3031 results about "Physical layer" patented technology

The invention discloses an intelligent heat supply regulation and control system based on digital twinning and deep reinforcement learning. The system comprises a physical layer, a control layer and a control layer, wherein the physical layer is a physical heat supply system composed of heat source equipment, a transmission and distribution pipe network and a user terminal; according to the digital twinborn layer, a virtual heat supply system mapped with the physical layer in real time is constructed, the virtual heat supply system comprises a multi-physics field coupling model based on the thermodynamics and fluid mechanics principle, operation data of the physical layer are collected through a distributed sensor network, and the state vector of the virtual system is dynamically updated; and the intelligent decision-making layer is integrated with a DRL intelligent agent, the state space of the DRL intelligent agent is defined as a virtual system state vector output by the digital twin layer, the action space of the DRL intelligent agent is a regulation and control instruction combination of heat source power and pump valve opening, and a reward function fuses an energy consumption penalty term, a room temperature comfort reward term and a pipe network stability constraint term. According to the method, global optimization, high-precision continuous regulation and control and collaborative balance are realized through deep collaboration of digital twinning and deep reinforcement learning.

The invention relates to the technical field of abnormal state prediction, provides a multi-dimensional time sequence equipment abnormal state prediction method and system, and solves the problems of high false alarm rate and risk prediction inaccuracy in the prior art. The method comprises the following steps: collecting a multi-node operation state data set and communication transmission layer time sequence offset information of an equipment distributed system; jitter and delay association processing is carried out on the data, and a communication stability feature set is generated by quantizing space-time correlation of a jitter extreme value and delay fluctuation; obtaining physical layer deformation and temperature drift data of the communication cable, analyzing and generating a physical layer disturbance feature sequence based on optical signal feature offset, and converting the physical layer disturbance feature sequence into channel abnormal strength features; and cross-level feature coupling is carried out on the communication stability feature and the channel abnormal strength feature, and a communication node failure or data transmission abnormal risk is predicted based on a coupling result. According to the invention, millisecond-level linkage prediction of equipment-level physical disturbance and system-level communication risks is realized, the fault false alarm rate is reduced, and the cascade failure risk is blocked.

The invention overcomes the constraints imposed by conventional wireless communication standards by introducing a physical-layer optimized architecture that decouples transmission control from any single protocol. Rather than being confined by the predefined behaviors of LTE, 5G NR, Wi-Fi, or NB-IoT, the system implements a unified control system that dynamically manages radio parameters—such as modulation, coding, and power—based on real-time link quality and network context. This cross-standard, multimode capability effectively supersedes traditional standard-driven implementations, enabling adaptive, low-latency, and spectrum-efficient communication in complex heterogeneous environments.The system dynamically controls radio access network (RAN) and physical layer parameters, including carrier aggregation, dynamic spectrum allocation, modulation and coding scheme (MCS) adaptation, beamforming configuration, channel coding, transmit power control, and frequency selection. The system architecture includes multi-mode base stations, relay nodes, and edge access points that support inter-RAT handover, fast radio link recovery, and seamless mobility across diverse wireless technologies.

The invention provides a data optimization processing method and system for edge calculation in architectural design. According to the method, geometric deviation and attribute change characteristics between building design models are obtained, and a version conflict identification graph for marking high-conflict areas is generated through topological relation comparison; deploying an incremental synchronous controller at an edge computing node of a physical layer, dynamically intercepting a high-conflict area association difference data fragment and compressing the high-conflict area association difference data fragment into an incremental data packet; analyzing a dependency topological relation between the models to predict a conflict propagation path; converting the path into a combined operation instruction conforming to a design rule through a collaborative modeling engine; and executing the instruction to integrate the difference, and outputting a conflict-free multi-building design integrated model after the models are fused. According to the method, second-level dynamic resolution and automatic fusion of building model conflicts are realized, the design iteration efficiency is improved, and the construction rework risk is eliminated.

