32 results about "Bandwidth constraint" patented technology

The invention provides a game accelerator packet loss optimization method and device based on flow priority management. The method comprises the following steps: executing periodic link detection on at least one proxy node, and generating a corresponding link monitoring result; judging whether the packet loss rates of two continuous monitoring periods exceed a first threshold value or not according to the link monitoring result; performing real-time classification on the to-be-sent data streams to obtain priority labels for different traffic categories; inputting a prediction algorithm based on a link monitoring result, obtaining a network quality prediction value of a next monitoring period, adaptively adjusting a redundancy proportion according to the network quality prediction value, and sending a queue bandwidth constraint parameter and an agent node; and sending the sorted source data packet and the redundant data packet to a target game server or a game client according to the updated proxy node so as to realize accelerated forwarding of the game data. According to the invention, the reliability, delay stability and bandwidth utilization rate of game data transmission in a cross-border high packet loss network environment can be improved.

The invention relates to the technical field of photovoltaic power generation, and discloses a photovoltaic power generation power prediction method based on spatial-temporal feature fusion, which comprises the following steps: acquiring an original signal, and optimizing the modal number K and bandwidth constraint alpha of VMD by adopting a CPO algorithm; taking the modal number K and the bandwidth constraint alpha as input parameters of a VMD algorithm, and decomposing the original signal into a plurality of modal components; for the plurality of modal components, extracting spatial features and time features in a manner of combining ST-GCN and LSTM, and fusing the spatial features and the time features to obtain spatial-temporal features; and mapping the fused spatial-temporal characteristics to a photovoltaic power prediction space through a full connection layer and a regression layer, and outputting a prediction value. According to the photovoltaic power generation power prediction method based on spatial-temporal feature fusion provided by the invention, photovoltaic power prediction is carried out based on combination of CPO optimized VMD, ST-GCN and LSTM, a basis can be provided for a power grid dispatching decision, and the power operation cost is reduced.

Systems and methods are disclosed to mitigate stalling of streaming content due to rebuffering so that, e.g., the content consumer does not experience gaps in playback. In some embodiments, by buffering streaming content simultaneously at two bitrate levels—e.g., one of the lowest bitrates and a better-quality bitrate, within the bandwidth limitations—rebuffering-caused gaps in playback of a higher quality (HQ) stream may be filled with a lower quality (LQ) stream. For instance, client-side dual buffers may store n segments from the HQ stream during a given time and a multiple of n number of segments from the LQ stream, thus allowing for many of the LQ segments to be output if the HQ stream is rebuffering. If a segment of content is beginning to be played back as an LQ segment, there is no reason to buffer the same segment from the HQ stream. Moreover, after a segment of content is played back (or decoded) as either HQ or LQ, the corresponding HQ segment and / or LQ segment may be discarded from the dual buffer, e.g., to create buffer space for upcoming segments.

The invention relates to the technical field of information, and discloses a data migration scheduling method based on equipment anomaly detection, which comprises the following steps of: S1, modeling through the health state of equipment, monitoring and estimating the health state of the equipment in real time, and judging whether the equipment is in an abnormal state or not based on an estimated value; s2, when the equipment is in an abnormal state, triggering data migration scheduling; s3, designing an optimization scheduling target, minimizing data migration delay, equipment load fluctuation and bandwidth resource consumption, and calculating a data migration path and a scheduling strategy based on an equipment health state and bandwidth constraints; and S4, solving an optimal scheduling problem with constraints by adopting a Lagrange multiplier method. Modeling and real-time estimation are carried out on the equipment health state through the stochastic differential equation and the Kalman filtering algorithm, accurate abnormal state detection is achieved, and the problems that in the prior art, response to equipment state changes is not timely, and accuracy is insufficient are effectively solved.

The present application relates to a communication-aware task allocation method and device based on a multi-objective asynchronous strategy. The method transforms the communication strategy optimization problem in the distributed task allocation algorithm of a multi-agent system into an asynchronous constraint decentralized partially observable Markov decision process according to bandwidth constraints; constructs an asynchronous constraint multi-agent reinforcement learning environment considering the communication process according to the asynchronous constraint decentralized partially observable Markov decision process; optimizes the multi-objective asynchronous communication strategy in the distributed task allocation method by using the multi-objective coupled PPO method according to the asynchronous constraint multi-agent reinforcement learning environment to obtain the final multi-objective asynchronous communication strategy; and each unmanned aerial vehicle adopts the final multi-objective asynchronous communication strategy to complete the communication-aware task allocation of the unmanned aerial vehicle cluster. This method uses the multi-objective coupled PPO method to simultaneously reduce bandwidth overhead and minimize task conflicts, achieving a better balance between communication efficiency and allocation reliability.

