RADE for Land Mobile Radio: A Neural Codec for Transmission of Speech over Baseband FM Radio Channels

Abstract: In the 1990s Land Mobile Radio (LMR) systems evolved from analog frequency modulation (FM) to standardised digital systems. Both digital and analog FM systems now co-exist in various services and exhibit similar speech quality. The architecture of many digital radios retains the analog FM modulator and demodulator from legacy analog radios, but driven by a multi-level digital pulse train rather than an analog voice signal. We denote this architecture baseband FM (BBFM). In this paper we describe a modern machine learning approach that uses an autoencoder to send high quality, 8 kHz bandwidth speech over the BBFM channel. The speech quality is shown to be superior to analog FM over simulated LMR channels in the presence of fading, and a demonstration of the system running over commodity UHF radios is presented.