The invention relates to a server cluster monitoring system based on multi-node collaboration and an implementation method thereof, a dynamic topology network module is configured to reconstruct a connection topology among monitoring nodes in real time according to node performance and link quality, support mixed configuration of a star type, a ring type and a net structure, and realize multi-node collaboration. Multi-dimensional data capture from a physical layer to an application layer is realized through a cross-level index acquisition module based on an integrated hardware sensor interface and a virtualization layer probe, and each node is enabled to perform collaborative reasoning through parameter encryption sharing through a decision model based on federated learning. A monitoring task fragmentation strategy is dynamically adjusted through an adaptive elastic fragmentation unit according to network delay and load fluctuation, and an abnormal event association rule base is updated in real time through an incremental knowledge graph construction unit. High availability and elastic expansion are realized through a multi-node collaborative architecture, the monitoring efficiency is improved in combination with dynamic load balancing and hybrid detection, and an intelligent multi-level response mechanism is constructed to guarantee the service continuity.

The invention discloses an adaptive modulation anti-multipath unmanned aerial vehicle swarm communication method and system based on MIMO-OFDM, and relates to the technical field of wireless communication, and the method comprises the steps: receiving a down-conversion baseband; synchronization and compensation are carried out; removing a cyclic prefix and carrying out fast Fourier transform; estimating a channel and noise on the training and pilot frequency, and correcting a common phase; performing frequency domain equalization and soft decision, forward error correction and cyclic redundancy check according to the estimation to obtain a control parameter, decoding a payload according to the control parameter, and performing statistics to form a link quality indication; modulating coding, bandwidth and spatial mode, configuring mapping, power and weight, and packaging physical layer protocol data; carrier sensing conflict avoiding sending, confirmation and retry are adopted to generate media access statistics; and the routing selects the next-hop multi-hop forwarding according to the transmission quality, and performs end-to-end statistics and recharge. Through cooperation of hierarchical synchronization and phase correction with cyclic prefix and FFT, crosstalk is suppressed, channel noise scale optimization soft decision is robust, data decoupling is controlled, and end-to-end availability is improved through multi-hop self-healing recharge.

The invention provides a property system virtual-real mapping inspection method, device and equipment based on digital twinning and a medium, and belongs to the technical field of property inspection. Real-time mapping of an equipment entity and a virtual model is achieved through layered design of a physical layer, a data layer, a twinning layer and an application layer; collecting static / dynamic data and reducing noise, and establishing a global coordinate system; constructing a 1: 1 parameterized model and binding equipment attributes; the state analysis model is used for evaluating the equipment health degree, and virtual-real identification and work order visualization are triggered when abnormity occurs; the inspection path is dynamically optimized, and the processing efficiency is improved in combination with AR assistance and dual-stage verification; and finally, updating the model weight and adjusting the inspection strategy through data-driven acceptance feedback. Real-time synchronization and intelligent decision making of the equipment state are realized, the inspection efficiency is improved, the fault omission ratio is reduced, the resource allocation is optimized, and the operation and maintenance transparency and reliability are enhanced.

The invention relates to the technical field of network security, in particular to a cloud data secure transmission system and method based on a quantum encryption technology. Comprising a quantum key generation and management unit used for generating a physical layer security key, realizing key true random generation through a quantum state unclonable principle, and optimizing key negotiation efficiency by adopting an improved adaptive basis vector matching algorithm; a data transmission encryption unit; a physical layer safety monitoring unit; and a channel fusion switching unit. According to the method, the physical layer security key is generated based on the quantum state unclonable principle, the dependency limitation of a traditional encryption algorithm on mathematics is broken through, and the cracking risk of quantum computing on bottom layer encryption logic can be reduced; according to the invention, photon polarization state parameters are collected in real time through the physical layer security monitoring unit, the eavesdropping behavior is detected based on the preset error rate threshold, real-time perception of the eavesdropping behavior in a transmission link is realized, and the defect that the security state of the physical layer cannot be perceived in real time in a traditional scheme is overcome.

