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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 魏宏宇(Hung-Yu Wei) | |
| dc.contributor.author | Kuan-Chieh Liao | en |
| dc.contributor.author | 廖冠傑 | zh_TW |
| dc.date.accessioned | 2021-05-15T17:50:32Z | - |
| dc.date.available | 2017-08-21 | |
| dc.date.available | 2021-05-15T17:50:32Z | - |
| dc.date.copyright | 2014-08-21 | |
| dc.date.issued | 2014 | |
| dc.date.submitted | 2014-08-19 | |
| dc.identifier.citation | [1] 3GPP R2-134096, ”Centralized D2D transmission for out-of-coverage”, Nov 2013 .
[2] Y. Xing and R. Chandramouli. Stochastic learning solution for distributed discrete power control game in wireless data networks. IEEE/ACM Transactions on Networking, 16(4):932–944, Aug 2008. [3] P. S. Sastry, V. V. Phansalkar, and M. Thathachar. Decentralized learning of nash equilibria in multi-person stochastic games with incomplete information. IEEE Transactions on Systems, Man and Cybernetics, 24(5):769–777, May 1994. [4] J. Seppala, T. Koskela, T. Chen, and S. Hakola. Network controlled device-to-device (d2d) and cluster multicast concept for lte and lte-a networks. In IEEE Wireless Communications and Networking Conference (WCNC), pages 986–991, 2011. [5] F. Wang, C. Xu, L. Song, Han Z, and B. Zhang. Energy-efficient radio resource and power allocation for device-to-device communication underlaying cellular networks. In International Conference on Wireless Communications Signal Processing (WCSP), 2012. [6] T. Koskela, S. Hakola, T. Chen, and J. Lehtomaki. Clustering concept using device-to-device communication in cellular system. In IEEE Wireless Communications and Networking Conference (WCNC), 2010. [7] J. Du, W. Zhu, J. Xu, Z. Li, and H. Wang. A compressed harq feedback for device-to-device multicast communications. In IEEE Vehicular Technology Conference (VTC Fall), 2012. [8] B. Zhou, H. Hu, S.Q. Huang, and H.H. Chen. Intracluster device-to-device relay algorithm with optimal resource utilization. IEEE Transactions on Vehicular Technology, 62(5):2315–2326, 2013. [9] M. Chatterjee, S.K. Das, and D. Turgut. Wca: A weighted clustering algorithm for mobile ad hoc networks. Cluster Computing, 5(2):193–204, 2002. [10] Q. Huang, C. Julien, and G.C. Roman. Relying on safe distance to achieve strong partitionable group membership in ad hoc networks. IEEE Transactions on Mobile Computing, 3(2):192–205, 2004. [11] L. Badia, M. Miozzo, M. Rossi, and M. Zorzi. Routing schemes in heterogeneous wireless networks based on access advertisement and backward utilities for qos support. IEEE Communications Magazine, 45(2):67–73, 2007. [12] Y. Narahari, D. Garg, R. Narayanam, and H. Prakash. Game Theoretic Problems in Network Economics and Mechanism Design Solutions,. Spinger, 2009. [13] C. Xu, L. Song, Z. Han, Q. Zhao, X. Wang, and B. Jiao. Interference-aware resource allocation for device-to-device communications as an underlay using sequential second price auction. In IEEE International Conference on Communications (ICC), pages 445–449, 2012. [14] C. Xu, L. Song, Z. Han, Q. Zhao, X. Wang, X. Cheng, and B. Jiao. Efficiency resource allocation for device-to-device underlay communication systems: A reverse iterative combinatorial auction based approach. IEEE Journal on Selected Areas in Communications, 31(9):348–358, 2013. [15] C. Xu, L. Song, Z. Han, D. Li, and B. Jiao. Resource allocation using a reverse iterative combinatorial auction for device-to-device underlay cellular networks. In IEEE Global Communications Conference (GLOBECOM), pages 4542–4547, 2012. [16] D. Wu, J. Wang, R.Q. Hu, Y. Cai, and L. Zhou. Energy-efficient resource sharing for mobile device-to-device multimedia communications. IEEE Transactions on Vehicular Technology, 63(5):2093–2103, Jun 2014. [17] N. Mastronarde, V. Patel, J. Xu, and M. Schaar. Learning relaying strategies in cellular d2d networks with token-based incentives. In IEEE Globecom Workshops (GC Wkshps)., pages 163–169, Dec 2013. [18] P. Zhou, Y. Chang, and J.A. Copeland. Reinforcement learning for repeated power control game in cognitive radio networks. IEEE Journal on Selected Areas in Communications, 30(1):54–69, Jan 2012. [19] S.H. Kang and N. Thinh. Distance based thresholds for cluster head selection in wireless sensor networks. IEEE Communications Letters, 16(9):1396–1399, Sep 2012. [20] J.S. Kim, S.Y. Choi, S.J. Han, J.H. Choi, J.H. Lee., and K.W. Rim. Alternative cluster head selection protocol for energy efficiency in wireless sensor networks. In Software Technologies for Future Dependable Distributed Systems., pages 159–163, Mar 2009. [21] L. Buttyan and T. Holczer. Private cluster head election in wireless sensor networks. In IEEE 6th International Conference on Mobile Adhoc and Sensor Systems., pages 1048–1053, Oct 2009. [22] D. C. Parkes and L. H. Ungar. Iterative combinatorial auctions: Theory and practice. In AAAI/IAAI, pages 74–81, 2000. [23] M.J. Osborne. An introduction to game theory, volume 3. [24] W. Vickrey. Counterspeculation, auctions, and competitive sealed tenders. The Journal of finance, 16(1):8–37, 1961. [25] 3GPP TR 36.843 1.0.0, ”Study on LTE Device to Device Proximity Services-Radio Aspects,” Oct 2013. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/4950 | - |
