Automatic Modulation Classification

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With the emergence of software-defined radios (SDRs), radio frequency (RF) communication devices have the capability to transmit in low power, change the transmitting frequency, and modify the modulation format on-the-fly.  Adaptive modulation varies the rate of data transmission relative to the channel condition. In an environment without handshaking between the transmitter and receiver, an RF signals need to be recognized.  Automatic Modulation Classification (AMC) is a widely used and demanded feature on receive to adapt without handshaking between the transmitter and receiver. AMC can be feature-based or likelihood-function-based.

We developed a low-cost sensor network solution that can perform AMC of weak RF signals. The goal was to demonstrate that AMC with multiple sensors can resolve modulation types in those scenarios where single sensor AMC methods fail.

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