OAM vortex communication system device and method of silicon-based photon integrated micro-ring resonator array
Through the dynamic regulation of silicon-based photonic integrated micro-ring resonator array and AI-driven dynamic regulation, the beam divergence, channel time-varying and multi-user interference problems of OAM technology in the Internet of Things scenarios are solved, efficient OAM beam generation and multi-user parallel transmission are achieved, and the spectrum efficiency and stability of the communication system are improved.
Patent Information
- Application Number
- CN202510897520.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-07-01
- Publication Date
- 2025-08-29
- Estimated Expiration
- Not applicable · inactive patent
AI Technical Summary
The existing OAM technology has low beam generation efficiency, difficult channel time-varying compensation, and serious interference from multiple users in the Internet of Things scenario, and cannot adapt to dynamic channels and mobile scenarios, resulting in limited transmission rate and spectrum efficiency.
The silicon-based photonic integrated micro-ring resonator array is adopted to achieve precise phase delay control through thermal and optical tuning, combining lightweight channel compensation architecture and heterogeneous multi-user access mechanism, and using AI-driven dynamic regulation to optimize vortex field parameters to achieve ultra-compact OAM beam generation and multi-user parallel transmission.
The purity of the mode is improved to more than 99%, real-time calibration of phase noise, expansion of the terahertz frequency band, and the vortex field opens up a new dimension of 6G rear space-division multiplexing, improving system performance and suitable for densely connected scenarios.
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Figure CN120567259A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of Internet of Things wireless communication technology, and specifically to an OAM vortex communication system device and method for a silicon-based photonic integrated microring resonator array, which is suitable for dense Internet of Things scenarios such as Industry 4.0, autonomous driving, smart agriculture, and other high-capacity and low-latency scenarios. Background Art
[0002] As a novel electromagnetic information carrier technology based on vortex electromagnetic fields, electromagnetic vortex rings (EVRs) possess the physical property of orthogonal OAM (OAM) of different topological charges, enabling simultaneous transmission of multiple data streams in communications applications. This holds great potential for improving spectrum efficiency and system capacity. In 2007, B. Thide et al. first applied OAM to the lower-frequency radio domain, proposing the use of vortex electromagnetic waves to expand wireless communication capacity. However, the divergence of vortex electromagnetic waves increases with modulus value, reducing system transmission rates. To address this issue, S. Gao et al. proposed using lenses to converge the OAM beam. While this approach reduced inter-signal interference and increased system capacity, it also increased system construction costs. Furthermore, OAM beam generation and control could not be tailored to different application scenarios, and improved accuracy and stability were difficult to achieve. W. Cheng et al. designed a parabolic antenna to converge vortex electromagnetic waves, achieving better spectral efficiency. However, this increased the complexity of the transceiver circuit design. For example, in terms of channel estimation and compensation, the complex time-varying characteristics of the OAM channel require effective channel estimation methods and compensation algorithms to improve system performance. At the same time, the problem of interference between users in multi-user communications also needs to be urgently addressed. Otherwise, it will be difficult to fully utilize the advantages of OAM communication technology.
[0003] Existing technologies still have many flaws: in terms of beamforming, the purity of the traditional spiral phase plate mode is only 78%, and atmospheric turbulence causes the beam offset to be ≥5λ; in terms of channel compensation, the processing delay of the Kalman filter algorithm is as high as 200ms, which cannot adapt to dynamic channels; in terms of multi-user interference, the isolation of traditional MIMO is only 20dB, and the spectrum efficiency is limited to 10bit / s / Hz, which cannot adapt to mobile scenarios such as drone inspections or the bottleneck of bit error rate (BER) ≥10⁻³ caused by multipath effects in typical agricultural IoT scenarios. Summary of the Invention
[0004] To address the above technical problems, the present invention provides a low-power, highly integrated OAM vortex communication system for the Internet of Things (IoT). This system addresses the problems of low beamforming efficiency, difficulty compensating for channel time-varying conditions, and severe multi-user interference. This invention proposes an innovative device and method for these problems. Through the collaborative optimization of silicon-based photonic integration technology, three-dimensional metasurface antenna arrays, and lightweight AI algorithms, this device and method address the beam divergence, sensitivity to channel time-varying conditions, and multi-user interference challenges faced by traditional OAM technologies in IoT scenarios. This device and method achieve IoT scenario adaptation through the following innovative technical solutions: An OAM vortex communication system device of a silicon-based photonic integrated microring resonator array, characterized by comprising: Silicon-based photonic integrated microring resonator arrays for precise phase delay control via thermo-optical tuning to achieve ultra-compact OAM beamforming; A lightweight channel compensation architecture, including a two-branch DNN model, where branch 1 is a CNN for processing delay spread and branch 2 is an LSTM for compensating Doppler shift, combined with NV color center quantum sensing to achieve real-time phase noise calibration; Heterogeneous multi-user access mechanism, based on Walsh-Hadamard coded orthogonal beamforming, supports multi-user parallel transmission. By combining mathematical coding with physical beamforming, it achieves efficient orthogonality and interference suppression in multi-user communications. By integrating AI-driven dynamic control, electromagnetic vortex rings and photonic crystals are integrated to achieve vortex communication in the optical frequency band, and deep neural networks are used to optimize vortex field parameters in real time to cope with complex environments.
