Channel equalization method and device, computer equipment, storage medium and program product

Abstract

The embodiment of the invention discloses a channel equalization method and device, computer equipment, a storage medium and a program product. According to the embodiment of the invention, the transmission loss of the task scheduling signal in the second path can be determined based on the transmission loss of the task scheduling signal in the first path; generating a scheduling function of the first path based on the transmission characteristics of the task scheduling information and the transmission loss of the second path; and adjusting the amplitude-frequency of the task scheduling signal in the first path based on the scheduling function of the first path. In a scene in which the traffic of the transmission task scheduling signal is dispersed into a plurality of paths to realize multipath transmission, the amplitude frequency of each path can be adjusted according to the scheduling function corresponding to each path, and the transmission performance of other paths can be referred to when the scheduling function of each path is generated. Therefore, according to the scheme, the load balancing among the channels can be realized, so that the communication efficiency is improved.

Description

Technical Field

[0001] The present application relates to the field of computers, and in particular to a channel equalization method, apparatus, computer equipment, storage medium and program product. Background Art

[0002] Cloud computing is an Internet-based computing method that allows users to access shared hardware and software resources and information through the Internet. These resources can be provided to computers and other devices on demand. Cloud computing breaks down huge data computing programs into countless small programs, processes and analyzes them through a system composed of multiple servers, and then returns the results to users.

[0003] In cloud computing network communications, a large number of processing tasks in the cloud need to be processed and scheduled. In the process of large-scale network data transmission and scheduling of cloud tasks, channel imbalance problems are prone to occur, resulting in low communication efficiency. Summary of the invention

[0004] The embodiments of the present application provide a channel equalization method, apparatus, computer device, storage medium and program product, which can achieve channel equalization and thus improve communication efficiency.

[0005] The present application provides a channel equalization method, including:

[0006] Determining a transmission loss of the task scheduling signal on the second path based on a transmission loss of the task scheduling signal on the first path;

[0007] generating a scheduling function of the first path based on the transmission characteristics of the task scheduling information and the transmission loss of the second path;

[0008] Based on the scheduling function of the first path, the amplitude and frequency of the task scheduling signal in the first path are adjusted.

[0009] The embodiment of the present application also provides a channel equalization device, including:

[0010] a loss unit, configured to determine a transmission loss of the task scheduling signal on the second path based on a transmission loss of the task scheduling signal on the first path;

[0011] A function unit, configured to generate a scheduling function of the first path based on the transmission characteristics of the task scheduling information and the transmission loss of the second path;

[0012] The adjustment unit is used to adjust the amplitude and frequency of the task scheduling signal in the first path based on the scheduling function of the first path.

[0013] In the transmission scenario of multipath traffic, traffic will be dispersed to multiple paths for transmission to avoid overloading a single path. Furthermore, this application analyzes the transmission characteristics and losses of each path, reasonably distributes traffic, avoids overloading of a single path, reduces delays and packet loss rates, and ensures the stability and reliability of data transmission. This flexible traffic management strategy can adapt to changes in network conditions in real time, optimize resource utilization, and improve overall system performance.

[0014] Among them, the present application ensures that the system has all possible path information through transmission characteristics, so that a comprehensive analysis of the task scheduling signal in each path can be achieved, and the transmission loss of the second path can be calculated through the transmission loss of the first path, so that the communication quality of certain paths can be more accurately discovered, thereby generating an accurate scheduling function, so that the scheduling function can accurately adjust the task allocation in each path, and finally the scheduling function can weigh the performance of each path, automatically adjust the amplitude and frequency of the task scheduling signal in each path, and realize the load balancing of the path transmission, that is, adjust the amplitude and frequency of the signal for different paths to optimize the transmission quality of the path, and ensure the channel balance of all paths.

[0015] Therefore, the embodiment of the present application evaluates the loss of one path and dynamically adjusts the transmission strategy of another path, so that the dynamically scheduled tasks between different paths can be evenly and effectively transmitted, ensuring that the tasks are evenly distributed on each path, avoiding the situation where some paths are overloaded or some paths are idle. Therefore, the present application can achieve channel balancing and improve communication efficiency.

[0016] In summary, the embodiments of the present application can effectively achieve channel equalization and thus improve communication efficiency by acquiring transmission characteristics, real-time evaluation of transmission loss, and dynamically generating scheduling functions. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0018] Figure 1a is a schematic diagram of a scenario of a channel equalization method provided in an embodiment of the present application;

[0019] Figure 1b It is a flow chart of a channel equalization method provided in an embodiment of the present application;

[0020] Figure 2It is a flow chart of the application of the channel balancing method provided in the embodiment of the present application in the SDN network communication scenario based on cloud computing;

[0021] Figure 3 It is a structural schematic diagram of a channel equalization device provided in an embodiment of the present application;

[0022] Figure 4 It is a schematic diagram of the structure of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0023] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of this application.

[0024] Embodiments of the present application provide a channel equalization method, apparatus, computer equipment, storage medium, and program product.

[0025] The channel equalization device can be integrated in a computer device, which can be a terminal, a server, or other devices. The terminal can be a mobile phone, a tablet computer, a smart Bluetooth device, a laptop, or a personal computer (PC), etc. The server can be a single server or a server cluster composed of multiple servers.

[0026] In some embodiments, the channel balancing device may also be integrated into multiple computer devices. For example, the channel balancing device may be integrated into multiple servers, and the channel balancing method of the present application may be implemented by multiple servers.

[0027] In order to better understand a channel equalization method, device, electronic device, storage medium and program product provided in the embodiments of the present application, a computer system applicable to the embodiments of the present application is first described below.

[0028] See also Figure 1a , Figure 1a A schematic diagram of a computer system for a channel equalization method provided in an embodiment of the present application is shown. As an implementation mode, the computer device provided in the embodiment of the present application may be a server. The electronic device may be as follows: Figure 1aThe server 110 shown in the figure can be connected to the data center 120 through a network, and the data center 120 can be a data center of a cloud computing server. The network is used to provide a medium for a communication link between the server 110 and the data center 120. The network can include various connection types, such as wired communication links, wireless communication links, etc., which are not limited in the embodiments of the present application. Optionally, in other embodiments, the electronic device can also be a smart phone, a laptop computer, etc.

[0029] It should be understood that Figure 1a The server 110, network and data center 120 are merely illustrative. Any number of servers, networks and terminal devices may be provided as required. For example, the server 110 may be a physical server or a server cluster composed of multiple servers, and the data center 120 may be a mobile phone, a tablet, a desktop computer, a laptop computer and the like. It is understood that the embodiments of the present application may also allow multiple data centers 120 to access the server 110 at the same time.