| dc.description.abstract | Device-to-Device (D2D) communications provides a proximity service, consuming less energy and having higher spectrum reuse. It has become more and more popular in recent years. In our work, we consider that the devices in a cell request the same data from a base station (BS). The devices will form some clusters to receive data. Every cluster will have one device be central entity. The central entity in a cluster receives the data from the BS, and then broadcasts the data to all other devices in the same cluster. The central entity suffers from the cost of transmit power consumption, which discourages the devices from being the central entity. As the devices are selfish in maximizing their own utility, game theory serve as a powerful technique for analyzing the behavior of the devices. We formulate the selfish and non-cooperative interaction of the devices under the system as a game problem. To solve this problem, we propose a central-entity-election mechanism that motivates the devices to report the true transmission costs, and elects the most appropriate devices as the central entities to reach the maximum system utility (social welfare). On the other way, we prove that the multiple-cluster central entity election is a NP hard problem. To avoid the NP hard problem, we propose the distributed central entity election learning (DCEE) algorithm to form clusters. We prove the DCEE algorithm can always converge and have many desirable properties as budget balance and individual rationality. In the simulation part, we verify the theoretical analysis in a real LTE system setting. With the proposed mechanism and the simulation results, D2D communications is shown to have the potential to improve the performance of wireless networks. | en |
| dc.description.provenance | Made available in DSpace on 2021-05-15T17:50:32Z (GMT). No. of bitstreams: 1 ntu-103-R01921036-1.pdf: 817696 bytes, checksum: 088f8f7c605a8e6233e27ab6d493e8c2 (MD5) Previous issue date: 2014 | en |
| dc.description.tableofcontents | Contents
口試委員會審定書 摘要ii Abstract iv 1 Introduction 1 2 Related Work 4 3 D2D System Framework 7 3.1 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 3.2 User’s Utility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 4 Central-Entity-Election Mechanism For One Cluster System 10 5 Auction Game in Mechanism 13 6 Analysis – the Equilibrium and the Desirable Properties 15 7 Extension From One-Cluster to Multiple-Cluster System 20 7.0.1 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 7.1 Centralized System Analysis . . . . . . . . . . . . . . . . . . . . . . . . 20 vi 7.2 Distributed System Analysis . . . . . . . . . . . . . . . . . . . . . . . . 22 7.2.1 User’s Utility . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 8 Distributed Central Entity Election(DCEE) Algorithm 26 8.1 Distributed Central Entity Election(DCEE) Algorithm . . . . . . . . . . . 26 8.2 The Convergence of the DCEE Algorithm . . . . . . . . . . . . . . . . . 28 9 Properties and Theorems of the DCEE Algorithm 33 10 Further Investigation of the DCEE Algorithm and Discussion 36 10.1 Theoretical Analysis in Small Step Size b . . . . . . . . . . . . . . . . . 36 10.2 Discussion and Comparison to Related Work . . . . . . . . . . . . . . . 38 11 Simulation Results 39 11.1 Simulation Scenario . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 11.2 Verification of the Theoretical Analysis in the Auction Mechanism Design 40 11.2.1 Truth Telling . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 11.2.2 Maximum Cluster Utility . . . . . . . . . . . . . . . . . . . . . . 41 11.2.3 Effect of the charge parameter . . . . . . . . . . . . . . . . . . 42 11.3 Verification of the Theoretical Analysis in DCEE algorithm . . . . . . . . 43 11.4 Observation in Different Parameters . . . . . . . . . . . . . . . . . . . . 43 11.4.1 Change Step Size b . . . . . . . . . . . . . . . . . . . . . . . . . 44 11.4.2 Change Transfer Price T . . . . . . . . . . . . . . . . . . . . . . 45 11.4.3 Change Initial condition pi(0) . . . . . . . . . . . . . . . . . . . 46 11.5 Oscillation Phenomenon . . . . . . . . . . . . . . . . . . . . . . . . . . 47 11.6 Compare Social Welfare . . . . . . . . . . . . . . . . . . . . . . . . . . 48 vii 12 Conclusion 50 Bibliography 51 | |
| dc.language.iso | zh-TW | |
| dc.subject | 學習演算法 | zh_TW |
| dc.subject | 裝置對裝置 | zh_TW |
| dc.subject | 集團 | zh_TW |
| dc.subject | 中央節點 | zh_TW |
| dc.subject | 賽局理論 | zh_TW |
| dc.subject | 機制設計 | zh_TW |
| dc.subject | central entity | en |
| dc.subject | learning algorithm | en |
| dc.subject | mechanism design | en |
| dc.subject | game theory | en |
| dc.subject | Device-to-Device (D2D) communications | en |
| dc.subject | cluster | en |
| dc.title | 使用賽局理論及學習演算法在裝置對裝置通訊系統中的中央節點選擇 | zh_TW |
| dc.title | Device-to-Device Central Entity Election using Game Theory and Learning Algorithm | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 102-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 陳和麟,蘇柏青,于天立,王志宇 | |
| dc.subject.keyword | 裝置對裝置,集團,中央節點,賽局理論,機制設計,學習演算法, | zh_TW |
| dc.subject.keyword | Device-to-Device (D2D) communications,cluster,central entity,game theory,mechanism design,learning algorithm, | en |
| dc.relation.page | 55 | |
| dc.rights.note | 同意授權(全球公開) | |
| dc.date.accepted | 2014-08-20 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 電機工程學研究所 | zh_TW |
| 顯示於系所單位： | 電機工程學系 | |
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|---|---|---|---|
| ntu-103-1.pdf | 798.53 kB | Adobe PDF | 檢視/開啟 |
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