Link adaptation method for multi-mode communication system

Abstract

The present invention relates to a link adaptation method for a multi-mode communication system, comprising the following steps: defining a priority list for waveforms, and defining a signal quality evaluation criterion for each waveform; sequentially monitoring the real-time signal quality of each waveform according to the priority list for waveforms, if it is detected that the signal quality of any waveform exceeds a preset threshold indicating good signal quality, determining the waveform as an optimal waveform, and otherwise, recording the current signal quality of the waveform; if none of the waveforms meets a criterion for good signal quality, selecting a waveform having the smallest difference as the optimal waveform; and dynamically adjusting the priority list and the threshold criterion on the basis of the system and user feedback, so as to improve the accuracy and efficiency of future decision-making. The problems of insufficient decision criteria and a single condition in multi-mode waveform switching technology are solved, resources can be effectively managed and allocated, and waveforms having good signal quality can be preferentially processed, thereby improving the response speed and efficiency of the overall system, and maintaining the optimal performance.

Description

A Link Adaptive Method for Multimode Communication Systems Technical Field

[0001] This invention relates to a telecommunications technology, and more particularly to a link adaptation method for multimode communication systems. Background Technology

[0002] Using multiple waveforms in mobile communications can better adapt to complex communication environments, meet different business needs, and enhance the flexibility and compatibility of the system.

[0003] Common multimode waveform technologies include: 1) Rate-based handover: The device judges the network transmission rate between different base stations and selects the best base station for handover according to actual needs; 2) Load-based handover: The device selects a base station with a lower network load for handover based on the current network load of the base station; 3) Latency-based handover: When the device finds that the latency of the current base station exceeds the set threshold, the device will switch to other base stations to obtain better network quality.

[0004] The above-mentioned multi-mode waveform switching technology has the following problems: 1) The judgment criteria only consider network transmission and do not take into account other services, such as voice call services; 2) The network transmission capacity is judged from the network side, but waveforms that do not require base stations are not considered, which is not comprehensive; 3) The evaluation criteria are too simplistic and do not take into account the user's usage scenarios. Summary of the Invention

[0005] To address the issues of insufficient judgment criteria and limited conditions in multimode waveform switching technology, a link adaptive method for multimode communication systems is proposed.

[0006] 1) Design an evaluation system that includes multiple dimensions, such as functional integrity, performance indicators, and security. Develop signal quality evaluation standards based on the characteristics of each waveform, avoiding the use of a single standard to define signal quality.

[0007] 2) Gain a deep understanding of user needs, behaviors, and usage scenarios; prioritize waveforms based on user needs; optimize the utilization of communication resources; and improve the stability and performance of the entire communication network.

[0008] 3) Evaluation criteria can be dynamically adjusted based on user feedback and usage data to adapt to ever-changing user needs.

[0009] The technical solution of this invention is as follows:

[0010] A link adaptation method for a multimode communication system includes the following steps:

[0011] Step 1: Define a priority list for waveforms and define the signal quality evaluation criteria for each waveform, including thresholds for good and poor signal quality; signal quality includes signal strength, signal stability, and signal noise level.

[0012] Step 2: According to the waveform priority list, monitor the real-time signal quality of each waveform in turn. If the signal quality of any waveform exceeds the preset threshold for best signal quality, then the waveform is determined as the optimal waveform. Otherwise, record the current signal quality of the waveform.

[0013] Step 3: If none of the waveforms meet the standard for good signal quality, then proceed to the optimization stage. Calculate the difference between the current signal quality of each waveform and the threshold for good signal quality, and select the waveform with the smallest difference as the optimal waveform.

[0014] Step 4: Dynamically adjust the priority list and threshold standards based on system and user feedback to improve the accuracy and efficiency of future decisions.

[0015] Furthermore, step 1 specifically includes the following steps:

[0016] Step 1.1: Define a priority list specifically for waveforms; the purpose of this list is to arrange different waveforms in a certain order to reflect their importance in a specific scenario or system.

[0017] Step 1.2: Define a signal quality evaluation standard for each waveform. This evaluation standard measures the signal quality of each waveform and sets reasonable thresholds for good and poor signal quality. Signal quality includes signal strength: a waveform with strong enough signal strength can better resist interference during transmission, thus ensuring accurate information transmission; signal stability: a stable signal waveform can maintain its characteristics during long-term transmission without significant fluctuations or distortion; and signal noise level: a lower noise level indicates higher purity of the waveform and relatively better signal quality.

[0018] Furthermore, step 3 specifically includes the following steps:

[0019] Step 3.1: Perform specific calculations for each waveform to calculate the difference between the current signal quality of each waveform and the optimal signal quality threshold. This difference is calculated precisely based on the various indicators in the previously determined signal quality evaluation criteria. Specifically, the difference between the current state of each waveform and the optimal signal quality threshold under the corresponding indicators of signal strength, stability, and noise level is calculated to obtain the overall difference value.

[0020] Step 3.2: From the difference values ​​calculated from all waveforms, select the waveform with the smallest overall difference according to the actual situation and determine it as the optimal waveform.