[0030] In some embodiments, the cloud computing servers in the data center 120 may be physical or virtual servers that provide computing, storage, and network resources. The cloud computing servers can allocate resources on demand and support the deployment of large-scale applications and services, such as virtual machines, containers, storage services, etc. The server 110 can effectively allocate and manage the computing resources of the cloud computing servers in the data center 120 to meet the needs of applications and optimize system performance.

[0031] As another implementation, the channel equalization method provided in the embodiment of the present application can be applied to different electronic devices. For example, the channel equalization method is applied to the server 110, and the server 110 can obtain the transmission characteristics of the task scheduling signal of the cloud computing server in the data center 120, the transmission characteristics including the transmission characteristics of the task scheduling signal in each path, and obtain the transmission loss of the task scheduling signal in the first path; based on the transmission loss of the first path, determine the transmission loss of the task scheduling signal in the second path; based on the transmission characteristics and the transmission loss, generate a scheduling function; based on the scheduling function, adjust the amplitude and frequency of the task scheduling signal in the path.

[0032] It should be noted that the serial numbers of the following embodiments are not intended to limit the preferred order of the embodiments.

[0033] like Figure 1b As shown, the specific process of the channel equalization method can be as follows:

[0034] 101. Determine a transmission loss of the task scheduling signal on a second path based on a transmission loss of the task scheduling signal on a first path.

[0035] The task scheduling signal is transmitted in multiple paths, and the first path and the second path are two different paths among the multiple paths. In some embodiments, the solution further includes:

[0036] Acquiring transmission characteristics of the task scheduling signal, where the transmission characteristics include transmission characteristics of the task scheduling signal on each path;

[0037] The transmission loss of the task scheduling signal in the first path is obtained.

[0038] Therefore, in the present application, the task scheduling signal will be dispersed into multiple paths for transmission. Step 101 can calculate the transmission loss of the second path based on the acquired transmission loss of the first path, so that the subsequent steps can generate and use the scheduling function based on the transmission loss of the second path to adjust the amplitude and frequency of the task scheduling signal in the first path.

[0039] Among them, the transmission characteristics include characteristics that characterize the transmission performance of the task scheduling signal on each path. For example, the transmission characteristics include a set of key parameters when the task scheduling signal is transmitted on each path. These parameters are used to describe the performance of the signal on the transmission path, including delay, bandwidth, packet loss rate, signal-to-noise ratio, channel stability, etc.

[0040] Among them, task scheduling signals refer to signals that need to be coordinated, allocated and managed between cloud computing resources in a cloud computing environment. For example, through control instructions, status updates, resource requests and other signals, it can ensure that task scheduling signals are efficiently distributed to multiple paths, and they are managed and optimized, and timely adjustments can be made when failures or channel changes occur.

[0041] Among them, the transmission characteristics refer to the transmission characteristics of the task scheduling signal in multiple paths. Transmission (Multipath Transmission) refers to dividing the data into multiple parts and transmitting them simultaneously through multiple independent network paths. This method can ensure that even if there is a problem with one of the paths (such as excessive latency, network interruption), the signal can still reach the destination through other paths. For example, through transmission, the task scheduling signal can choose the optimal path (the path with the lowest latency) for transmission. At the same time, the scheduler can dynamically adjust the signal transmission strategy according to the status of different paths to reduce scheduling delays.

[0042] In some embodiments, the embodiments of the present application can be applied to a cloud computing-based SDN environment that requires high reliability, low latency, and complex network management. Through the centralized control and path optimization capabilities of SDN, transmission can effectively improve the overall effect of task scheduling and ensure that the system can run stably under various network conditions.

[0043] For example, in some embodiments, a channel balancing method for SDN network communication based on cloud computing is provided, wherein SDN provides a flexible and programmable network infrastructure for cloud computing, enabling cloud computing servers to manage network resources and security policies more efficiently. At the same time, cloud computing also ensures that the SDN structure can cope with network requirements in large-scale, complex, and multi-tenant environments. The transmission characteristics of task scheduling signals enhance the reliability, performance, and efficiency of signal transmission by utilizing multiple network paths.

[0044] In some embodiments, the task scheduling signal a b The expression is:

[0045]

[0046] Among them, C n is the input signal, i.e., the transmission characteristic of the nth path, N is the total number of paths, and bn is the index of the nth path. b At the receiving end, multiple paths are superimposed, and the phase difference of these paths is determined by e 2πbn / N Indicates that 2πbn / N is a complex exponential function, which is used to describe the phase change of the signal.

[0047] Therefore, in some embodiments, step 101 of acquiring the transmission characteristics of the task scheduling signal includes:

[0048] Get task scheduling signal a b The transmission characteristics C in each path n ;

[0049] Obtain the phase modulation index of each path;

[0050] The phase modulation function of each path is accumulated to obtain the transmission characteristic a of the task scheduling signal b , the phase modulation function is the product of the complex exponential of the path and the transmission characteristics of the task scheduling signal in the path.

[0051] In some embodiments, the phase modulation function is the product of the complex exponential of the path n and the transmission characteristic of the task scheduling signal in the path. For example, the phase modulation function can be e 2πbn / N 、e jβm(t) ,πm(t), etc. Among them, for e jβm(t) , β is the modulation index, and m(t) is the modulation signal; where, for πm(t), the modulation signal m(t) is a binary sequence (0 or 1), and the phase can only be 0 or π, corresponding to the two states of the modulation signal.

[0052] Transmission loss refers to the attenuation of signal transmission in the path due to various factors (such as distance, medium, interference, etc.).

[0053] The embodiment of the present application can obtain the transmission losses of all paths by repeatedly calculating the loss of another path based on the loss of one path.

[0054] In some embodiments, there are multiple ways to calculate the transmission loss of a path. For example, the following scheme may be referred to:

[0055] For example, the transmission power and the receiving power of the path may be measured, and the transmission loss U may be determined based on the transmission power and the receiving power:

[0056] U=P tx -P rx

[0057] Among them, P tx is the transmission power, P rx is the received power.

[0058] For example, the transmission loss U can be determined based on the frequency and distance of the path:

[0059]

[0060] Where d is the path distance between the transmitting source and the receiving source, f is the frequency of the signal (Hz), and c is the speed of light (about 3×10 8 m / s).

[0061] The embodiment of the present application can calculate the transmission loss of the second path according to the transmission loss of the first path. In some embodiments, a correction term can be introduced to correct the transmission loss of the first path, thereby obtaining the transmission loss of the second path.

[0062] The correction term is used to adjust the transmission loss of the first path to reflect the actual situation of the second path.

