MITSUBISHI ELECTRIC RESEARCH LABORATORIES http://www.merl.com DNN-based Overhead Reduction for High-Quality Soft Delivery Fujihashi, T.; Koike-Akino, T.; Watanabe, T.; Orlik, P.V. TR2019-133 December 09, 2019 Abstract Soft delivery, i.e., analog transmission, has been proposed to provide graceful video/image quality even in unstable wireless channels. However, existing analog schemes require a sig- nificant amount of metadata for power allocation and decoding operations. It causes large overheads and quality degradation due to rate and power losses. Although the amount of overheads can be reduced by introducing Gaussian Markov random field (GMRF) model, the model mismatch can degrade reconstruction quality. In this paper, we propose a novel analog transmission scheme to simultaneously reduce the overheads and yield better reconstruction quality. The proposed scheme uses a deep neural network (DNN) for metadata compression and decompression. Specifically, the metadata is compressed into few variables using the pro- posed DNN-based metadata encoder before transmission. The variables are then transmitted and decompressed at the receiver for high-quality video/image reconstruction. Evaluations using test images demonstrate that our proposed scheme reduces overheads by 80.0 % with 11.2 dB improvement of reconstruction quality compared to the existing analog transmission schemes. IEEE Global Communications Conference (GLOBECOM) This work may not be copied or reproduced in whole or in part for any commercial purpose. Permission to copy in whole or in part without payment of fee is granted for nonprofit educational and research purposes provided that all such whole or partial copies include the following: a notice that such copying is by permission of Mitsubishi Electric Research Laboratories, Inc.; an acknowledgment of the authors and individual contributions to the work; and all applicable portions of the copyright notice. Copying, reproduction, or republishing for any other purpose shall require a license with payment of fee to Mitsubishi Electric Research Laboratories, Inc. All rights reserved. Copyright c  Mitsubishi Electric Research Laboratories, Inc., 2019 201 Broadway, Cambridge, Massachusetts 02139