[0005] The silicon-based photonic integrated microring resonator array is manufactured on an SOI substrate using a CMOS-compatible process. A piezoelectric deformable mirror is integrated through MEMS technology to form a closed-loop feedback system. Multiple microring resonators and their auxiliary structures are integrated on the same silicon-based chip, including an SOI substrate, a top silicon layer, and a buried oxide layer. The microring resonator consists of a ring waveguide silicon waveguide ring made of silicon nitride or germanium-doped silicon and a coupler. The resonant wavelength is thermo-optically tuned by integrating a heating electrode or a PN junction.
[0006] The lightweight channel compensation architecture includes a lightweight channel estimation algorithm module, an efficient signal processing unit, a dynamic adaptive controller and a protocol layer collaborative design; the lightweight channel estimation algorithm module includes sparse channel perception, differential channel estimation, blind equalization technology and a low-power digital signal processor; the efficient signal processing unit includes an integrated fixed-point operation unit, a hardware accelerator and a memory optimization module; the dynamic adaptive controller includes channel state feedback and adaptive parameter adjustment; the protocol layer collaborative design includes physical layer and MAC layer linkage and signaling compression.
[0007] The heterogeneous multi-user access mechanism includes a user terminal layer, an access network layer, a core control layer, and a protocol and algorithm layer; the user terminal layer includes traditional terminals, low-power terminals, and industrial terminals; the access network layer includes multi-standard base stations and spectrum resources; the core control layer includes a software-defined network controller, network function virtualization, and multi-access edge computing; the protocol and algorithm layer includes multiple access technology, RAT selection algorithm, and QoS management.
[0008] A method for controlling an OAM vortex communication system of a silicon-based photonic integrated microring resonator array, characterized by applying the device described in any one of the above items, comprising the following steps: S1 achieves precise control of phase delay through thermo-optical tuning of a silicon-based photonic integrated microring resonator array, generating ultra-compact OAM beams. S2 uses a dual-branch DNN model with a lightweight channel compensation architecture combined with NV color center quantum sensing to perform real-time phase noise calibration of the channel; S3 uses a heterogeneous multi-user access mechanism based on Walsh-Hadamard coding and orthogonal beamforming to achieve multi-user parallel transmission and interference suppression; S4 integrates AI-driven dynamic control and uses deep neural networks to optimize vortex field parameters in real time to adapt to complex environments.
[0009] In the step of generating an ultra-compact OAM beam, the resonant wavelength of the silicon-based photonic integrated microring resonator array is determined by the formula \(\lambda_{\text{res}} = \frac{n_{\text{eff}} \cdot L}{m}\), where \(n_{\text{eff}}\) is the effective refractive index of the waveguide, L is the ring circumference, and m is an integer.
[0010] The implementation process of the heterogeneous multi-user access mechanism includes dynamic spectrum sensing and resource allocation, multi-domain coordinated access control and differentiated QoS guarantee.
[0011] The dynamic regulation driven by fusion AI is achieved through a closed-loop mechanism consisting of a data acquisition layer, an AI model layer, a decision engine layer, and an execution layer. The data acquisition layer collects real-time data and performs feature extraction and cleaning. The AI model layer uses supervised learning models, reinforcement learning models, and meta-learning models for processing. The decision engine layer makes decisions through a real-time reasoning framework and a policy optimizer. The execution layer executes decisions and provides feedback.
