CN116723574A - Self-adaptive data rate adjustment method based on link margin and signal-to-noise ratio weighting - Google Patents

Self-adaptive data rate adjustment method based on link margin and signal-to-noise ratio weighting Download PDF

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Publication number
CN116723574A
CN116723574A CN202310789229.7A CN202310789229A CN116723574A CN 116723574 A CN116723574 A CN 116723574A CN 202310789229 A CN202310789229 A CN 202310789229A CN 116723574 A CN116723574 A CN 116723574A
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noise ratio
signal
link margin
adjustment
transmission power
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章辉
杨茂恒
宋雨昕
李美锟
贾奇铭
王晶晶
吴虹
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Nankai University
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Nankai University
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/04—Wireless resource allocation
    • H04W72/044—Wireless resource allocation based on the type of the allocated resource
    • H04W72/0473—Wireless resource allocation based on the type of the allocated resource the resource being transmission power
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B1/00—Details of transmission systems, not covered by a single one of groups H04B3/00 - H04B13/00; Details of transmission systems not characterised by the medium used for transmission
    • H04B1/69—Spread spectrum techniques
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/50—Allocation or scheduling criteria for wireless resources
    • H04W72/535—Allocation or scheduling criteria for wireless resources based on resource usage policies
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

An adaptive data rate adjustment method based on link margin and signal-to-noise ratio weighting: calculating the instantaneous data extraction rate of a data packet counter in a network server platform; acquiring an ordered weighted average signal-to-noise ratio; adjusting the link margin parameters; acquiring an adjustment step number through a link margin signal-to-noise ratio; setting a loop start condition, performing a loop execution operation of adjusting and reducing the spreading factor and adjusting the number of steps, and performing a loop execution operation of adjusting and reducing the number of steps and transmitting power, or performing a loop execution operation of adjusting and increasing the number of steps and transmitting power when the loop is ended. The invention provides support for dense deployment of wireless terminals, solves the problems of the prior self-adaptive data rate technology, and provides a more effective and efficient solution for wireless networks, especially in dense population areas where link conditions are continuously changed due to interference of other devices. It has the potential to significantly improve the performance of low power internet of things applications that rely on wireless networks while reducing energy consumption and extending the battery life of the device.

Description

Self-adaptive data rate adjustment method based on link margin and signal-to-noise ratio weighting
Technical Field
The invention relates to a data rate adjustment method. And more particularly to an adaptive data rate adjustment method based on link margin and signal to noise ratio weighting that can be used in wireless networks.
Background
The low-power-consumption wide area network technology has wide wireless coverage, free frequency band use and low energy consumption, and plays an important role in the scene of the Internet of things. The transmission distance of the remote radio wide area network can reach several kilometers, the data rate is as high as 5.5kb/s, and the application scene covers various Internet of things use cases such as intelligent city monitoring, accurate agriculture, industrial sensor communication, remote environment monitoring, infrastructure monitoring, intelligent power grid and the like. The long-range radio wide area network allows the sensing terminal to transmit information to a gateway located several centimeters away in a low power consumption manner.
The adaptive data rate technique of wireless networks is a solution to dynamically adjust the terminal data rate and transmission power in order to increase network capacity and maximize terminal battery life. By estimating the link budget, i.e., the sum of the gain and loss of each wireless link between the terminal device and the gateway, the adaptive data rate technique enables dynamic adjustment of the transmission rate and power of the terminal device. When the terminal device is far away from the gateway, the adaptive data rate technology can improve the transmission power of the terminal device so as to ensure the reliability and stability of data transmission. When the terminal device is close to the gateway, the adaptive data rate technology can properly reduce the transmission power of the terminal device, so as to reduce the energy consumption and prolong the service life of the battery. Through the application of the self-adaptive data rate technology, the wireless network can better meet the application requirements of the Internet of things, the overall performance and reliability of the network are improved, and meanwhile, the maintenance cost of the terminal of the Internet of things is reduced. The adaptive data rate mechanism operates asynchronously on the wireless network terminal and the network server. Most of the complexity in the adaptive data rate is allocated to the network server in order to make the terminal as simple as possible.