The invention provides a cross-protocol identification data intelligent analysis middleware method and system. The method comprises the following steps: taking multiple industrial communication protocol identifiers in advance to form a metadata set, and constructing a protocol feature element model library containing a non-standard protocol feature template; a programmable logic device is introduced, physical layer signal waveform characteristics are matched, and corresponding communication protocol stacks are dynamically switched at a hardware level according to a matching result; receiving a communication data stream through an electric domain processing unit of the programmable logic device, and generating a protocol analysis logic sequence in combination with a state transition rule of the meta-model library and a mode matching rule of the protocol stack; performing combined operation on the structured feature template and the analysis logic sequence to generate an executable cross-protocol data analysis rule; and when unknown protocol characteristics are detected, triggering dynamic reconstruction of the template, so that the analysis rule is adapted to a newly added protocol. According to the technical scheme provided by the invention, the protocol compatibility development cost in an industrial multi-protocol scene is remarkably reduced.

The invention relates to the technical field of BMS and the like, and provides a battery management system based on adaptive digital twinning, a physical layer of the battery management system comprises a battery pack, a sensor network and an edge computing node, and is responsible for data acquisition and preprocessing; the digital twin layer comprises a self-adaptive multi-scale model and a real-time data engine, battery behaviors are dynamically simulated by coupling electrochemical, thermal and aging models, a future state trajectory prediction result is output, and the real-time data engine fuses sensor data, historical data and simulation data to drive model updating; the intelligent decision-making layer comprises a reinforcement learning controller and a fault prediction module which are deployed in a local server, the reinforcement learning controller dynamically optimizes a charging and discharging strategy according to a prediction result of the digital twinborn layer and issues and executes the charging and discharging strategy, and the fault prediction module analyzes multi-source time sequence data based on an LSTM network so as to early warn thermal runaway and short circuit risks in advance. According to the invention, long-term accurate mapping and adaptive adjustment between the battery physical entity and the digital model can be realized.

The invention discloses a digital twin autonomous optimization system based on building structure quality monitoring. According to the system, structure state data, environmental influence data, material performance data and historical record data are comprehensively collected through a multi-source data collection module; feature data such as a structure degradation rate and a material aging coefficient are extracted through an edge calculation preprocessing module; a digital twinborn body is constructed through a multi-layer fusion module, geometric layer fusion achieves crack grading labeling, physical layer fusion corrects parameters such as material elasticity modulus, and behavior layer fusion updates the structural damping ratio to reproduce dynamic behaviors. Outputting a structure health index, residual life prediction and maintenance suggestion through an autonomous optimization decision module; and in combination with a dynamic iteration updating module, the system is ensured to continuously adapt to the structure change through validity evaluation and parameter adjustment. The accuracy of building structure quality evaluation and the scientificity of maintenance decision making are improved, and the method is suitable for full-life-cycle management of various buildings.

The invention discloses a multi-modal attack identification method fusing BMama and difference to guide trans-attention, which comprises the following steps: simulating a false data injection attack, a denial of service attack, an address resolution protocol spoofing attack and a domain name system spoofing attack, collecting physical layer sensor data and network layer flow data, and preprocessing multi-modal data; bMama is constructed to perform dynamic time modeling on multi-modal data, a graph neural network is combined to adversariate a variational auto-encoder, features of a power grid system topology and a communication topology structure are fused, and robustness of potential representation is enhanced through adversarial training; the method comprises the following steps of: guiding feature complementary fusion by using modal difference through a difference guide iteration cross-attention fusion mechanism, improving the capability of distinguishing complex attacks, finally carrying out attack detection and classification on fused modals, and executing end-to-end optimization according to a weighted combination of loss of each part. The method can effectively detect and classify the multi-modal attack in the smart power grid, and enhances the safety and reliability of a complex system.

The invention belongs to the technical field of network test equipment, and discloses network response test equipment and a test method thereof, and is characterized in that the network response test equipment comprises the following modules: a distributed multi-mode dynamic sensing probe used for capturing service flow characteristics and microsecond-level performance indexes of a network link in real time; the extensible data middle table is in data connection with the probe and is used for establishing a unified spatio-temporal index for cross-level performance data from a physical layer to an application layer; and the causal atlas analysis engine based on artificial intelligence is used for positioning a network fault root cause according to the cross-level performance data. According to the invention, an evaluation standard is automatically calibrated according to historical business load characteristics through an extensible data-in-station dynamic baseline threshold mechanism, so that a test environment completely fits complex scenes such as video burst frame transmission, database synchronization ACK, high-frequency transaction chain and the like, the simulation distortion of a traditional tool to business traffic burst and multi-protocol mixed characteristics is eliminated, and the test efficiency is improved. And the test result is ensured to accurately map the long-term stability requirement.

