Article(id=1266342842868851495, tenantId=1146029695717560320, journalId=1146031591421210625, issueId=1266342817036128371, articleNumber=null, orderNo=null, doi=10.3981/j.issn.1000-7857.2026.02.00019, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1770480000000, receivedDateStr=2026-02-08, revisedDate=1776182400000, revisedDateStr=2026-04-15, acceptedDate=null, acceptedDateStr=null, onlineDate=1779849261240, onlineDateStr=2026-05-27, pubDate=1778601600000, pubDateStr=2026-05-13, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1779849261240, onlineIssueDateStr=2026-05-27, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1779849261240, creator=13701087609, updateTime=1779849261240, updator=13701087609, issue=Issue{id=1266342817036128371, tenantId=1146029695717560320, journalId=1146031591421210625, year='2026', volume='44', issue='9', pageStart='1', pageEnd='136', issueExtLink='null', onlineDate='null', pubDate='1778601600000', pubDateStr='2026-05-13', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1779849255084, creator='13701087609', updateTime=1779849689565, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1266344639704485987, tenantId=1146029695717560320, journalId=1146031591421210625, issueId=1266342817036128371, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1266344639708680292, tenantId=1146029695717560320, journalId=1146031591421210625, issueId=1266342817036128371, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=22, endPage=42, ext={EN=ArticleExt(id=1266342844504630057, articleId=1266342842868851495, tenantId=1146029695717560320, journalId=1146031591421210625, language=EN, title=Vortex wave communication technology: Advantages and challenges, columnId=1157710593584190220, journalTitle=Science & Technology Review, columnName=Special to S & T Review, runingTitle=null, highlight=null, articleAbstract=

With the rapid advancement of sixth−generation (6G) mobile communications and the vision of the Internet of Everything, spectrum scarcity has become a critical bottleneck limiting further improvements in wireless system capacity. The efficiency of traditional time−frequency domain resource mining is gradually approaching the Shannon limit. Vortex wave technology, which exploits orbital angular momentum (OAM) as an independent physical degree of freedom, offers a promising solution by breaking the constraints of conventional planar−wave transmission and opening new possibilities for high−capacity wireless communications. This paper reviews the key technologies of vortex−wave−based communication, with particular emphasis on recent progress in beam generation and manipulation, full−space multiplexed transmission, physical−layer security, and intelligent signal processing. First, reconfigurable intelligent surfaces (RIS), owing to their flexible electromagnetic parameter control and ease of integration, are expected to play a pivotal role in multi−mode vortex beam shaping and dynamic reconfiguration. Second, the incorporation of deep learning algorithms enables high−accuracy mode recognition and wavefront correction at the receiver, significantly improving system robustness and environmental adaptability. Furthermore, the inherent mode orthogonality and phase singularity of vortex waves provide unique advantages for overcoming capacity limits, enhancing physical−layer security, and enabling high−dimensional quantum information processing. Finally, the difficulties and challenges still faced by vortex wave communication, including beam divergence, atmospheric turbulence phase distortion, and mode crosstalk, are discussed, and future trends are prospected.

, authors=null, authorsList=Liming SI, Yuyuan CHEN, Qitao SHEN, Chenyang DANG, Tianyu MA, Houjun SUN, authorCompany=null, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=All rights reserved. Unauthorized reproduction is prohibited., copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1266342863370609483, articleId=1266342842868851495, tenantId=1146029695717560320, journalId=1146031591421210625, language=CN, title=涡旋波通信技术:优势与挑战, columnId=1150494644438708440, journalTitle=科技导报, columnName=本刊专稿, runingTitle=null, highlight=null, articleAbstract=