[0012] The beneficial effects of the present invention are: achieving ultra-compact OAM beamforming, with a mode purity of more than 99% in the 28 GHz frequency band, which is 11% higher than that of traditional spiral phase plates, realizing real-time calibration of phase noise, and achieving the expansion of the terahertz frequency band to 0.1-10 THz. The vortex field can open up a new dimension of post-6G space division multiplexing, solving the problems of beam divergence, channel time-varying sensitivity and multi-user interference faced by traditional OAM technology in IoT scenarios, and improving by more than 3 times compared with traditional MIMO technology. It is particularly suitable for densely connected scenarios such as smart agricultural sensor networks and industrial IoT edge nodes. BRIEF DESCRIPTION OF THE DRAWINGS
[0013] Figure 1: Silicon-based photonic integrated microring resonator array 100, microring resonator 10, SOI substrate 11, top silicon layer 12, buried oxide layer 13, lightweight channel compensation architecture 200, lightweight channel estimation algorithm module 20, sparse channel perception 20-a, differential channel estimation 20-b, blind equalization technology 20-c, low-power digital signal processor 20-d, efficient signal processing unit 21, integrated fixed-point operation unit 21-a, hardware accelerator 21-b, memory optimization module 21-c, dynamic adaptive controller 22, channel state feedback 22-a, adaptive parameter adjustment 22-b, protocol layer collaborative design 23, physical layer and MAC layer linkage 23-a, signaling compression 23-b, heterogeneous multi-user access mechanism 300, user terminal layer 30, access network layer 31, core control layer 32, protocol and algorithm layer 33, integrated AI-driven dynamic regulation 400.
[0014] Figure 1 : Schematic diagram of the overall architecture of the system device (showing the synergistic relationship between the photonic integrated microring resonator array, lightweight channel compensation architecture, heterogeneous multi-user access mechanism, and AI-driven dynamic control).
[0015] Figure 2 :Schematic diagram of the photonic integrated microring resonator array structure and the method of determining the resonant wavelength.
[0016] Figure 3 : Schematic diagram of the collaborative relationship of lightweight channel compensation architecture.
[0017] Figure 4 :Heterogeneous multi-user access mechanism and process steps diagram.
[0018] Figure 5 : Schematic diagram of the process steps of AI-driven dynamic control method. DETAILED DESCRIPTION
[0019] The technology of the present invention is further described below with reference to the accompanying drawings and embodiments.
[0020] like Figure 1A schematic diagram of the overall architecture of an OAM vortex communication system with a silicon-based photonic integrated microring resonator array is shown, demonstrating the synergistic relationship between the photonic integrated microring resonator array, lightweight channel compensation architecture, heterogeneous multi-user access mechanism, and AI-driven dynamic control. The system device of the present invention includes a silicon-based photonic integrated microring resonator array 100, a lightweight channel compensation architecture 200, a heterogeneous multi-user access mechanism 300 and a dynamic control 400 driven by fusion AI.
[0021] The silicon-based photonic integrated microring resonator array 100 achieves precise control of phase delay through thermo-optical tuning to generate ultra-compact OAM beams; the lightweight channel compensation architecture 200 uses a dual-branch DNN model combined with NV color center quantum sensing to achieve real-time calibration of phase noise; the heterogeneous multi-user access mechanism 300 supports multi-user parallel transmission based on the orthogonal beamforming scheme based on Walsh-Hadamard coding; the integrated AI-driven dynamic control 400 integrates electromagnetic vortex rings with photonic crystals to realize vortex communication in the optical frequency band, and optimizes vortex field parameters in real time through deep neural networks to cope with complex environments.
[0022] The microring resonator 10 is composed of a ring waveguide and a straight waveguide. Its core principle is the resonance condition. When the phase change of light propagating in the ring waveguide is an integer multiple of \(2\pi\), resonance occurs, causing light of a specific wavelength (resonance wavelength) to circulate and enhance within the ring, and exchange energy with the straight waveguide through the coupler.
