面向6G全域融合的智能接入關鍵技術綜述

王雪; 孟姝宇; 錢志鴻

doi:10.11999/JEIT231224

面向6G全域融合的智能接入關鍵技術綜述

doi: 10.11999/JEIT231224 cstr: 32379.14.JEIT231224

吉林大學通信工程學院長春 130012

基金項目: 國家自然科學基金(62171198)

詳細信息

作者簡介:
王雪：女，教授，研究方向為物聯(lián)網、D2D通信技術與異構無線網絡等

孟姝宇：女，博士生，研究方向為非正交多址接入技術

錢志鴻：男，教授，研究方向為物聯(lián)網、D2D, Wi-Fi, RFID等無線網絡與通信技術

通訊作者:
錢志鴻　dr.qzh@163.com

中圖分類號: TN92
計量
- 文章訪問數(shù): 1207
- HTML全文瀏覽量: 940
- PDF下載量: 243
- 被引次數(shù): 0
出版歷程
- 收稿日期: 2023-11-03
- 修回日期: 2024-01-24
- 網絡出版日期: 2024-01-31
- 刊出日期: 2024-05-30

An Overview of Key Technologies for Intelligent Access Toward 6G Full-domain Convergence

College of Communication Engineering, Jilin University, Changchun 130012, China

Funds: The National Natural Science Foundation of China (62171198)

摘要

摘要: 針對空天地一體化接入網絡，該文在總結相關研究的基礎上，闡述了未來空天地一體化接入架構的關鍵技術，分析了空口技術、多址技術、干擾分析、計算技術和人工智能(AI)技術等幾個重點方向的研究進展，提出了多種接入形式并存的靈活性網絡架構。針對6G全域融合網絡接入的重點研究問題，結合用戶的服務質量需求，構建了一體化AI賦能架構，提出了大規(guī)模混合多址接入及彈性資源適配策略?；诰W絡架構立體化、網絡協(xié)同傳輸、一體化網絡資源管理、未來空天地接入技術以及網絡協(xié)同計算等未來重點研究方向進行了討論和展望。
- 6G /
- 網絡架構 /
- 接入技術 /
- 空天地一體化接入網絡 /
- 空口技術
Abstract: Considering the integrated air-to-ground access network, based on summarizing the relevant research, the key technologies of future air-to-ground integrated access architecture are elaborated, and the research progress in several key directions, such as air-port technology, multiple-access technology, interference analysis, computation technology, and Artificial Intelligence (AI) technology are analyzed, and a flexible network architecture with the coexistence of multiple access forms is proposed. Considering the key research problems of the access architecture in the current air-to-ground integrated network, an integrated AI-enabled architecture is constructed by combining the user’s quality of service demand, and the large-scale hybrid multiple access and flexible resource adaptation strategy is proposed. Based on the future key research directions of network architecture stereoscopic, network cooperative transmission, integrated network resource management, future air-to-ground access technology, and network cooperative computation are discussed and outlooked.
- 6G /
- Network infrastructure /
- Access technology /
- Integrated air-to-ground access network /
- Air-port technology

HTML全文

圖 1 研究背景

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圖 2 星地統(tǒng)一空口設計思路

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圖 3 衛(wèi)星對地面系統(tǒng)產生干擾

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圖 4 6G衛(wèi)星通信網絡接入架構

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圖 5 SAGIN接入架構中的AI賦能應用

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圖 6 星地頻率共享與干擾規(guī)避

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表 1 空口可變參數(shù)集的主要參數(shù)

主要參數(shù)	參考范圍	備注
信道帶寬	180 kHz～1 GHz	適應物聯(lián)網、帶寬傳輸?shù)榷囝愋蜆I(yè)務需求
調制波形	循環(huán)前綴-正交頻分復用(Cyclic Prefix-Orthogonal Frequency Division Multiplexing, CP-OFDM)	單載波波形/OFDM
編碼方式	Polar碼、卷積碼等	可支持其他類型編碼
子載波間隔	15 kHz, 60 kHz等	提供多種子載波間隔
多址接入方式	正交頻分多址接入(Orthogonal Frequency Division Multiple Access, OFDMA)，圖樣分割非正交多址接入(Pattern Division Multiple Access, PDMA)等	根據(jù)不同場景選取不同多址接入方式
多波束協(xié)同傳輸	支持多場景波束聯(lián)合傳輸	發(fā)揮多波束聯(lián)合分集增益，提高系統(tǒng)容量
隨機接入方式	隨遇、極簡接入	根據(jù)業(yè)務需求、網絡狀態(tài)選擇接入
切換方式	極智切換	支持基于位置、終端需求的切換方式

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表 2 AI技術研究現(xiàn)狀

智能化內容/目標	AI方法	代表文獻
衛(wèi)星通信干擾感知	循環(huán)神經網絡(Recurrent Neural Network, RNN)	[55]
衛(wèi)星通信智能干擾技術	強化學習(Reinforcement Learning, RL)	[56]
信道資源調度	智能水滴算法	[57]
衛(wèi)星信道中信號失真問題	RL	[58]
多波束衛(wèi)星資源分配	多目標強化和自適應神經網路	[59]
6G衛(wèi)星通信網絡	AI賦能技術	[60]
多層衛(wèi)星通信	智能改進的深度強化學習(Deep Reinforcement Learning, DRL)算法	[61]
多波束衛(wèi)星動態(tài)資源分配	DRL	[62]

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