As one of the key techniques to realize semantic communications, end-to-end optimized
neural joint source-channel coding (JSCC) has made great progress over the past few …

Semantic communications is considered a promising technology that will increase the
efficiency of next-generation communication systems, particularly human-machine and …

In this paper, we propose a class of high-efficiency deep joint source-channel coding
methods that can closely adapt to the source distribution under the nonlinear transform, it …

This paper presents a novel wireless image transmission paradigm that can exploit
feedback from the receiver, called JSCCformer-f. We consider a block feedback channel …

The increased throughput brought by MIMO technology relies on the knowledge of channel
state information (CSI) acquired in the base station (BS). To make the CSI feedback …

We consider the design of low-delay joint source-channel coding (JSCC) schemes for the
transmission of discrete-time analog sources over noisy channels based on deep neural …

Deep learning driven joint source-channel coding (JSCC) for wireless image or video
transmission, also called DeepJSCC, has been a topic of interest recently with very …

Semantic communications are expected to accomplish various semantic tasks with relatively
less spectrum resource by exploiting the semantic feature of source data. To simultaneously …

We first develop a rate-distortion (RD) model for DCT-based video coding incorporating the
macroblock (MB) intra refreshing rate. For any given bit rate and intra refreshing rate, this …

In this paper, we present a learning scheme for Joint Source-Channel Coding (JSCC) over
analog independent additive noise channels. We formulate the learning problem by …