The invention discloses a four-rotor aircraft data driving control method breaking through bandwidth constraint under hostile attack. The method specifically comprises the following steps: establishing a kinetic model of a four-rotor aircraft; converting the obtained kinetic model into an equivalent dynamic linearization equation by using a dynamic linearization method; designing a criterion function, and designing a data driving control method of the four-rotor aircraft; an event triggering mechanism is introduced, denial of service attack is considered, and then the final four-rotor aircraft safety event triggering data driving control method is obtained through arrangement of the obtained control method. According to the method, model-free adaptive control is applied to attitude control of the four-rotor aircraft, the advantages of PID are combined, malicious denial of service attacks are considered, an event triggering mechanism is introduced, the good flight quality of the aircraft is guaranteed, system bandwidth resources can be saved, and the working time of the aircraft is prolonged.

This invention discloses a satellite image compression method under extremely low bandwidth conditions. The steps are as follows: collect a static image dataset; establish a variable bitrate image encoding / decoding network; train the encoding / decoding network; embed a generative adversarial network (GAN) at the decoder and retrain it; embed a super-resolution network after the encoder / decoder and retrain it; the user selects a region of interest (ROI), and the selected region is compressed; the decoder restores the bitstream to an image and displays it; the unselected regions are compressed; when bandwidth is sufficient, the unselected regions are transmitted, and the decoder stitches the images together; super-resolution processing is performed. This image transmission method, under extremely low bandwidth constraints, provides a superior subjective reconstruction effect compared to traditional image coding methods such as JPEG and deep learning-based image coding methods in a large number of test images.

Systems and methods are disclosed to mitigate stalling of streaming content due to rebuffering so that, e.g., the content consumer does not experience gaps in playback. In some embodiments, by buffering streaming content simultaneously at two bitrate levels—e.g., one of the lowest bitrates and a better-quality bitrate, within the bandwidth limitations—rebuffering-caused gaps in playback of a higher quality (HQ) stream may be filled with a lower quality (LQ) stream. For instance, client-side dual buffers may store n segments from the HQ stream during a given time and a multiple of n number of segments from the LQ stream, thus allowing for many of the LQ segments to be output if the HQ stream is rebuffering. If a segment of content is beginning to be played back as an LQ segment, there is no reason to buffer the same segment from the HQ stream. Moreover, after a segment of content is played back (or decoded) as either HQ or LQ, the corresponding HQ segment and / or LQ segment may be discarded from the dual buffer, e.g., to create buffer space for upcoming segments.

The invention relates to the technical field of video transmission, in particular to a video secure transmission method, device and system in a low-bandwidth scene, and aims to improve the video secure transmission efficiency by defining the influence weight of a historical frame image on a current frame image and combining the characteristic that each motion area is in a continuous high ROI state in the historical frame image. Determining a code rate increasing factor of each motion area of the current frame image; constructing the weight of each motion area of the current frame image in a smooth matrix by using the code rate increasing factor and the space center position of each motion area, constructing the smooth matrix in combination with a Gaussian kernel function, and performing smooth processing on the code rate increasing factor, thereby effectively inhibiting the visual discontinuity phenomenon between the frame images; determining a code rate relative weight of each motion region of the current frame image by jumping maximization of the visual quality of the key region and minimization of the quality between the regions into a target design target function; and in combination with the real-time network bandwidth and the dynamic scaling code rate allocation result, the optimal balance of quality and smoothness is realized under the bandwidth constraint.

This invention discloses a power communication routing optimization method considering fault risk. The method establishes a primary and backup routing model for the communication system; correlates the importance of load control services in the power system with the information flow, proposing a communication link importance evaluation index; then, combined with a conditional risk measurement model, it proposes a power communication routing optimization method; it treats communication service losses in each fault scenario as risk values, aiming to minimize the losses of important services across all fault scenarios, and considers constraints such as node constraints, bandwidth constraints, and routing constraints to solve for the primary and backup routing paths of the power communication network. This invention flexibly formulates communication routing paths based on changes in the fault area, and the route selection can proactively avoid fault risk areas, effectively reducing load losses during fault processes; it can be used to formulate power communication routing schemes, improving the resilience of power communication systems in responding to faults.

