Rateless DeepJSCC for Broadcast Channels: a Rate-Distortion-Complexity Tradeoff

• URL: http://arxiv.org/abs/2603.21616v1
• Date: Mon, 23 Mar 2026 06:25:39 GMT
• Title: Rateless DeepJSCC for Broadcast Channels: a Rate-Distortion-Complexity Tradeoff
• Abstract summary: This paper introduces nonlinear transform rateless source-channel coding (NTR SCC) for broadcast channels based on rateless codes.<n>We develop unequal protection schemes that exploit decoder side information, and devise approximations to enable end-to-end optimization of rateless parameters.<n>Our framework enables heterogeneous receivers to adaptively adjust their received number of rateless symbols and decoding iterations in belief propagation.
• Score: 29.652183083806776
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In recent years, numerous data-intensive broadcasting applications have emerged at the wireless edge, calling for a flexible tradeoff between distortion, transmission rate, and processing complexity. While deep learning-based joint source-channel coding (DeepJSCC) has been identified as a potential solution to data-intensive communications, most of these schemes are confined to worst-case solutions, lack adaptive complexity, and are inefficient in broadcast settings. To overcome these limitations, this paper introduces nonlinear transform rateless source-channel coding (NTRSCC), a variable-length JSCC framework for broadcast channels based on rateless codes. In particular, we integrate learned source transformations with physical-layer LT codes, develop unequal protection schemes that exploit decoder side information, and devise approximations to enable end-to-end optimization of rateless parameters. Our framework enables heterogeneous receivers to adaptively adjust their received number of rateless symbols and decoding iterations in belief propagation, thereby achieving a controllable tradeoff between distortion, rate, and decoding complexity. Simulation results demonstrate that the proposed method enhances image broadcast quality under stringent communication and processing budgets over heterogeneous edge devices.

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