A high-reliability cross-layer transmission method fusing perception requirements and link states

Abstract

This invention provides a highly reliable cross-layer transmission method that integrates sensing requirements and link status, belonging to the field of wireless communication technology. The transmission method includes: collecting multi-source information data of the current scheduling cycle of the power system to obtain data packets to be transmitted; constructing a sensing requirement vector for the data packets to be transmitted; obtaining a comprehensive priority value based on the sensing requirement vector and obtaining a link risk assessment value of the current wireless channel to generate a scheduling constraint parameter set; constructing an OFDM candidate resource set and selecting a target resource block from the OFDM candidate resource set according to the scheduling constraint parameter set; mapping the data packets to be transmitted to the target resource block and performing HARQ adaptive control to determine the transmission strategy of the data packets to be transmitted; sending the data packets to be transmitted according to the transmission strategy and recording the transmission status and feedback information from the receiving end. This invention can achieve highly reliable, low-latency, and stable transmission of critical services in complex wireless environments, improving the stability of the control closed loop and resource utilization efficiency.

Description

Technical Field

[0001] This invention relates to the field of wireless communication technology, and more specifically to a highly reliable cross-layer transmission method that integrates sensing requirements and link status. Background Technology

[0002] With the rapid development of new power systems, the increasing demand for large-scale new energy access, widespread deployment of distributed energy, and efficient interaction between power generation, grid, load, and storage, the power system faces unprecedentedly stringent requirements for real-time, accurate data sensing and reliable, low-latency communication transmission. Traditional sensing layer communication networks, primarily focused on data acquisition, are no longer sufficient to meet the diverse demands for bandwidth, real-time performance, reliability, and security from new services such as low-voltage side monitoring and control in distribution networks and rapid power group control of distributed new energy sources.

[0003] In typical application scenarios of the power Internet of Things (IoT), transmission lines face complex environmental threats such as icing, galloping, wildfires, and geological disasters; distribution links need to support high-frequency data acquisition and low-latency interactive control; and substations need to achieve real-time status monitoring of core equipment such as transformers and switchgear. These scenarios place stringent multi-dimensional demands on the resource scheduling of wireless communication systems: they need to dynamically adapt to the differentiated quality of service requirements of different service categories (such as critical status quantities and control commands) under limited bandwidth and power constraints, while coping with the harsh transmission environment of power line channels, which are susceptible to multipath, attenuation, time-varying, and frequency selection effects. Existing power IoT communication technologies suffer from high packet loss, unstable transmission, large latency jitter, and retransmission mismatch in complex wireless environments for critical status quantities and control commands. Summary of the Invention

[0004] The purpose of this invention is to provide a highly reliable cross-layer transmission method that integrates sensing requirements and link status, enabling highly reliable, low-latency, and stable transmission of critical services in complex wireless environments, and improving the stability of the control closed loop and the efficiency of resource utilization.

[0005] To achieve the above objectives, embodiments of the present invention provide a highly reliable cross-layer transmission method that integrates sensing requirements and link status, the transmission method comprising: Collect multi-source information data of the power system during the current dispatch cycle and obtain data packets to be transmitted; Construct the perception demand vector of the data packet to be transmitted; Based on the perceived demand vector, a comprehensive priority value is obtained, and the link risk assessment value of the current wireless channel is obtained to generate a set of scheduling constraint parameters; Construct an OFDM candidate resource set, and select a target resource block from the OFDM candidate resource set according to the scheduling constraint parameter set; The data packet to be transmitted is mapped to the target resource block, and HARQ adaptive control is performed to determine the transmission strategy of the data packet to be transmitted; The data packet to be transmitted is sent according to the transmission strategy, and the transmission status and feedback information from the receiving end are recorded.

[0006] Optionally, the transmission method further includes: Construct a Lyapunov drift penalty function that includes delay default constraints, reliability default constraints, and resource cost constraints, and construct an optimization objective for the drift penalty; Based on the drift penalty optimization objective function, obtain the optimal transmission strategy for the current scheduling period; The control closed-loop performance value of the transmitted data packet is obtained based on the feedback information. The multi-source information data, OFDM resource mapping parameters, and HARQ adaptive control parameters are updated based on the optimal transmission strategy and the control closed-loop performance value.

[0007] Optionally, a comprehensive priority value is obtained based on the perceived demand vector, and a link risk assessment value for the current wireless channel is obtained to generate a scheduling constraint parameter set, including: The comprehensive priority value of the perceived demand vector is obtained according to formula (1). (1) in, This is a comprehensive priority value. These are the weighting coefficients. To prevent tiny constants with a denominator of 0, Based on business importance, For the remaining time limit, For reliability requirements, To meet latency requirements, To meet the requirements of data freshness, To control risk values, For the data packet to be transmitted, This is the current scheduling period; The link risk assessment value of the current wireless channel is obtained according to formula (2). (2) in, This is the link risk assessment value. For channel quality indicators, Historical NACK rate For interference intensity indicators, These are the weighting coefficients; A set of scheduling constraint parameters is generated based on the comprehensive priority value and the link risk assessment value.

[0008] Optionally, an OFDM candidate resource set is constructed, and a target resource block is selected from the OFDM candidate resource set according to the scheduling constraint parameter set, including: Based on the current wireless channel status information, obtain the instantaneous link quality value of the candidate resource block in formula (3). (3) in, Candidate resource blocks Instantaneous link quality value, Candidate resource blocks Signal-to-interference-to-noise ratio, This is the estimated block error rate for the candidate resource block. The level of interference experienced by this candidate resource block. These are the weighting coefficients. For resource block index, For time slot index; Construct a resource selection utility function based on formula (4). (4) in, Choose a utility function for the resource. To map services to time slots The introduced queuing delay, In modulation and coding scheme and transmission power The resource cost function under, These are the weighting coefficients. It is a modulation coding method. This refers to the transmission power. Construct the target resource mapping function according to formula (5). (5) in, For the target resource mapping result, For at any time The set of candidate resources For parameter optimization operators, it means that in the current scheduling period Within the candidate resource set, a joint search is performed on the resource block index, time slot index, modulation and coding scheme, and transmit power to select the parameter combination that maximizes the resource selection utility function.

