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Mobile users in future wireless networks face limited wireless resources suchas data plan, computation capacity and energy storage. Given that some of theseusers may not be utilizing fully their wireless resources, device-to-device(D2D) resource sharing is a promising approach to exploit users' diversity inresource use and for pooling their resources locally. In this paper, we proposea novel two-sided D2D trading market model that enables a large number oflocally connected users to trade resources. Traditional resource allocationsolutions are mostly centralized without considering users' local D2Dconnectivity constraints, becoming unscalable for large-scale trading. Inaddition, there may be market failure since selfish users will not truthfullyreport their actual valuations and quantities for buying or selling resources.To address these two key challenges, we first investigate the distributedresource allocation problem with D2D assignment constraints. Based on thegreedy idea of maximum weighted matching, we propose a fast algorithm toachieve near-optimal average allocative efficiency. Then, we combine it with anew pricing mechanism that adjusts the final trading prices for buying andselling resources in a way that buyers and sellers are incentivized totruthfully report their valuations and available resource quantities. Unliketraditional double auctions with a central controller, this pricing mechanismis fully distributed in the sense that the final trading prices between eachmatched pair of users only depend on their own declarations and hence can becalculated locally. Finally, we analyze the repeated execution of the proposedD2D trading mechanism in multiple rounds and determine the best tradingfrequency.

Distributed Double Auctions for Large-Scale Device-to-Device Resource Trading