[0063] In some embodiments, the correction term can be adjusted based on the transmission delay of the first and second acquisitions. The transmission delay is the time it takes for a signal to travel from a source to a destination. Changes in the transmission delay can affect the quality of the task scheduling signal and the throughput of the network. If the transmission delay changes between two acquisitions, it may cause changes in signal quality, thereby affecting transmission loss.

[0064] In some embodiments, the correction term may take into account the influence of the symbol rate and the transmission delay between two acquisitions, so that the adjustment of the loss is more accurate under different transmission conditions.

[0065] The symbol rate refers to the number of symbols transmitted per second. In digital communications, a symbol is the basic unit of data transmission, and each symbol represents a group of bits. The symbol rate determines the speed of signal transmission and the bandwidth requirements.

[0066] Therefore, in some embodiments, the correction term takes into account the change in signal quality reflected by the delay in two acquisitions, so as to better measure the transmission loss. Therefore, based on the transmission loss of the first path, determining the transmission loss of the task scheduling signal in the second path includes:

[0067] Acquire a symbol rate, a first transmission delay, and a second transmission delay of a task scheduling signal;

[0068] Determining a correction term according to a symbol rate, a first transmission delay, and a second transmission delay;

[0069] The transmission loss of the first path is corrected based on the correction item to obtain the transmission loss of the task scheduling signal on the second path.

[0070] Among them, the first transmission delay refers to the transmission delay of the first collection, and the second transmission delay refers to the transmission delay of the second collection. If the first transmission delay and the second transmission delay are equal, it indicates that the path transmission is stable and unchanged. If the first transmission delay and the second transmission delay are not equal, it indicates that the path transmission is unstable.

[0071] For example, in some embodiments, determining the correction term according to the symbol rate, the first transmission delay, and the second transmission delay includes:

[0072] constructing a symbol-delay characteristic based on a symbol rate and a first transmission delay;

[0073] Determining a Dirac function according to the first transmission delay and the second transmission delay;

[0074] Based on the symbol-delay characteristics and the Dirac function, a correction term is determined.

[0075] The symbol-delay feature is a feature composed of the symbol rate and the first transmission delay, and the feature can be a vector, a vector, etc. For example, the symbol-delay feature can be a two-dimensional vector, in which one dimension is the symbol rate and the other dimension is the first transmission delay.

[0076] In some embodiments, the symbol rate, the first transmission delay, and the second transmission delay of the task scheduling signal transmitted in any path can be detected in real time to calculate the correction term; for example, in some embodiments, the symbol rate, the first transmission delay, and the second transmission delay of the task scheduling signal transmitted in the second path can be detected in real time to calculate the correction term.

[0077] In some embodiments, the symbol rate, the first transmission delay, and the second transmission delay of the task scheduling signal transmitted in all paths can be detected in real time, so as to calculate the correction item; for example, in some embodiments, the average symbol rate, the average first transmission delay, and the average second transmission delay of the task scheduling signal transmitted in all paths can be detected in real time, so as to calculate the correction item based on the average symbol rate, the average first transmission delay, and the average second transmission delay.

[0078] In some embodiments, the symbol-delay feature characterizes the transmission characteristics of each symbol during the transmission process. For example, the symbol-delay feature can be a multidimensional vector, each dimension of which can be symbol rate, delay, amplitude, phase, etc.

[0079] For example, refer to the formula:

[0080] U cc =U c ' c -(α 1 ,β)δ(α 1 -α 2 )

[0081] Among them, Ucc is the transmission loss of the second path, U′cc is the transmission loss of the first path, and the correction term is (α 1 ,β)δ(α 1 -α 2 ), α 1 is the first transmission delay, α 2 is the second transmission delay, (α 1 , β) is the symbol-delay characteristic, β is the symbol rate, and δ can be the Dirac function.

[0082] The Dirac function is used to introduce or remove the correction term according to the stability of the path. For example, if α 1 and α 2 Equal (ie, δ(α 2 -α 2 )=1), symbol-delay characteristic (α 1 ,β) will be subtracted from U′cc; if α 1 and α 2 Not equal (ie δ(α 2 -α 2 )=0), symbol-delay characteristic (α 1 ,β) will have no effect on U′cc.

[0083] Therefore, in some embodiments, determining the Dirkat function according to the first transmission delay and the second transmission delay includes:

[0084] determining a delay difference between a first transmission delay and a second transmission delay;

[0085] If the delay difference is equal to 0, the value of the Dirac function is the first preset value;

[0086] If the delay difference is not equal to 0, the value of the Dirac function is the second preset value.

[0087] The first preset value may be set to 1, and the second preset value may be set to 0; or the first preset value may be set to 0, and the second preset value may be set to 1, and so on.

[0088] In summary, the correction term provides an adjustment for path transmission loss by taking into account changes in symbol rate and transmission delay. These factors directly affect the quality and transmission efficiency of the signal, so accurate correction terms help compensate for the losses caused by delay and symbol rate changes, ensuring more accurate loss calculations.

[0089] 102. Generate a scheduling function for the first path based on transmission characteristics of the task scheduling information and the transmission loss of the second path, where the transmission characteristics include characteristics that characterize transmission performance of the task scheduling signal in each path.

[0090] The scheduling function is used to optimize resource allocation in the cloud task scheduling process, and is used to adjust the amplitude and frequency of the task scheduling signal in step 103 to achieve more efficient task allocation and data transmission.

[0091] Among them, the scheduling functions generated based on transmission characteristics and transmission losses are diverse, for example, they may include minimizing total transmission loss scheduling, minimizing transmission power loss scheduling, minimizing signal distortion scheduling, minimizing inter-code interference scheduling, and frequency modulation scheduling functions.

[0092] For example, in some embodiments, a scheduling function based on transmission loss and signal quality optimization is proposed. The scheduling function can comprehensively consider transmission characteristics, transmission loss, frequency modulation slope and signal amplitude to optimize the scheduling of cloud tasks to improve signal quality and resource utilization efficiency in network communications.

[0093] Therefore, in some embodiments, step 102 generates a scheduling function based on the transmission characteristics and the transmission loss, including:

[0094] Obtaining a phase offset of the first path, and determining a transmission characteristic of the phase offset;

[0095] Determining an overall transmission characteristic according to an initial transmission characteristic of the first path and a transmission characteristic of the phase offset;

[0096] Determine the transmission loss of the phase offset;

[0097] determining a total transmission loss according to an initial transmission loss of the first path and a transmission loss of the phase offset;

[0098] A scheduling function of the first path is generated based on the total transmission characteristic and the total transmission loss.