The invention discloses a PCIe cross-version link capability mapping and transaction data reconstruction method, which comprises the following steps: link negotiation and physical layer opposite end simulation: a cross-generation PCIe bridging device simulates high-version equipment behavior training and establishes a first link between the cross-generation PCIe bridging device and a host, the cross-generation PCIe bridging device simulates behavior training of low-version equipment and establishes a second link between the cross-generation PCIe bridging device and the low-version equipment; data processing and transmission: the cross-generation PCIe bridging device processes data received from the host to adapt to and transmit the data to the low-version device, the cross-generation PCIe bridging device processes data received from the low-version device to adapt to and transmit the data to the host, the high version is a PCIe Gen6 protocol, and the low version is a PCIe Gen6 protocol. The low version is a PCIe (Peripheral Component Interconnect Express) Gen5 protocol or a PCIe Gen4 protocol.

The invention provides an FPGA program loading and updating method and system, and relates to the technical field of FPGA configuration management. The FPGA program loading and updating method comprises the following steps: S1, based on an RS422 physical layer protocol, adopting a self-adaptive block verification algorithm, acquiring a signal-to-noise ratio parameter in real time through a channel quality monitoring module, dynamically adjusting the size of a data packet, and implementing a double-buffer alternate receiving mechanism; and verifying each data block by using cyclic redundancy check and serial number continuity detection, discarding abnormal data packets with bit error rates exceeding the limit, and generating a data block set passing verification. Through combination of an adaptive block check algorithm and channel quality dynamic monitoring, real-time optimization and adjustment of the size of a data packet in a transmission process are realized, transmission requirements in different channel environments are effectively adapted, the data retransmission probability is reduced, and through cooperative application of a double-buffer alternate receiving mechanism, cyclic redundancy check and a serial number tracking technology, the transmission efficiency is improved. And continuity and integrity of data receiving are ensured.

The invention relates to the technical field of wireless communication, and discloses a communication equipment command and dispatch system based on artificial intelligence, the system maps the state of communication equipment into a standardized carrier phase disturbance mode, and after the disturbance mode is adaptively adjusted in combination with channel noise perception and conflict arbitration logic, the communication equipment is commanded and dispatched. Controlling the radio frequency front end to carry out injection; the adjacent communication equipment directly detects the disturbance mode to trigger the cooperative scheduling action by monitoring the physical error signal of the carrier synchronization loop of the adjacent communication equipment, and the implicit cooperative mode based on the physical layer beacon is constructed, so that the complex high-level signaling interaction required by the traditional scheduling is avoided, and the scheduling efficiency is improved. According to the method, the millisecond level, determined by a software protocol, of the collaborative response time between the devices is substituted into the microsecond level determined by the hardware physical layer response entscheid, the system can still maintain reliable transmission of scheduling instructions when facing high-density concurrent conflicts and strong channel noise, and a technical implementation path is provided for ultra-low-delay and high-reliability communication.

The invention relates to the technical field of backhaul monitoring, in particular to a backhaul link monitoring method and system applied to a 5G base station, and the method comprises the steps: collecting physical signal statistical data, backhaul service data and network topology data of a backhaul link in real time; according to physical signal statistical data, a physical layer entropy value is calculated through a Shannon entropy formula, and recessive degradation characteristics of a physical layer are quantified; a pulse neural network space-time coding mechanism is used to generate business layer anomaly prediction parameters, and cross-layer anomaly prediction is realized; according to service types and priorities, constructing a time-varying service awareness reference model by adopting a chaos kinetic equation to serve as a dynamic judgment reference; when the return state is abnormal, combining the physical layer entropy and the network topology data to construct a feedback correction loop, and generating a self-adaptive protection strategy; according to the method, advanced prediction and accurate positioning of recessive degradation of the backhaul link are realized, and the self-healing capability and the service quality guarantee level of the backhaul link in a multi-service scene are improved.