The invention relates to a time-sensitive network routing and scheduling method based on a conflict graph, and belongs to the technical field of industrial automation communication. The method comprises the following steps: firstly, reading network topology, node processing delay, traffic period, traffic frame length, source node and destination node information, and carrying out initialization representation on the TSN network topology; then, according to the configuration information of the data flow and the network topology, generating candidate paths meeting delay, bandwidth and load balancing constraints; then, establishing a conflict graph by taking the configuration of routing and phase and the color as vertexes and taking the space-time conflict of any frame in a period on any shared link as an edge; and solving the maximum independent polychromatic set in the conflict graph, namely, distributing proper transmission starting time for each flow in the network. According to the method, the scheduling constraint is mapped into the conflict graph, and the independent set solving algorithm is combined, so that a rapid and low-memory-occupation scheduling scheme is generated, the link utilization rate and the system adaptability are improved, and meanwhile, strict delay and bandwidth constraints are met.

The application provides a scheduling optimization method and system for multi-link data transmission of an earth observation satellite. In a network topology structure, a path indicator of a sub-flow, a data rate of the sub-flow, and a data transmission time of a source node are obtained according to a network topology graph of each time slot in a task cycle, capacities of various links, sources of requested data, a data amount required to be transmitted by each source node, and a destination node set. The obtained information is subjected to bandwidth constraint and data amount constraint, and a shortest path set from the source node to the destination node is obtained with a total data transmission time being minimized as an optimization target. Then, the shortest path set from a source satellite to each target ground station is calculated, and an optimal path is selected based on a joint degree and a survival time. Based on the selected optimal path, bandwidth resources are allocated according to a priority of a source satellite task, and data transmission from the source satellite to a destination is performed to realize multi-link efficient data transmission of data and improve data transmission efficiency.

The application relates to a time-deterministic multi-path routing method based on a random time-varying graph, comprising the following steps: constructing a random time-varying graph model; the minimum link bandwidth of a selected path is smaller than or equal to the bandwidth boundary required by a service; according to the bandwidth constraint condition of the path, the random time-varying graph model is first simplified, and the path that does not meet the bandwidth requirement is deleted; the shortest path considering load balancing is obtained according to a load balancing breadth-first search path optimization algorithm; the second shortest path and the path in the set are compared until two paths meeting the optimization target are found; the capacity of each occupied path is updated according to the calculation result, and the path set is returned. The application plans end-to-end transmission multi-paths meeting the differential delay requirement, effectively avoids network congestion, improves the reliability of end-to-end communication, and guarantees the certainty of service transmission delay.

The invention discloses a joint optimization method for multi-unmanned aerial vehicle relay communication in a cognitive wireless network and application, and relates to the technical field of wireless communication, a joint optimization model in a multi-unmanned aerial vehicle relay communication scene in the cognitive wireless network is constructed, the joint optimization model takes maximization of the minimum throughput of a user as an optimization target, and the optimal throughput of the user is maximized. Solving the joint optimization model by taking an unmanned aerial vehicle distribution constraint, a minimum bandwidth constraint, a bandwidth equivalent constraint, a maximum throughput constraint and a master user interference constraint as constraint conditions to obtain a joint optimization scheme; therefore, unmanned aerial vehicle-slave user matching, unmanned aerial vehicle position deployment and bandwidth allocation in a multi-unmanned aerial vehicle relay communication scene in a cognitive wireless network can be jointly optimized, the minimum throughput of the slave user is improved on the premise of ensuring the communication quality of a main network, and the frequency use fairness of the slave user is ensured.

The invention relates to the technical field of driving intention recognition, in particular to a driving intention recognition method and system based on a friction nanometer generator, and the recognition method comprises the steps: collecting a TENG signal of a current operation; after processing the TENG signal, normalizing to generate a to-be-identified query sequence; a DTW algorithm with bandwidth constraints and a lower bound pruning strategy are adopted to find out a standard template sequence most matched with the to-be-recognized query sequence; an LSTM recognition model with a gating mechanism introduced is adopted, and a driving intention recognition category label is output; generating a vehicle control decision result; the method is applied to the recognition system, the friction nanometer generator can be flexibly deployed, signal conditioning and analog-to-digital conversion processing can be carried out on the collected TENG signals, driver operation behavior signals are collected in a low-power-consumption and non-intrusive mode, meanwhile, the DTW algorithm with multiple constraints is adopted, operation behavior feature sequences can be aligned at low calculation cost, and the recognition accuracy is improved. And accurate identification of the driving intention is facilitated.

