Framework of network centric signal sensing for automatic modulation classification

This paper proposes a sensor network framework for sensing and exploiting unknown signals. It includes distributed decision fusion, distributed processing, centralized synchronous signal sensing, centralized asynchronous signal sensing, and system of systems single sensing. Data fusion is applied to enhance the SNR of weak signals and to eliminate channel distortion. Statistical estimation and modulation classification techniques are discussed.