Disclosure of Invention
The invention aims to solve the technical problem of providing a self-adaptive data rate adjustment method based on link margin and signal-to-noise ratio weighting, which is applicable to a wireless network server, in order to overcome the defects of the prior art.
The technical scheme adopted by the invention is as follows: an adaptive data rate adjustment method based on link margin and signal-to-noise ratio weighting comprises the following steps:
1) Calculating the instantaneous data extraction rate of a data packet counter in a network server platform;
2) Acquiring an ordered weighted average signal-to-noise ratio;
3) Adjusting the link margin parameters;
4) Acquiring an adjustment step number through a link margin signal-to-noise ratio;
5) Setting a loop starting condition, performing the operations of adjusting and reducing the spreading factor and adjusting the number of steps in a loop, and performing the step 6) or the step 7) when the loop is ended;
6) Cyclically executing the operations of adjusting the number of steps and transmitting power;
7) The operations of increasing the number of adjustment steps and transmitting power are cyclically performed.
Step 1) comprises:
no data packet counter and signal to noise ratio contained in network server platformThe last n data packets of the line terminal are ordered in descending order { a } according to the signal to noise ratio of the data packets 1 ,a 2 ,…,a n "a 1 ≥a 2 ≥…≥a n To obtain the data packet signal-to-noise ratio vector A= (a) 1 ,a 2 ,…,a n ) The packet counter is incremented with each transmission and the instantaneous data extraction rate DER is calculated according to the following equation inst
Where LastCounter is the packet counter value of the last received packet of the n packets and FirstCounter is the packet counter value of the first received packet of the n packets.
Step 2) comprises:
by beta i Representing the ordered weighted average weight of the ith packet, the ordered weighted average weight vector is represented by B, i.e., b= (β) 1 ,β 2 ,…,β n ) T Wherein beta is i ∈[0,1]I is more than or equal to 1 and less than or equal to n, andset DER inst =δ, the ordered weighted average weight of the ith packet is obtained according to:
β 1 ＝δ n-1
0≤δ≤1
where δ=der inst N represents the last n packets of the wireless terminal in the network server platform containing the packet counter and the signal-to-noise ratio;
ordered weighted average signal-to-noise ratio SNR using ordered weighted average weight vector B according to owa The calculation is performed such that,
SNR owa =a.b, i.e
The step 3) comprises the following steps:
when the instantaneous data extraction rate is lower than the reference data extraction rate and the link margin parameter can be increased, increasing the link margin parameter until the instantaneous data extraction rate is equal to the reference data extraction rate;
when the instantaneous data extraction rate is larger than the reference data extraction rate and the link margin parameter is not lower than the threshold value, the instantaneous data extraction rate is reduced until the instantaneous data extraction rate is equal to the reference data extraction rate;
when the instantaneous data extraction rate is within a set range, the link margin parameter is kept unchanged;
the link margin parameter includes a margin_db parameter.
Step 4) comprises:
the method comprises the steps that an ordered weighted average signal-to-noise ratio is adopted to subtract a required signal-to-noise ratio and a link margin parameter to obtain a link margin signal-to-noise ratio, and then an adjustment step number is obtained through calculation of the link margin signal-to-noise ratio, wherein the required signal-to-noise ratio is set according to actual performance requirements;
the adjustment step number indicates the number of times of adjusting the transmission power and the spreading factor.
The loop of step 5) performs operations of reducing the spreading factor and adjusting the number of steps, including: setting that when the adjustment step number is larger than 0 and the spreading factor is larger than 7, the spreading factor subtracting 1 and the adjustment step number subtracting 1 are circularly executed; in the operations of circularly executing the spreading factor reduction 1 and the adjustment step number reduction 1, the following judgment is carried out:
when the spreading factor is equal to 7 and the adjustment step number is greater than 0, ending the cycle and executing the step 6;
when the spreading factor is equal to 7 and the adjustment step number is smaller than 0, ending the cycle and executing the step 7;
when the spreading factor is equal to 7 and the number of adjustment steps is equal to 0, the algorithm is ended.