随着第6代移动通信(6G)与万物互联愿景的深入推进,频谱资源稀缺已成为制约无线通信系统容量提升的核心瓶颈,传统的时频域资源挖掘效率正逐渐逼近香农极限。涡旋波技术通过利用轨道角动量这一独立的新型物理自由度,突破了传统平面波传输模式的限制,在无线通信领域具有巨大的应用潜力。综述了涡旋波通信的关键技术,重点介绍了其在波束生成与调控、全空间复用传输、物理层安全及智能信号处理等方面的研究进展。首先,可重构智能超表面凭借独特的电磁参量调控能力和易集成优势,有望在多模态涡旋波束赋形与动态重构中起到关键作用。其次,深度学习算法的引入,可以在接收端实现高精度模态识别与波前校正,从而显著提升系统的鲁棒性与环境适应能力。再次,论述了涡旋波凭借模态正交性与相位奇点特性,在突破通信容量极限、增强物理层安全及实现高维量子信息处理方面的显著优势。最后,讨论了涡旋波通信仍面临的困难和挑战,包括波束发散、大气湍流相位畸变及模态串扰,并提出未来涡旋波通信技术的研究应重点聚焦硬件架构创新、智能算法优化及系统集成3个方向。

, authors=

司黎明,教授,研究方向为电磁场与微波技术,电子信箱:

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3Tangshan Research Institute, Beijing Institute of Technology, Tangshan 063000, China
4State Key Laboratory of Millimeter Waves, Nanjing 210096, China
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技术路线核心优势关键局限与物理代价典型适用场景
均匀圆阵列 射频基带兼容性高;易于实现“模态−频率”双重复用 模态发散角随阶数非线性增加;存在中心能量空洞 6 GHz以下及微波/毫米波频段; 基站天线;高视距多径回传链路
螺旋相位板 宽频带内相位响应稳定;极化保持能力好;高功率容量 物理形态固化,无动态重构能力;低频段器件体积庞大冗余 太赫兹及光波段;固定点对点骨干网;高能激光通信
智能超表面 亚波长低剖面易集成;具备多模态实时切换与全息重构潜力 宽带色散效应明显;有源器件引入额外插入损耗与布线控制复杂度 毫米波至太赫兹频段;6G全空间智能反射覆盖;动态多用户波束调度
), ArticleFig(id=1266342890520339379, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1266342842868851495, language=CN, label=表1, caption=

主流涡旋波生成技术的物理特性与适用场景

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技术路线核心优势关键局限与物理代价典型适用场景
均匀圆阵列 射频基带兼容性高;易于实现“模态−频率”双重复用 模态发散角随阶数非线性增加;存在中心能量空洞 6 GHz以下及微波/毫米波频段; 基站天线;高视距多径回传链路
螺旋相位板 宽频带内相位响应稳定;极化保持能力好;高功率容量 物理形态固化,无动态重构能力;低频段器件体积庞大冗余 太赫兹及光波段;固定点对点骨干网;高能激光通信
智能超表面 亚波长低剖面易集成;具备多模态实时切换与全息重构潜力 宽带色散效应明显;有源器件引入额外插入损耗与布线控制复杂度 毫米波至太赫兹频段;6G全空间智能反射覆盖;动态多用户波束调度
), ArticleFig(id=1266342890591642548, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1266342842868851495, language=EN, label=null, caption=null, figureFileSmall=null, figureFileBig=null, tableContent=
涡旋波通信优势涡旋波核心特点潜在应用价值
全空间复用[89,4445] 模态正交性:不同拓扑荷数的波束在空间上互不干扰,具备天然的正交隔离能力 突破资源瓶颈:在同频、同时、同极化条件下建立多路并行信道,突破了传统时频复用的维度限制
高通信容量[8,4647] 维度线性扩展:利用理论上无限的模态集合作为新的数据载体 频谱效率提升:实现频谱效率的线性增长,在毫米波/太赫兹频段可达Tbit/s级传输速率
强抗干扰性能[4749] 物理隔离:利用特定的模态检测机制滤除无螺旋相位特征的噪声 抗噪抗干扰:在强背景噪声和复杂电磁环境中,降低对高精度跟踪系统的依赖
物理层内生安全[5052] 相位奇点特性:波束中心存在零场强,非轴向区域相位发生畸变 天然防窃听:窃听者无法在非对准位置正确解调信号,为物理层安全提供了天然屏障
高效量子处理[5254] 高维量子态:单光子携带多个比特信息,替代传统二进制编码信息密度跃升:大幅提升单光子携带的信息量,开辟了超越传统MIMO的新物理资源
), ArticleFig(id=1266342890675528629, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1266342842868851495, language=CN, label=表2, caption=

涡旋波通信技术核心优势与应用价值

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涡旋波通信优势涡旋波核心特点潜在应用价值
全空间复用[89,4445] 模态正交性:不同拓扑荷数的波束在空间上互不干扰,具备天然的正交隔离能力 突破资源瓶颈:在同频、同时、同极化条件下建立多路并行信道,突破了传统时频复用的维度限制
高通信容量[8,4647] 维度线性扩展:利用理论上无限的模态集合作为新的数据载体 频谱效率提升:实现频谱效率的线性增长,在毫米波/太赫兹频段可达Tbit/s级传输速率
强抗干扰性能[4749] 物理隔离:利用特定的模态检测机制滤除无螺旋相位特征的噪声 抗噪抗干扰:在强背景噪声和复杂电磁环境中,降低对高精度跟踪系统的依赖
物理层内生安全[5052] 相位奇点特性:波束中心存在零场强,非轴向区域相位发生畸变 天然防窃听:窃听者无法在非对准位置正确解调信号,为物理层安全提供了天然屏障
高效量子处理[5254] 高维量子态:单光子携带多个比特信息,替代传统二进制编码信息密度跃升:大幅提升单光子携带的信息量,开辟了超越传统MIMO的新物理资源
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涡旋波通信技术:优势与挑战
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司黎明 1, 2, 3, 4, 5 , 陈玉渊 1, 2 , 沈琦涛 1, 2 , 党晨阳 1, 2 , 马天宇 1, 2 , 孙厚军 1, 2, 3
科技导报 | 本刊专稿 2026,44(9): 22-42
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科技导报 |本刊专稿 2026 , 44 (9) : 22 -42
涡旋波通信技术:优势与挑战
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司黎明1, 2, 3, 4, 5 , 陈玉渊1, 2, 沈琦涛1, 2, 党晨阳1, 2, 马天宇1, 2, 孙厚军1, 2, 3
作者信息
  • 1北京理工大学集成电路与电子学院,北京 100081
  • 2临近空间环境特性及效应全国重点实验室,北京 100081
  • 3北京理工大学唐山研究院,唐山 063000
  • 4毫米波全国重点实验室,南京 210096
  • 5深圳北理莫斯科大学工程系,深圳 518172
Vortex wave communication technology: Advantages and challenges
Liming SI1, 2, 3, 4, 5 , Yuyuan CHEN1, 2, Qitao SHEN1, 2, Chenyang DANG1, 2, Tianyu MA1, 2, Houjun SUN1, 2, 3
Affiliations
  • 1School of Integrated Circuits and Electronics, Beijing Institute of Technology, Beijing 100081, China