[0023] As shown in Figure 2, the silicon-based photonic integrated microring resonator array 100 utilizes high-density optical component integration based on silicon-based photonics technology. The microring resonator array is fabricated on an SOI substrate using a CMOS-compatible process, and piezoelectric deformable mirrors are integrated using MEMS technology to form a closed-loop feedback system. It consists of multiple microring resonators 10 and their supporting structures integrated on a single silicon-based chip, including an SOI substrate 11, a top silicon layer 12 (approximately 220 nm thick for waveguiding), and a buried oxide layer 13. The microring resonator 10 consists of a silicon waveguide ring (typically with a radius between 1 and 100 μm, which determines the resonant wavelength and mode volume) made of silicon nitride or germanium-doped silicon, and a coupler. The resonance depth is controlled by adjusting the coupling spacing, and integrated heating electrodes or PN junctions are used for thermo-optical tuning of the resonant wavelength.
[0024] The core principle is that resonance occurs when the phase change of light propagating in a ring waveguide is an integer multiple of 2π. The resonant wavelength is determined by the formula \(\lambda_{\text{res}} = \frac{n_{\text{eff}} \cdot L}{m}\).
[0025] As shown in Figure 3, the lightweight channel compensation architecture 200 is a low-power, energy-efficient channel correction technology designed for resource-constrained scenarios. It consists of a lightweight channel estimation algorithm module 20, an efficient signal processing unit 21, a dynamic adaptive controller 22, and a protocol layer collaborative design 23. The lightweight channel estimation algorithm module 20 includes sparse channel sensing 20-a, differential channel estimation 20-b, blind equalization technology 20-c, and a low-power digital signal processor 20-d. The efficient signal processing unit 21 includes an integrated fixed-point arithmetic unit 21-a, a hardware accelerator 21-b, and a memory optimization module 21-c. The dynamic adaptive controller 22 includes channel state feedback 22-a and adaptive parameter adjustment 22-b. The protocol layer collaborative design 23 includes physical and MAC layer linkage 23-a and signaling compression 23-b. This architecture achieves efficient channel correction in resource-constrained scenarios through algorithmic innovation, hardware optimization, and system collaboration.
[0026] As shown in Figure 4, the heterogeneous multi-user access mechanism 300 supports access from various types of user devices and different communication protocols. It includes a user terminal layer 30, an access network layer 31, a core control layer 32, and a protocol and algorithm layer 33. The user terminal layer 30 includes traditional terminals, low-power terminals, and industrial terminals; the access network layer 31 includes multi-standard base stations and spectrum resources; the core control layer 32 includes software-defined network controllers, network function virtualization, and multi-access edge computing; and the protocol and algorithm layer 33 includes multiple access technologies, RAT selection algorithms, and QoS management. It achieves efficient multi-user access through processes such as dynamic spectrum sensing and resource allocation, multi-domain coordinated access control, and differentiated QoS assurance.
[0027] As shown in Figure 5, the AI-driven dynamic control 400 achieves adaptive optimization through a closed-loop "perception-decision-execution-feedback" mechanism. It comprises a data acquisition layer S1, an AI model layer S2, a decision engine layer S3, and an execution layer S4. The data acquisition layer S1 collects and processes real-time data; the AI model layer S2 processes data using supervised learning, reinforcement learning, and meta-learning models; the decision engine layer S3 makes decisions using a real-time inference framework and policy optimizer; and the execution layer S4 executes decisions and provides feedback, enabling adaptation to communication needs in complex environments.
[0028] This invention integrates silicon-based photonics with MEMS technology to achieve cross-scale integrated innovation in miniaturized OAM beamforming systems (volume <10 cm³). It also achieves cognitive radio fusion with integrated channel state sensing and compensation through a DNN-NV color center hybrid architecture. It also proposes a heterogeneous coding design for a Walsh-Hadamard-OAM dual orthogonal coding scheme. Any simple improvements, modifications, or equivalent conversions based on the essence of this invention fall within the scope of protection of the claims.
Claims
1. An OAM vortex communication system device of a silicon-based photonic integrated microring resonator array, characterized in that: include: Silicon-based photonic integrated microring resonator array (100) for achieving precise phase delay control via thermo-optical tuning to realize ultra-compact OAM beamforming; A lightweight channel compensation architecture (200) includes a dual-branch DNN model, where branch 1 is a CNN for processing delay spread and branch 2 is an LSTM for compensating Doppler shift, combined with NV color center quantum sensing to achieve real-time phase noise calibration; Heterogeneous multi-user access mechanism (300), based on Walsh-Hadamard coded orthogonal beamforming, supports multi-user parallel transmission, and achieves efficient orthogonality and interference suppression in multi-user communication by combining mathematical coding with physical beamforming; By integrating AI-driven dynamic control (400), electromagnetic vortex rings are integrated with photonic crystals to achieve vortex communication in the optical frequency band, and deep neural networks are used to optimize vortex field parameters in real time to cope with complex environments.
