University of Oulu

G. Lee, W. Saad, M. Bennis, A. Mehbodniya and F. Adachi, "Online Channel Allocation for Full-Duplex Device-to-Device Communications," 2016 IEEE Globecom Workshops (GC Wkshps), Washington, DC, 2016, pp. 1-6. doi: 10.1109/GLOCOMW.2016.7848985

Online channel allocation for full-duplex device-to-device communications

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Author: Lee, Gilsoo1; Saad, Walid1; Bennis, Mehdi2;
Organizations: 1Wireless@VT, Bradley Department of Electrical and Computer Engineering, Virginia Tech, Blacksburg, VA, USA
2Centre for Wireless Communications, University of Oulu, Finland
3Dept. of Communication Engineering, Graduate School of Engineering, Tohoku University, Sendai, Japan
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.7 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2018080633432
Language: English
Published: Institute of Electrical and Electronics Engineers, 2016
Publish Date: 2018-08-06
Description:

Abstract

Full-duplex device-to-device (D2D) communications over cellular networks is a promising solution for maximizing wireless spectral efficiency. However, in practice, due to the unpredictable arrival of D2D users, the base station (BS) must smartly allocate suitable channels to arriving D2D pairs. In this paper, the problem of dynamic channel allocation is studied for full-duplex D2D networks. In particular, the goal of the proposed approach is to maximize the system sum-rate under complete uncertainty on the arrival process of D2D users. To solve this problem, a novel approach based on an online weighted bipartite matching is proposed. To find the desired solution of the channel allocation problem, a greedy online algorithm is developed to enable the BS to decide on the channel assignment for each D2D pair, without knowing any prior information on future D2D arrivals. For an illustrative case study, upper and lower bounds on the competitive ratio that compares the performance of the proposed online algorithm to that of an offline algorithm are derived. Simulation results show that the proposed online algorithm can achieve a near- optimal sum-rate with an optimality gap that is no higher than 8.3% compared to the offline, optimal solution that has complete knowledge of the system.

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Series: IEEE Globecom Workshops
ISSN: 2166-0069
ISSN-L: 2166-0069
ISBN: 978-1-5090-2482-7
ISBN Print: 978-1-5090-2483-4
Pages: 1 - 6
DOI: 10.1109/GLOCOMW.2016.7848985
OADOI: https://oadoi.org/10.1109/GLOCOMW.2016.7848985
Host publication: 2016 IEEE Globecom Workshops (GC Wkshps)
Conference: IEEE Globecom Workshops
Type of Publication: A4 Article in conference proceedings
Field of Science: 213 Electronic, automation and communications engineering, electronics
Subjects:
Funding: This research been supported by the U.S. National Science Foundation under Grant CNS-1460333 and by Towards Energy-Efficient Hyper-Dense Wireless Networks with Trillions of Devices, the Commissioned Research of National Institute of Information and Communications Technology (NICT), Japan, and by the Academy of Finland.
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