  • 2State Key Laboratory of Environment Characteristics and Effects for Near−space, Beijing 100081, China
  • 3Tangshan Research Institute, Beijing Institute of Technology, Tangshan 063000, China
  • 4State Key Laboratory of Millimeter Waves, Nanjing 210096, China
  • 5Faculty of Engineering, Shenzhen MSU−BIT University, Shenzhen 518172, China
出版时间: 2026-05-13 doi: 10.3981/j.issn.1000-7857.2026.02.00019
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随着第6代移动通信(6G)与万物互联愿景的深入推进,频谱资源稀缺已成为制约无线通信系统容量提升的核心瓶颈,传统的时频域资源挖掘效率正逐渐逼近香农极限。涡旋波技术通过利用轨道角动量这一独立的新型物理自由度,突破了传统平面波传输模式的限制,在无线通信领域具有巨大的应用潜力。综述了涡旋波通信的关键技术,重点介绍了其在波束生成与调控、全空间复用传输、物理层安全及智能信号处理等方面的研究进展。首先,可重构智能超表面凭借独特的电磁参量调控能力和易集成优势,有望在多模态涡旋波束赋形与动态重构中起到关键作用。其次,深度学习算法的引入,可以在接收端实现高精度模态识别与波前校正,从而显著提升系统的鲁棒性与环境适应能力。再次,论述了涡旋波凭借模态正交性与相位奇点特性,在突破通信容量极限、增强物理层安全及实现高维量子信息处理方面的显著优势。最后,讨论了涡旋波通信仍面临的困难和挑战,包括波束发散、大气湍流相位畸变及模态串扰,并提出未来涡旋波通信技术的研究应重点聚焦硬件架构创新、智能算法优化及系统集成3个方向。

涡旋波  /  轨道角动量  /  通信技术  /  智能超表面

With the rapid advancement of sixth−generation (6G) mobile communications and the vision of the Internet of Everything, spectrum scarcity has become a critical bottleneck limiting further improvements in wireless system capacity. The efficiency of traditional time−frequency domain resource mining is gradually approaching the Shannon limit. Vortex wave technology, which exploits orbital angular momentum (OAM) as an independent physical degree of freedom, offers a promising solution by breaking the constraints of conventional planar−wave transmission and opening new possibilities for high−capacity wireless communications. This paper reviews the key technologies of vortex−wave−based communication, with particular emphasis on recent progress in beam generation and manipulation, full−space multiplexed transmission, physical−layer security, and intelligent signal processing. First, reconfigurable intelligent surfaces (RIS), owing to their flexible electromagnetic parameter control and ease of integration, are expected to play a pivotal role in multi−mode vortex beam shaping and dynamic reconfiguration. Second, the incorporation of deep learning algorithms enables high−accuracy mode recognition and wavefront correction at the receiver, significantly improving system robustness and environmental adaptability. Furthermore, the inherent mode orthogonality and phase singularity of vortex waves provide unique advantages for overcoming capacity limits, enhancing physical−layer security, and enabling high−dimensional quantum information processing. Finally, the difficulties and challenges still faced by vortex wave communication, including beam divergence, atmospheric turbulence phase distortion, and mode crosstalk, are discussed, and future trends are prospected.

vortex electromagnetic waves  /  orbital angular momentum  /  communication technology  /  intelligent metasurface
司黎明, 陈玉渊, 沈琦涛, 党晨阳, 马天宇, 孙厚军. 涡旋波通信技术:优势与挑战. 科技导报, 2026 , 44 (9) : 22 -42 . DOI: 10.3981/j.issn.1000-7857.2026.02.00019
Liming SI, Yuyuan CHEN, Qitao SHEN, Chenyang DANG, Tianyu MA, Houjun SUN. Vortex wave communication technology: Advantages and challenges[J]. Science & Technology Review, 2026 , 44 (9) : 22 -42 . DOI: 10.3981/j.issn.1000-7857.2026.02.00019
在数字经济快速发展和万物互联愿景的驱动下,全球移动通信系统正加速向第6代移动通信(6G)演进。超高清全息交互、数字孪生,以及空天地一体化网络等新兴应用场景,对通信系统容量与传输速率提出了更为严苛的要求[1]。随着数据业务呈指数级增长,频谱资源稀缺已成为制约无线通信技术持续发展的关键瓶颈,传统基于时域、频域与码域的资源利用效率逐步逼近香农极限[2]。在现有以正交频分复用(orthogonal frequency division multiplexing,OFDM)和多输入多输出(multiple input multiple output,MIMO)为核心的技术体系下,单纯依赖扩展带宽或增加天线规模来提升系统容量,受到物理尺寸与能耗的双重约束,难以有效弥补未来通信面临的“容量鸿沟”[3]。因此,在有限频谱资源条件下挖掘新的物理维度以构建多模态传输机制,探索独立于频率、时间及极化之外的新型自由度,已成为学术界与工业界亟待突破的重要方向[4]。在此背景下,通信技术亟需由传统平面波传输模式向高维空间结构化电磁波方向拓展,以实现频谱利用效率的跨越式提升[5]
涡旋波是一类携带轨道角动量(orbital angular momentum,OAM)的新型电磁波束,其螺旋相位波前结构及理论上无限的正交模态特性,为突破无线通信频谱瓶颈提供了新的技术途径[6]。不同于传统平面电磁波主要利用自旋角动量(spin angular momentum,SAM)表征极化状态,涡旋波在传播轴上存在相位奇点,且相位分布随方位角呈螺旋变化[7]。不同拓扑荷数对应的OAM模态之间有严格的数学正交性,为多模复用奠定了理论基础。基于该特性,在相同频率、时间及极化条件下,可将不同OAM模态作为彼此独立的信道实现并行传输。该机制能在不增加物理带宽的前提下显著提升信道容量与频谱利用效率[8]。自Thidé等[9]首次在无线电频段实验验证电磁波可携带OAM特性以来,相关研究迅速从基础理论拓展至工程应用。当前,涡旋波通信技术被认为是后第5代移动通信(5G)及6G通信系统的重要使能技术之一。