Techniques and apparatuses are described for receiving multiple audio streams from multiple audio sources. In an example aspect, a hearable (102-1) receives different audio streams (108), which are respectively transmitted by different audio sources (118). Due to bandwidth limitations, the hearable (102) receives at least two of the multiple audio streams (108) using at least two different wireless communication channels (404). With a first wireless communication channel (404-1), the hearable (102-1) receives a first audio stream (108-1) directly from a first audio source (118-1). With a second wireless communication channel (404-2), the hearable (102-1) receives a second audio stream (108-2), which is forwarded by another device (402) from a second audio source (118-2). To further free up bandwidth or temporal resources on the first wireless communication channel (404-1), the hearable (102-1) can perform general overhead operations with a second hearable (102-2) using the wireless second communication channel (404‑2).

The application discloses a limited time privacy protection consistency method under an event triggering mechanism, based on the event triggering mechanism, effective event triggering conditions are derived, and limited time theory is introduced to guarantee the convergence performance of multi-agent consistency, meanwhile, an output mapping function is introduced to ensure that the state of each agent in the multi-agent system is unknown to the outside world, that is, the real state information of the agent cannot be acquired by adjacent agents and external intruders, and limited time privacy protection consistency convergence is realized. The method of the application combines the event triggering mechanism and the limited time theory, improves the convergence performance of multi-agent privacy protection consistency control, and reduces the resource consumption of algorithm calculation, comprehensively considers communication security, bandwidth constraints and performance indexes, further expands the application scene of the algorithm, and to some extent, completes the comprehensive consideration of privacy protection, system performance and execution efficiency and the like.

The application discloses a joint optimization method and application of multi-unmanned aerial vehicle relay communication in a cognitive wireless network, relates to the technical field of wireless communication, and constructs a joint optimization model under a multi-unmanned aerial vehicle relay communication scenario in a cognitive wireless network. The joint optimization model takes maximizing the minimum throughput of a slave user as an optimization target, takes unmanned aerial vehicle distribution constraints, minimum bandwidth constraints, bandwidth equalization constraints, maximum throughput constraints and primary user interference constraints as constraint conditions, solves the joint optimization model, obtains a joint optimization scheme, and thus can jointly optimize unmanned aerial vehicle-slave user matching, unmanned aerial vehicle position deployment and bandwidth distribution under the multi-unmanned aerial vehicle relay communication scenario in the cognitive wireless network, improves the minimum throughput of the slave user under the premise of guaranteeing the communication quality of the primary network, and guarantees the frequency use fairness of the slave user.

This application provides an artificial intelligence-based elevator fault detection method and system. The method determines the search range for the number of vibration signal decomposition layers based on the differences in the vibration physical characteristics between various mechanical components during elevator operation and the sudden load changes during elevator operation. It determines the candidate range of bandwidth constraints for each mechanical component's vibration with the goal of minimizing the aliasing of vibration physical characteristics between the components. Modal decomposition is performed by traversing different parameter combinations within the search range and the candidate range. Feature components containing fault information of each mechanical component are selected from the decomposition results. All feature components are input into a trained artificial intelligence classification model to determine the fault type of the elevator traction system. Using the solution of this application, the vibration characteristics of each mechanical component of the elevator can be extracted completely and independently under conditions of vibration coupling and sudden load changes.

The invention discloses an emergency rescue method based on Beidou communication and conduction integrated fusion. The method comprises the steps that S1, an airborne terminal obtains motion state data and environment data in the parachuting process of a pilot; s2, compressing the collected data, and sending the compressed data to a rescue command center through a Beidou short message channel; and S3, the rescue command center decompresses the compressed data, combines the motion state data and the environment data, and uses a prediction model to calculate the landing point of the pilot. According to the method, the relative wind speed vector measured by the airborne sensor is acquired in real time, and high-frequency attitude matrix transformation is combined, so that the problem of lateral deviation caused by a high-altitude complex wind field is effectively solved, the prediction precision of the landing drop point is remarkably improved, and the problem of huge deviation of the calculated drop point caused by wind speed interference is solved. Through relative differential compression and a self-adaptive LSB quantization mechanism, it is ensured that high-dynamic trajectory details of more than 10 Hz can still be completely restored under extremely low bandwidth limitation.

