2016/11/27 by Lin Zhang, Guodong Zhao, Zhang, Lin +9
Computer Science · Engineering · #Advanced MIMO Systems Optimization #Cognitive Radio Networks and Spectrum Sensing #FOS: Computer and information sciences #Information Theory (cs.IT) #Molecular Communication and Nanonetworks
paper · pdf · doi:10.48550/arxiv.1611.08811
openalex publication_date 2016/11/27 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We study the coexistence problem in a two-tier heterogeneous network (HetNet) with cognitive small cells. In particular, we consider an underlay HetNet, where the cognitive small base station (C-SBS) is allowed to use the frequency bands of the macro cell with an access probability (AP) as long as the C-SBS satisfies a preset interference probability (IP) constraint at macro users (MUs). To enhance the AP (or transmission opportunity) of the C-SBS, we propose a learning-based algorithm for the C-SBS and exploit the distance information between the macro base station (MBS) and MUs. Generally, the signal from the MBS to a specific MU contains the distance information between the MBS to the MU. We enable the C-SBS to analyze the MBS signal on a target frequency band, and learn the distance information between the MBS and the corresponding MU. With the learnt distance information, we calculate the upper bound of the probability that the C-SBS may interfere with the MU, and design an AP with a closed-form expression under the IP constraint. Numerical results indicate that the proposed algorithm outperforms the existing methods up to 60% AP (or transmission opportunity).