抄録
With the demand for rapid exchanges of information, device to device (D2D) communications become one of the essential components of next-generation network architecture. To realize efficient D2D communication, peer discovery plays an important role since the discovery result strongly affects further performance. Most of the researches on peer discovery in D2D communication are based on discovering proximity devices to recognize nearby destination devices. In particular, some researches focus on time slot distribution to broadcast address information for discovering proximity devices. Moreover, other researches pay attention to user grouping with different beacon probing signals. However, these peer discovery mechanisms do not consider the risks that source devices may encounter malicious devices in real situations. As a solution to this, this paper proposes a peer discovery mechanism which applies the social network relationship information to exclude malicious devices. The proposed mechanism contributes to decrease the probability of encountering malicious devices and enhances the efficiency of peer discovery by excluding malicious devices. Simulations clarify that the base station (BS) extracts trusted candidates among devices to quantify the trust degree of devices based on the potential social information.
| 元の言語 | English |
|---|---|
| ホスト出版物のタイトル | 21st International Conference on Advanced Communication Technology |
| ホスト出版物のサブタイトル | ICT for 4th Industrial Revolution!, ICACT 2019 - Proceeding |
| 出版者 | Institute of Electrical and Electronics Engineers Inc. |
| ページ | 91-97 |
| ページ数 | 7 |
| ISBN（電子版） | 9791188428021 |
| DOI | |
| 出版物ステータス | Published - 2019 4 29 |
| イベント | 21st International Conference on Advanced Communication Technology, ICACT 2019 - Pyeongchang, Korea, Republic of 継続期間: 2019 2 17 → 2019 2 20 |
出版物シリーズ
| 名前 | International Conference on Advanced Communication Technology, ICACT |
|---|---|
| 巻 | 2019-February |
| ISSN（印刷物） | 1738-9445 |
Conference
| Conference | 21st International Conference on Advanced Communication Technology, ICACT 2019 |
|---|---|
| 国 | Korea, Republic of |
| 市 | Pyeongchang |
| 期間 | 19/2/17 → 19/2/20 |
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ASJC Scopus subject areas
- Electrical and Electronic Engineering
これを引用
A Deep Learning Based Social-aware D2D Peer Discovery Mechanism. / Long, Yu; Yamamoto, Ryo; Yamazaki, Taku; Tanaka, Yoshiaki.
21st International Conference on Advanced Communication Technology: ICT for 4th Industrial Revolution!, ICACT 2019 - Proceeding. Institute of Electrical and Electronics Engineers Inc., 2019. p. 91-97 8701911 (International Conference on Advanced Communication Technology, ICACT; 巻 2019-February).研究成果: Conference contribution
}
TY - GEN
T1 - A Deep Learning Based Social-aware D2D Peer Discovery Mechanism
AU - Long, Yu
AU - Yamamoto, Ryo
AU - Yamazaki, Taku
AU - Tanaka, Yoshiaki
PY - 2019/4/29
Y1 - 2019/4/29
N2 - With the demand for rapid exchanges of information, device to device (D2D) communications become one of the essential components of next-generation network architecture. To realize efficient D2D communication, peer discovery plays an important role since the discovery result strongly affects further performance. Most of the researches on peer discovery in D2D communication are based on discovering proximity devices to recognize nearby destination devices. In particular, some researches focus on time slot distribution to broadcast address information for discovering proximity devices. Moreover, other researches pay attention to user grouping with different beacon probing signals. However, these peer discovery mechanisms do not consider the risks that source devices may encounter malicious devices in real situations. As a solution to this, this paper proposes a peer discovery mechanism which applies the social network relationship information to exclude malicious devices. The proposed mechanism contributes to decrease the probability of encountering malicious devices and enhances the efficiency of peer discovery by excluding malicious devices. Simulations clarify that the base station (BS) extracts trusted candidates among devices to quantify the trust degree of devices based on the potential social information.
AB - With the demand for rapid exchanges of information, device to device (D2D) communications become one of the essential components of next-generation network architecture. To realize efficient D2D communication, peer discovery plays an important role since the discovery result strongly affects further performance. Most of the researches on peer discovery in D2D communication are based on discovering proximity devices to recognize nearby destination devices. In particular, some researches focus on time slot distribution to broadcast address information for discovering proximity devices. Moreover, other researches pay attention to user grouping with different beacon probing signals. However, these peer discovery mechanisms do not consider the risks that source devices may encounter malicious devices in real situations. As a solution to this, this paper proposes a peer discovery mechanism which applies the social network relationship information to exclude malicious devices. The proposed mechanism contributes to decrease the probability of encountering malicious devices and enhances the efficiency of peer discovery by excluding malicious devices. Simulations clarify that the base station (BS) extracts trusted candidates among devices to quantify the trust degree of devices based on the potential social information.
KW - D2D communication
KW - deep neural network
KW - malicious device
KW - peer discovery
KW - social network information
UR - http://www.scopus.com/inward/record.url?scp=85065655783&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85065655783&partnerID=8YFLogxK
U2 - 10.23919/ICACT.2019.8701911
DO - 10.23919/ICACT.2019.8701911
M3 - Conference contribution
T3 - International Conference on Advanced Communication Technology, ICACT
SP - 91
EP - 97
BT - 21st International Conference on Advanced Communication Technology
PB - Institute of Electrical and Electronics Engineers Inc.
ER -