近來,人工智能和機器學(xué)習(xí)技術(shù)在無線通信領(lǐng)域的應(yīng)用受到極大關(guān)注。人工智能在語音理解、圖像識別、自然語言處理等領(lǐng)域取得成功,展示了其解決難以建模問題的巨大潛力。無線通信在大量應(yīng)用場景中存在著日益增長且多樣的需求,而人工智能已成為滿足這些需求的重要使能技術(shù)。本文詳細(xì)介紹無線通信中人工智能發(fā)揮重要作用的一些典型場景,包括信道建模、信道譯碼和信號檢測以及信道編碼設(shè)計。進而,從信息瓶頸的角度討論了人工智能和信息論的關(guān)系。最后,討論了將人工智能技術(shù)深入集成在無線通信系統(tǒng)的一些想法。 

【文章來源】：Frontiers of Information Technology & Electronic Engineering. 2020,21(10)EISCICSCD

【文章頁數(shù)】：14 頁

【文章目錄】：
1 Introduction
2 AI-based channel modeling
3 AI-based channel decoding and signal detection
    3.1 Channel decoding
    3.2 Signal detection
4 AI-based channel coding design
    4.1 Polar codes with a fixed length and rate
    4.2 Polar codes within a range of code rates
5 AI-based scheduling
    5.1 Network scenario and problem formulation
    5.2 Learning methodology
6 AI and information theory
7 Future of wireless AI
8 Conclusions
Contributors
Compliance with ethics guidelines


【參考文獻】：
期刊論文
[1]Visual interpretability for deep learning:a survey[J]. Quan-shi ZHANG,Song-chun ZHU.  Frontiers of Information Technology & Electronic Engineering. 2018(01)



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