当前,涡旋波通信的研究热点主要集中在高效涡旋波束的生成与调控、复杂环境下的信道传输特性分析,以及基于人工智能的智能信号处理等方向,如图1所示。在波束生成方面,具有亚波长结构特征的电磁超表面凭借低剖面、易集成及电磁参数灵活调控等优势,已成为实现多模涡旋波束赋形与动态重构的重要技术途径[10]。在太赫兹频段,智能超表面不仅能够实现双频段圆极化手性吸收与异常反射,还可对反射相位进行动态调控,从而实现高精度波束成形与多功能电磁调控,为非视距通信场景下的多用户覆盖提供了新的解决思路[1112]。针对大气湍流与多径效应引起的模态串扰和相位畸变问题,融合深度学习与卷积神经网络的波前校正及模态识别方法已取得显著进展,有效提升了系统在非视距与移动通信场景中的鲁棒性[1314]。此外,基于涡旋波相位奇点特性的物理层安全机制,以及OAM技术与全息成像、量子通信等领域的交叉融合,正逐渐成为新的研究方向[1516]。本文系统梳理涡旋波通信的基础理论与技术优势,重点综述其在全空间复用、抗干扰传输与智能信号处理等方面的最新进展,并探讨其面向工程应用所面临的关键挑战与未来发展趋势。
在电磁波传播过程中,电磁场不仅传输能量,同时还携带动量。其中,动量可以分为线性动量和角动量2大类,角动量J的定义如下[17]
$ \; {J}=\int\varepsilon_0{r}\times Re\left\{{E}\times{B}^*\right\}\mathrm{d}V $
式中,${{\varepsilon}_{\text{0}}}$为真空中介电常数,r为电磁场的位置矢量,E为电场矢量,B为磁场矢量,V表示积分区域的体积。
电磁波的角动量J可以分解为与极化状态相关的自旋角动量S和与空间相位分布相关的轨道角动量L
$ {{J}} = {{L}}+{{S}} $
$ {S}=\varepsilon_0\int_{ }^{ }Re\left\{{E}^*\times{A}\right\}\mathrm{d}V $
$ {L}=\varepsilon_0\int_{ }^{ }Re\left\{\mathrm{i}{E}^*\left[\hat{{L}}\cdot{A}\right]\right\}\mathrm{d}V $
式中,$ \hat{{L}}=-\mathrm{i}\left({r}\times\nabla\right) $表示OAM算子,A为矢量位函数。
具有OAM的电磁波是一类特殊的非平面波,其波前呈螺旋状分布,并在传播轴上形成相位奇点,因此通常被称为涡旋波。不同于传统平面电磁波仅携带SAM,涡旋波同时携带SAM与OAM。从波粒二象性视角来看,电磁波不仅具有幅度、频率和相位等波动性参数,同时还携带自旋角动量(对应极化)和轨道角动量(对应涡旋模态)等粒子性参数。通过对这些参数的独立调控,可显著拓展通信系统的维度和容量,如图2[18]所示。
在极化自旋量子力学体系中,与极化特性相关的固有自旋被定义为自旋角动量,其模态参数以符号s表征。线极化电磁波对应s = 0,左旋圆极化电磁波对应s = −1,右旋圆极化电磁波则对应s = 1。与之相对,电磁波的外在旋转行为被称为轨道角动量,模态参数记为l,也被称为轨道角动量的拓扑荷,表示涡旋波的旋转次数。当波前相位呈顺时针旋转时,l取负号;呈逆时针旋转时,l取正号;若波前为平面波形态,则l = 0。基于上述定义,电磁场的总角动量可以表示为j = l+s。当电磁波沿+z方向传播时,其角动量模态的具体计算需依托电磁场各分量的幅度与相位完整信息,表述如下[17]
$ j=\frac{\omega J_z}{\dfrac{\varepsilon_0}{2}\int_{ }^{ }\left(\left|{E}\right|^2+c^2\left|{B}\right|^2\right)\mathrm{d}V} $
式中
$ J_z=\varepsilon_0\int_{ }^{ }\mathrm{Re}\left\{x\left(E_zB_x^*-E_xB_z^*\right)-y\left(E_yB_z^*-E_zB_y^*\right)\right\}\mathrm{d}V $
涡旋波的相位$\phi $的变化可以用如下公式进行描述[1920]
$ \phi = {{kr}}+l\theta $
式中,k是波矢量,r是传播方向的单位矢量,$\theta $是波前的旋转角度。
由上式可知,涡旋波的相位变化包含2个核心分量:一部分与波的传播特性相关,用${{kr}}$表示;另一部分与波前的旋转角度相关,用$l\theta $表示。相位特性在涡旋波传播过程中具有关键作用,其变化直接影响波的干涉与衍射行为,进而决定涡旋波的传播规律及实际应用。涡旋波的部分典型结构如图3所示。
此外,涡旋波具备轴对称特性,在传播过程中会带有特定的轨道角动量,不同的OAM模态之间存在如下关系
$ \int\nolimits_0^{2\pi}\mathrm{e}^{\mathrm{i}l_1\varphi}\mathrm{e}^{\mathrm{i}l_2\varphi}\mathrm{d}\varphi\left\{ \begin{array}{*{20}{c}} =0,\left(l_1\ne l_2\right) \\ \ne 0,\left(l_1=l_2\right)\end{array}\right. $
式中,$ \mathrm{e}^{il_n\phi} $是OAM模态的相位项。
由上式可得,不同模态的涡旋波具有正交特性。这一独特属性使得涡旋波相较于传统电磁波,拥有更多维度的信息调制自由度,在无线通信领域,可有效提升通信系统的信道容量,并增强系统的抗干扰能力。
涡旋波的产生本质上取决于对电磁波波前相位的精确操控,即通过引入方位角依赖的相位因子来构建螺旋波前。随着无线通信频谱资源向毫米波、太赫兹乃至光波段的不断拓展,涡旋波生成技术正经历着从传统大尺寸有源天线阵列向集成化、动态化超表面器件演进的深刻变革。早期的研究多奠基于Allen等[7]关于Laguerre−Gaussian光束携带OAM的物理机制,而当前的技术焦点已转向如何在高频段实现高纯度模态的激发、多模态复用信道的隔离以及波束特性的实时动态调控。这种技术模式的转变,旨在克服传统方法在体积、带宽及灵活性上的固有局限,为构建下一代大容量、高维度的无线通信系统奠定物理层基础。
在微波与毫米波频段,基于均匀圆形阵列的涡旋波生成技术因其结构简单且易于拓展,已成为当前产生涡旋波束的主流方案。传统的均匀圆形阵列产生机制主要依赖于相控阵原理,然而这种方法生成的涡旋波束天然呈现出中心能量为空的形态,且波束的发散角会随着OAM模态值的增加而变大,导致传输增益降低。为了突破这一能量发散的瓶颈,Ma等[21]提出了一种基于波形分集的生成方案,该方法通过消除波束中心场的相干抵消效应,成功将原本发散的空心波束转化为能量高度集中的定向实心波束,在保留涡旋特性的同时实现了波束的准直发射,极大地提升了均匀圆形阵列在OAM应用中的工程价值,如图4(a)[21]所示。Guo等[22]提出了一种径向均匀圆形天线阵列的结构,通过多层堆叠设计与特定的馈电网络优化,有效抑制了寄生辐射对主模态的干扰,如图4(b)[22]所示。实验结果表明,该天线在5.72~5.95 GHz频带内能够同时激发$l = \pm 1$的双模态涡旋波束,且模态间的隔离度显著提升至19 dB以上。
受限于金属加工精度的物理瓶颈,传统金属天线难以在更高频段继续发挥作用,此时,基于介质厚度调控的螺旋相位板因其结构简单而成为高频涡旋波产生的有效手段。针对传统螺旋相位板普遍存在的表面反射损耗问题,Hui等[23]引入传输线理论对介质层进行了阻抗匹配设计,成功制备出毫米波段的超低反射率螺旋相位板,将反射损耗降低了20 dB以上,如图4(c)[23]所示,极大提升了能量传输效率。与此同时,制造技术的进步为复杂光学器件的快速制备提供了新途径,Pinnock等[24]利用高精度3D打印技术制造了太赫兹波段的螺旋相位板,并结合马赫−曾德尔干涉仪精确表征了生成光束的拓扑电荷,如图4(d)[24]所示,证明了这种低成本制造方法在快速原型验证中的巨大潜力。
为了进一步顺应通信设备小型化与集成化的趋势,具有亚波长厚度的超表面技术以其独特的二维紧凑架构优势[25],逐渐成为涡旋波产生领域的研究前沿。Lü等[26]提出了一种基于单层介质基板的低剖面透射超表面,如图5(a)[26]所示,通过引入“维度扩展”设计理念,在Ku波段实现了高效的涡旋波束生成,该设计不仅显著降低了器件剖面,还简化了加工工艺,易于与平面集成电路兼容。除了标量波束的调控,超表面在矢量光场操控方面也展现出独特优势,Si等[27]基于Pancharatnam−Berry(P−B)几何相位原理,设计了像素化靶盘结构的透射超表面,成功生成了具有不同偏振分布的双矢量涡旋波束。Faraz等[28]通过引入多重几何相位机制,实现了兼具宽带透射与反射功能的超表面,如图5(b)[28]所示,展示了由对称性破缺引起的模态分裂等物理现象。为了进一步突破多层结构中的效率瓶颈与串扰限制,Si等[29]提出了一种基于几何相位的无串扰自旋选择性超表面,以高达97%的效率实现了对反射与透射涡旋波束的独立相位调控。此外,针对传统超表面单元设计中存在的参数扫描效率低下与物理性能受限问题,Wu等[30]通过引入像素级修饰设计出能够同时实现波束聚焦与多模态(l=1, 2, 3)涡旋波产生的高性能多功能惠更斯超表面,如图5(c)[30]所示,为超表面的自动化与高效设计提供了新思路。