[0099] The phase offset represents the phase change of the signal due to various factors (such as propagation, interference or system non-ideality), and the phase offset may affect the modulation and demodulation process of the signal. Therefore, in the cloud computing and communication system embodiments of the present application, the phase offset needs to be corrected to ensure accurate transmission and reception of the signal.

[0100] In the propagation environment, the signal will reach the receiving end through multiple paths. Each path may have different attenuation and delay when transmitting different data at different times. Therefore, the initial transmission characteristics of the path may include the transmission characteristics of the path in the initial state; the initial transmission loss of the path is the transmission loss of the path in the initial state.

[0101] For example, the initial transmission characteristics may include basic channel characteristics that describe the path in an initial state, such as bandwidth, delay, jitter error rate, signal-to-noise ratio, and the like.

[0102] For example, the initial transmission loss may include a description of the loss of a signal or data transmitted by the path in an initial state, such as signal attenuation, interference loss, phase shift loss, packet loss rate, and the like.

[0103] There are many ways to obtain initial transmission characteristics and initial transmission losses, for example, they can be obtained through database reading, real-time traffic detection, active testing, historical data analysis, etc.

[0104] In some embodiments, the total transmission characteristic may be the square of the sum of the initial transmission characteristic of the first path and the transmission characteristic of the phase offset; in some embodiments, the total transmission loss may be the square of the sum of the initial transmission loss of the first path and the transmission loss of the phase offset.

[0105] In some embodiments, the scheduling function can also be combined with the frequency modulation parameter to modulate the signal. For example, the scheduling function f(s) can be:

[0106] f(s)=Q{[C(v 1 )+C(v 2 )] 2 +[U(v 1 )+U(v 2 )] 2}

[0107] Among them, v 1 is the phase shift, v 2is the initial transmission characteristic of the first path, Q is the amplitude-frequency parameter used to adjust the amplitude and frequency of the signal; C() is used to calculate the transmission characteristic, and U() is used to calculate the transmission loss.

[0108] The scheduling function f(s) mainly focuses on the transmission characteristics C() and transmission loss U(), and combines the frequency-amplitude parameter Q to optimize signal scheduling and resource allocation.

[0109] The amplitude-frequency parameter refers to a parameter describing the amplitude response of a system or signal at different frequencies in the field of signal processing and communication. In some embodiments, the amplitude-frequency parameter includes amplitude and frequency.

[0110] Therefore, in some embodiments, based on the total transmission characteristics and the total transmission loss, a scheduling function of the first path is generated, including:

[0111] The sum of the total transmission characteristics and the total transmission loss is weighted based on the amplitude-frequency parameters of the task scheduling signal to obtain the scheduling function of the first path.

[0112] In some embodiments, the amplitude-frequency values ​​in the adjustment function can be manually or dynamically adjusted. For example, based on the scheduling function, the amplitude-frequency of the task scheduling signal in the path is adjusted, including numerically adjusting the amplitude-frequency parameters in the scheduling function, thereby achieving amplitude-frequency adjustment of the task scheduling signal in each path.

[0113] For example, manual adjustments can help the team quickly verify the effectiveness of the scheduling function, find the most appropriate parameter configuration, and speed up the debugging and optimization process; for example, manual adjustments can select the optimal amplitude and frequency settings based on historical data and experience, thereby improving the overall performance of task scheduling, reducing latency, and increasing throughput.

[0114] In some embodiments, the frequency-amplitude parameter Q can be determined by the amplitude A and the frequency modulation slope. For example, the amplitude-frequency parameter includes amplitude and frequency. The amplitude-frequency parameter in the scheduling function is numerically adjusted, including numerically adjusting the amplitude in the scheduling function and numerically adjusting the frequency in the scheduling function.

[0115] For example, in some embodiments, the amplitude-frequency parameter is the product of the square root of one times the frequency and the amplitude.

[0116]

[0117] Where A is the amplitude of the task scheduling signal, and p is the frequency modulation slope, which is the rate at which the frequency changes over time in frequency modulation (FM). During the scheduling process, the frequency modulation slope indicates the degree of change in the signal frequency, which affects the bandwidth and modulation method of the signal.

[0118] Similar to the scheduling function f(s) mentioned above, v1 is the phase offset, v2 is the initial transmission characteristic of the first path, Q is the amplitude-frequency parameter, which is used to adjust the amplitude and frequency of the signal; function C() is used to calculate the transmission characteristics, and function U() is used to calculate the transmission loss.

[0119] The frequency modulation slope p can affect the frequency change in the scheduling process, so the scheduling function f(s) also involves the optimization of frequency modulation scheduling to balance the frequency characteristics and transmission effect of the signal. Therefore, the scheduling function f(s) is a scheduling function based on transmission loss and signal quality optimization, and also involves frequency modulation scheduling, which optimizes the scheduling of cloud tasks by comprehensively considering transmission characteristics, transmission loss, frequency modulation slope and signal amplitude to improve signal quality and resource utilization efficiency in network communication.

[0120] 103. Based on the scheduling function of the first path, adjust the amplitude and frequency of the task scheduling signal in the first path.

[0121] In the transmission scenario, the amplitude and frequency of the task scheduling signal in each path can be adjusted to optimize based on the scheduling function. By adjusting the scheduling function, the amplitude and frequency characteristics of the signal can be optimized to improve the transmission effect and reduce interference and loss.

[0122] For example, based on step 102, it can be known that the amplitude A, the frequency modulation slope p, the transmission characteristics C() and the transmission loss U() of the correction signal can be adjusted first, and the optimized amplitude and frequency modulation slope can be applied to the task scheduling signal on each corresponding path, thereby reducing transmission loss and interference and improving the overall performance of the system.

[0123] In some embodiments, the amplitude and frequency in the scheduling function can be numerically adjusted to obtain an adjusted scheduling function of the first path; the amplitude and frequency of the task scheduling signal in the first path can be adjusted according to the adjusted scheduling function of the first path, thereby implementing step 103.

[0124] In some embodiments, the above scheduling function may be executed in combination with SDN (Software Defined Network) modulation and settlement technology to perform cross-equalization attenuation, dynamic allocation and scheduling, and suppress inter-symbol interference.

[0125] For example, the SDN controller can centrally control and dynamically adjust the network configuration to optimize network resource allocation and task scheduling. The SDN controller can be used to apply the optimized parameters to task scheduling, and the network configuration in the SDN controller can be adjusted to achieve the optimization effect. The network status can be obtained in real time and the scheduling strategy can be adjusted to meet the task requirements.

