Multi-cap optimization for wireless data plans with time flexibility

An effective way for a Mobile network operator (MNO) to improve its revenue is price discrimination, i.e., providing different combinations of data caps and subscription fees. Rollover data plan (allowing the unused data in the current month to be used in the next month) is an innovative data mechanism with time flexibility. In this paper, we study the MNO's optimal multi-cap data plans with time flexibility in a realistic asymmetric information scenario. Specifically, users are associated with multi-dimensional private information, and the MNO designs a contract (with different data caps and subscription fees) to induce users to truthfully reveal their private information. This problem is quite challenging due to the multi-dimensional private information. We address the challenge in two aspects. First, we find that a feasible contract (satisfying incentive compatibility and individual rationality) should allocate the data caps according to users' willingness-to-pay (captured by the slopes of users' indifference curves). Second, for the non-convex data cap allocation problem, we propose a Dynamic Quota Allocation Algorithm, which has a low complexity and guarantees the global optimality. Numerical results show that the time-flexible data mechanisms increase both the MNO's profit (25 percent on average) and users' payoffs (8.2 percent on average) under price discrimination.