静态超表面虽然实现了器件的轻量化,但其功能一旦固化便无法适应动态时变的信道环境,因此,动态可重构与数字编码超表面成为当前的学术焦点。特别是集成了传感与计算能力的智能超表面系统,已展现出通过多模态交互实现电磁波束实时主动调控的潜力[31]。在具体的涡旋波生成应用中,Han等[32]设计了一种基于positive intrinsic−negative(PIN)二极管的1−bit数字编码反射超表面,如图6(a)[32]所示,通过现场可编程门阵列(field programmable gate array,FPGA)控制单元的通断状态,实现了对反射相位的实时重构及OAM模态的电子切换。在此基础上,Tang等[33]进一步引入时空编码概念,对应的时空编码超表面如图6(b)[33]所示。利用时间维度的周期性调制引入谐波分量,实现了对涡旋波束复振幅的准连续调节。
在太赫兹与光学等更高频段,新型二维材料与相干合成技术的引入为动态涡旋波生成赋予了更多自由度。Tang等[34]利用石墨烯电导率的可调谐特性,设计了宽带可调的太赫兹超表面,通过混合调制机制实现了复振幅调控及全息成像的动态切换,展示了碳基材料在动态光子器件中的应用前景。在此基础上,Ma等[35]进一步提出了石墨烯时空可重构智能超表面,通过动态调控石墨烯化学势,在太赫兹频段成功实现了多波束偏振态的实时操控与全息成像。而在高能激光领域,Zhi等[36]提出并验证了利用光束阵列相干合成技术产生高功率轨道角动量光束的新方案,如图6(c)[36]所示。该研究基于六单元六边形光纤放大器阵列,采用单频抖动算法的主动相位锁定技术控制阵列光束间的活塞相位差,并通过施加螺旋阶梯状的相位调制,成功在实验中合成了拓扑荷数为±1的高功率涡旋光束。这种方法有效克服了传统涡旋相位调制器及单路光束的功率限制,且合成的不同模态OAM光束具有正交性,表明未来的涡旋波生成技术将向着全频谱覆盖、全参数调控及智能化集成的方向加速发展。
尽管上述多种涡旋波生成技术在拓展通信维度方面均展现出显著潜力,但在实际系统部署中,其物理形态、调制灵活性与系统损耗之间不可避免地存在着固有的工程权衡。表1展示了当前主流涡旋波生成技术的物理特性与适用场景对比。可以发现,无论是传统阵列的发散效应、介质相位板的模态固化,还是有源超表面的色散与损耗,物理层生成器件的硬件瓶颈往往难以被单一的技术手段彻底抹平。这种硬件层面的固有非理想特性,对接收端信号的抗畸变与高精度解析提出了严苛要求。
随着OAM通信技术从理想实验室环境向复杂实际场景应用发展,大气湍流、多径效应及非理想对准等物理因素已成为制约系统性能的关键瓶颈。Willner等[15]指出,大气湍流引起的波前相位畸变与模态间串扰,会显著降低链路信噪比并提升误码率。针对这些高度非线性的信道损伤,传统自适应光学与信号处理方法往往面临计算复杂度、硬件成本高等问题。在此背景下,人工智能技术,尤其是深度学习,凭借其强大的特征提取能力与高维非线性拟合能力,正在深刻改变OAM系统的接收、检测与信号处理流程。通过数据驱动的模式,深度学习能够有效补偿湍流引起的波前畸变,实现对模态的精确识别与纠错。相关研究表明,该方法在非视距及移动通信场景中表现出优异的鲁棒性与适应性。由此,人工智能为复杂环境下的涡旋波通信提供了新的高效解决方案,并推动其向工程化应用迈进。
深度学习为涡旋波通信系统的优化与工程化应用提供了新的高效工具。例如,针对大气湍流引起的相位畸变问题,深度学习提供了一种高效的无波前传感器补偿方案。Zhai等[37]构建了一个能够从畸变强度图直接推断湍流相位的深度神经网络模型,如图7(a)[37]所示。该网络通过学习光强分布与前20阶Zernike多项式系数之间的非线性映射关系,可实时生成校正相位图并加载到空间光调制器上,从而有效恢复光束的模态纯度与偏振特性。该方法摒弃了传统自适应光学系统中昂贵的Shack−Hartmann传感器,显著降低系统成本并提升校正响应速度,为自适应光学技术在商业化自由空间光通信中的应用提供了可行路径。除用于大气湍流补偿外,机器学习在涡旋波器件前端的快速设计中也展现出巨大潜力。通过构建神经网络预测超表面结构的反射相位,可在亚毫米波及太赫兹频段显著提升多模态涡旋波束的设计精度与效率[38]
在接收端的模态识别与解复用中,基于计算机视觉的卷积神经网络展现出替代传统光学模态排序器的巨大潜力。Doster等[39]指出涡旋波束在叠加或传输后形成的干涉图样具有独特的“指纹”特征。通过训练卷积神经网络直接处理接收到的光强图像,可在无须严格光学对准或复杂解调光学链路的条件下,实现对叠加OAM模态的高精度分类与解复用,如图7(b)[39]所示。这种方法显著简化了接收机的物理架构,同时降低了系统复杂度。更重要的是,在大气湍流干扰下,该方法的鲁棒性优于传统共轭模式检测技术。因此,卷积神经网络为涡旋波通信接收端的高效、可靠处理提供了新的可行路径。
针对实际传输链路中常见的遮挡效应与强噪声干扰,人工智能算法表现出优于传统解析方法的信号恢复能力。Sun等[40]在射频频段的研究发现,即使涡旋波束受到部分物理遮挡,其剩余的局部场分布仍蕴含着核心的拓扑荷信息。他们提出了一种基于深度卷积神经网络的稀疏采样识别方法,采用了34层残差网络的结构。该方法仅利用3×3的极少采样点,即可实现对整数阶,甚至分数阶OAM模态的快速准确识别,且在信噪比极低的环境下仍能保持高分类精度。该成果对城市峡谷等复杂电磁环境或受限观测条件下的OAM通信系统具有重要工程指导意义。研究充分证明了人工智能在非完备信息条件下的信号重构与模态识别能力,为实际通信系统的可靠部署提供了新的技术路径。
为进一步提升系统集成度与处理效率,研究者开始探索将OAM模态识别与波前畸变补偿联合处理的多任务学习框架。Lu等[41]设计了一种具有共享骨干网络的卷积神经网络架构,如图7(c)[41]所示。该网络能够同时并行执行OAM模态识别和波前畸变补偿2个任务。通过联合训练策略,网络不仅能够在湍流干扰下准确识别OAM信号类别,还可解析信号的精细相位结构。多任务学习充分利用了任务间的特征相关性,在保证高识别精度和补偿效果的同时,显著降低了计算资源消耗和推理延迟。这为对实时性要求极高的光通信系统提供了一种紧凑、高效的解决方案,也为涡旋波接收端的智能化处理提供了新的实现途径。
OAM模态已被引入光计算领域,并与人工智能硬件架构实现深度融合,为全光计算开辟了新方向。Wang等[42]提出一种基于光学衍射神经网络的逻辑运算单元,通过多层物理衍射板在光速下对入射OAM光束进行相位调制,并利用光场的衍射叠加与干涉实现逻辑判断。该全光计算架构有效避免了传统光电转换带来的延迟瓶颈与能耗,展现了OAM在高通量、低能耗光子计算及智能处理中的独特优势。此外,在涡旋波核心器件设计与构建中,人工智能也表现出强大的逆向设计能力。Wu等[43]提出了一种融合深度神经网络与遗传算法的“相位−图案”逆向设计架构,有效克服了传统超表面设计依赖烦琐全波仿真的瓶颈,实现了OAM发生器等功能性超表面的快速与精准构建。这些研究表明,OAM技术与人工智能方法的结合不仅提升了器件设计效率,也为全光计算与智能光子处理提供了新的实现路径。
涡旋波通信系统的构建本质上是一种基于正交基函数展开的信号处理过程,其核心在于利用OAM模态作为空间域的独立载波,从而建立多维度的信号传输模型。在发射链路的数学建模中,通信过程被视为将多路基带信号映射到一组空间正交基$\left\{ {{\Psi _l}(r,\phi )} \right\}$上的线性变换过程。具体而言,发射机将N路独立的时间域数据流${s_n}(t)$分别进行加权,与具有特定拓扑荷数${l_n}$的高斯波束进行复振幅调制。与传统通信仅利用时频资源不同,OAM发射信号${S_{Tx}}$在空间域表现为多个正交本征模态的相干叠加。其数学表达式可描述为各路信号在空间基底上的线性组合[5]
$ S_{Tx}(r,\phi,t)=\sum\limits_{n=1}^N\beta_ns_n(t)A_n(r)\mathrm{e}^{\mathrm{i}l_n\phi} $
式中,${\beta _n}$为功率分配系数,${A_n}(r)$为径向幅度包络,$ \mathrm{e}^{\mathrm{i}l_n\phi} $则是赋予信号空间指纹的相位项。
这种信号构建方式确立了信息流在物理层面的并行共存机制,为后续在同一频点下的独立传输提供了严谨的数学基础。
在接收端的信号检测环节,其物理本质是执行基于空间内积运算的匹配滤波过程,而非简单的能量检测。接收系统利用与发射模态共轭的相位掩膜或模态分拣器,构建出针对特定信道${l_k}$的空间相关器。根据泛函分析中的正交性原理,当接收到的混合场与本地生成的检测基函数$ \mathrm{e}^{-\mathrm{i}l_k\phi} $进行卷积积分时,只有与目标模态指数匹配的分量会产生非零的互相关峰值,而其他正交模态分量则因相位在圆周积分路径上的矢量抵消而归零。针对第k路信号的解调输出${y_k}(t)$可由下述空间积分公式精确描述[17]
