Optimal Pricing Strategy for Wireless Social Community Networks

The increasing number of mobile applications fuels the demand for affordable and ubiquitous wireless access. The traditional wireless network technologies such as EV-DO or WiMAX provide this service but require a huge upfront investment in infrastructure and spectrum. On the contrary, as they do not have to face such an investment, 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 for wireless social community networks 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 for social community operators in monopoly situations. Moreover, we have developed a simulator to verify optimal prices of social community operators with complete and incomplete knowledge. Our simulation results show that the optimal fair pricing strategy significantly improves the cumulative payoff of social community operators.