Long-Term Contracts With Dynamic Asymmetric Information for Traffic Offloading in Heterogeneous 5G and Beyond Networks

Abstract

To achieve a green heterogeneous 5G network, a promising approach is to shut off the light-loaded low-power nodes (LPNs) and transfer the load to the remote radio heads (RRHs) nearby. However, the RRHs may refuse to cooperate when there is no incentive. Considering a user will stay in an RRH for a period of time, how to provide proper long-term incentives for the potential RRHs and select the best one is an essential issue. Since the offloading capability of an RRH is private information, that is, unavailable to the LPNs, in this article, the RRHs’ collaboration incentive problem under such asymmetric information condition is modeled as a long-term contract design problem. In the formulated problem, the channel condition and traffic load, which represent both RRH’s instantaneous state and long-term state, are combined to capture the RRHs’ offloading capacity and used to classify their types. Due to the dynamic of state, an RRH’s type varies with time, which greatly complicates the contract design. We first study the state transition of RRHs and the long-term utilities of both parties, with which the contract-theoretic framework is formulated. Then, we theoretically analyze and simplify the individual rational and incentive-compatible constraints for a feasible long-term contract. Finally, we propose a low time complexity algorithm to find the optimal contract. Numerical results verify that the long-term contract-based incentive mechanism not only improves the utilities of both cooperation parties, but also is superior to the existing works in reducing handover cost and energy consumption.