Resource Allocation for Multi-Tenant Network Slicing: A Multi-Leader Multi-Follower Stackelberg Game Approach
Thinh Duy Tran, Long Bao Le
Abstract
Network slicing provides great opportunities for network service providers (SPs) to scale up and achieve higher revenue by enabling fast and efficient creation of new services and customizable networks for enterprises and user equipment (UEs). This can only be achieved at the expense of more complicated radio resource management and service/trading interactions among different involved stakeholders. In this paper, we study the resource allocation and pricing problem for network slicing that captures interactions among access/backhaul service providers and their UEs by using the multi-leader multi-follower (MLMF) Stackelberg game approach. Toward this end, we show how to formulate such a Stackelberg game and prove the existence of a unique game equilibrium. Then, we develop a distributed algorithm based on updating underlying best-response functions, which is proved to converge to the game equilibrium. Numerical results are presented to provide important insights into the interactions among the involved stakeholders and demonstrate the economical efficacy of the proposed design with respect to existing benchmarks.