[0021] Furthermore, step 4 specifically includes the following steps:

[0022] Step 4.1: Dynamically adjust the priority list and threshold standards based on system feedback; the system accumulates a large amount of data and information about waveform processing during continuous operation; if the system finds that certain waveforms, under specific operating conditions, although they are in a low position in the current priority list, actually have a significant impact on the system's key performance indicators, then the priority list needs to be adjusted based on system feedback; for threshold standards, when the system detects that in certain special cases, judging according to the existing standards will result in deviations, the signal quality evaluation standard system needs to be adjusted based on system feedback;

[0023] Step 4.2: Dynamically adjust the priority list and threshold standards based on user feedback; In actual operation, users may find that the processing results of certain waveforms do not meet expectations when using the existing priority list and threshold standards; Based on user feedback, this method needs to dynamically adjust the priority list and threshold standards.

[0024] Furthermore, in step 4.1, the system will accumulate a large amount of data and information about waveform processing during continuous operation. For example, the system will record data on the transmission effect of different waveforms in different time periods, their impact on the overall system performance, and their performance under different workloads.

[0025] Furthermore, in step 4.2, the processing results of some waveforms do not meet expectations. For example, users may feel that some waveforms that are not important to the current business are given a lower priority, which affects the business process; according to the current threshold standard, some waveforms are misjudged as poor quality, which affects the user's normal use.

[0026] The beneficial effects of this invention are as follows:

[0027] 1) Setting priorities for waveforms can effectively manage and allocate resources, prioritizing waveforms with better signal quality, and improving the overall system response speed and efficiency;

[0028] 2) When none of the waveforms meet the preset quality standard, this method can calculate the difference between each waveform and the ideal state, and select the waveform that is closest to the target, thereby ensuring that the system can maintain the best performance under different conditions.

[0029] 3) This solution adjusts the waveform in real time to adapt to changes during the communication transmission process, ensuring that communication can be transmitted in the best possible state and meeting users' needs for high speed and stability. Attached Figure Description

[0030] Figure 1 is a flowchart of the waveform switching process of the present invention. Detailed Implementation

[0031] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments. These embodiments are based on the technical solution of the present invention and provide detailed implementation methods and specific operating procedures. However, the scope of protection of the present invention is not limited to the following embodiments.

[0032] A link adaptation method for multimode communication systems, as shown in Figure 1, includes the following steps:

[0033] Step 1: Define a priority list for waveforms and define the signal quality evaluation criteria for each waveform, including thresholds for good and poor signal quality;

[0034] Step 1 includes the following steps:

[0035] Step 1.1: Define a priority list specifically for waveforms. This list arranges different waveforms in a certain order to reflect their importance in a specific scenario or system. For example, in a complex communication system, certain waveforms may be given higher priority because of their advantages in transmitting critical information.

[0036] Step 1.2: Define a signal quality evaluation criterion for each waveform. This criterion measures the signal quality of each waveform and sets reasonable thresholds for good and poor signal quality. Signal quality includes...

[0037] 1) Signal strength: If the signal strength of a waveform is strong enough, it means that it can better resist interference during transmission, thereby ensuring the accurate transmission of information;

[0038] 2) Signal stability: A stable signal waveform can maintain its characteristics during long-term transmission without significant fluctuations or distortion;

[0039] 3) Noise level of the signal: A lower noise level indicates that the waveform is more pure and the signal quality is relatively better.

[0040] Step 2: According to the waveform priority list, monitor the real-time signal quality of each waveform in turn. If the signal quality of any waveform exceeds the preset threshold for best signal quality, then the waveform is determined as the optimal waveform. Otherwise, record the current signal quality of the waveform.

[0041] Step 3: If none of the waveforms meet the standard for good signal quality, then proceed to the optimization stage. Calculate the difference between the current signal quality of each waveform and the threshold for good signal quality, and select the waveform with the smallest difference as the optimal waveform.

[0042] Step 3 includes the following steps:

[0043] Step 3.1: Perform specific calculations for each waveform to determine the difference between the current signal quality and the optimal signal quality threshold. This difference calculation is based on the various indicators in the previously determined signal quality evaluation criteria. Specifically, calculate the difference between the current state of each waveform and the optimal signal quality threshold for each indicator, including signal strength, stability, and noise level, to obtain the overall difference value.

[0044] Step 3.2: From the difference values ​​calculated from all waveforms, select the waveform with the smallest overall difference according to the actual situation and determine it as the optimal waveform. This selection method is a suboptimal selection strategy when all waveforms fail to meet the ideal signal quality standard. By selecting the waveform with the smallest difference from the optimal signal quality threshold, we can select a relatively better waveform for subsequent operations under the current unsatisfactory conditions, and make adjustments based on this relatively optimal waveform.

[0045] For waveforms with minimal differences, in practical applications, signal strength, signal stability, and noise level need to be comprehensively considered based on waveform characteristics. For example, for communication over long distances, a high signal strength is required to ensure coverage; for waveforms primarily used for voice services, a low noise level is needed to ensure audio signal clarity.

[0046] Step 4: Based on system feedback, dynamically adjust the priority list and threshold standards to improve the accuracy and efficiency of future decisions.