The cyclically performing the operations of adjusting the number of adjustment steps and the transmission power of step 6) includes: when the adjustment step number is greater than 0 and the transmission power is greater than the set minimum transmission power, the loop starts to execute the adjustment step number reduction 1 and the transmission power reduction 3 operations, and the following judgment is made in the loop execution of the adjustment step number reduction 1 and the transmission power reduction 3 operations:
when the number of the adjustment steps is smaller than 0, ending the cycle, and executing the step 7;
and ending the algorithm when the number of the adjustment steps is equal to 0 or the transmission power is smaller than the set minimum transmission power.
The cyclically executing step number adjusting and transmission power adjusting operation in the step 7) includes: when the adjustment step number is smaller than 0 and the transmission power is smaller than the set maximum transmission power, the adjustment step number plus 1 and the transmission power plus 3 operations are cyclically executed, and the following judgment is made in the cyclic execution of the adjustment step number plus 1 and the transmission power plus 3 operations:
and ending the algorithm when the number of the adjustment steps is equal to 0 or the transmission power is larger than the set maximum transmission power.
The self-adaptive data rate adjustment method based on the link margin and the signal to noise ratio weighting selects the link margin parameter by taking the channel noise condition into consideration, adopts ordered weighted average as a transmission parameter configuration decision method capable of taking the channel condition into consideration, and reasonably controls decision key parameters. The invention uses the ordered weighted average of the dynamic link margin and the signal to noise ratio to configure parameters, thereby having good performance under all channel conditions, and can dynamically configure the spread spectrum factor and the transmission power of the terminal so as to adapt to different channel conditions.
Simulation results show that the method has excellent performance, the performance in medium and high noise channels is superior to that of other algorithms, and in the high noise channels, the packet delivery ratio is greatly improved with a small amount of extra energy consumption. The present invention also exhibits excellent performance in remote suburban scenarios. The invention is sensitive to the change of the channel state, uses the instantaneous data extraction rate to represent the current environment, and converges more quickly than other algorithms.
The self-adaptive data rate adjustment method based on the link margin and the signal-to-noise ratio weighting provides support for dense deployment of wireless terminals, solves the problems of the original self-adaptive data rate technology, and provides a more effective and efficient solution for the wireless network, especially in dense population areas where the link condition is continuously changed due to interference of other devices. It has the potential to significantly improve the performance of low power internet of things applications that rely on wireless networks while reducing energy consumption and extending the battery life of the device.
Drawings
Fig. 1 is a flow chart of an adaptive data rate implementation on the terminal side of the prior art;
FIG. 2 is a flow chart of an adaptive data rate implementation of a prior art network server side;
fig. 3 is a flow chart of an adaptive data rate adjustment method based on link margin and signal to noise ratio weighting in accordance with the present invention.
Detailed Description
The following describes the adaptive data rate adjustment method based on link margin and snr weighting in detail with reference to the embodiments and the accompanying drawings, but it should be understood that these drawings are designed for illustrative purposes only and are not intended to limit the scope of the invention. Moreover, unless specifically indicated otherwise, the drawings are intended to depict only the structural configuration described herein conceptually.
As shown in fig. 3, the adaptive data rate adjustment method based on link margin and signal to noise ratio weighting of the present invention includes the following steps:
1) Calculating the instantaneous data extraction rate of a data packet counter in a network server platform; comprising the following steps:
sorting { a } the last n packets of a wireless terminal in a network server platform including a packet counter and a signal-to-noise ratio in descending order according to the signal-to-noise ratio of the packets 1 ,a 2 ,…,a n "a 1 ≥a 2 ≥…≥a n To obtain the data packet signal-to-noise ratio vector A= (a) 1 ,a 2 ,…,a n ) The packet counter is incremented with each transmission and the instantaneous data extraction rate DER is calculated according to the following equation inst
Where LastCounter is the packet counter value of the last received packet of the n packets and FirstCounter is the packet counter value of the first received packet of the n packets.