$\begin{split} y_k(t)=\left\langle S_{Tx},\Psi_{l_k}\right\rangle=&\int\nolimits_0^{2\pi}S_{Tx}(r,\phi,t)\mathrm{e}^{-\mathrm{i}l_k\phi}\mathrm{d}\phi\\=&\; 2\pi\beta_ks_k(t)A_k(r) \end{split} $
式中,${\beta _k}$为第k路信号的功率分配系数,${A_k}(r)$为第k路信号的径向幅度包络,${s_k}(t)$为第k路信号的数据流。
这一数学过程揭示了涡旋波通信区别于传统空分复用的核心特征:它不依赖于复杂的信道状态信息反演或迫零均衡算法,而是依靠波前结构的物理正交性直接实现信道的对角化分离,从而在理论上消除了流间干扰。
从信息论的自由度视角审视,涡旋波通信技术通过引入角向指数,显著拓展了通信系统的状态空间维度。不同于传统单模系统受限于时频带宽积,涡旋波通信系统的信道容量上限由空间模态的有效数量决定。对于一个拥有N个正交模态的传输系统,其总谱效率并非单一信道的简单延伸,而是表现为N个独立并行高斯信道谱效率的代数和。在理想的加性高斯白噪声信道下,系统的理论极限容量$ C\mathrm{_{total}} $可由扩展的香农公式导出[8]
$ C\mathrm{_{total}}\approx\sum\limits_{n=1}^NBlog_2(1+\frac{P_n\left|h_n\right|^2}{\sigma^2}) $
式中,$ {P_n} $$ {h_n} $分别为第n个模态的发射功率和信道增益,${\sigma ^2}$为噪声功率。
该模型表明,涡旋波通信技术本质上是在物理空间中开辟了新的通信维度,使得系统能够在保持频带宽度B不变的情况下,通过增加模态维度N来线性提升信息吞吐量,这为解决未来超宽带通信的瓶颈提供了确定性的理论支撑。
在无线通信频谱日益紧缺的背景下,涡旋波凭借其携带的轨道角动量,为现代通信系统提供了独立于频率、时间、码域及极化之外的新物理自由度。不同于传统平面波技术依赖带宽扩展或大规模天线阵列叠加以提升系统容量,涡旋波利用模态间的严格正交性,可在物理层面直接构建多路并行传输通道,从而在受限资源条件下实现传输效率的显著提升。基于这一特性,涡旋波通信在工程应用中展现出5方面的优势:全空间复用机制、系统容量的实质性提高、复杂环境下的抗干扰能力、物理层内生安全特性,以及高效量子信息处理能力。这些特性不仅为传统通信系统提供了新的设计思路,也为后5G及6G通信网络的容量扩展和可靠性保障提供了理论依据。表2总结了涡旋波通信技术的核心优势及其潜在应用价值。
涡旋波技术利用轨道角动量在空间域构建了真正的“全空间复用”架构,从根本上突破了平面波通信的维度限制。传统的频分复用和时分复用技术对资源的挖掘已接近香农极限,而OAM技术通过引入拓扑荷数这一离散且理论上无限的复用自由度,实现了信道资源的维度解耦。这意味着在同一中心频率、同一传输时刻以及同一极化状态下,通信系统可以共存多路互不干扰的独立信道,每路信道对应一个独特的正交模态,如图8(a)[8]所示。Thidé等[9]发表的研究证实,利用OAM模态的数学正交性,通信链路可以在不增加物理带宽消耗的前提下,通过同轴叠加不同模态的波束来实现传输能力的线性扩展。这种复用方式本质上是对空间谱资源的深度开发,将原本单一的无线信道转化为由多个正交子信道组成的空间通道,极大地提升了频谱利用效率。
基于涡旋波的全空间复用技术在工程实现上展现出了与现有通信体制极高的兼容性,能够以低成本实现系统升级。Sasaki等[44]在28 GHz毫米波频段的实验中证明,基于均匀圆形阵列的OAM复用系统能够与正交频分复用技术完美结合,形成高效的“模态−频率”双重复用架构,如图8(b)[44]所示。与传统空分复用严重依赖复杂的基带信号处理算法来消除用户间干扰不同,OAM复用的信道隔离度源于电磁波物理层面的天然正交性。这种“物理硬隔离”特性显著降低了接收端的计算复杂度,使得在点对点回程链路或光纤替代场景中,能够以较低的硬件成本实现吞吐量的倍增。
全空间复用还体现在对“内禀”与“外禀”2种空间属性的综合利用上,为系统资源调度提供了双重自由度。Zhang等[45]研究指出,OAM物理量不仅包含依赖于天线空间分布与坐标系选择的外禀角动量,还包含独立于坐标选取的内禀角动量。在系统设计中,利用外禀模态可以实现宏观尺度的空间波束复用,解决多用户接入问题;而利用内禀模态则可以在紧凑的发射孔径内实现高密度的信号调制,解决设备小型化问题。这种多维度的资源调度能力,使得通信系统能够在受限的物理空间和功耗约束下,最大化地挖掘电磁波的承载潜力,实现了单位体积内信息传输效率的最优化。图8(c)[45]展示了从传统MIMO到基于均匀圆阵列、专用天线及量子OAM传输的硬件形态演进。
基于OAM的模分复用技术利用波束的正交特性,为大幅提升无线通信系统的容量提供了确定的物理层解决方案。Gong等[46]研究指出,在自由空间通信链路中,该技术允许通过单一孔径同时传输多个相互正交的波束,其中每一个涡旋波束均可作为一个独立的信道来携带互不相关的信息流。系统的总通信容量将直接随着所复用的独立波束数量的增加而成倍增长。该研究进一步表明在发射端将多个OAM模态调制进单一波束,并在接收端利用波束的正交性进行解复用是完全可行的。尽管高阶模态的强度奇异性在远场传输中会导致扩散和串扰,但在近场或中场范围内,OAM复用技术能够有效维持各信道间的隔离度,从而在不增加频带资源的前提下显著拓展通信容量。
OAM技术与MIMO架构的深度融合显著解决了传统视距传输下的信道秩亏缺问题,从而大幅提升了通信容量。在传统的视距MIMO系统中,由于缺乏丰富的散射体环境,信道矩阵往往呈现高度相关性甚至奇异性,导致多天线带来的空间复用增益急剧下降。Yan等[8]的实验数据表明,涡旋波束特有的螺旋相位结构能够天然地降低视距信道间的相关性,使得MIMO系统在强视距环境下依然能保持满秩传输状态。这意味着OAM−MIMO架构在不需要复杂散射环境的情况下,也能充分释放多天线的并行传输能力,将视距链路的极限传输速率提升至Tbit/s量级,极大地拓展了高频段通信的应用边界。
从系统整体吞吐量的优化角度来看,OAM技术为受限孔径下的容量最大化提供了确定的物理优化手段,能够显著提升系统吞吐量。Ren等[47]的研究分析表明,在发射孔径有限的实际约束下,单纯增加MIMO流数可能会导致信道相关性增加,而通过混合使用OAM模态流和传统MIMO流,可以精确匹配信道的特征值分布。图9[47]展示了在传统空间复用技术基础上采用OAM复用技术的视距毫米波通信链路,通过自适应地分配发射功率和选择最优的模态子集,OAM−MIMO系统能够在多径效应和视距传输并存的混合信道中保持稳健的高吞吐量性能。这种高容量特性使得OAM技术在数据中心内部高速互联、基站前传、回传等对带宽要求极高的固定无线接入场景中,具备了超越传统平面波技术的显著性能优势。
涡旋波通信在复杂电磁环境中还表现出优异的抗干扰能力与频谱兼容性。由于OAM模态间的严格正交性,接收机可以通过特定的模态检测机制,像滤波器一样有效滤除不具备相应螺旋相位特征的背景噪声或多径干扰信号。基于模态间隔优化的自适应传输策略,显著提升了OAM系统针对天线未对准等工程问题的鲁棒性。Xiong等[48]建立了包含未对准参数的信道模型,研究发现模态间的能量串扰并非均匀分布,而是主要集中在相邻阶数之间。基于此发现,通过动态采用稀疏模态配置,系统可以有效规避高串扰区域,从而维持较高的信干噪比。这种从算法层面进行的智能优化,赋予了系统在物理抖动或对准偏差发生时的避险能力,确保了通信链路在非理想机械条件下的信噪比稳定性,大幅降低了对高精度跟踪系统的依赖。
在此基础上,新型手性超表面天线的设计进一步从物理层增强了系统的抗干扰与极化隔离能力。Liao等[49]提出了一种基于自旋选择性超表面的圆极化轨道角动量折叠透射阵列天线,如图10[49]所示。利用圆极化波束天然抑制多径效应和极化失配的特性来提升链路鲁棒性。该设计采用了具有自旋依赖响应的超原子单元,实现了对特定旋向入射波的高效透射与正交极化波的反射滤波,从而在硬件端构建了针对非目标极化噪声的天然屏障。实验结果表明,该系统在8.7~9.5 GHz的宽频带内不仅保持了低于3 dB的轴比,确保了良好的圆极化特性,而且生成的OAM模态纯度超过0.8,有效遏制了模态间的能量串扰。此外,这种折叠式结构在实现低剖面集成的同时,提供了高达18.3 dBi的峰值增益,通过显著提升接收端的信干噪比,进一步巩固了OAM通信在长距离传输中对抗环境噪声的工程能力。
跨层信号处理技术进一步增强了涡旋波通信系统对大气湍流的抗扰能力。尤其是MIMO均衡算法的应用,通过在接收端同时对多模OAM信号进行联合解耦与相位校正,实现了不同模态间干扰的有效抑制,提高了系统在复杂信道下的信号恢复精度和传输可靠性。大气湍流引起的折射率随机波动会破坏波前相位结构,导致能量泄漏至其他OAM模态。Ren等[47]的研究表明,通过在接收端部署数字域MIMO均衡器,可以逆向恢复被混叠的信号。该方法通过导频信号精确估计信道传递函数,并利用逆矩阵运算高保真地重建原始正交模态,有效抵消了大气信道引起的相位畸变。该协同机制显著提升了OAM通信在非理想环境下的鲁棒性。借助这一技术,系统不再依赖实验室理想条件,即可在风雨、雾霾等复杂气象环境中维持稳定连接。由此,跨层信号处理与MIMO均衡技术为OAM通信的工程化应用提供了可靠保障。