[0009] Optionally, the data packet to be transmitted is mapped to the target resource block, and HARQ adaptive control is performed to determine the transmission strategy of the data packet to be transmitted, including: The data packets to be transmitted are divided into critical status quantity data packets and control instruction data packets; Perform freshness-first mapping on critical state quantity data packets; The freshness-driven value of the key state quantity data packet is obtained according to formula (6). (6) in, For the first Key state variable data packets in the current scheduling period Freshness-driven value For the first Key state variable data packets in the current scheduling period The state estimation error, The maximum allowed age threshold for information. These are the weighting coefficients. For the first Key state variable data packets in the current scheduling period The information age is used to characterize the freshness of data; Prioritize mapping of control command data packets based on their deadlines; The number of redundant copies of the control command data packet is obtained according to formula (7). (7) in, For the first A control instruction data packet in the current scheduling period The number of redundant replicas, The maximum number of redundant replicas, These are the weighting coefficients. This is the minimum value operator. To control the remaining time limit of the instruction data packet.

[0010] Optionally, the data packet to be transmitted is mapped to the target resource block, and HARQ adaptive control is performed to determine the transmission strategy of the data packet to be transmitted, including: The maximum number of retransmissions of the data packet to be transmitted is obtained according to formula (8). (8) in, This is the maximum number of retransmissions allowed by HARQ. This represents the maximum number of retransmissions for the data packet to be transmitted. These are the weighting coefficients; According to formula (9), the first... The cumulative success rate after round transmission (9) in, For the first The cumulative success rate after round transmission For the first The success rate of a single round of round transmission; The joint decision value is obtained according to formula (10). (10) in, For joint decision value, The optimal resource mapping utility value, To estimate the probability of success, To estimate the total transmission delay, To predict resource consumption, These are the weighting coefficients; A mode selection function is constructed based on the joint decision value to determine the transmission strategy.

[0011] Optionally, a Lyapunov drift penalty function is constructed, which includes delay default constraints, reliability default constraints, and resource cost constraints. The drift penalty optimization objective is also constructed, including: Based on formula (11), establish a virtual queue for delay default, a virtual queue for reliability default, and a virtual queue for resource cost. (11) in, This is the current virtual queue for delay defaults. This is a virtual queue for current reliability failures. This is a virtual queue representing the current resource cost. For the next time delay default virtual queue, For the next moment, a virtual queue for reliability defaults. A virtual queue for resource costs in the next time step. As a time delay threshold, For packet loss threshold, As a resource budget threshold, For the current scheduling period The actual end-to-end transmission delay of the data packets to be transmitted. For the current scheduling period The packet loss rate of the data packets to be transmitted. For the current scheduling period Resource consumption within; Construct the Lyapunov drift penalty function according to formula (12). (12) in, This is the Lyapunov drift penalty function; Based on formula (13), construct the drift penalty optimization objective. (13) in, This is the Lyapunov drift amount. It is a combination function of immediate performance loss and resource cost. To weigh the parameters.

[0012] Optionally, the optimal transmission strategy for the current scheduling period is obtained based on the drift penalty optimization objective function, including: The joint control variables at the current moment are obtained according to formula (14). (14) in, For the joint control variables of the current scheduling period, Indicates the first The resource mapping result of each data packet to be transmitted. Indicates the maximum number of retransmissions. Indicates the modulation and coding scheme. Indicates the transmission power. This represents the set of data packets to be sent within the current scheduling period; The joint optimization results are obtained according to formula (15). (15) in, To jointly optimize the results, This represents the set of feasible strategies at the current moment. To predict the amount of delay defaults, To predict reliability defaults, To predict resource costs, It is a combination function of immediate performance loss and resource consumption. To balance the parameters, This indicates that the constraints are met. Under the premise of minimizing the joint optimization result, select the joint control variable.

[0013] Optionally, obtaining the control closed-loop performance value of the transmitted data packet based on the feedback information includes: The control closed-loop performance value is obtained according to formula (16). (16) in, To control the closed-loop performance value, For state estimation error, To control deviation, For task execution error, As a stability margin indicator, These are the weighting coefficients.

[0014] Optionally, updating the multi-source information data, OFDM resource mapping parameters, and HARQ adaptive control parameters according to the optimal transmission strategy and the control closed-loop performance value includes: The control risk value is obtained according to formula (17). (17) in, The control risk value for the next scheduling cycle. These are the weighting coefficients; The transmission mode for the next scheduling cycle is determined according to formula (18). (18) in, Indicates a high-reliability protection mode. Indicates the balance mode. Indicates a resource-saving model. These are the mode switching thresholds for the latency default virtual queue, the reliability default virtual queue, and the resource cost virtual queue, respectively.

