TW-SemanticComm

KO | EN

gitlite — search

#python #ai #typescript #llm #golang #go #deep-learning #docker #java #windows #awesome #vue #ios #openai

TW-SemanticComm

(★ 27)

Python code for IEEE TVT: Two-Way Semantic Communications without Feedback (Semantic Communication)

TW-SemanticComm 최신버젼 다운로드

최종 버전 다운로드 (.zip)

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

# Two-way semantic communications without feedbac

Tensorflow implementation of the [paper](https://ieeexplore.ieee.org/document/10400867) "Two-way semantic communications without feedback".

# Introduction
Semantic communications can significantly improve transmission efficiency, especially in the low signal-to-noise (SNR) regime. However, two-way semantic communications still remain an unexplored topic, which is a critical issue in many machine communication scenarios. Simply extending existing semantic communication systems to the two-way situation requires bidirectional information feedback during the training process, resulting in significant communication overhead. To fill this gap, we investigate a two-way semantic communication (TW-SC) system, where the information feedback can be omitted by exploiting the weight reciprocity in the transceiver. Particularly, the channel simulator and semantic transceiver are implemented on both TW-SC nodes and the channel distribution is modeled by a conditional generative adversarial network. Simulation results demonstrate that the proposed TW-SC system performs closing to the state-of-the-art one-way semantic communication systems but requiring no feedback between the transceiver in training process.

# System Model: Illustration of the structure of proposed TW-SC.
![ ](https://raw.githubusercontent.com/KevinKaiwenYu/TW-SemanticComm/main/figure/TW_SC.png)

# Prerequites
* [Python 3.7]

# Quick Start

Install the environment and run the Twoway_SC.py function directly for training

# Experimental results

## The loss and PSNR performance of the proposed TW-SC system during channel SNR decay

![ ](https://raw.githubusercontent.com/KevinKaiwenYu/TW-SemanticComm/main/figure/LOSSandPSNRvsSNRdecay-eps-converted-to.png)

# Citation

Please use the following BibTeX citation, if you find the code is useful for your research:

```
@article{yu2024two,
  title={Two-way semantic communications without feedback},
  author={Yu, Kaiwen and He, Qi and Wu, Gang},
  journal={IEEE Transactions on Vehicular Technology},
  volume={73},
  number={6},
  pages={9077--9082},
  year={2024},
  publisher={IEEE}
}
```

TW-SemanticComm

TW-SemanticComm 최신버젼 다운로드

오늘의 추천 프로젝트

Was this content helpful?

Recent Feedback

TW-SemanticComm

TW-SemanticComm 최신버젼 다운로드

오늘의 추천 프로젝트

Was this content helpful?

Recent Feedback

Download README