In an embodiment of the present invention, n is 20. In a dynamic adaptive data rate algorithm, δ is dynamically configured according to network conditions. For this purpose, the instantaneous data extraction rate DER is used inst As an indicator of the channel condition. DER (DER) inst The lower indicates fewer packets received and higher channel noise, which can be calculated by the platform using the counters FirstCounter and LastCounter for the first and last packets in the 20-unit array recorded for each terminal. Taking the example of the last 20 packets received from a terminal node having FirstCounter and LastCounter values of 20 and 60, respectively, this indicates that the terminal node has sent 40 packets, 20 of which have been lost, DER inst Then 50%.
2) Acquiring an ordered weighted average signal-to-noise ratio; comprising the following steps:
by beta i Representing the ordered weighted average weight of the ith packet, the ordered weighted average weight vector is represented by B, i.e., b= (β) 1 ,β 2 ,…,β n ) T Wherein beta is i ∈[0,1]I is more than or equal to 1 and less than or equal to n, andset DER inst =δ, the ordered weighted average weight of the ith packet is obtained according to:
β 1 ＝δ n-1
0≤δ≤1
where δ=der inst N represents the last n packets of the wireless terminal in the network server platform containing the packet counter and the signal-to-noise ratio;
using the ordered weighted average weight vector B to perform the following stepsSequence weighted average signal-to-noise ratio SNR owa The calculation is performed such that,
SNR owa =a.b, i.e
For dynamic configuration of δ, it is set to δ=der inst Specifically, if the delta value is low, the ordered weighted average operator will be closer to the minimum function of the signal-to-noise ratio of the last 20 packets. On the other hand, higher delta values result in an ordered weighted average operator that tends to be the largest function of the signal-to-noise ratio in the last 20 packets.
The platform is provided with [ PacketCounter, SNR ]]The last 20 packets of the terminal is shown as a PacketList, where PacketCounter is the counter of data packets, and with each transmission, the SNR is the signal-to-noise ratio. Algorithm calculation of DER inst And to delta, which indicates the number of transmissions the terminal has made to successfully deliver 20 packets. And the platform sorts the PacketList in descending order according to the signal-to-noise ratio of the message. Then, an ordered weighted average weight is obtained according to a formula and used for SNR owa And (5) calculating.
3) Adjusting the link margin parameters; comprising the following steps:
when the instantaneous data extraction rate is lower than the reference data extraction rate and the link margin parameter can be increased, increasing the link margin parameter until the instantaneous data extraction rate is equal to the reference data extraction rate;
when the instantaneous data extraction rate is larger than the reference data extraction rate and the link margin parameter is not lower than the threshold value, the instantaneous data extraction rate is reduced until the instantaneous data extraction rate is equal to the reference data extraction rate;
when the instantaneous data extraction rate is within a set range, the link margin parameter is kept unchanged;
the link margin parameter includes a margin_db parameter.
In an embodiment of the invention, the reference data extraction rate DER is used ref The setting is made to be 0.95,
when instantaneous data extraction rate DER inst Lower than reference data extraction rate DER ref When (1): if the margin parameter margin_db is smaller than 30, adding 5 to the margin parameter margin_db, and if the margin parameter margin_db is greater than or equal to 30, keeping the margin parameter margin_db unchanged;
when instantaneous data extraction rate DER inst Greater than reference data extraction rate DER ref When (1): subtracting 2.5 from the margin parameter margin_db if the margin parameter margin_db is greater than 5, and keeping the margin parameter margin_db unchanged if the margin parameter margin_db is less than or equal to 5;
when instantaneous data extraction rate DER inst Equal to the reference data extraction rate DER ref When (1): the link margin parameter margin dB is unchanged.
4) Acquiring an adjustment step number through a link margin signal-to-noise ratio; comprising the following steps:
the method comprises the steps that an ordered weighted average signal-to-noise ratio is adopted to subtract a required signal-to-noise ratio and a link margin parameter to obtain a link margin signal-to-noise ratio, and then an adjustment step number is obtained through calculation of the link margin signal-to-noise ratio, wherein the required signal-to-noise ratio is set according to actual performance requirements;
in particular the required signal-to-noise ratio SNR req The spreading factor that can be used per packet is obtained by table one:
TABLE 1 required SNR values at different spreading factors
Link margin signal-to-noise ratio SNR margin Dividing by 3 and rounding down gives an adjustment step number NStep, which represents the number of times the transmission power and spreading factor are adjusted, when the adjustment step number is 0, meaning that the wireless terminal is already using the optimal transmission parameters.
