGax) will adopt dynamic sensitivity control (DSC) in the next generation WLAN. DSC is a new scheme to improve spatial spectrum reuse by configuring the carrier sensing threshold (CST). In this study, we propose a deep belief network based DSC (DBN-DSC) algorithm to improve the spatial spectrum reuse in dense WLANs. We evaluate the DBN-DSC algorithm under all six standard dense scenarios proposed by IEEE 802.11 TGax. Our simulation results show that both the throughput and fairness of DBN-DSC algorithm outperform the established, beacon RSSI based DSC (BR-DSC) algorithm, under all six scenarios. |
(英) |
Recently, with the development of wireless local area network (WLAN) applications, a considerable expansion of wireless devices has resulted in dense WLANs. However, due to the limited resource such as spectrum, an increasing number of these wireless devices are working on the same channel. This dense deployment may incur co-channel interference and lead to the degradation of the overall network performance. To solve this problem, IEEE 802.11ax task group (IEEE 802.11 TGax) will adopt dynamic sensitivity control (DSC) in the next generation WLAN. DSC is a new scheme to improve spatial spectrum reuse by configuring the carrier sensing threshold (CST). In this study, we propose a deep belief network based DSC (DBN-DSC) algorithm to improve the spatial spectrum reuse in dense WLANs. We evaluate the DBN-DSC algorithm under all six standard dense scenarios proposed by IEEE 802.11 TGax. Our simulation results show that both the throughput and fairness of DBN-DSC algorithm outperform the established, beacon RSSI based DSC (BR-DSC) algorithm, under all six scenarios. |
キーワード |
(和) |
IEEE 802.11ax / Deep learning / Dynamic sensitivity control (DSC) / Dense deployment / Spatial spectrum reuse / / / |
(英) |
IEEE 802.11ax / Deep learning / Dynamic sensitivity control (DSC) / Dense deployment / Spatial spectrum reuse / / / |
文献情報 |
信学技報, vol. 118, no. 489, CS2018-121, pp. 81-86, 2019年3月. |
資料番号 |
CS2018-121 |
発行日 |
2019-03-01 (CAS, CS) |
ISSN |
Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 |
著作権に ついて |
技術研究報告に掲載された論文の著作権は電子情報通信学会に帰属します.(許諾番号:10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
PDFダウンロード |
CAS2018-153 CS2018-121 |
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