[0015] Through the above technical solution, this invention provides a highly reliable cross-layer transmission method that integrates sensing requirements and link status. It acquires multi-source information data from the current scheduling cycle of the power system to obtain data packets to be transmitted, constructs a sensing requirement vector for the data packets, obtains a comprehensive priority value based on the sensing requirement vector, and acquires the link risk assessment value of the current wireless channel to generate a scheduling constraint parameter set. An OFDM candidate resource set is then constructed. Based on the scheduling constraint parameter set, a target resource block is selected from the OFDM candidate resource set, the data packets to be transmitted are mapped to the target resource block, and HARQ adaptive control is executed to determine the transmission strategy for the data packets to be transmitted. The data packets are then sent according to the transmission strategy, and the transmission status and feedback information from the receiving end are recorded. The sensing requirement-driven sensing-communication cross-layer collaborative highly reliable transmission method proposed in this invention can jointly optimize OFDM resource mapping and HARQ adaptive control parameters in a dynamic wireless environment based on service importance, remaining time limit, reliability requirements, link risk, and control closed-loop feedback information. Compared with existing fixed transmission schemes and adaptive schemes lacking closed-loop feedback, the method of this invention can simultaneously improve the on-time successful delivery rate of critical services, reduce the average end-to-end latency, improve resource utilization efficiency, and enhance the stability of the control closed loop. Therefore, it has good practicality and application value.

[0016] Other features and advantages of the embodiments of the present invention will be described in detail in the following detailed description section. Attached Figure Description

[0017] The accompanying drawings are provided to further illustrate embodiments of the present invention and form part of the specification. They are used together with the following detailed description to explain the embodiments of the present invention, but do not constitute a limitation thereof. In the drawings: Figure 1 This is a flowchart of a perception-demand driven, perception-communication cross-layer collaborative high-reliability transmission method according to an embodiment of the present invention. Figure 2 This is a flowchart of updating multi-source information data, OFDM resource mapping parameters and HARQ adaptive control parameters according to an embodiment of the present invention; Figure 3 This is a comparison chart of the on-time successful delivery rate of key services under different signal-to-noise ratio conditions according to an embodiment of the present invention; Figure 4 This is a comparison chart of average end-to-end latency under different service load conditions according to an embodiment of the present invention; Figure 5 This is a comparison chart of resource efficiency under different service load conditions according to an embodiment of the present invention; Figure 6 This is a graph showing the change of closed-loop performance feedback index with scheduling cycle under high load scenario according to an embodiment of the present invention; Figure 7 This is a graph showing the change of the latency default virtual queue with scheduling cycle under a high-load scenario according to an embodiment of the present invention. Detailed Implementation

[0018] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit the scope of the present invention.

[0019] In the embodiments of this application, certain software, components, models and other existing solutions in the industry may be mentioned. These should be regarded as exemplary and are only intended to illustrate the feasibility of implementing the technical solution of this application. However, they do not mean that the applicant has used or necessarily used the solution.

[0020] Existing power IoT communication technologies suffer from high packet loss, unstable transmission, large latency jitter, and retransmission mismatch issues when transmitting critical state quantities and control commands in complex wireless environments. This invention provides a highly reliable cross-layer transmission method that integrates sensing requirements and link status. For example... Figure 1 The diagram shown is a flowchart of a perception-communication cross-layer collaborative high-reliability transmission method driven by perception requirements according to an embodiment of the present invention. Figure 1 In this context, the transmission method includes: In step S1, multi-source information data of the current dispatch cycle of the power system is collected to obtain the data packet to be transmitted; In step S2, a perception demand vector for the data packet to be transmitted is constructed; In step S3, the comprehensive priority value is obtained based on the sensing demand vector, and the link risk assessment value of the current wireless channel is obtained to generate a set of scheduling constraint parameters; In step S4, an OFDM candidate resource set is constructed, and a target resource block is selected from the OFDM candidate resource set according to the scheduling constraint parameter set; In step S5, the data packet to be transmitted is mapped to the target resource block, and HARQ adaptive control is performed to determine the transmission strategy of the data packet to be transmitted. In step S6, the data packet to be transmitted is sent according to the transmission strategy, and the transmission status and feedback information from the receiving end are recorded.

[0021] In Figure 1 In the method shown, step S1 can be used to collect multi-source information data of the current dispatch cycle of the power system to obtain the data packets to be transmitted. Specifically, at the transmitting end, receiving end, or edge control node, multi-source information related to wireless closed-loop control is collected, including key state quantity data, control command data, wireless channel state information, service queue state information, historical ACK / NACK feedback information, and control closed-loop performance feedback information. Key state quantity data is used to characterize the current state of the controlled object, control command data is used to drive the execution end action, and wireless channel state information includes at least one or more of channel quality indication, signal-to-noise ratio, block error rate estimate, and interference intensity. Control closed-loop performance feedback information includes at least one or more of state estimation error, control deviation, stability index, and task execution error. The data packets to be transmitted are obtained and divided into two categories: key state quantity data packets and control command data packets. Key state quantity data packets prioritize data freshness, continuous updates, and state observability, while control command data packets prioritize successful delivery probability and execution effectiveness within the deadline, thereby establishing a differentiated protection mechanism for different service semantics.

[0022] Step S2 can be used to construct the perception demand vector of the data packet to be transmitted. The specific method for constructing the perception demand vector can be of various forms known to those skilled in the art. In one example of the present invention, the perception demand vector can be constructed according to formula (19). (19) in, Based on business importance, For the remaining time limit, For reliability requirements, To meet latency requirements, To meet the requirements of data freshness, To control risk values.

[0023] Step S3 can be used to obtain a comprehensive priority value based on the sensing demand vector and to obtain the link risk assessment value of the current wireless channel, so as to generate a scheduling constraint parameter set. In one example of the present invention, the comprehensive priority value of the sensing demand vector is obtained according to formula (1). (1) in, This is a comprehensive priority value. These are the weighting coefficients. To prevent tiny constants with a denominator of 0, Based on business importance, For the remaining time limit, For reliability requirements, To meet latency requirements, To meet the requirements of data freshness, To control risk values, For the data packet to be transmitted, For the current scheduling period, when the data packet to be transmitted is a control command data packet, increase the priority. and The weight is increased when the data packet to be transmitted is a critical state quantity data packet. Weights are assigned to highlight the deadline constraint and the freshness constraint, respectively.