涡旋波束独特的空间强度分布天然构建了物理层安全屏障,从底层限制了非授权接收的可能性。与传统平面波在空间上均匀覆盖不同,涡旋波束在横截面上呈现中心光强为零的“甜甜圈”形分布,且相位围绕中心轴存在奇异点。由此,只有位于波束主轴附近并配备匹配解调模态的合法接收者,才能获得最大信号增益并正确恢复信息。对于偏离主轴的窃听者,由于无法精确对准相位奇点,其接收到的信号将产生严重波前畸变和能量衰减。该空间位置选择性机制无须依赖上层复杂加密算法,即可在物理层提供基础安全保障,尤其适用于对低延迟与高安全性同时有要求的通信场景。涡旋波的这一特性为未来OAM通信系统在安全可靠性方面提供了天然优势,也为物理层安全设计提供了新的思路。
可重构智能表面技术的引入将系统的安全机制从被动隔离升级为主动防御。Wang等[50]提出的联合优化方案利用可重构智能表面对电磁波的灵活调控能力,在物理空间中制造出了一个仅对合法用户透明的通道,如图11(a)[50]所示。该方案一方面通过波束赋形增强指向合法用户的信号强度,另一方面向潜在的窃听方向人为引入人工噪声或扰乱波束的相位结构。这种智能调控能力,极大地增加了窃听者的信号处理难度,有效抵御了主动式和被动式的窃听攻击,并且在可重构智能表面辅助下,合法信道与窃听信道之间的容量差得到了显著提升。在此基础上,Gu等[51]进一步提出了一种基于双频复振幅超表面的物理层加密架构,如图11(b)[51]所示,通过融合改进的视觉秘密共享方案与三维波前重构算法,成功实现了不需要码本传输的高容量与高鲁棒性安全通信。
OAM模态的高维正交特性为动态密钥生成提供了丰富的物理层随机性,从而显著增强了通信的不可预测性。通信双方可利用不同模态在湍流信道中衰减特性的差异,提取高度随机的信道特征作为动态密钥,实现物理层加密。尤其在量子密钥分发中,引入高维OAM态使单个光子能够携带多个比特的密钥信息,这不仅显著提升了密钥生成速率,而且增强了对窃听干扰的容忍度[52]。一旦窃听者尝试对光子进行测量或拦截,必然破坏其高维量子态,从而产生高误码率并被系统即时检测。借助这一特性,OAM在构建下一代高等级安全通信网络中具有独特优势。结合物理层的空间选择性与量子态不可克隆性,OAM技术为实现低延迟、高安全的通信提供了新的技术路径。该机制为未来高安全通信系统设计提供了坚实的理论基础与工程参考。
传统量子比特受限于二维希尔伯特空间,单光子的信息承载能力十分有限,而OAM光子所携带的拓扑荷数在理论上构成了无限维度的正交基。Mirhosseini等[52]的研究表明,利用OAM的高维特性,可以实现七维乃至更高维度的量子态制备与分发,该高维量子通信系统示意如图12[52]所示。高维OAM编码能够显著增加单光子承载的信息量(即log2d比特,其中d为维度),从而在相同光子通量下实现信息传输速率的成倍提升。对于光子资源受限的远距离量子通信,这意味着传输效率的质的飞跃,是传统极化编码难以企及的物理优势。更高维度的量子态还可增强系统对噪声与窃听干扰的容忍能力,提高量子密钥分发的安全性和可靠性。结合OAM的高维正交特性与物理层随机性,未来高效量子通信网络的容量与安全性均可得到显著优化。这一特性为量子通信技术在远距离、高速、高安全场景下的工程应用提供了新的理论支撑与实现路径。
光子集成技术的突破实现了高维量子态的高效制备与测量,推动了基于OAM的量子系统向实用化发展。Ahmad等[53]提出利用光子晶体面发射激光器直接产生高纯度OAM光束的方法,有效克服了传统空间光调制器体积大、响应速度慢的局限。结合高灵敏度单光子探测阵列,系统能够在极低光子通量下实现对高维OAM态的精准制备与测量。芯片级光源与探测器的紧密结合,使得在弱光条件下进行长距离高维量子纠缠分发成为可能。该方案有效解决了量子网络在传输距离与信噪比方面的双重挑战,同时提升了量子态制备与测量的稳定性和可靠性。依托此类集成化硬件,高维OAM量子通信系统在实际量子互联网部署中具备可行性与扩展性。由此,光子集成技术为构建广域、高速、安全的量子通信网络奠定了坚实的工程基础。
高维OAM态在抗量子信道噪声方面展现出显著的容错优势,从而增强了量子链路的稳定性。Ecker等[54]的研究表明,高维纠缠态相较于传统二维纠缠态,对环境噪声具有更强的鲁棒性,能够在更高误码率门限下维持量子安全性。这意味着,在相同信道湍流或背景噪声条件下,基于OAM的量子通信系统能够承受更强的干扰或窃听尝试而保持链路连续性。高维编码带来的信噪比增益,对于构建穿越大气层的卫星量子通信链路或复杂城域量子网络具有重要工程意义。与此同时,这一特性有助于提升量子密钥分发的速率与安全性,为大规模量子网络部署提供技术保障。高维OAM态的应用体现了量子通信从低维、低容量向高维、高稳定性方向的技术升级趋势,为未来广域量子互联网的可靠实现奠定了基础。
涡旋波通信技术通过引入轨道角动量作为全新的模分复用维度,在理论上为突破传统无线通信的香农极限提供了新的物理自由度。然而,与传统平面波通信主要依赖时频域资源分配不同,OAM通信系统的信道容量严格依赖于波前螺旋相位结构的完整性与模态正交性。在实际应用中,这种复杂的空间相位拓扑对环境扰动极为敏感,任何物理扰动均可能破坏模态间的正交性,导致信号串扰与能量泄漏。当前的研究挑战已从传统的信噪比优化转向空间相位分布的高精度维持与动态重构。制约OAM技术工程化落地的关键因素包括宽带相位响应的非线性色散、模态依赖的衍射发散极限、受限孔径下的正交性破缺,以及高维信号处理的实时算力瓶颈等。针对这些问题,亟需在器件设计、波束控制与跨层信号处理等方面建立协同优化策略。图13展示了涡旋波通信在实际环境下所面临的主要物理限制及工程挑战,为后续相关技术的研究与优化提供参考依据。
涡旋波束特有的“模态依赖性发散”物理机制,导致了通信容量与传输距离、接收孔径之间存在着传统视距通信所不具备的非线性约束。在传统微波或激光通信中,波束的发散角主要取决于波长与发射孔径,与信号携带的信息量无直接关联。然而,Padgett等[55]基于物理光学的推导证实,涡旋波束的中心暗斑半径及远场发散角不仅与传播距离有关,更与拓扑荷数l的平方根成正比。这意味着,为了通过增加模态阶数l来提升系统容量,波束的横截面积将呈非线性扩张,导致能量在长距离传输后迅速稀释至接收范围之外。此外,在宽带通信场景中,相位响应的非线性色散特性[56]及连续模态生成中的频率依赖性[57],会导致不同频率成分的波束发散角不一致,这进一步加剧了接收端在捕获完整信号能量时的孔径匹配难度。这种发散特性使得OAM通信在链路预算上比传统MIMO系统更为紧张,在长距离骨干网中的应用面临严峻的功率挑战。
接收端物理孔径的有限性在OAM通信中会引发“孔径截断效应”,导致模态间的本征正交性在物理层面上受损,产生不可逆的信道串扰。传统通信中孔径受限主要导致接收功率下降,而OAM模态的正交性依赖于在完整环形区域内的复振幅积分,一旦接收孔径无法覆盖整个光斑,正交性条件即不再成立。Zheng等[58]的理论分析表明,孔径截断会导致原本单一的模态频谱发生严重的展宽与混叠,使得单一发射模态被接收端解析为多个模态的叠加。此外,大气湍流对螺旋相位波前的非线性调制效应,构成了自由空间OAM通信链路中不可忽视的环境干扰因素,其破坏机理远复杂于传统衰落。OAM通信面临的湍流效应表现为折射率随机起伏引起的相位扭曲,这直接破坏了涡旋波束的轴对称性。Krenn等[59]的研究表明,大气湍流引起的一阶波前畸变会导致OAM模态与接收端检测孔径之间发生相对未对准。Ren等[60]提出的深度学习恢复方案虽然证明了抗湍流的潜力,如图14[60]所示,但也揭示了在强湍流下,高阶模态的相位结构极易破碎成无序的散斑,这要求系统必须配备比传统通信更为稳健的实时波前补偿机制。
总体而言,涡旋波在接收端面临的核心挑战,本质上是复杂传输环境导致的物理波前与接收硬件孔径之间的“时空失配”问题。无论是发散效应引起的能量稀释,还是湍流导致的相位扭曲,都打破了理论上完美正交的接收前提。为了跨越这一物理鸿沟,未来的研究应聚焦于多维度的动态波束追踪与自适应孔径补偿技术。在射频与微波前端层面,亟需引入基于高精度S参数在线校准的自适应匹配网络,通过实时提取各通道的幅相畸变信息来进行底层硬件补偿。同时,构建大规模相控阵与动态可重构超表面相协同的混合接收架构,利用可编程逻辑门阵列驱动的高速波束赋形算法,在电磁波到达物理接收机基带前,可在空间域与模拟域完成第一轮波前预畸变校正,从而最大限度地降低孔径截断带来的不可逆损失。