The invention discloses an FTTR network resource planning method, system and device and a medium, and relates to the technical field of networks, and the method comprises the steps: determining a target terminal according to the current position information; determining a signal intensity sequence according to the current position information, and determining a target node according to the signal intensity sequence; obtaining the current network speed and behavior data of each user terminal, and determining a target network speed sequence according to the current network speed and the behavior data; setting a bandwidth constraint condition and a performance constraint condition, calling a network speed prediction model, and determining a planned bandwidth sequence and a planned performance sequence corresponding to the planned bandwidth sequence according to a gradient descent algorithm; and converting the Internet access node of the target terminal into the target node, and adjusting the bandwidth of each network node to the corresponding planned bandwidth according to the planned bandwidth sequence. The method and the device have the effect of improving the flexibility of the FTTR network.

Systems and methods are disclosed for utilizing frequency multiplier (FX) based transmitters to generate wideband, substantially distortion-free signals, when a transmitter operates under bandwidth constraints. A receiver is configured to acquire the feedback signal at the multiplier output. The systems and methods alleviate the bandwidth constraints of the receiver. Additionally, the invention includes a training methodology for estimating predistortion coefficients configured to operate under constrained transmitter and receiver bandwidth conditions.

This invention discloses a method and system for joint optimization of video quality and latency under bandwidth-constrained conditions, relating to the fields of video processing and communication technology. The method operates in a closed-loop, discrete time slot manner. It generates link state data through network metric collection and latency decomposition, and obtains optimal coding parameters under a multi-objective cost function that integrates perceived quality, end-to-end latency, region of interest (ROI) task relevance, and stability penalties. These parameters are then solidified into a versioned pre-decision parameter set, achieving cross-stage timing alignment. Based on the importance of the ROI and the latency budget, the system performs differentiated redundancy configuration and bandwidth-latency dual-threshold scheduling. It combines receiver-side experience quality and link state feedback, and utilizes machine learning to predict link anomalies and dynamically correct parameters. This achieves collaborative optimization of video quality and latency in weak network environments, improving system robustness and transmission stability.

The invention discloses an isogeometric robust topological optimization method of a composite material structure considering frequency band constraints, which comprises the following steps of: firstly, constructing an isogeometric robust topological optimization model of the composite material structure considering material attribute related uncertainty and frequency band constraints; the mean value and the standard deviation of the dynamic flexibility of the structure under the related uncertainty are calculated through Nataf transformation and Gauss-Hermite integration; then solving a worst limit state approximation function and an uncertainty parameter point vector corresponding to each limit state function through a gradient search algorithm; and finally, calculating the sensitivities of the target function, the worst limit state approximation function and the volume constraint function, and obtaining a robust and optimal topological structure meeting the dynamic performance requirement in combination with a moving asymptote method. The isogeometric robust topological optimization model of the composite material structure established by the invention can truly reflect the correlation and dynamic performance requirements of the material attribute uncertainty, can efficiently obtain the optimization result, and has good engineering application value.

In a first example, a processing system may transmit one or more reception parameters for a video call, where the one or more reception parameters include a first depth parameter defining a first depth of video content that the processing system is to display. The processing system may then receive the video content in accordance with the first depth parameter and present the video content in accordance with the first depth parameter. In a second example, a processing system may detect a bandwidth constraint for a transmission of video content for a video call, select a first depth parameter based upon the bandwidth constraint, and transmit a video stream comprising the video content in accordance with the first depth parameter.