[0047] Step 4 includes the following steps:

[0048] Step 4.1: Dynamically adjust the priority list and threshold standards based on feedback from the multimode communication system. During continuous operation, the system accumulates a large amount of data and information related to waveform processing. For example, the system records data on the transmission effect of different waveforms at different time periods, their impact on overall system performance, and their performance under different workloads. If the system finds that certain waveforms, under specific operating conditions, although ranked low in the current priority list, actually have a significant impact on the system's key performance indicators, the priority list needs to be adjusted based on system feedback. Regarding threshold standards, when the system detects deviations in judgments based on existing standards under certain special circumstances, the signal quality evaluation standard system needs to be adjusted based on system feedback.

[0049] Step 4.2: Dynamically adjust the priority list and threshold standards based on user feedback. In actual operation, users may find that the processing results of certain waveforms do not meet expectations when using the existing priority list and threshold standards. For example, users may feel that some waveforms that are not critical to the current business are assigned lower priorities, affecting the business process; according to the current threshold standards, some waveforms are misjudged as poor quality, affecting normal user experience. Based on user feedback, this method needs to dynamically adjust the priority list and threshold standards.

[0050] The above-described embodiments are merely one implementation of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the scope of protection of the present invention. Therefore, the scope of protection of this invention should be determined by the appended claims.

Claims

1. A link adaptive method for a multimode communication system, characterized in that, Includes the following steps: Step 1: Define a priority list for waveforms and define the signal quality evaluation criteria for each waveform, including thresholds for good and poor signal quality; signal quality includes signal strength, signal stability, and signal noise level. Step 2: According to the waveform priority list, monitor the real-time signal quality of each waveform in turn. If the signal quality of any waveform exceeds the preset threshold for best signal quality, then the waveform is determined as the optimal waveform. Otherwise, record the current signal quality of the waveform. Step 3: If none of the waveforms meet the standard for good signal quality, then proceed to the optimization stage. Calculate the difference between the current signal quality of each waveform and the threshold for good signal quality, and select the waveform with the smallest difference as the optimal waveform. Step 4: Dynamically adjust the priority list and threshold standards based on system and user feedback to improve the accuracy and efficiency of future decisions.

2. The link adaptive method for a multimode communication system according to claim 1, characterized in that, Step 1 specifically includes the following steps: Step 1.1: Define a priority list specifically for waveforms; the purpose of this list is to arrange different waveforms in a certain order to reflect their importance in a specific scenario or system. Step 1.2: Define a signal quality evaluation standard for each waveform. This evaluation standard measures the signal quality of each waveform and sets reasonable thresholds for good and poor signal quality. Signal quality includes signal strength: a waveform with strong enough signal strength can better resist interference during transmission, thus ensuring accurate information transmission; signal stability: a stable signal waveform can maintain its characteristics during long-term transmission without significant fluctuations or distortion; and signal noise level: a lower noise level indicates higher purity of the waveform and relatively better signal quality.

3. The link adaptation method for a multimode communication system according to claim 2, characterized in that, Step 3 specifically includes the following steps: Step 3.1: Perform specific calculations for each waveform to calculate the difference between the current signal quality of each waveform and the optimal signal quality threshold. This difference is calculated precisely based on the various indicators in the previously determined signal quality evaluation criteria. Specifically, the difference between the current state of each waveform and the optimal signal quality threshold under the corresponding indicators of signal strength, stability, and noise level is calculated to obtain the overall difference value. Step 3.2: From the difference values ​​calculated from all waveforms, select the waveform with the smallest overall difference according to the actual situation and determine it as the optimal waveform.

4. The link adaptive method for a multimode communication system according to claim 3, characterized in that, Step 4 specifically includes the following steps: Step 4.1: Dynamically adjust the priority list and threshold standards based on system feedback; the system accumulates a large amount of data and information about waveform processing during continuous operation; if the system finds that certain waveforms, under specific operating conditions, although they are in a low position in the current priority list, actually have a significant impact on the system's key performance indicators, then the priority list needs to be adjusted based on system feedback; for threshold standards, when the system detects that in certain special cases, judging according to the existing standards will result in deviations, the signal quality evaluation standard system needs to be adjusted based on system feedback; Step 4.2: Dynamically adjust the priority list and threshold standards based on user feedback; In actual operation, users may find that the processing results of certain waveforms do not meet expectations when using the existing priority list and threshold standards; Based on user feedback, this method needs to dynamically adjust the priority list and threshold standards.

5. The link adaptation method for a multimode communication system according to claim 4, characterized in that, In step 4.1, the system will accumulate a large amount of data and information about waveform processing during continuous operation. For example, the system will record data on the transmission effect of different waveforms in different time periods, their impact on the overall system performance, and their performance under different workloads.

6. The link adaptation method for a multimode communication system according to claim 4, characterized in that, In step 4.2, the processing results of some waveforms do not meet expectations. For example, users may feel that some waveforms that are not important to the current business are given a lower priority, which affects the business process; according to the current threshold standard, some waveforms are misjudged as poor quality, which affects the normal use of the user.

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