2. The OAM vortex communication system device of a silicon-based photonic integrated microring resonator array according to claim 1, characterized in that: The silicon-based photonic integrated microring resonator array (100) adopts a CMOS compatible process to manufacture a microring resonator (10) array on an SOI substrate (11), integrates a piezoelectric deformable mirror through MEMS technology to form a closed-loop feedback system, and is integrated with multiple microring resonators (10) and their auxiliary structures on the same silicon-based chip, including an SOI substrate (11), a top silicon layer (12) and a buried oxide layer (13). The microring resonator (10) is composed of a ring waveguide silicon waveguide ring made of silicon nitride or germanium-doped silicon and a coupler, and is used for thermo-optical tuning of the resonant wavelength through an integrated heating electrode or a PN junction.
3. The OAM vortex communication system device of a silicon-based photonic integrated microring resonator array according to claim 1, characterized in that: The lightweight channel compensation architecture (200) includes a lightweight channel estimation algorithm module (20), an efficient signal processing unit (21), a dynamic adaptive controller (22) and a protocol layer collaborative design (23); the lightweight channel estimation algorithm module (20) includes sparse channel sensing (20-a), differential channel estimation (20-b), blind equalization technology (20-c) and a low-power digital signal processor (20-d); the efficient signal processing unit (21) includes an integrated fixed-point operation unit (21-a), a hardware accelerator (21-b) and a memory optimization module (21-c); the dynamic adaptive controller (22) includes channel state feedback (22-a) and adaptive parameter adjustment (22-b); the protocol layer collaborative design (23) includes physical layer and MAC layer linkage (23-a) and signaling compression (23-b).
4. The OAM vortex communication system device of a silicon-based photonic integrated microring resonator array according to claim 1, characterized in that: The heterogeneous multi-user access mechanism (300) includes: a user terminal layer (30), an access network layer (31), a core control layer (32) and a protocol and algorithm layer (33); the user terminal layer (30) includes: traditional terminals, low-power terminals and industrial terminals; the access network layer (31) includes: multi-standard base stations and spectrum resources; the core control layer (32) includes: software-defined network controller, network function virtualization and multi-access edge computing; the protocol and algorithm layer (33) includes: multiple access technology, RAT selection algorithm and QoS management.
5. A method for controlling an OAM vortex communication system of a silicon-based photonic integrated microring resonator array, characterized in that: The method of using the device according to any one of claims 1 to 4 comprises the following steps: S1 achieves precise control of phase delay through thermo-optical tuning of a silicon-based photonic integrated microring resonator array, generating ultra-compact OAM beams. S2 uses a dual-branch DNN model with a lightweight channel compensation architecture combined with NV color center quantum sensing to perform real-time phase noise calibration of the channel; S3 uses a heterogeneous multi-user access mechanism based on Walsh-Hadamard coding and orthogonal beamforming to achieve multi-user parallel transmission and interference suppression; S4 integrates AI-driven dynamic control and uses deep neural networks to optimize vortex field parameters in real time to adapt to complex environments.
6. The method according to claim 5, characterized in that In the step of generating an ultra-compact OAM beam, the resonant wavelength of the silicon-based photonic integrated microring resonator array is determined by the formula \(\lambda_{\text{res}} = \frac{n_{\text{eff}} \cdot L}{m}\), where \(n_{\text{eff}}\) is the effective refractive index of the waveguide, L is the ring circumference, and m is an integer.
7. The control method according to claim 5, characterized in that: The implementation process of the heterogeneous multi-user access mechanism includes dynamic spectrum sensing and resource allocation, multi-domain coordinated access control and differentiated QoS guarantee.
8. The control method according to claim 5, characterized in that: The dynamic regulation driven by fusion AI is achieved through a closed-loop mechanism consisting of a data acquisition layer, an AI model layer, a decision engine layer, and an execution layer. The data acquisition layer collects real-time data and performs feature extraction and cleaning. The AI model layer uses supervised learning models, reinforcement learning models, and meta-learning models for processing. The decision engine layer makes decisions through a real-time reasoning framework and a policy optimizer. The execution layer executes decisions and provides feedback.