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Mobile data rewards is now leading a new economic trend in wireless networks, where the operators stimulate mobile users to view ads with data rewards and ask for corresponding payments from advertisers. Yet, due to the uncertain nature of users' preferences, it is always challenging for the advertiser to find the best choice of data rewards to attain an optimum balance between ad revenue and rewards spent. In this paper, we develop a general contract-theoretic framework to address the problem of data rewards design in a realistic asymmetric information scenario, where each user is associated with multidimensional private information. Specifically, we model the interplay between the advertiser and users by using a multidimensional contract design approach, and theoretically analyze optimal data rewarding schemes. To ensure global incentive compatibility, we convert the multi-dimensional contract problem into an equivalent one-dimensional contract problem. Necessary and sufficient conditions for an optimal and feasible contract are then derived to provide incentives for engagement of users in data rewarding scheme. We leverage numerical results to evaluate the performance of the designed multi-dimensional contract for data rewarding scheme.
Xiong et al. (Fri,) studied this question.