The invention relates to the technical field of computer hardware and network communication, in particular to a high-speed I / O (input / output) virtualization server based on an FPGA (field programmable gate array) and a remote forwarding method.The high-speed I / O virtualization server comprises an FPGA chip, a network processing unit, an I / O protocol processing unit, a protocol conversion and scheduling unit, a time sequence and transaction management unit and a data buffering and flow control unit are integrated in the FPGA chip; the optical fiber Ethernet interface module comprises a physical layer interface and an MAC layer processing and network configuration interface; the local I / O interface module comprises a USB interface circuit, a serial port interface circuit, a PCIe interface circuit and an interface expansion connector; the power supply and monitoring module comprises a multi-path power supply management system, a state monitoring and diagnosis system and an LED indication system; according to the self-adaptive Baud rate detection circuit, the Baud rate can be accurately locked under the condition that data with less than two characters is received, the number of data bits, the type of a check bit and the length of a stop bit are automatically identified, and compared with a traditional microcontroller scheme, the self-adaptive Baud rate detection circuit has higher precision and higher detection speed.

The invention belongs to the technical field of base station equipment management, and discloses a base station equipment management method and system based on big data. The method comprises the following steps: firstly, collecting security situation data of a physical layer, a network layer and an application layer, extracting time sequence behavior characteristics, performing cross-layer correlation analysis, and constructing an equipment security credibility dynamic evaluation model; then, identifying vulnerability indexes of control nodes according to the trust attenuation curve, and constructing a cascade risk conduction model in combination with a topological connection relationship; dynamically dividing a security isolation domain based on the model and generating protection parameters and control rules; further, a differentiated security policy is configured, and a cross-domain collaborative response channel is established; and finally, dynamically adjusting the isolation domain boundary and the security policy by monitoring the security event frequency and the interception success rate in real time. According to the invention, the conversion from passive defense to active prediction is realized, and the safety protection capability and operation stability of the base station equipment are improved.

The invention discloses a self-adaptive equipment dormancy method based on a Wi-Fi signal state, and the method comprises the following steps: 1, based on the continuous monitoring of a physical layer index of associated equipment, sending a suggested wake-up instruction to the corresponding associated equipment when it is predicted that the signal quality is rapidly reduced but does not fall off a switching threshold; step 2, according to a received suggested wake-up instruction or a signal degradation trend detected by the corresponding associated device, specifically, switching from a deep sleep state to a standby wake-up state, shortening a sleep period and pre-loading authentication information; 3, the wireless access point dynamically adjusts the sending opportunity of the suggested wake-up instruction according to the service delay requirement of the associated equipment; 4, the associated device dynamically elects a main link and a slave link based on a multi-attribute decision algorithm, and the main link is responsible for receiving a wireless access point instruction and uniformly scheduling dormancy and awakening of the slave link; and 5, generating a prediction result of future data traffic, and controlling the on-demand wake-up time of the slave link by the main link.

The invention belongs to the technical field of seismic equipment monitoring, and provides a seismic network communication fault positioning method based on multi-dimensional protocol diagnosis, which comprises physical layer IOT analysis, network layer protocol analysis, transport layer protocol analysis, application layer protocol analysis, a protection mechanism adaptive adjustment algorithm and a cross-layer collaborative analysis state mechanism. According to the method, multi-dimensional protocol fault analysis is realized, and the analysis accuracy is higher than that of a single-dimensional mode through analysis of application, transmission, network and physical four-layer protocols. Analysis is carried out through the sequence from the physical layer to the application layer, positioning can be completed after the problem is positioned on the upper layer, and high analysis efficiency is achieved. According to the method, the analysis process is completed mainly in a network detection mode, only physical layer analysis needs IOT hardware equipment to participate, the analysis can be achieved in a pure soft mode, and the method has the good cost advantage.