[0024] The link risk assessment value of the current wireless channel is obtained according to formula (2). (2) in, This is the link risk assessment value. For channel quality indicators, Historical NACK rate For interference intensity indicators, The weighting coefficients and link risk assessment values ​​characterize the transmission risk level of the current service in a complex wireless environment. A set of scheduling constraint parameters is generated based on the comprehensive priority value and the link risk assessment value, including reliability threshold, latency threshold, mapping redundancy level, retransmission priority, and resource occupancy limit. These parameters serve as inputs for subsequent OFDM resource dynamic mapping and HARQ adaptive control.

[0025] Step S4 can be used to construct an OFDM candidate resource set, and select a target resource block from the OFDM candidate resource set according to the scheduling constraint parameter set. In one embodiment of the present invention, an OFDM candidate resource set is first constructed based on the current available bandwidth, subcarrier occupancy status, time slot occupancy status, transmit power budget, and modulation and coding scheme set, and the current scheduling period is obtained according to formula (20). The set of candidate resources (20) in, For at any time The set of candidate resources Represents the resource block index. Indicates the time slot index. Indicates the modulation and coding scheme. Indicates the transmission power. This indicates a resource occupancy indicator variable, when a resource block... The value is 1 when the resource is occupied, and 0 when it is not occupied. Due to the maximum transmit power constraint, For the set of optional modulation and decoding methods, the candidate resource set is marked according to frequency domain position, time domain position, modulation coding level and power adjustable range, so as to facilitate subsequent resource screening and dynamic mapping.

[0026] Based on the current wireless channel status information, obtain the instantaneous link quality value of the candidate resource block in formula (3). (3) in, For resource blocks Instantaneous link quality value, For resource blocks Signal-to-interference-to-noise ratio, This is the estimated block error rate for the corresponding resource block. The intensity of the interference experienced by this resource block. These are the weighting coefficients. For resource block index, This serves as a time slot index. Candidate resource sets are labeled according to frequency domain location, time domain location, modulation and coding level, and adjustable power range for subsequent resource filtering and dynamic mapping.

[0027] For different data packets to be transmitted, target resource blocks are selected from the OFDM candidate resource set based on the comprehensive priority value, link risk assessment value, and service scheduling constraint parameter set, and subcarrier allocation, time slot allocation, modulation and coding scheme, and power allocation parameters are determined. For the first... For each data packet to be transmitted, a resource selection utility function is constructed according to formula (4). (4) in, Choose a utility function for the resource. To map services to time slots The introduced queuing delay, In modulation and coding scheme and power The resource cost function under, These are the weighting coefficients. It is a modulation coding method. This refers to the transmission power. Then the first The target resource mapping result of each data packet to be transmitted is obtained by constructing a target resource mapping function according to formula (5). (5) in, For the target resource mapping result, In the current scheduling cycle The set of candidate resources For parameter optimization operators, it means that in the current scheduling period Within the candidate resource set, a joint search is performed on the resource block index, time slot index, modulation and coding scheme, and transmit power to select the parameter combination that maximizes the resource selection utility function. When the reliability requirement of the data packet to be transmitted exceeds a preset threshold, priority is given to selecting... For higher frequency domain resource blocks, when the service scheduling constraint parameters specify a higher redundancy level, multiple candidate resource blocks are reserved for the same data packet. The predicted block error rate of the data packet to be transmitted on the selected resource blocks is obtained according to formula (21). ,(twenty one) in, Let be the block error rate estimation function. To predict the block error rate, if If the reliability requirement exceeds the upper limit of the data packet to be transmitted, the modulation and coding order should be reduced or the transmission power increased until the reliability constraint is met.

[0028] Step S5 can be used to map the data packets to be transmitted to the target resource block and perform HARQ adaptive control to determine the transmission strategy of the data packets to be transmitted. In an embodiment of the present invention, the data packets to be transmitted are divided into critical state quantity data packets and control command data packets, and freshness-first mapping is performed on the critical state quantity data packets. Specifically: For critical state quantity data packets, the information age value is obtained according to formula (22). ,(twenty two) in, For the first The generation time of key state variable data packets This indicates the information age of the state variable at the current moment, and is used to characterize the freshness of the data.

[0029] The freshness-driven value of the key state quantity data packet is obtained according to formula (6). (6) in, For the first Key state variable data packets in the current scheduling period Freshness-driven value For the first Key state variable data packets in the current scheduling period The state estimation error, The maximum allowed age threshold for information. These are the weighting coefficients. For the first Key state variable data packets in the current scheduling period The information age is used to characterize the freshness of data; when If the remaining valid time of the target state quantity is lower than the preset threshold, a lightweight protection and fast transmission mechanism is adopted, and it is preferentially mapped to the earliest available time slot. When the old state variable has lost its validity, that is, when the condition is met. , If a state variable is discarded according to a threshold, its retransmission is abandoned, and newly acquired state variables are sent first. When the state estimation error increases, its frequency domain priority and transmission frequency are increased, and its update period can be expressed according to formula (23). ,(twenty three) in, For the update cycle, Based on the update cycle, For adjustment coefficients, It decreases as the state estimation error increases, in order to ensure continuous updating and observability of state information.

[0030] Prioritize the mapping of execution deadlines for control command data packets. For control command data packets, obtain the execution deadline margin according to formula (24). ,(twenty four) in, To control the remaining time limit of the command, To predict transmission delay, This characterizes whether the control command can still be effectively executed in the control closed loop after it has been transmitted.

