| Presentation | 2018-08-20 A Study of Autoregressive Model and Autoregressive Integrated Model Based Channel Idle/ Busy Status Duration Prediction for Real Environment WLAN Channel Naoya Hokimoto, Yafei Hou, Satoshi Denno, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Recently, due to the increase of huge number of wireless devices such as smartphones or sensors, mobile wireless traffic is dramatically expanding each year. Therefore, how to improve spectrum efficiency (SE) for cognitive wireless system is important and urgent research topic. Till now, there are many researches considering the prediction of Channel Occupancy Ratio (COR: the ration between busy duration length to resolution period $T$). If the start and end points of Busy and Idle duration can be correctly predicted, it will largely benefit the wireless system design and SE improvement. In this paper, we will consider such research based on autoregressive (AR) and autoregressive integrated (ARI) models using traffic data captured from the wireless channel in real environment. The major idea is that the Busy and Idle duration length can be calculated from COR value when the resolution period $T$ is short. In this paper, we first investigate the COR prediction performance using AR and ARI predictors with different value of $T$. Then using relationship between the Busy and Idle duration length and COR value, the Busy and Idle duration length prediction can be realized. From the results, we can confirm our proposal has better prediction accuracy than that of AR/ARI predictor using only Busy and Idle duration traffic data. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Autoregressive model / Autoregressive Integrated model / Channel Occupancy Ratio prediction / prediction of Idle/Busy duration |
| Paper # | SRW2018-13 |
| Date of Issue | 2018-08-13 (SRW) |
| Conference Information | |
| Committee | SRW |
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| Conference Date | 2018/8/20(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Okayama Univ. |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Network, MAC, Sensor technology, mmWave, etc. |
| Chair | Tadao Nakagawa(Tottori Univ.) |
| Vice Chair | Satoshi Denno(Okayama Univ.) / Makoto Hamaminato(Fujitsu labs.) |
| Secretary | Satoshi Denno(Kyoto Univ.) / Makoto Hamaminato(Tokyo Inst. of Tech.) |
| Assistant | Hiromasa Yamauchi(Fujitsu labs.) / Hanako Noda(Anritsu) |
| Paper Information | |
| Registration To | Technical Committee on Short Range Wireless Communications |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | A Study of Autoregressive Model and Autoregressive Integrated Model Based Channel Idle/ Busy Status Duration Prediction for Real Environment WLAN Channel |
| Sub Title (in English) | |
| Keyword(1) | Autoregressive model |
| Keyword(2) | Autoregressive Integrated model |
| Keyword(3) | Channel Occupancy Ratio prediction |
| Keyword(4) | prediction of Idle/Busy duration |
| 1st Author's Name | Naoya Hokimoto |
| 1st Author's Affiliation | Okayama University(Okayama Univ.) |
| 2nd Author's Name | Yafei Hou |
| 2nd Author's Affiliation | Okayama University(Okayama Univ.) |
| 3rd Author's Name | Satoshi Denno |
| 3rd Author's Affiliation | Okayama University(Okayama Univ.) |
| Date | 2018-08-20 |
| Paper # | SRW2018-13 |
| Volume (vol) | vol.118 |
| Number (no) | SRW-183 |
| Page | pp.pp.25-30(SRW), |
| #Pages | 6 |
| Date of Issue | 2018-08-13 (SRW) |