Joint Neighbor Discovery and Contention Relationship Inference in Wireless Networks

In this paper, we investigate the problem of joint neighbor discovery and contention relationship inference in wireless networks with multiple broadcast domains. In contrast to existing work, we represent neighboring relationship as ternaries {1,0, δ} based on the strength of the received signal. An active ternary inference algorithm is proposed that utilizes decentralized randomized schedules to infer neighboring and contention relationships through mixed signal at the receiver nodes. Simulation studies show that the proposed algorithm outperforms an Aloha-like algorithm in neighbor discovery time, and can achieve high accuracy in determining the relationship.