Incumbent and LSA Licensee Classification Through Distributed Cognitive Networks

In licensed shared access (LSA), incumbents (i.e. primary users) control the access to their spectrum bands through temporarily leasing to a third party (called LSA licensees) in a specific spatial region. Such shared access takes place based on spectrum availability information acquired from LSA repositories. In this context, this paper presents the following contributions: 1) The use of a cognitive cooperative framework based on measurement-capable devices (MCDs) in order to provide valuable information both to generate and to update radio-environment maps for LSA repositories, thus enabling more dynamic spectrum-access opportunities. 2) A new distributed and cooperative scheme among cognitive MCDs to detect and classify incumbents and LSA licensees in the LSA network. The proposal suggests a clustering strategy for cooperative spectrum sensing when neighboring MCDs observe different licensed users-whether incumbents or LSA licensees. The clustering considers the differences in underlying hidden Markov models associated with the detection of distinct licensed users. 3) Theoretical expressions for the overall probability of detection and false alarm are derived for hard cooperation strategies that may include failed MCDs in the clustering process.