Optimal pricing strategy for wireless social community networks

Wireless social community operators rely on subscribers who constitute a community of users. The pricing strategy of the provided wireless access is an open problem for this new generation of wireless access providers. In this paper, using both analytical and simulation approaches, we study the problem comprised of modeling user subscription and mobility behavior and of coverage evolution with the objective of finding optimal subscription fees. We compute optimal prices with both static and semi-dynamic pricing. Coping with an incomplete knowledge about users, we calculate the best static price and prove that optimal fair pricing is the optimal semi-dynamic pricing. Moreover, we have developed a simulator to verify optimal prices of social community operators with complete and incomplete knowledge. Our results show that the optimal fair pricing strategy significantly improves the cumulative payoff of social community operators.