5) Setting a loop starting condition, performing the operations of adjusting and reducing the spreading factor and adjusting the number of steps in a loop, and performing the step 6) or the step 7) when the loop is ended;
the cyclic execution reduces the spread spectrum factor and adjusts the step number operation, including: setting that when the adjustment step number is larger than 0 and the spreading factor is larger than 7, the spreading factor subtracting 1 and the adjustment step number subtracting 1 are circularly executed; in the operations of circularly executing the spreading factor reduction 1 and the adjustment step number reduction 1, the following judgment is carried out:
when the spreading factor is equal to 7 and the adjustment step number is greater than 0, ending the cycle and executing the step 6;
when the spreading factor is equal to 7 and the adjustment step number is smaller than 0, ending the cycle and executing the step 7;
when the spreading factor is equal to 7 and the number of adjustment steps is equal to 0, the algorithm is ended.
6) Cyclically performing a step-down and transmit power operation, comprising: when the adjustment step number is greater than 0 and the transmission power is greater than the set minimum transmission power, the loop starts to execute the adjustment step number reduction 1 and the transmission power reduction 3 operations, and the following judgment is made in the loop execution of the adjustment step number reduction 1 and the transmission power reduction 3 operations:
when the number of the adjustment steps is smaller than 0, ending the cycle, and executing the step 7;
and ending the algorithm when the number of the adjustment steps is equal to 0 or the transmission power is smaller than the set minimum transmission power.
7) Cyclically performing an increase adjustment step number and transmission power operation, comprising: when the adjustment step number is smaller than 0 and the transmission power is smaller than the set maximum transmission power, the adjustment step number plus 1 and the transmission power plus 3 operations are cyclically executed, and the following judgment is made in the cyclic execution of the adjustment step number plus 1 and the transmission power plus 3 operations:
and ending the algorithm when the number of the adjustment steps is equal to 0 or the transmission power is larger than the set maximum transmission power.
The foregoing examples illustrate the invention in detail, but are merely preferred embodiments of the invention and are not to be construed as limiting the scope of the invention. All equivalent changes and modifications within the scope of the present invention are intended to be covered by the present invention.

Claims (8)

1. The self-adaptive data rate adjusting method based on the link margin and the signal-to-noise ratio weighting is characterized by comprising the following steps:
1) Calculating the instantaneous data extraction rate of a data packet counter in a network server platform;
2) Acquiring an ordered weighted average signal-to-noise ratio;
3) Adjusting the link margin parameters;
4) Acquiring an adjustment step number through a link margin signal-to-noise ratio;
5) Setting a loop starting condition, performing the operations of adjusting and reducing the spreading factor and adjusting the number of steps in a loop, and performing the step 6) or the step 7) when the loop is ended;
6) Cyclically executing the operations of adjusting the number of steps and transmitting power;
7) The operations of increasing the number of adjustment steps and transmitting power are cyclically performed.
2. The adaptive data rate adjustment method based on link margin and signal-to-noise ratio weighting of claim 1, wherein step 1) comprises:
the last n data packets of the wireless terminal comprising the data packet counter and the signal-to-noise ratio in the wireless network server platform are sorted into a set { a } according to the descending order of the signal-to-noise ratio of the data packets 1 ,a 2 ,…,a n "a 1 ≥a 2 ≥…≥a n To obtain the data packet signal-to-noise ratio vector A= (a) 1 ,a 2 ,…,a n ) The packet counter is incremented with each transmission and the instantaneous data extraction rate DER is calculated according to the following equation inst
Where LastCounter is the packet counter value of the last received packet of the n packets and FirstCounter is the packet counter value of the first received packet of the n packets.