[0126] In order to better implement the above method, the present application embodiment provides a channel equalization method, referring to Figure 2,This method can optimize the scheduling of a large number of cloud tasks, obtain the propagation loss of cloud task transmission scheduling through feedback equalization control of network communication transmission channels, remove phase offset, suppress inter-code interference, and improve the stability of cloud task scheduling transmission. It is of great significance in improving the transmission accuracy of network communication and reducing output bit errors and distortion. At the same time, a suitable feature subset is selected through the feature selection algorithm to establish a mapping subspace. Through vector comparison analysis, anomaly detection of traffic characteristics can be performed, which can timely detect network attacks and illegal access behaviors, thereby protecting the security of network communications. By adjusting the data transmission order and selectively sorting the switches according to the information arrival rate, the best allocation path is found, channel balance is achieved, and network communication efficiency and network operation quality are guaranteed.

[0127] 201. Global network resource control.

[0128] Global network resource control can optimize network performance and improve resource utilization through centralized control and network view management in the context of cloud computing and SDN.

[0129] For example, through the cloud computing platform, the SDN controller obtains a global view of the entire network, including real-time status information of all network devices and links. The controller performs global traffic analysis, path calculation, and policy formulation based on this information.

[0130] For example, in some embodiments, the steps of implementing global network resource control include:

[0131] 1. Data collection and global view construction:

[0132] For example, integrate the status information of network devices and links to build network topology.

[0133] In some embodiments, the SDN controller can communicate with network devices (such as switches, routers, channel equalizers, etc.) and use network monitoring tools and protocols (such as NetFlow, sFlow, SNMP, etc.) to collect real-time status information of the network, such as link utilization, traffic channels, network topology, device status, etc.

[0134] In some embodiments, the network topology can be automatically discovered based on the SDN controller using protocols (such as OpenFlow, LLDP, etc.) to build a complete network view. Among them, the data collected from different network devices and links can be integrated to form a global view of the network, including the connection relationship between devices, traffic paths, latency and bandwidth, etc.

[0135] 2. Traffic analysis and prediction:

[0136] For example, analyzing real-time traffic data to predict future demand.

[0137] In some embodiments, traffic data can be analyzed to identify traffic patterns, bottlenecks, and hot spots, using analytical tools (such as traffic analyzers and data mining algorithms) to process and interpret the data, and evaluate link performance and network channels to identify potential performance issues and optimization opportunities.

[0138] In some embodiments, historical traffic data and forecasting algorithms (such as time series analysis, machine learning models, etc.) can be used to predict future traffic trends and demands, and based on the forecast results, the traffic allocation strategy can be dynamically adjusted to cope with changing demands.

[0139] 3. Path calculation and dynamic adjustment:

[0140] For example, optimizing data transmission paths and implementing channel equalization.

[0141] In some embodiments, a path calculation algorithm (such as Dijkstra algorithm, A* algorithm, etc.) can be used to determine the optimal data transmission path. These algorithms take into account network topology, link channels, and bandwidth limitations to achieve channel balancing of traffic, optimize path selection, and avoid network bottlenecks.

[0142] In some embodiments, the routing path can be dynamically adjusted to adapt to network changes based on the real-time network status; for example, the SDN controller is used to recalculate the route to avoid congested links and improve network performance.

[0143] 4. Strategy formulation and application:

[0144] For example, configure traffic engineering and security policies, and dynamically adjust network configurations.

[0145] In some embodiments, traffic engineering policies can be configured to optimize network performance, such as setting QoS (Quality of Service) policies to prioritize high-priority traffic, developing security policies, configuring access control, traffic filtering, and firewall rules, and protecting the network from attacks and abuse.

[0146] In some embodiments, the SDN controller can send the formulated policies and configurations to the network devices to adjust the network behavior, thereby adjusting the policies in real time according to the network status and business needs, for example, increasing bandwidth, adjusting traffic priority, etc.

[0147] 5. Feedback and optimization:

[0148] For example, continuously monitor performance and adjust policies to optimize network resource utilization.

[0149] In some embodiments, network performance can be continuously monitored, feedback data can be collected, the effectiveness of policies can be evaluated, and network performance indicators (such as latency, throughput, packet loss rate, etc.) can be analyzed to detect anomalies and performance issues.

[0150] In some embodiments, policies may be adjusted and optimized based on monitoring data and performance analysis results, and adaptive algorithms may be used to achieve automatic adjustment and optimization of network resources to cope with changing network conditions and demands.

[0151] Therefore, global network resource control enables the network to respond to dynamic demands efficiently and flexibly, improving overall network performance.

[0152] 202. Requirements collection and analysis.

[0153] In some embodiments, the SDN controller may receive requirements from the application plane through a northbound interface, including requirements for network traffic, bandwidth, latency, etc. The northbound interface (Northbound API) is an interface between the SDN controller and the application layer, and is used to receive and process requirements from the application layer.

[0154] 203. Standardized interfaces and protocols.

[0155] The cloud computing-based SDN network communication control method focuses on openness and interoperability. Based on standardized interfaces and protocols, devices from different manufacturers can be seamlessly integrated into the SDN network.

[0156] In some embodiments, standardized southbound and northbound interfaces may be used.

[0157] In some embodiments, the openness and interoperability of the system can be ensured based on standardized interfaces and protocols, such as OpenFlow, RESTful API, and NetConf, so that devices from different manufacturers can be seamlessly integrated into the SDN network to achieve unified network management and scheduling. At the same time, the SDN controller supports dynamic resource scheduling and elastic expansion through the integration of the cloud platform to meet the diverse needs of the modern cloud computing environment.

[0158] 204. Dynamic allocation and scheduling.

[0159] For example, refer to steps 101 to 105, which will not be described in detail here.

[0160] Therefore, it can be known that step 204 can solve the problem in cloud computing network communication that the scheduling has poor anti-interference ability due to the need to process and schedule a large number of processing tasks in the cloud and the influence of phase deviation and inter-symbol interference.

[0161] 205. Communication security testing.

[0162] In some embodiments, anomaly detection may be performed based on the transmission characteristics of the task scheduling signal. For example, the transmission process of the task scheduling signal may be reconstructed according to the conditions and distribution space of the transmission characteristics to facilitate further feature analysis and anomaly detection.

[0163] For example, in some embodiments, the reconstruction of the transmission process may be implemented by the following formula:

[0164]

[0165] Among them, y(t) is the part of the time series of the flow (i.e., the task scheduling signal) in the path at the tth moment, x is the vector of the flow matrix, k is the sampling frequency, It represents the sampling value at the tth moment, which is the traffic data after time scaling. h(t) is the response function, which characterizes the influencing factors in the network transmission process, including signal attenuation, noise, interference, etc. The response function h(t) is used to transform the task scheduling signal to obtain the high-dimensional characteristics of the traffic.