The invention relates to a digital twin-assisted collaborative awareness and resource allocation method in the Internet of Vehicles, and belongs to the technical field of mobile communication. Aiming at the problems of high sensing delay and insufficient cooperative stability caused by low broadcast mode spectrum efficiency and poor static resource allocation adaptability in the Internet of Vehicles, a digital twin Internet of Vehicles scene is constructed, a double-layer sensing area dynamic triggering mechanism is designed, and the cooperative stability of the Internet of Vehicles is improved based on Cramer-Rao bound quantitative sensing precision and bandwidth constraint. And screening high-stability cooperative nodes by adopting an improved K-means algorithm, and establishing a deep reinforcement learning driven joint optimization model to realize dynamic allocation of communication bandwidth, power and computing resources. According to the method, the redundant communication traffic is reduced by 30%, the target positioning error is reduced by 25%, the cooperative link stability is improved by 40%, the system utility is improved by 18-22%, the task processing time delay is shortened to 65% of that of a traditional scheme, and the cooperative sensing efficiency and the resource utilization rate in the Internet of Vehicles environment are remarkably improved.

The invention relates to an Internet of Vehicles cooperative sensing method based on space confidence map driving, and the method comprises the steps: screening a high-value sensing region from a source through a local space confidence map, and achieving the reduction of the order of magnitude of a communication load through combining with the transmission of sensing feature data of a to-be-transmitted grid set, and fundamentally relieving the bandwidth constraint. Secondly, global optimization scheduling based on a perception missing score ensures that limited communication resources are accurately delivered to a link which is most effective for compensating a perception blind area, so that the target detection recall rate and the average precision in a key scene are improved on the contrary while great load reduction is carried out, and unification of load reduction and precision increase is realized; finally, according to the scheme, through periodic global optimization, multi-vehicle resource competition is effectively coordinated, transmission conflicts are avoided, the system is endowed with excellent real-time adaptability to dynamic scenes such as vehicle movement and shielding changes, and the technical requirements of cooperative sensing of the Internet of Vehicles for high efficiency, accuracy and reliability are comprehensively met.

The present invention specifically relates to a method for allocating integrated sensory resources based on multi-device collaboration, including: defining the bandwidth constraints of the ISAC device in time slot m based on the fixed bandwidth of the cellular user, the number of cellular users in time slot m, and the total bandwidth; defining the energy consumption constraints of the ISAC device in M ​​consecutive time slots based on the time the ISAC device executes the sensing mode and communication mode in each time slot, the transmission power of the ISAC device in a single time slot, and the total energy budget of the ISAC device in m time slots; defining the maximization discriminant gain problem based on each constraint, including the joint optimization of sensing power, transmission power, quantization gain, and communication bandwidth; optimizing the sensing power, transmission power, and quantization gain in the first stage based on predefined bandwidth conditions; and allocating the communication bandwidth in the second stage based on the optimization results of the first stage. This method can realize dynamic resource allocation and can realize integrated sensory resource allocation that adapts to multiple devices and multiple time slots.

The invention provides an NPU performance optimization method and system. The method comprises a compiling stage, a bandwidth sampling stage and a performance verification stage. The compiling stage comprises the steps that a calculation graph is segmented into a plurality of sub-graphs, performance evaluation of the sub-graphs is completed in combination with specified bandwidth constraints, estimated performance of the sub-graphs is obtained, and an NPU execution file is generated; the bandwidth sampling stage comprises the following steps: running an execution file, and sampling to obtain an actual bandwidth constraint; the performance verification stage comprises the steps of obtaining the operation performance of the NPU in the bandwidth sampling stage, verifying the difference between the estimated performance and the operation performance, if the difference is smaller than or equal to a threshold value, completing optimization, and if the difference is larger than the threshold value, taking the actual bandwidth constraint as the specified bandwidth constraint to re-carry out the compiling stage, the bandwidth sampling stage and the performance verification stage. The difference is less than or equal to the threshold. According to the method, the dynamic bandwidth constraint is used for replacing the static bandwidth constraint in the prior art, the bandwidth resources on the SoC are fully utilized, and the NPU performance is optimized.

The invention discloses a composite trans-impedance amplifier configuration method based on multi-objective optimization, and the method comprises the following steps: S1, constructing a composite TIA model, and determining a transfer function; the transfer function comprises an open-loop transfer function, a closed-loop transfer function and a noise transfer function; s2, constructing a phase margin constraint and a bandwidth constraint based on the open-loop transfer function and the closed-loop transfer function; calculating system output noise based on the noise transfer function; s3, by taking minimization of system output noise as a target, calculating an optimal solution under the phase margin constraint and the bandwidth constraint to obtain a TIA configuration parameter; on the premise of ensuring the stability and the closed-loop bandwidth, the balance of the phase margin constraint, the closed-loop bandwidth index and the output noise is realized by taking the noise as an optimization target.