3. The adaptive data rate adjustment method based on link margin and signal-to-noise ratio weighting of claim 1, wherein step 2) comprises:
by beta i Representing the ith data packetThe ordered weighted average weight vector of (c) is represented by B, i.e., b= (β) 1 ,β 2 ,…,β n ) T Wherein beta is i ∈[0,1]I is more than or equal to 1 and less than or equal to n, andset DER inst =δ, the ordered weighted average weight of the ith packet is obtained according to:
β 1 ＝δ n-1
0≤δ≤1
where δ=der inst N represents the last n packets of the wireless terminal in the network server platform containing the packet counter and the signal-to-noise ratio;
ordered weighted average signal-to-noise ratio SNR using ordered weighted average weight vector B according to owa The calculation is performed such that,
SNR owa =a.b, i.e
4. The adaptive data rate adjustment method based on link margin and signal-to-noise ratio weighting of claim 1, wherein step 3) comprises:
when the instantaneous data extraction rate is lower than the reference data extraction rate and the link margin parameter can be increased, increasing the link margin parameter until the instantaneous data extraction rate is equal to the reference data extraction rate;
when the instantaneous data extraction rate is larger than the reference data extraction rate and the link margin parameter is not lower than the threshold value, the instantaneous data extraction rate is reduced until the instantaneous data extraction rate is equal to the reference data extraction rate;
when the instantaneous data extraction rate is within a set range, the link margin parameter is kept unchanged;
the link margin parameter includes a margin_db parameter.
5. The adaptive data rate adjustment method based on link margin and signal-to-noise ratio weighting of claim 1, wherein step 4) comprises:
the method comprises the steps that an ordered weighted average signal-to-noise ratio is adopted to subtract a required signal-to-noise ratio and a link margin parameter to obtain a link margin signal-to-noise ratio, and then an adjustment step number is obtained through calculation of the link margin signal-to-noise ratio, wherein the required signal-to-noise ratio is set according to actual performance requirements;
the adjustment step number indicates the number of times of adjusting the transmission power and the spreading factor.
6. The adaptive data rate adjustment method based on link margin and signal-to-noise ratio weighting of claim 1, wherein the loop of step 5) performs the operations of adjusting the spreading factor and the number of adjustment steps, comprising: setting that when the adjustment step number is larger than 0 and the spreading factor is larger than 7, the spreading factor subtracting 1 and the adjustment step number subtracting 1 are circularly executed; in the operations of circularly executing the spreading factor reduction 1 and the adjustment step number reduction 1, the following judgment is carried out:
when the spreading factor is equal to 7 and the adjustment step number is greater than 0, ending the cycle and executing the step 6;
when the spreading factor is equal to 7 and the adjustment step number is smaller than 0, ending the cycle and executing the step 7;
when the spreading factor is equal to 7 and the number of adjustment steps is equal to 0, the algorithm is ended.
7. The adaptive data rate adjustment method based on link margin and signal-to-noise ratio weighting according to claim 1, wherein the cyclically performing the operations of adjusting the number of adjustment steps and the transmission power of step 6) includes: when the adjustment step number is greater than 0 and the transmission power is greater than the set minimum transmission power, the loop starts to execute the adjustment step number reduction 1 and the transmission power reduction 3 operations, and the following judgment is made in the loop execution of the adjustment step number reduction 1 and the transmission power reduction 3 operations:
when the number of the adjustment steps is smaller than 0, ending the cycle, and executing the step 7;
and ending the algorithm when the number of the adjustment steps is equal to 0 or the transmission power is smaller than the set minimum transmission power.
8. The adaptive data rate adjustment method based on link margin and snr weighting of claim 1 wherein the loop of step 7) performs the operations of increasing the number of adjustment steps and the transmission power, comprising: when the adjustment step number is smaller than 0 and the transmission power is smaller than the set maximum transmission power, the adjustment step number plus 1 and the transmission power plus 3 operations are cyclically executed, and the following judgment is made in the cyclic execution of the adjustment step number plus 1 and the transmission power plus 3 operations:
and ending the algorithm when the number of the adjustment steps is equal to 0 or the transmission power is larger than the set maximum transmission power.
CN202310789229.7A 2023-06-25 2023-06-29 Self-adaptive data rate adjustment method based on link margin and signal-to-noise ratio weighting Pending CN116723574A (en)

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