[0166] The y(t) sequence generated by this formula can be used for further traffic analysis, such as anomaly detection, pattern recognition, etc.

[0167] For example, high-dimensional spectral feature extraction can be performed on the y(t) sequence to help identify normal behavior and potential abnormal behavior of complex traffic. There are various methods for extracting high-dimensional spectral features. For example, high-dimensional feature extraction can be achieved using neural networks or other machine learning algorithms.

[0168] In some embodiments, the extracted high-dimensional features may be input into the traffic matrix X, and the traffic matrix X may be decomposed into a normal subspace and an abnormal subspace by principal component analysis (PCA) or other dimensionality reduction techniques, respectively. 1 and x 2 express.

[0169] Among them, the calculation formula of the traffic matrix X is:

[0170] x=x 1 +x 2

[0171] Among them, x 1 is the projection vector of x in the normal subspace, x 2 is the projection vector of x in the abnormal subspace.

[0172] In some embodiments, the vector x may be measured to determine whether there is an abnormal flow condition, for example, by calculating x 1 and x 2 If the difference between 1and x 2 If there is a difference, it means that there is a traffic anomaly at this time, which may indicate a security threat or network attack.

[0173] In some embodiments, any vector x in the traffic matrix X that does not conform to the normal behavior pattern will have a significant mapping in the abnormal subspace s. Therefore, this scheme can effectively detect and identify complex attack patterns such as DDoS attacks, packet loss or tampering, etc.

[0174] Therefore, it can be seen that through step 205, communication security detection can be performed on network traffic anomalies, which can significantly improve the security of the network and ensure the safe transmission of tasks and data, thereby solving the problem of network communication failures caused by network attacks and illegal access under the influence of the diversification and complexity of data types.

[0175] 206. Channel equalization.

[0176] In some embodiments, channel equalization may be achieved by adjusting the data transmission order.

[0177] For example, in some embodiments, data with large amounts of information can be transmitted first to ensure that important data arrives first; data containing less information or invalid information can be deleted or transmitted later, thereby effectively utilizing the bandwidth of the communication channel and avoiding unnecessary data occupying channel resources.

[0178] In some embodiments, the traffic of the routers may be monitored and initialized to ensure that all interface parameters and masks are correctly configured so that the traffic can be evenly distributed among different routers.

[0179] In some embodiments, a signal processing formula may be introduced to adjust the data transmission order to achieve channel equalization:

[0180]

[0181] Among them, A(S) is the operation cycle of channel scheduling, and S is the parameter of data operation, which reflects the state of the signal during transmission. 0 (S) / V 1 (S) can determine the relationship between the input and output voltages, which is also related to the resistance R 1 and R 2 This further affects the transmission efficiency of the signal.

[0182] Where f(A) is the operating frequency of the task scheduling signal, which is affected by the input voltage V 1 and resistor R 1 The frequency of the task scheduling signal is determined by the physical characteristics of the circuit.

[0183] Among them, A H Indicates the controller's control capability over network communication, which is determined by the signal frequency f. As the frequency increases, the control capability A H Will decrease.

[0184] After adjusting the data transmission order, the information arrival rate calculated by the above formula can be used to determine how to selectively sort the switches, thereby achieving channel balance in the network.

[0185] For example, in some embodiments, when initializing channel parameters, the channel operation period is determined using formula A(S), and the signal frequency is determined using formula f(A). H To adjust the control capabilities of the server.

[0186] Therefore, it can be seen that step 206 can ensure that key data is transmitted first, while avoiding excessive channel occupancy, and solving the problem that diverse network information types are prone to channel imbalance and low communication efficiency in large-scale network data.

[0187] In summary, the embodiments of the present application optimize the scheduling of a large number of cloud tasks, obtain the propagation loss of cloud task transmission scheduling through feedback equalization control of the network communication transmission channel, and remove the phase offset, thereby suppressing the inter-code interference in the transmission process and improving the stability of cloud task scheduling transmission. At the same time, through the abnormal detection of traffic characteristics, network attacks and illegal access behaviors can be discovered in time, thereby protecting the security of network communications. By adjusting the data transmission order and selectively sorting the switches according to the information arrival rate, channel balance is achieved and network communication efficiency is guaranteed.

[0188] In order to better implement the above method, the embodiment of the present application also provides a channel equalization device, which can be integrated in a computer device, and the computer device can be a terminal, a server, etc. Among them, the terminal can be a mobile phone, a tablet computer, a smart Bluetooth device, a laptop, a personal computer, etc.; the server can be a single server or a server cluster composed of multiple servers.

[0189] For example, in this embodiment, the method of the embodiment of the present application is described in detail by taking the channel equalization device being specifically integrated in the server as an example.

[0190] For example, Figure 3 As shown, the channel equalization device may include a loss unit 301, a function unit 302, and an adjustment unit 303, as follows:

[0191] (i) Loss unit 301.

[0192] The loss unit 301 is used to determine the transmission loss of the task scheduling signal in the second path based on the transmission loss of the task scheduling signal in the first path, and the task scheduling signal is transmitted in multiple paths.

[0193] The first path and the second path are two different paths among the multiple paths.

[0194] In some embodiments, the method further includes a first acquisition subunit and a second acquisition subunit, wherein:

[0195] The first acquisition subunit is used to acquire the transmission characteristics of the task scheduling signal, where the transmission characteristics include the transmission characteristics of the task scheduling signal on each path;

[0196] The second acquisition subunit is used to acquire the transmission loss of the task scheduling signal in the first path.

[0197] In some embodiments, the loss unit 301 is further configured to:

[0198] Obtain the transmission characteristics of the task scheduling signal in each path;

[0199] Obtain the phase modulation index of each path;

[0200] The phase modulation function of each path is accumulated to obtain the transmission characteristics of the task scheduling signal. The phase modulation function is the product of the complex exponential of the path and the transmission characteristics of the task scheduling signal in the path.

[0201] In some embodiments, the loss unit 301 includes an acquisition subunit, a correction term subunit, and a correction subunit:

[0202] The acquisition subunit is used to acquire the symbol rate, the first transmission delay and the second transmission delay of the task scheduling signal;

[0203] The correction item subunit is used to determine the correction item according to the symbol rate, the first transmission delay and the second transmission delay;

[0204] The correction subunit is used to perform correction processing on the transmission loss of the first path based on the correction item to obtain the transmission loss of the task scheduling signal on the second path.

[0205] In some embodiments, the correction term subunit includes a vector submodule, a scalar submodule, and a combination submodule:

[0206] 1. Vector submodule.

