Dynamic Social-Aware Peer Selection for Cooperative Relay Management With D2D Communications

• Published in: IEEE transactions on communications Vol. 67; no. 5; pp. 3124 - 3139
• Main Authors: Gao, Yulan, Xiao, Yue, Wu, Mingming, Xiao, Ming, Shao, Jinliang
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.05.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Cellular communication; Cellular networks; Computer simulation; Copper; Device-to-device communication; Device-to-Device communications; Energy management; Energy transmission; Frequency division multiple access; Level (quantity); Lyapunov optimization; Optimization; peer selection; Peer-to-peer computing; Permutations; Power consumption; Power management; Relaying; Relays; Social networks; social trust level; Transmitters; Uplink
• ISSN: 0090-6778; 1558-0857; 1558-0857
• DOI: 10.1109/TCOMM.2019.2894138

In this paper, we investigate the optimal dynamic social-aware peer selection with spectrum-power trading to maximize the average sum energy efficiency (EE) of cellular users (CUs) for uplink transmission for an orthogonal frequency division multiple access cellular network with device-to-device (D2D) communications. Different from the previous studies, which mostly focus on how to exploit social ties in human social networks to construct the permutation of all the feasible peers, we consider dynamic peer selection with social awareness-aided spectrum-power trading in D2D overlaying communications. Specifically, the amount of transmit power from the D2D transmitters to relay the CUs for uplink transmission is determined by their social trust levels. Likewise, the D2D transmitters can gain the corresponding amount of spectrum from the CUs for D2D pair link communications, which can be regarded as the compensation of the power consumption for relaying CUs. We formulate the dynamic peer selection problems with social awareness-aided spectrum-power trading in cooperative D2D communications into the infinite-horizon time-average renewal-reward problems subject to time average constraints on a collection of penalty processes. And the Lyapunov optimization concepts-based drift-plus-penalty algorithms are proposed to solve them. The simulation results demonstrate the effectiveness of the proposed dynamic peer selection algorithms. And further performance comparison indicates that the proposed dynamic peer selection algorithms not only maximize the average EE of CUs but also guarantee higher privacy protection.