A game theoretic approach to content trading in proactive wireless networks

In this paper, the interactions between a wireless network carrier and a set of end-users trading data contents that were downloaded proactively are studied. In particular, we investigate the profit maximization problem for wireless network carrier and payment minimization for end-users. Motivated by recent findings on proactive resource allocation, we focus on the scenario whereby end-users harness their predictable demands and the possibility of being connected together in downloading proactive data and selling them again to minimize their expected payments. The carrier, on the other hand, takes a commission from each trade and utilizes smart pricing schemes to differentiate between off-peak and peak hour prices to spreadout the peak load and maximize its profit. A marketplace based on risk sharing concept is achieved where the tension between carrier and end-users and the competition between end-users themselves is formulated as a Stackelberg game. The existence and uniqueness of the non-cooperative sub-game Nash equilibrium is shown. We compare the new equilibria with the baseline scenario of smart pricing proactive model without trading between users. Despite the uncertainty about future demand, and the freshness of proactively downloaded contents, we characterize new equilibria point that yield to a win-win situation with respect to the baseline equilibrium. We show that users´ activity patterns can be harnessed to create a marketplace that will maximize the carrier´s profit while users pay less.