{"ID":2868285,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2509.17286","arxiv_id":"2509.17286","title":"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.","short_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...","url_abs":"https://arxiv.org/abs/2509.17286","url_pdf":"https://arxiv.org/pdf/2509.17286v1","authors":"[\"David Rowe\",\"Tibor Bece\"]","published":"2025-09-21T23:52:11Z","proceeding":"eess.AS","tasks":"[\"eess.AS\",\"cs.SD\"]","methods":"[]","has_code":false}