[0207] The vector submodule is used to construct a symbol-delay feature according to the symbol rate and the first transmission delay.

[0208] 2. Scalar submodule.

[0209] The vector submodule is used to determine the Dirac function according to the first transmission delay and the second transmission delay.

[0210] In some embodiments, a scalar submodule is used to:

[0211] determining a delay difference between a first transmission delay and a second transmission delay;

[0212] If the delay difference is equal to 0, the value of the Dirac function is the first preset value;

[0213] If the delay difference is not equal to 0, the value of the Dirac function is the second preset value.

[0214] 3. Combine sub-modules.

[0215] The vector submodule is used to determine the correction term based on the symbol-delay characteristics and the Diktral function.

[0216] (ii) Function unit 304.

[0217] The function unit 304 is used to generate a scheduling function of the first path based on the transmission characteristics of the task scheduling information and the transmission loss of the second path.

[0218] The transmission characteristics include characteristics that characterize the transmission performance of the task scheduling signal in each path.

[0219] In some embodiments, the function unit 304 includes a feature subunit, a total feature subunit, a loss subunit, a total loss subunit, and a function subunit:

[0220] The characteristic subunit is used to obtain the phase offset of the first path and determine the transmission characteristics of the phase offset;

[0221] The total characteristic subunit is used to determine the total transmission characteristic according to the initial transmission characteristic of the first path and the transmission characteristic of the phase offset;

[0222] The loss subunit is used to determine the transmission loss of the phase offset;

[0223] The total loss subunit is used to determine the total transmission loss according to the initial transmission loss of the first path and the transmission loss of the phase offset;

[0224] The function subunit is used to generate a scheduling function of the first path based on the total transmission characteristics and the total transmission loss.

[0225] In some embodiments, the function subunit is used to weight the sum of the total transmission characteristics and the total transmission loss based on the amplitude-frequency parameters of the task scheduling signal to obtain the scheduling function of the first path.

[0226] In some embodiments, the adjustment unit is used to obtain an adjusted scheduling function of the first path by numerically adjusting the amplitude and frequency in the scheduling function; and adjust the amplitude and frequency of the task scheduling signal in the first path according to the adjusted scheduling function of the first path.

[0227] In some embodiments, the amplitude-frequency parameter is the product of the square root of one times the frequency and the amplitude.

[0228] In specific implementation, the above units can be implemented as independent entities, or can be arbitrarily combined to be implemented as the same or several entities. The specific implementation of the above units can refer to the previous method embodiments, which will not be repeated here.

[0229] The present application also provides a computer program product, including a computer program, which is loaded by a processor to execute any of the above-mentioned channel equalization methods.

[0230] For example, in the embodiments of the present application, the term "module" or "unit" refers to a computer program or a part of a computer program with a predetermined function, and works together with other related parts to achieve a predetermined goal, and can be implemented in whole or in part by using software, hardware (such as processing circuits or memories), or a combination thereof. Similarly, a processor (or multiple processors or memories) can be used to implement one or more modules or units. In addition, each module or unit can be part of an overall module or unit that includes the function of the module or unit.

[0231] As can be seen from the above, the channel equalization device of this embodiment obtains the transmission characteristics of the task scheduling signal by the characteristic unit, and the transmission characteristics include the transmission characteristics of the task scheduling signal in each path; the first loss unit obtains the transmission loss of the task scheduling signal in the first path, and the transmission loss of the first path includes the initial transmission loss of the first path; the second loss unit determines the transmission loss of the task scheduling signal in the second path based on the transmission loss of the first path; the function unit generates a scheduling function based on the transmission characteristics and the transmission loss, and the transmission loss includes the transmission loss of the task scheduling signal in each path; the adjustment unit adjusts the amplitude and frequency of the task scheduling signal in the path based on the scheduling function.

[0232] Therefore, the embodiments of the present application can achieve channel equalization, thereby improving communication efficiency.

[0233] The embodiment of the present application also provides a computer device, which may be a terminal, a server, etc. The terminal may be a mobile phone, a tablet computer, a smart Bluetooth device, a laptop computer, a personal computer, etc. The server may be a single server or a server cluster composed of multiple servers, etc.

[0234] In some embodiments, the channel balancing device may also be integrated into multiple computer devices. For example, the channel balancing device may be integrated into multiple servers, and the channel balancing method of the present application may be implemented by multiple servers.

[0235] In this embodiment, the computer device of this embodiment is a server as an example for detailed description. Figure 4 As shown, it shows a schematic diagram of the structure of the computer device involved in the embodiment of the present application, specifically:

[0236] The computer device may include one or more processing core processors 401, one or more computer-readable storage media memories 402, a power supply 403, an input module 404, and a communication module 405. Those skilled in the art will appreciate that Figure 4 The computer device structure shown in the figure does not constitute a limitation on the computer device, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently. Among them:

[0237] The processor 401 is the control center of the computer device. It uses various interfaces and lines to connect various parts of the entire computer device. By running or executing software programs and / or modules stored in the memory 402 and calling data stored in the memory 402, it executes various functions of the computer device and processes data, thereby performing overall detection of the computer device. In some embodiments, the processor 401 may include one or more processing cores; in some embodiments, the processor 401 may integrate an application processor and a modem processor, wherein the application processor mainly processes the operating system, user interface, and application programs, and the modem processor mainly processes wireless communications. It is understandable that the above-mentioned modem processor may not be integrated into the processor 401.

[0238] The memory 402 can be used to store software programs and modules. The processor 401 executes various functional applications and data processing by running the software programs and modules stored in the memory 402. The memory 402 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area may store data created according to the use of the computer device, etc. In addition, the memory 402 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage devices. Accordingly, the memory 402 may also include a memory controller to provide the processor 401 with access to the memory 402.

[0239] The computer device also includes a power supply 403 for supplying power to various components. In some embodiments, the power supply 403 can be logically connected to the processor 401 through a power management system, so that the power management system can manage charging, discharging, power consumption, etc. The power supply 403 can also include any components such as one or more DC or AC power supplies, recharging systems, power failure detection circuits, power converters or inverters, and power status indicators.

[0240] The computer device may further include an input module 404, which may be used to receive input digital or character information and generate keyboard, mouse, joystick, optical or trackball signal input related to user settings and function control.

[0241] The computer device may further include a communication module 405. In some embodiments, the communication module 405 may include a wireless module. The computer device may perform short-range wireless transmission through the wireless module of the communication module 405, thereby providing the user with wireless broadband Internet access. For example, the communication module 405 may be used to help the user send and receive emails, browse web pages, and access streaming media.