[0031] When the remaining time limit of the target control command is lower than the first threshold and the control risk level is higher than the second threshold, time-frequency redundancy mapping, strong protection modulation and coding scheme and priority transmission strategy are adopted, and the number of redundant copies of the control command data packet is obtained according to formula (7). (7) in, For the first A control instruction data packet in the current scheduling period The number of redundant replicas, The maximum number of redundant replicas, These are the weighting coefficients. The minimum value operator indicates that the smaller value is taken between the maximum upper limit of the number of redundant replicas and the dynamic redundancy requirement calculated by weighting the control risk value, the reciprocal of the remaining time limit, and the link risk assessment value. This ensures that the actual number of redundant replicas allocated meets reliability requirements while not exceeding the system's allowed resource limit. To control the remaining time limit of the command data packet, time-frequency redundancy mapping maps the same control command copy to multiple separate frequency domain resource blocks and time domain resource blocks to improve the success rate of a single delivery.

[0032] If the first Each copy is mapped to a resource block. Then it requires This ensures that the replicas have frequency-domain and time-domain dispersion characteristics. The probability of successful delivery of control commands on the first attempt can be expressed by formula (25). (25) in, For the first The probability of a single replica successfully transmitting.

[0033] Based on the service category, remaining time limit, historical ACK / NACK feedback count, link risk assessment value, and control risk value of the data packet to be transmitted, HARQ adaptive control is executed to dynamically determine whether to start HARQ, the maximum number of retransmissions, the redundancy version, the feedback decision threshold, and the early termination condition. Specifically, the maximum number of retransmissions of the data packet to be transmitted is obtained according to formula (8). (8) in, This is the maximum number of retransmissions allowed by HARQ. This represents the maximum number of retransmissions for the data packet to be transmitted. As a weighting coefficient, when the remaining time limit is short, the maximum number of retransmissions is reduced and the initial transmission protection strength is increased; when the link risk is high, the redundancy version protection level is increased; when the target service is an old state quantity that has lost its timeliness, its HARQ process is terminated. Further, according to formula (9), the first... The cumulative success rate after round transmission (9) in, For the first The cumulative success rate after round transmission For the first The success rate of a single round of transmission, when When, terminate subsequent retransmissions in advance; when If the status variable exceeds the timeout threshold, stop retransmission and release resources.

[0034] In one embodiment of the present invention, in order to achieve synergy between resource mapping and HARQ control, a joint decision value is obtained according to formula (10). (10) in, For joint decision value, The optimal resource mapping utility value, To estimate the probability of success, To estimate the total transmission delay, To predict resource consumption, The weighting coefficient is used. A mode selection function is constructed based on the joint decision value to determine the transmission strategy. When the overall priority is high and the link risk is low, the efficient mapping mode is adopted; when the overall priority is high and the link risk is high, the high-reliability protection mode is adopted; when the overall priority is low and system resources are scarce, the resource-saving mode is adopted. A mode selection function is constructed based on formula (26). (26) in, Indicates an efficient mapping pattern. Indicates a high-reliability protection mode. Indicates a resource-saving model. To determine the threshold based on overall priority, Thresholds for link risk assessment For the current scheduling period The system resource utilization rate This is the system resource utilization threshold.

[0035] The transmission strategy includes at least the resource block location, modulation and coding scheme, transmit power, redundancy level, and HARQ parameters.

[0036] Step S6 can be used to send the data packets to be transmitted according to the transmission strategy, and record the transmission status and feedback information from the receiving end. Key status data packets and control command data packets are sent to the receiving end respectively, and the initial transmission time, resource usage, feedback status, and retransmission status of each data packet are recorded. For the first... Each data packet is used to define a transmission state vector according to formula (27). (27) in, The initial transmission time, For the selected set of resource blocks, It is a modulation coding method. For transmission power, The maximum number of retransmissions. For feedback status, This represents the current number of retransmissions. After transmission is complete, the receiver returns ACK / NACK feedback, and the sender updates the service statistics based on the transmission state vector and the feedback result.

[0037] In one embodiment of the present invention, the transmission method further includes, for example, Figure 2 The steps shown are in this Figure 2 middle, In step S11, a Lyapunov drift penalty function containing delay default constraints, reliability default constraints, and resource cost constraints is constructed, and a drift penalty optimization objective is constructed. In step S12, the optimal transmission strategy for the current scheduling period is obtained by optimizing the objective function based on the drift penalty. In step S13, the control closed-loop performance value of the transmitted data packet is obtained based on the feedback information; In step S14, the multi-source information data, OFDM resource mapping parameters, and HARQ adaptive control parameters are updated according to the optimal transmission strategy and control closed-loop performance values.

[0038] In Figure 2 In the method shown, step S11 can be used to construct a Lyapunov drift penalty function that includes delay default constraints, reliability default constraints, and resource cost constraints, and to construct a drift penalty optimization objective. Specifically: Based on formula (11), establish a virtual queue for delay default, a virtual queue for reliability default, and a virtual queue for resource cost. (11) in, This is the current virtual queue for delay defaults. This is a virtual queue for current reliability failures. This is a virtual queue representing the current resource cost. For the next time delay default virtual queue, For the next moment, a virtual queue for reliability defaults. A virtual queue for resource costs in the next time step. As a time delay threshold, For packet loss threshold, As a resource budget threshold, For the current scheduling period The actual end-to-end transmission delay of the data packets to be transmitted. For the current scheduling period The packet loss rate of the data packets to be transmitted. For the current scheduling period Resource consumption within; Construct the Lyapunov drift penalty function according to formula (12). (12) in, This is the Lyapunov drift penalty function; Based on formula (13), construct the drift penalty optimization objective. (13) in, This is the Lyapunov drift amount. It is a combination function of immediate performance loss and resource cost. The parameters are used to balance long-term queue stability with the benefits of instant transmission.

