D2D Relay Selection Based on Joint Fuzzy and Entropy Theories With Social Similarity

• Published in: IEEE transactions on vehicular technology Vol. 67; no. 9; pp. 8796 - 8807
• Main Authors: Wu, Kuan, Jiang, Ming, Tan, Hong-Zhou
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.09.2018; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: 3GPP; Analytic hierarchy process; Computer simulation; Decision making; Device-to-device (D2D); Device-to-device communication; Entropy; entropy weight; Integer linear programming; Integer programming; intuitionistic fuzzy analytic hierarchy process (IFAHP); Linear programming; long-term evolution (LTE); Message passing; mobile social network (MSN); multi-objective binary integer linear programming (MOBILP); Multiple objective analysis; Relay; Relays; Similarity; Social factors; UE-to-network (UE-NW) relay selection (RS); Weight
• ISSN: 0018-9545; 1939-9359
• DOI: 10.1109/TVT.2018.2848544

The employment of social similarity (SS) aware device-to-device (D2D) user equipment (UE)-to-network (UE-NW) relay helps to improve system capacity and UEs' accessability to the evolved Node B (eNB), where a crucial aspect is the design of the relay helper UE (HUE) selection process. However, few existing studies jointly consider the diverse impacts from various design criteria on the performance of HUE selection. In this paper, we formulate the SS-aware D2D UE-NW relay selection (RS) issue as a multiobjective binary integer linear programming (MOBILP) problem under the constraints of several criteria. Then, we propose a new two-stage D2D UE-NW selection scheme. Specifically, a joint algorithm exploiting the intuitionistic fuzzy analytic hierarchy process and the entropy weight generation method is designed for stage one, which provides both subjective and objective preferences for assisting decision making. In stage two, with the constructed decision weights, the MOBILP can be transformed to a simpler binary integer linear programming problem and thus be solved distributively through an efficient message passing method. Based on realistic social data traces, our simulation results validate the benefits of the proposed two-stage scheme, which ensures high system performances in terms of throughput, fairness and energy efficiency.