[0242] Although not shown, the computer device may further include a display unit, etc., which will not be described in detail herein. Specifically in this embodiment, the processor 401 in the computer device will load the executable files corresponding to the processes of one or more application programs into the memory 402 according to the following instructions, and the processor 401 will run the application programs stored in the memory 402, thereby realizing various functions, as follows:

[0243] Determining a transmission loss of the task scheduling signal on the second path based on a transmission loss of the task scheduling signal on the first path;

[0244] generating a scheduling function for the first path based on the transmission characteristics of the task scheduling information and the transmission loss of the second path;

[0245] Based on the scheduling function of the first path, the amplitude and frequency of the task scheduling signal in the first path are adjusted.

[0246] The specific implementation of the above operations can be found in the previous embodiments, which will not be described in detail here.

[0247] It can be seen from the above that the embodiments of the present application can improve communication efficiency.

[0248] A person of ordinary skill in the art will appreciate that all or part of the steps in the various methods of the above embodiments may be completed by instructions, or by controlling related hardware through instructions. The instructions may be stored in a computer-readable storage medium and loaded and executed by a processor.

[0249] To this end, an embodiment of the present application provides a computer-readable storage medium, in which a plurality of instructions are stored, and the instructions can be loaded by a processor to execute the steps in any channel equalization method provided in the embodiment of the present application. For example, the instructions can execute the following steps:

[0250] Determining a transmission loss of the task scheduling signal on the second path based on a transmission loss of the task scheduling signal on the first path;

[0251] generating a scheduling function for the first path based on the transmission characteristics of the task scheduling information and the transmission loss of the second path;

[0252] Based on the scheduling function of the first path, the amplitude and frequency of the task scheduling signal in the first path are adjusted.

[0253] The storage medium may include: a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0254] According to one aspect of the present application, a computer program product or a computer program is provided, the computer program product or the computer program including computer instructions, the computer instructions being stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the method provided in various optional implementations of the task scheduling aspect or the channel equalization aspect provided in the above embodiments.

[0255] Since the instructions stored in the storage medium can execute the steps in any channel equalization method provided in the embodiments of the present application, the beneficial effects that can be achieved by any channel equalization method provided in the embodiments of the present application can be achieved. Please refer to the previous embodiments for details and will not be repeated here.

[0256] The above is a detailed introduction to a channel equalization method, device, computer equipment and computer-readable storage medium provided in an embodiment of the present application. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea; at the same time, for technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A channel equalization method, characterized in that: include: Determining a transmission loss of the task scheduling signal on the second path based on a transmission loss of the task scheduling signal on the first path; generating a scheduling function of the first path based on the transmission characteristics of the task scheduling information and the transmission loss of the second path; Based on the scheduling function of the first path, the amplitude and frequency of the task scheduling signal in the first path are adjusted.

2. The channel equalization method according to claim 1, characterized in that: Determining the transmission loss of the task scheduling signal on the second path based on the transmission loss of the task scheduling signal on the first path includes: Acquire a symbol rate, a first transmission delay, and a second transmission delay of the task scheduling signal; Determining a correction term according to the symbol rate, the first transmission delay, and the second transmission delay; The transmission loss of the first path is corrected based on the correction item to obtain the transmission loss of the task scheduling signal on the second path.

3. The channel equalization method according to claim 2, characterized in that: The determining of the correction term according to the symbol rate, the first transmission delay and the second transmission delay comprises: constructing a symbol-delay characteristic based on the symbol rate and the first transmission delay; Determining a Dicket function according to the first transmission delay and the second transmission delay; A correction term is determined based on the symbol-delay characteristic and the Dirkat function.

4. The channel equalization method according to claim 3, characterized in that: The determining of the Dirkat function according to the first transmission delay and the second transmission delay includes: determining a delay difference between the first transmission delay and the second transmission delay; If the delay difference is equal to 0, the value of the Dirkat function is the first preset value; If the delay difference is not equal to 0, the value of the Diktonic function is a second preset value.

5. The channel equalization method according to claim 1, characterized in that: Generating a scheduling function of the first path based on the transmission characteristics of the task scheduling information and the transmission loss of the second path, including: Acquire a phase offset of the first path, and determine a transmission characteristic of the phase offset; determining an overall transmission characteristic according to an initial transmission characteristic of the first path and a transmission characteristic of the phase offset; determining a transmission loss of the phase offset; determining a total transmission loss according to an initial transmission loss of the first path and a transmission loss of the phase offset; A scheduling function of the first path is generated based on the total transmission characteristic and the total transmission loss.

6. The channel equalization method according to claim 5, characterized in that: The generating the scheduling function of the first path based on the total transmission characteristic and the total transmission loss comprises: The sum of the total transmission characteristic and the total transmission loss is weighted based on the amplitude-frequency parameters of the task scheduling signal to obtain the scheduling function of the first path.

7. The channel equalization method according to claim 6, characterized in that: The amplitude-frequency parameters include amplitude and frequency, and the scheduling function based on the first path adjusts the amplitude and frequency of the task scheduling signal in the first path, including: By numerically adjusting the amplitude and frequency in the scheduling function, an adjusted scheduling function of the first path is obtained; The amplitude and frequency of the task scheduling signal in the first path are adjusted according to the adjusted scheduling function of the first path.

8. The channel equalization method according to claim 1, characterized in that: The method further comprises: obtaining a transmission characteristic of the task scheduling signal in each path; Obtaining a phase modulation index of each of the paths; The phase modulation function of each path is accumulated to obtain the transmission characteristics of the task scheduling signal, wherein the phase modulation function is the product of the complex exponential of the path and the transmission characteristics of the task scheduling signal in the path.

9. A channel equalization device, characterized in that: include: a loss unit, configured to determine a transmission loss of the task scheduling signal on the second path based on a transmission loss of the task scheduling signal on the first path; a function unit, configured to generate a scheduling function of the first path based on the transmission characteristics of the task scheduling information and the transmission loss of the second path; An adjustment unit is used to adjust the amplitude and frequency of the task scheduling signal in the first path based on the scheduling function of the first path.

10. A computer device, characterized in that: The invention comprises a processor and a memory, wherein the memory stores a plurality of instructions; the processor loads instructions from the memory to execute the steps in the channel equalization method according to any one of claims 1 to 8.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a plurality of instructions, and the instructions are suitable for being loaded by a processor to execute the steps in the channel equalization method according to any one of claims 1 to 8.

12. A computer program product, comprising a computer program, wherein the computer program is loaded by a processor to execute the steps in the channel equalization method according to any one of claims 1 to 8.

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