[0039] Step S12 can be used to optimize the objective function based on the drift penalty to obtain the optimal transmission strategy for the current scheduling period. Based on the drift penalty optimization objective function, OFDM resource dynamic mapping and HARQ adaptive control are jointly solved online in each scheduling period to obtain the current optimal transmission strategy or a near-optimal resource allocation and retransmission control decision. Specifically: The joint control variables at the current moment are obtained according to formula (14). (14) in, For the joint control variables at the current moment, Indicates the first Resource mapping results for each data packet Indicates the maximum number of retransmissions. Indicates the modulation and coding scheme. Indicates the transmission power. This represents the set of data packets to be sent within the current scheduling period; The joint optimization results are obtained according to formula (15). (15) in, To jointly optimize the results, This represents the set of feasible strategies at the current moment. To predict the amount of delay defaults, To predict reliability defaults, To predict resource costs, It is a combination function of immediate performance loss and resource consumption. To balance the parameters, This indicates that the constraints are met. Under the premise of minimizing the joint optimization result, the joint control variables are selected. The optimization objective is to reduce spectrum occupancy, invalid retransmissions, and power consumption while satisfying long-term reliability and delay constraints.

[0040] Step S13 can be used to obtain the control closed-loop performance value of the transmitted data packet based on the feedback information. After completing data decoding, the receiving end returns ACK / NACK feedback to the sending end. The controller generates control closed-loop performance feedback information based on the execution effect of the received key state data packets and control command data packets. Specifically, for the first... Each data packet defines a feedback indicator variable. , The control closed-loop performance value is obtained according to formula (16). (16) in, To control the closed-loop performance value, For state estimation error, To control deviation, For task execution error, As a stability margin indicator, These are weighting coefficients. If an increase in state estimation error, a deterioration in control bias, a decrease in stability margin, or an increase in task execution error is detected, then the corresponding... Increase; when When this happens, it is determined that the current transmission strategy cannot meet the control closed-loop requirements, whereby... This is the threshold for closed-loop performance judgment.

[0041] Step S14 can be used to update multi-source information data, OFDM resource mapping parameters, and HARQ adaptive control parameters according to the optimal transmission strategy and control closed-loop performance value. The transmitting end updates the service importance, remaining time limit, control risk level, OFDM resource mapping parameters, and HARQ control parameters in subsequent scheduling cycles based on ACK / NACK feedback information and control closed-loop performance feedback information. Specifically, based on the receiving feedback and control closed-loop performance feedback, the first... Each data packet controls the risk value. (17) in, The control risk value for the next scheduling cycle. These are the weighting coefficients; Based on the virtual queue state and closed-loop performance feedback, the transmission mode for the next scheduling cycle is determined according to formula (18). (18) in, Indicates a high-reliability protection mode. Indicates the balance mode. Indicates a resource-saving model. These are the mode switching thresholds for the delay violation virtual queue, reliability violation virtual queue, and resource cost virtual queue, respectively. When the delay violation virtual queue or reliability violation virtual queue exceeds the preset threshold, the system switches to a high-reliability protection mode; when channel quality improves and control risk decreases, it switches to a balanced mode or resource-saving mode, and adjusts the OFDM resource mapping parameters and HARQ control parameters accordingly. Repeating these steps forms a closed-loop collaborative transmission mechanism between the perception layer, communication layer, and control layer, driven by perception requirements, corrected by control effects, and constrained by Lyapunov optimization. This achieves high-reliability, low-latency, and stable transmission of critical state variables and control commands in complex wireless environments. The current scheduling period... The cross-layer collaborative state is represented by formula (28). (28) The closed-loop update relationship for the next scheduling cycle is then expressed according to formula (29). (29) in, This is the set of ACK / NACK feedback for the current scheduling period. To control the closed-loop performance feedback indicators. To jointly optimize decision-making outcomes, Update the mapping for cross-layer closed loop.

[0042] Through the above iterative updates, the sensing demand vector, OFDM resource dynamic mapping, HARQ adaptive control, and Lyapunov constraint optimization are coordinated and evolved within a continuous scheduling cycle, thereby achieving highly reliable, low-latency, and stable transmission of key state variables and control commands in complex wireless environments.

[0043] In one embodiment of the present invention, to verify the practicality of the highly reliable cross-layer transmission method that integrates sensing requirements and link states, a discrete-time simulation scenario is constructed to compare the performance of the method of the present invention with that of a comparative scheme. The simulation scenario comprehensively considers critical state quantity services and control command services, dynamic wireless channel conditions, dynamic mapping of OFDM resources, HARQ adaptive control, ACK / NACK feedback, control closed-loop performance feedback, and Lyapunov virtual queue constraints.

[0044] The following three schemes are set up for comparison in the simulation: (1) Fixed OFDM + Fixed HARQ scheme: without considering differences in service requirements, changes in link risks and control loop feedback information, fixed resource mapping and fixed HARQ parameters are used for transmission; (2) Channel / service adaptive scheme only: The transmission parameters are adjusted according to the service priority and link status, but no control closed-loop performance feedback and Lyapunov long-term constraint adjustment are introduced; (3) The method of the present invention: By jointly utilizing the perceived demand vector, link risk assessment results, ACK / NACK feedback, control closed-loop performance feedback and Lyapunov virtual queue status, the OFDM resource mapping and HARQ control parameters are dynamically and jointly optimized.

[0045] like Figure 3 As shown, under different average signal-to-noise ratios, the on-time delivery rate of critical services using the method of this invention is generally higher than that of the fixed OFDM+fixed HARQ scheme and the channel / service adaptive scheme only. This result demonstrates that the method of this invention can dynamically adjust resource mapping and retransmission control strategies based on link risk, service importance, remaining time limits, and reliability requirements, thereby improving the on-time and reliable transmission capability of critical services in complex wireless environments.

[0046] like Figure 4 As shown, under different service load conditions, the average end-to-end latency of the method of this invention is lower than that of the comparative scheme, especially under medium-to-high load scenarios, the advantage is more obvious. This result shows that by introducing the Lyapunov drift penalty optimization mechanism, the present invention incorporates latency default constraints into the cross-layer scheduling decision process, which can effectively suppress the latency growth caused by retransmission accumulation and resource contention.

