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http://dx.doi.org/10.3837/tiis.2018.09.004

Interference Pricing based Resource Allocation for D2D Communications in Cellular Networks  

Li, Xiaomeng (School of Information and Communication Engineering Beijing University of Posts and Telecommunications)
Lv, Tiejun (School of Information and Communication Engineering Beijing University of Posts and Telecommunications)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.12, no.9, 2018 , pp. 4166-4182 More about this Journal
Abstract
We consider the Device-to-Device (D2D) communications in cellular networks where each cellular user (CU) shares the same resource with multiple D2D users (DUs). In this paper, we aim to maximize the energy efficiency (EE) of the D2D networks, subject to an interference constraint required by the CU. Since the cellular and D2D communications belong to different networks, we consider to incentivize base station (BS) while assisting the DUs. To this end, we propose a Stackelberg game based interference pricing framework for the considered D2D communications in cellular networks. Unlike most of the existing methods, we use interference pricing framework to jointly address the EE resource allocation problem and the interference management in our networks rather than only improve the EE of the DUs or protect cellular networks. In particular, BS and all the users do not need all channel state information, which is more realistic in practice. In addition, two different pricing strategies are also proposed. Based on the two strategies, we analyze the equilibrium of the game. Moreover, in the first strategy, the upper and lower boundaries of the interference price are obtained. The closed-form expression is gained with a backward induction for the second strategy. Both offer valuable insights to the considered scenarios. Finally, compared with the existing work, the EE of the D2D communications is significantly improved. The advantageous performance of our scheme are demonstrated by the simulation results.
Keywords
Energy efficiency; interference pricing framework; resource allocation; Stackelberg game;
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