Rate adaptive distributed source coding for wireless applications

Distributed source coding techniques enable distributed receivers to independently compress samples to a rate above the Slepian-Wolf bound, by leveraging statistical correlations between different receivers observations. The wireless channel can impose many compression challenges, such as unknown or dynamic compression bounds due to time-varying fading and mobility. This work derives a novel rate adaptive non-binary distributed source coding scheme which is motivated by these challenges. Applications are derived for distributed detection and distributed multiple-input multiple-output (MIMO) reception. Results demonstrate strong performance with these applications along with near-bound compression at various SNR levels and channel realizations.