涡旋波束中心固有的相位奇点特性限制了传统自适应光学系统的适用性,使得涡旋波通信无法简单沿用现有的波前校正技术。涡旋波束中心存在光强为零的区域(即相位奇点),这使得依赖光强梯度的传统波前传感器在波束核心区域形成探测盲区,无法有效提取关键的畸变信息。Guo等[61]指出,在强湍流环境下引起的相位畸变,传统的线性相位校正算法难以精确拟合,残余的相位误差仍可能导致高阶OAM模态的判决错误。相比之下,传统通信系统对相位噪声通常具有一定的容忍度,且可以通过导频技术进行线性估计,而涡旋波系统则需面对“相位畸变即误码”的严峻挑战。此外,信号处理算法的复杂度还受到硬件执行单元物理特性的制约。Abdelraouf等[62]指出,现有的动态调控超表面往往伴随着不可忽视的相位非线性响应与插入损耗,使接收端算法必须在处理外部信息的同时,需要额外消耗算力来对器件本身的固有畸变进行非线性均衡,进一步加剧了系统实时处理的延迟瓶颈。图15[62]展示了多种典型的电控可调材料与器件结构,包括氧化铟锡(ITO)全固态超表面、砷化铟(InAs)等离激元结构、液晶集成器件、铁电材料及相变材料天线。
针对涡旋波信道特有的非线性畸变,卷积神经网络等数据驱动方法在波前恢复与模态识别方面表现出明显优于传统算法的性能。然而,Wang等[63]研究指出,为在强湍流条件下实现高精度模态识别,神经网络通常需要处理高分辨率的光强图像,涉及海量浮点运算,计算开销极大。Ren等[60]在实验中采用的深度卷积神经网络虽然能够实现极高的恢复精度,但其复杂的网络结构导致推理延迟难以满足高速通信的实时性要求。由此,在功耗受限的移动终端环境下,如何兼顾深度学习模型的恢复精度与纳秒级实时推理能力,成为当前OAM信号处理领域亟待突破的算力瓶颈。总体而言,传统的线性信号处理范式难以应对相位奇点带来的非线性畸变,而一味堆叠深度学习模型的参数量又会使得通信系统延迟变高。为了解决这一问题不仅要在算法层面推进网络模型的轻量化,而且要从底层硬件架构出发,进行深度的“算法−硬件”协同重构。在数据流转路径上,需要打破传统的总线吞吐瓶颈。在计算加速层面,则需要将波前恢复与非线性均衡算法直接固化至物理层硬件中。通过底层硬件剥离对上层处理器的算力依赖,系统才能在微秒,甚至纳秒级的时钟周期内完成特征提取与模态判决,真正实现极低延迟的实时通信闭环。
高阶模态在非理想探测条件下的特征混叠现象,使得接收端的模态识别面临着分辨率不足的挑战,限制了多维复用潜力的释放。为了进一步提升信道容量,利用径向指数与角向指数的联合复用成为必然趋势,但这显著增加了检测的复杂性。Wang等[63]研究发现,高阶径向涡旋光束具有复杂的多环强度分布,经过传输畸变后,其光斑特征极易与相邻模态发生混淆。传统基于强度特征的分类器在高阶模态面前区分度降低,导致误码率随着复用维度的增加而显著上升,图16(a)[63]展示了一种大气湍流环境中OAM模态的传播和检测系统。实际上,测量系统的精度不仅受限于探测器,还受限于核心器件的微纳加工工艺。Genevet等[64]指出,高深宽比结构中的制造误差会直接降低模态纯度,从而在测量端引入额外的模态串扰。此外,随着技术向连续整数阶与分数阶模态复用发展[57],频谱特征的精细化对测量分辨率提出了极高的要求,若缺乏高精度的测量手段,理论上的多维复用优势在实际应用中将大打折扣,这与正交振幅调制通过增加星座点即可线性提升速率的规律大相径庭。
在非视距或强散射环境中的涡旋波测量面临着数据采集带宽的物理极限,传统基于成像的探测模式难以满足高速通信的吞吐率需求。当涡旋波束穿过云雾、生物组织或多模光纤等散射介质时,原本规则的波前会被打散形成极度复杂的随机散斑场。Wang等[65]指出散射介质会导致信号散斑化,为了从散斑中无损恢复OAM信息,传统方法通常依据奈奎斯特采样定理,利用百万像素级的高分辨率相机进行全场密集采样。这种方式产生的数据流极其庞大,对传输总线带宽和后端处理器的实时吞吐能力构成了巨大压力。最新的研究虽然提出了基于散射介质编码的稀疏采样技术,如图16(b)[65]所示,但在动态变化的信道中,如何以极低的采样率实现鲁棒的单次测量,仍是制约OAM技术在未来6G网络中大规模部署的关键因素。
综上所述,涡旋波测量技术在工程应用中面临的主要瓶颈,在于高维空间信息量与探测系统物理带宽及制造精度之间的不匹配。在复杂散射信道中,传统的高分辨面阵成像与密集采样范式不仅会放大微纳加工误差造成的模态串扰,还会导致接收端传输总线的数据过载。针对上述限制,未来的测量系统需要向特征驱动的物理降维与智能感知方向演进。硬件设计应逐步降低对面阵探测器的依赖,在物理层直接实现空间波前的能量映射与模态筛选;同时,利用轻量化算法在低稀疏采样率下提取关键散斑特征。这种硬件降维与端到端稀疏重构相协同的架构,能够有效缓解系统的数据吞吐压力,可以实现动态信道下鲁棒测量。
本文围绕涡旋波通信技术,从轨道角动量的基础物理属性出发,对其生成方法、系统优势及工程实现中的关键挑战进行了系统综述。研究表明,涡旋波通过开发电磁波的空间相位维度,利用OAM模态间的严格正交性,实现了同频、同时、同极化条件下的多路复用,为缓解未来无线通信的频谱资源枯竭与容量瓶颈提供了有效物理层解决方案。该技术不仅可显著提升频谱效率与信道容量,还凭借螺旋波前与中心相位奇点,在物理层安全通信与高维量子信息处理中展现出抗截获能力强与高密度编码优势。当前,涡旋波的生成与探测技术已取得显著进展,涵盖从均匀圆阵列、螺旋相位板到超表面、反射阵列等多种实现方式,人工智能的引入亦有效提升了复杂环境下的模态识别精度与系统鲁棒性。然而,该技术在从理论到工程应用转化过程中仍面临诸多物理与工程限制,如波束发散、孔径约束导致的能量损失与模态正交性破坏,以及大气湍流、收发端对准误差引起的模间串扰等问题。同时,现有信号处理方法在强湍流非线性畸变下仍存在计算复杂度高与实时性不足的矛盾。
未来涡旋波通信技术的研究应重点聚焦硬件架构创新、智能算法优化及系统集成3个方向。首先,在硬件与器件层面,应发展宽带、动态可重构的涡旋波收发端及数字编码超表面,实现对OAM模态、波束指向及功率分配的实时动态调控,并结合可重构智能表面构建虚拟视距链路,以提升系统覆盖能力与可靠性。其次,在信号处理与算法层面,应构建物理驱动的轻量化人工智能模型,将电磁传播机理嵌入深度学习网络,以降低计算开销并增强复杂信道下的特征提取与波前恢复能力;同步推进标准化信道模型的构建,建立涵盖大气湍流、多径效应、硬件非理想特性、收发端对准误差等核心影响因素的参数化信道模型,形成与现有通信标准化体系兼容的仿真与评估基准,为不同研究成果的横向对标与性能验证提供统一规范。最后,在系统集成层面,应推动涡旋波与大规模MIMO及索引调制等技术的深度融合,充分挖掘空间自由度,实现频谱与能量效率的协同提升。加快多场景原型验证系统的搭建,首先完成实验室环境下的多模态复用通信链路功能验证,逐步拓展至典型工程场景的外场测试,通过原型系统的迭代优化验证技术的工程可行性,暴露并解决实际应用中的核心瓶颈问题,推动理论成果向实用化转化。随着材料科学、微波工程及信息理论的持续发展,涡旋波通信技术有望逐步突破现有物理与工程限制,为未来超高速、高安全性的空天地一体化信息网络提供核心支撑。
  • 国家自然科学基金项目(62271056)
  • 国家自然科学基金项目(62571049)
  • 国家自然科学基金项目(62171186)
  • 国家自然科学基金项目(62201037)
  • 国家市场监督管理总局专项(AKYKF2423)
  • 河北省自然科学基金项目(F2025105029)
  • 毫米波国家重点实验室开放课题(KN20250214)
  • 高等学校学科科研创新引智计划项目(B14010)
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2026年第44卷第9期
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doi: 10.3981/j.issn.1000-7857.2026.02.00019
  • 接收时间:2026-02-08
  • 首发时间:2026-05-27
  • 出版时间:2026-05-13
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  • 收稿日期:2026-02-08
  • 修回日期:2026-04-15
基金
国家自然科学基金项目(62271056)
国家自然科学基金项目(62571049)
国家自然科学基金项目(62171186)
国家自然科学基金项目(62201037)
国家市场监督管理总局专项(AKYKF2423)
河北省自然科学基金项目(F2025105029)
毫米波国家重点实验室开放课题(KN20250214)
高等学校学科科研创新引智计划项目(B14010)
作者信息
    1北京理工大学集成电路与电子学院,北京 100081
    2临近空间环境特性及效应全国重点实验室,北京 100081
    3北京理工大学唐山研究院,唐山 063000
    4毫米波全国重点实验室,南京 210096
    5深圳北理莫斯科大学工程系,深圳 518172
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2种不同金属材料的力学参数

Family
属数
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genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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