Win–Win-Driven D2D Content Sharing
Dan Wu, Liang Zhou, Ping C. Lu · IEEE Internet of Things Journal · 2020
Win-win cooperation has been broadly treated as one of the most promising goals for device-to-device (D2D) content sharing, especially for the ultrareliable low-latency communications (URLLC) scenario. Unfortunately, the exiting solutions are built on several seemly unpractical conditions: 1) abundant prior information on network and user; 2) optimization variables limited to 1-D space; and 3) a preset order on users' decision making. In this work, we propose a win-win-driven D2D content-sharing scheme by exploring the blind matching theory. Specifically, we first derive the closed-form expressions of latency and reliability performance for D2D content-sharing scenarios. Accordingly, the URLLC-oriented joint optimization problem for provider-demander pairing and power control of potential providers is formulated as a two-sided one-to-one context-free matching game, which involves a collection of agreement functions of potential providers and demanders' aspiration levels and exploits a modified notion of pairwise stability as the solution concept. Then, we design a distributed algorithm by utilizing the market and information decentralization characteristics of the blind matching algorithm. Both theoretical analysis and numerical results validate the performance properties, including convergence, optimality, and complexity.