[0047] like Figure 5As shown, under different service load conditions, the resource efficiency of the method of the present invention is generally better than that of the fixed OFDM+fixed HARQ scheme, and it maintains a good level of resource utilization under high load conditions. This result indicates that the present invention does not simply rely on increasing redundancy or expanding resource allocation to improve reliability, but rather achieves a better balance between reliability, latency, and resource consumption through the joint driving force of service requirements, link status, and feedback information.

[0048] like Figure 6 As shown, under high-load scenarios, the closed-loop performance feedback index corresponding to the method of this invention changes more smoothly over time, and its overall level is lower than that of the comparative scheme. This result indicates that by introducing control closed-loop performance feedback information, this invention can promptly detect changes in state estimation error, control deviation, and stability margin, and accordingly adaptively correct the transmission mode and HARQ control parameters in subsequent scheduling cycles, thereby helping to maintain the stable operation of the control system's closed loop.

[0049] like Figure 7 As shown, under high-load scenarios, the virtual queue for delay defaults in the method of this invention grows more slowly and is easier to maintain at a low level. This result demonstrates that the present invention, by constraining long-term delay default risks through Lyapunov virtual queues, can effectively suppress delay accumulation within continuous scheduling cycles, thereby improving the long-term operational stability and constraint satisfaction capability of the system.

[0050] In summary, the simulation results show that the perception-communication cross-layer collaborative high-reliability transmission method driven by perception requirements proposed in this invention can jointly optimize OFDM resource mapping and HARQ adaptive control parameters based on service importance, remaining time limit, reliability requirements, link risks, and control closed-loop feedback information in a dynamic wireless environment.

[0051] Through the above technical solution, this invention provides a highly reliable cross-layer transmission method that integrates sensing requirements and link status. It acquires multi-source information data from the current scheduling cycle of the power system to obtain data packets to be transmitted, constructs a sensing requirement vector for the data packets, obtains a comprehensive priority value based on the sensing requirement vector, and acquires the link risk assessment value of the current wireless channel to generate a scheduling constraint parameter set. An OFDM candidate resource set is then constructed. Based on the scheduling constraint parameter set, a target resource block is selected from the OFDM candidate resource set, the data packets to be transmitted are mapped to the target resource block, and HARQ adaptive control is executed to determine the transmission strategy for the data packets to be transmitted. The data packets are then sent according to the transmission strategy, and the transmission status and feedback information from the receiving end are recorded. The sensing requirement-driven sensing-communication cross-layer collaborative highly reliable transmission method proposed in this invention can jointly optimize OFDM resource mapping and HARQ adaptive control parameters in a dynamic wireless environment based on service importance, remaining time limit, reliability requirements, link risk, and control closed-loop feedback information. Compared with existing fixed transmission schemes and adaptive schemes lacking closed-loop feedback, the method of this invention can simultaneously improve the on-time successful delivery rate of critical services, reduce the average end-to-end latency, improve resource utilization efficiency, and enhance the stability of the control closed loop. Therefore, it has good practicality and application value.

[0052] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0053] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0054] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0055] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0056] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0057] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0058] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0059] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0060] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A highly reliable cross-layer transmission method that integrates sensing requirements and link status, characterized in that, The transmission method includes: Collect multi-source information data of the power system during the current dispatch cycle and obtain data packets to be transmitted; Construct the perception demand vector of the data packet to be transmitted; Based on the perceived demand vector, a comprehensive priority value is obtained, and the link risk assessment value of the current wireless channel is obtained to generate a set of scheduling constraint parameters; Construct an OFDM candidate resource set, and select a target resource block from the OFDM candidate resource set according to the scheduling constraint parameter set; The data packet to be transmitted is mapped to the target resource block, and HARQ adaptive control is performed to determine the transmission strategy of the data packet to be transmitted; The data packet to be transmitted is sent according to the transmission strategy, and the transmission status and feedback information from the receiving end are recorded.

2. The transmission method according to claim 1, characterized in that, The transmission method further includes: Construct a Lyapunov drift penalty function that includes delay default constraints, reliability default constraints, and resource cost constraints, and construct an optimization objective for the drift penalty; Based on the drift penalty optimization objective function, obtain the optimal transmission strategy for the current scheduling period; The control closed-loop performance value of the transmitted data packet is obtained based on the feedback information. The multi-source information data, OFDM resource mapping parameters, and HARQ adaptive control parameters are updated based on the optimal transmission strategy and the control closed-loop performance value.

3. The transmission method according to claim 1, characterized in that, Based on the perceived demand vector, a comprehensive priority value is obtained, and the link risk assessment value of the current wireless channel is obtained to generate a set of scheduling constraint parameters, including: Obtain the overall priority value according to formula (1). ，（1） in, This is a comprehensive priority value. These are the weighting coefficients. To prevent tiny constants with a denominator of 0, Based on business importance, For the remaining time limit, For reliability requirements, To meet latency requirements, To meet the requirements of data freshness, To control risk values, For the data packet to be transmitted, This is the current scheduling period; The link risk assessment value of the current wireless channel is obtained according to formula (2). ，（2） in, This is the link risk assessment value. For channel quality indicators, Historical NACK rate For interference intensity indicators, These are the weighting coefficients; A set of scheduling constraint parameters is generated based on the comprehensive priority value and the link risk assessment value.