The invention discloses a power monitoring system mimicry defense architecture based on dynamic heterogeneous redundancy, which relates to the field of smart grid network security protection and comprises a physical layer, a twinborn layer and a simulation layer. All the layers communicate through encryption channels, a collaborative architecture of a physical layer, a twinborn layer, a simulation layer and an application layer is constructed, accurate mapping of a virtual environment and a physical power monitoring system is achieved by means of the digital twinborn technology, and a virtual carrier fitting the reality is provided for anomaly detection and attack simulation. The adaptability of the defense architecture to the power business logic is improved through analysis and simulation support on the power dedicated protocol; each layer ensures that the normal operation of the power monitoring system is not interfered through encryption communication and reasonable resource control; meanwhile, the digital twinborn body is used for replacing the traditional physical test environment, so that the construction, operation and maintenance cost of a defense system is reduced, the management efficiency is improved, and an adaptive service, efficient and reliable basic framework is laid for the safety protection of the power monitoring system.

The invention relates to the technical field of data processing, and provides a communication bus anomaly detection method and device, electronic equipment and a readable storage medium. The method comprises the steps of collecting multi-dimensional communication parameters of at least one communication bus in a vehicle, wherein the multi-dimensional communication parameters comprise protocol layer parameters and physical layer electrical parameters; the multi-dimensional communication parameters are input into a health degree scoring model, the health degree score of the communication bus is obtained, and the health degree scoring model is obtained through training according to historical communication parameter data; determining a state level of the communication bus according to a comparison result of the health degree score and a preset threshold value; when the state level is abnormal, performing matching with a predefined abnormal mode feature library based on the multi-dimensional communication parameters to obtain an initial abnormal type; and performing consistency verification according to the initial exception type and the state verification data from different data sources to obtain a target exception type of the communication bus.

The invention discloses an unmanned aerial vehicle communication data feature extraction method and an unknown type intrusion detection method. Physical layer information and network layer information of an unmanned aerial vehicle are acquired; wherein the physical layer information comprises the position, attitude, height and command type of the unmanned aerial vehicle, and the network layer information comprises an IP address, a port number, a protocol type and packet metadata; constructing an unmanned aerial vehicle state feature vector according to the physical layer information and the network layer information of the unmanned aerial vehicle; based on the trained CNN branch network, extracting communication data features used for intrusion detection in the unmanned aerial vehicle state feature vectors; a double-branch network structure of the convolutional neural network and the time sequence convolutional network is provided, a loss function is improved, an information entropy regularization item is introduced, efficient detection and distinguishing of unknown attack samples are achieved, the network structure has the advantages of being high in calculation efficiency and light in weight, and the method is suitable for large-scale popularization and application. The method is suitable for being deployed in resource-limited edge computing scenes such as unmanned aerial vehicles.

The invention belongs to the field of star flash mouse communication, and discloses a star flash mouse low-power-consumption communication system and method based on Polar code and SLE collaborative optimization, the system adopts a layered architecture design, collaborative optimization of energy efficiency and performance is realized through deep coupling of a physical layer and a link layer, and the performance of the system is improved. The core of the system is composed of three functional units including a Polar code coding module, an SLE control engine and a cross-layer optimization interface, and a complete closed-loop control system is formed. According to the invention, through deep cooperation of the Polar code and the SLE mechanism, the overall power consumption is reduced by 42.7% compared with the traditional scheme; according to the Polar code dynamic construction method based on track prediction, an ultra-low bit error rate of 10 <-5 > magnitude can still be kept in a 2.4 GHz complex interference environment, and in combination with signal-to-noise ratio self-adaptive coding parameter adjustment, it is ensured that transmission delay within 0.5 ms is always kept from a low-speed office scene to a high-speed electronic sports scene; in the aspect of engineering implementation, the method has the capability of quickly adapting to hardware platforms of different manufacturers, and a complete solution with high performance and low cost is provided for large-scale commercial use of the satellite flash technology in the consumer electronics field.

