Distributed Automatic Modulation Classification With Multiple Sensors

作者：Xu, Jefferson L.^*; Su, Wei; Zhou, MengChu

来源：IEEE Sensors Journal, 2010, 10(11): 1779-1785.

DOI：10.1109/JSEN.2010.2049487

• Cognitive radio
• distributed classification
• distributed detection
• likelihood ratio test (LRT)
• modulation classification
• wireless sensor networks (WSN)

Automatic modulation classification (AMC) has been intensively studied to enhance the successful classification rate, particularly for overcoming the physical limit that deals with weak signals received in a noncooperative communication environment. A wireless sensor network (WSN) has multiple geometrically distributed sensors to work cooperatively. The distributed signal sensing and classification performed by collaborated sensors is proven to be beneficial to increasing the modulation classification reliability. In this paper, we apply the likelihood ratio-based distributed detection fusion technique to address the issues of general binary modulation classifications. The data fusion algorithm performed in the primary node is presented. Its numerical performance with simulation results is demonstrated.

• 出版日期2010-11
• 单位同济大学