4. The transmission method according to claim 3, characterized in that, Constructing an OFDM candidate resource set, and selecting a target resource block from the OFDM candidate resource set according to the scheduling constraint parameter set, including: Based on the current wireless channel status information, obtain the instantaneous link quality value of the candidate resource block represented by formula (3). ，（3） in, Candidate resource blocks Instantaneous link quality value, Candidate resource blocks Signal-to-interference-to-noise ratio, This is the estimated block error rate for the candidate resource block. The level of interference experienced by this candidate resource block. These are the weighting coefficients. For resource block indexing, For time slot index; Construct a resource selection utility function based on formula (4). ，（4） in, Choose a utility function for the resource. To map services to time slots The introduced queuing delay, In modulation and coding scheme and transmission power The resource cost function under, These are the weighting coefficients. It is a modulation coding method. This refers to the transmission power. Construct the target resource mapping function according to formula (5). ，（5） in, For the target resource mapping result, In the current scheduling cycle The set of candidate resources For parameter optimization operators, it means that in the current scheduling period Within the candidate resource set, a joint search is performed on the resource block index, time slot index, modulation and coding scheme, and transmit power to select the parameter combination that maximizes the resource selection utility function.

5. The transmission method according to claim 4, characterized in that, Mapping the data packet to be transmitted to the target resource block and performing HARQ adaptive control to determine the transmission strategy of the data packet to be transmitted includes: The data packets to be transmitted are divided into critical status quantity data packets and control instruction data packets; Perform freshness-first mapping on critical state quantity data packets; The freshness-driven value of the key state quantity data packet is obtained according to formula (6). ，（6） in, For the first Key state variable data packets in the current scheduling period Freshness-driven value For the first Key state variable data packets in the current scheduling period The state estimation error, The maximum allowed age threshold for information. These are the weighting coefficients. For the first Key state variable data packets in the current scheduling period The information age is used to characterize the freshness of data; Prioritize mapping of control command data packets based on their deadlines; The number of redundant copies of the control command data packet is obtained according to formula (7). ，（7） in, For the first A control instruction data packet in the current scheduling period The number of redundant replicas, The maximum number of redundant replicas, These are the weighting coefficients. This is the minimum value operator. To control the remaining time limit of the instruction data packet.

6. The transmission method according to claim 5, characterized in that, Mapping the data packet to be transmitted to the target resource block and performing HARQ adaptive control to determine the transmission strategy of the data packet to be transmitted includes: The maximum number of retransmissions of the data packet to be transmitted is obtained according to formula (8). ，（8） in, This is the maximum number of retransmissions allowed by HARQ. This represents the maximum number of retransmissions for the data packet to be transmitted. These are the weighting coefficients; According to formula (9), the first... The cumulative success rate after round transmission ，（9） in, For the first The cumulative success rate after round transmission For the first The success rate of a single round of round transmission; The joint decision value is obtained according to formula (10). ，（10） in, For joint decision value, The optimal resource mapping utility value, To estimate the probability of success, To estimate the total transmission delay, To predict resource consumption, These are the weighting coefficients; Based on the joint decision values, collaborative decision rules are constructed to determine the transmission strategy.

7. The transmission method according to claim 2, characterized in that, Construct a Lyapunov drift penalty function that includes delay default constraints, reliability default constraints, and resource cost constraints, and construct the drift penalty optimization objective, including: Based on formula (11), establish a virtual queue for delay default, a virtual queue for reliability default, and a virtual queue for resource cost. ，（11） in, This is the current virtual queue for delay defaults. This is a virtual queue for current reliability failures. This is a virtual queue representing the current resource cost. For the next time delay default virtual queue, For the next moment, a virtual queue for reliability defaults. A virtual queue for resource costs in the next time step. As a time delay threshold, For packet loss threshold, As a resource budget threshold, For the current scheduling period The actual end-to-end transmission delay of the data packets to be transmitted. For the current scheduling period The packet loss rate of the data packets to be transmitted. For the current scheduling period Resource consumption within; Construct the Lyapunov drift penalty function according to formula (12). ，（12） in, This is the Lyapunov drift penalty function; Based on formula (13), construct the drift penalty optimization objective. ，（13） in, This is the Lyapunov drift amount. It is a combination function of immediate performance loss and resource cost. To weigh the parameters.

8. The transmission method according to claim 2, characterized in that, Based on the drift penalty optimization objective function, the optimal transmission strategy for the current scheduling period is obtained, including: The joint control variables for the current scheduling cycle are obtained according to formula (14). ，（14） in, For the joint control variables of the current scheduling period, Indicates the first The resource mapping result of each data packet to be transmitted. Indicates the maximum number of retransmissions. Indicates the modulation and coding scheme. Indicates the transmission power. This represents the set of data packets to be sent within the current scheduling period; The joint optimization results are obtained according to formula (15). ，（15） in, To jointly optimize the results, This is the set of feasible strategies for the current scheduling period. To predict the amount of delay defaults, To predict reliability defaults, To predict resource costs, It is a combination function of immediate performance loss and resource consumption. To balance the parameters, This indicates that the constraints are met. Under the premise of minimizing the joint optimization result, select the joint control variable.

9. The transmission method according to claim 2, characterized in that, The control closed-loop performance value of the transmitted data packet is obtained based on the feedback information, including: The control closed-loop performance value is obtained according to formula (16). ，（16） in, To control the closed-loop performance value, For state estimation error, To control deviation, For task execution error, As a stability margin indicator, These are the weighting coefficients.

10. The transmission method according to claim 9, characterized in that, Update the multi-source information data, OFDM resource mapping parameters, and HARQ adaptive control parameters according to the optimal transmission strategy and the control closed-loop performance value, including: The control risk value is obtained according to formula (17). ，（17） in, The control risk value for the next scheduling cycle. These are the weighting coefficients; The transmission mode for the next scheduling cycle is determined according to formula (18). ，（18） in, Indicates a high-reliability protection mode. Indicates the balance mode. Indicates a resource-saving model. These are the mode switching thresholds for the latency default virtual queue, the reliability default virtual queue, and the resource cost virtual queue, respectively.

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