A method performed by an access point (AP) to receive uplink trigger-based physical layer protocol data units (PPDUs) from stations (STAs) in accordance with a distributed tone resource unit (dRU) tone plan for a distribution bandwidth. The method includes assigning dRUs to the STAs in the distribution bandwidth, wherein the dRU tone plan for the distribution bandwidth specifies a set of non-contiguous data tones for each of the dRUs, wherein the dRU tone plan for the distribution bandwidth further specifies pilot tones that are located at the same subcarrier indices as pilot tones specified by a regular non-distributed tone resource unit (rRU) tone plan for the distribution bandwidth. The method further includes soliciting the uplink trigger-based PPDUs from the STAs in accordance with the assignment and receiving the uplink trigger-based PPDUs from the STAs in the dRUs assigned to the STAs in accordance with the dRU tone plan for the distribution bandwidth.

The invention discloses a secure data transmission method for a wireless communication system, which relates to the technical field of secure data transmission and comprises three steps of key generation and synchronization, physical layer subcarrier encryption and key enhancement and authentication. The method comprises the following steps: firstly, extracting multi-dimensional features through channel detection to generate a dynamic initial key, and setting a trigger condition to realize key synchronization; then, a permutation matrix is generated by using a secret key to perform scrambling encryption on a data subcarrier position, and a receiving end performs descrambling and then performs feedback through CRC verification so as to guarantee data integrity; and finally, quantum noise is introduced to enhance the randomness of the secret key, and zero-knowledge authentication is adopted to verify the identity, so that the security and the anti-attack capability of wireless communication data transmission are effectively improved.

The invention belongs to the field of PCIe (Peripheral Component Interconnect Express) chips, and relates to a CXL switching chip of a multi-core-grain architecture and a cross-core-grain routing switching method thereof, and a plurality of CXL switching core grains with uniform specifications are packaged and interconnected to form the CXL switching chip; each CXL switching core particle comprises a plurality of ports, each port can be configured to be in a CXL mode and a D2D mode, and the port of each CXL switching core particle at least comprises a physical layer, a CXL link layer, a CXL transaction layer, a D2D routing layer, a bypass and a multipath selection module; the CXL switching chip further comprises a multi-VC on-chip CXL switching network, and the multi-VC on-chip CXL switching network comprises at least one order-preserving switching VC and one out-of-order switching VC. According to the method, CXL switching chips of various specifications can be flexibly constructed, the design complexity and verification difficulty of the large-scale or multi-port CXL switching chips are effectively reduced, and the production yield of the chips is improved.

The invention discloses a communication network rapid adaptive control strategy generation method based on meta reinforcement learning, and relates to the field of communication network adaptive control, and the method comprises the steps: collecting and processing a physical layer signal and a network layer index, and obtaining a standardized multi-dimensional time sequence matrix; inputting the standardized multi-dimensional time sequence matrix into a hybrid encoder formed by CNN-LSTM, dynamically weighting through a self-attention mechanism, and outputting an environment feature vector; inputting the environment feature vector into a neural differential equation network, generating a strategy parameter increment and updating a strategy network parameter; and constructing a dynamic reward function based on physical layer features in the environment feature vector, and performing detection to obtain an adjusted dynamic reward value. According to the method, continuous time evolution of strategy parameters is realized through a neural differential equation network, and a dual-channel ResNet-ODE architecture is combined with a gating fusion mechanism, so that the problem of oscillation caused by discrete updating of a traditional reinforcement learning strategy is solved.

The invention discloses a dormancy and awakening system and method of an enterprise-level solid state disk, and belongs to the technical field of power consumption management of the enterprise-level solid state disk. According to the system, a nonvolatile cache unit, an independent hardware state machine and an ultra-low power consumption wake-up detection circuit are integrated in a main controller. When entering the dormancy state, key data such as an FTL mapping table are stored in a nonvolatile cache, then the power management module cuts off power supply to the NAND flash memory and the main control core, and only the operation of the minimum circuit is maintained, so that the dormancy power consumption is reduced to be below 100mW; and during wakeup, the detection circuit identifies a physical layer signal to trigger rapid power-on, and the hardware state machine directly recovers the system state from the cache and bypasses the software initialization process, so that wakeup is completed and the NAND access capability is reconstructed within 1ms, and the industrial problem that ultra-low power consumption and rapid wakeup cannot be considered at the same time is effectively solved.