CN112020105B - LoRa transmission-based rate self-adaption method for power grid - Google Patents
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- H04W28/00—Network traffic management; Network resource management
- H04W28/16—Central resource management; Negotiation of resources or communication parameters, e.g. negotiating bandwidth or QoS [Quality of Service]
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- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S40/00—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them
- Y04S40/12—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them characterised by data transport means between the monitoring, controlling or managing units and monitored, controlled or operated electrical equipment
- Y04S40/126—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them characterised by data transport means between the monitoring, controlling or managing units and monitored, controlled or operated electrical equipment using wireless data transmission
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Abstract
The invention discloses a speed self-adaption method based on LoRa transmission for a power grid, which adopts different speed adjustment directions according to application types, divides power grid application into a deviation stabilization type application and a deviation speed type application, and respectively adopts speed adjustment schemes from low to high and from high to meet the requirements of the deviation stabilization type application on stability and the speed of the deviation speed type application; two application types are marked by using a reserved bit of an MAC header in an LoRa data packet so as to save the throughput overhead; and estimating the collision probability according to the number of the nodes, and designing a rate adjustment mechanism considering the node ratio so as to balance the collision probability of different rates and improve the reliability.
Description
Technical Field
The invention belongs to the field of wireless transmission of a power grid, and particularly relates to a rate self-adaption method based on LoRa transmission for the power grid.
Background
At present, electric meter remote centralized meter reading and distribution network terminal monitoring control communication of a domestic power grid are mainly public network wireless communication, and the problems of high communication charge, many base station signal coverage blind areas, unstable signals, large data delay, frequent disconnection and the like exist. By adopting a LoRa equipment construction wireless private network mode, the success rate, stability and reliability of meter centralized reading and distribution network automatic switch and terminal communication can be improved, and the communication charge can be further reduced.
In the intelligent power grid management proposed in the past, data collection is directly performed by adopting an LoRa node. The rate adaptation scheme used by LoRaWAN is simple, it adjusts the rate based on throughput, the rate adjustment is slow, requiring thousands of seconds to converge to a suitable rate. And, its rate adaptation scheme does not take into account packet loss caused by collisions between nodes. However, the existing proposed LoRa rate adaptive algorithm is based on the estimation of the channel state, such as SNR, and directly maps to a corresponding rate, and this algorithm can quickly adjust the rate, but since LoRa works in an environment below the noise level and is submerged by noise, the estimation of SNR is not accurate, and the selected rate is also not accurate.
Therefore, the rate adaptive scheme of LoRaWAN is slow in convergence, and is not suitable for power grid applications with high rate requirements (such as real-time monitoring applications of distribution box temperature, voltage parameters and the like, which require continuous data transmission); whereas SNR-based schemes do not map exactly to the appropriate rate,
the risk of packet loss exists, and the method is not suitable for power grid applications with higher stability requirements than speed requirements (such as remote meter reading and other applications, only data needs to be transmitted intermittently).
Disclosure of Invention
Aiming at the defects of the prior art, the invention aims to solve the problem that when a unified rate self-adaptive scheme is adopted for a node, the requirement of an intermittent transmission type power grid application on the transmission rate and the requirement of a continuous transmission type power grid application on the stability of a transmission link cannot be met simultaneously.
In order to achieve the above object, an embodiment of the present invention provides a rate adaptive transmission method based on LoRa transmission for a power grid, including the following steps:
s1: the terminal node classifies the transmitted application type and uses a flag bit to represent;
s2: the terminal node transmits first frame data to the LoRa gateway by using SF 12;
s3: the LoRa gateway estimates SNR according to the received data packet, selects a rate SF B for the node by combining the SNR and the application type, and sends the rate SF B to the terminal node through ACK;
s4: the terminal node selects a corresponding rate to transmit the next frame data according to the ACK information, wherein M is 1;
s5: the LoRa gateway counts the number N of received data packets of the node, if N is greater than 20, the packet receiving rate N/M of the node is calculated, if the packet receiving rate of the current rate is greater than 90%, the rate SF C to be increased is SF B-1, and if the current packet receiving rate is less than 60%, the rate SF C to be decreased is SF B + 1;
s6: the LoRa gateway predicts the collision probability of the speed SF C for the speed SF C to be selected, if the collision probability of the speed SF C is judged to be higher and the node number ratio of the speed SF C is larger than a threshold value, the speed is not changed, and the speed SF B is continuously used; if the collision probability is judged to be low, changing the rate, selecting the rate SF C, sending the selected rate to the terminal node through ACK, and returning N and M to zero;
s7: the terminal node selects a corresponding rate to transmit the next frame data, M +1, according to the ACK information;
s8: repeating the steps S6-S7 until the terminal node is disconnected;
specifically, in step S1, the application type is classified as either a biased-stable type application or a biased-rate type application.
Specifically, in step S1, the one-bit flag is embedded in the MAC header of the data frame, and the fourth bit of the MAC header is reserved as the flag.
Specifically, in step S3, a rate SF is selected for the node according to the SNR and the application type, a rate a corresponding to the SNR is obtained according to the SNR, and if the gateway knows that the application type is a biased-to-stable application from the flag, a rate B is selected as a +1 for the terminal node; if the gateway knows that the application type is the biased rate application from the zone bit, the gateway selects a rate B as A-1 for the terminal node.
Specifically, in step S6, the collision probability of the rate C is estimated according to the formula
Wherein N is the number of nodes using the rate C, N _ C is the number of sub-channels, T is the transmission duration of the data packet, and lambda is the number of packets sent in unit time of the node.
Specifically, in step S6, the threshold values of the node count ratio of the rate SF C from SF7 to SF12 are 45.6%, 25.5%, 14.6%, 7.4%, 4.6%, and 2.3%, respectively, and when the respective rate node count ratios meet the threshold values, their collision probabilities are equal.
A second aspect of the present invention is directed to a computer device comprising a memory, a processor and a computer program stored on the memory and capable of running on the processor, the processor implementing the method as described above when executing the computer program.
It is an object of a third aspect of the invention to provide a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the method as described above.
Generally, compared with the prior art, the above technical solution conceived by the present invention has the following beneficial effects:
1. according to the observation that different power grid applications have different requirements on stability and speed, the method classifies the applications, and adopts a speed regulation scheme from low to high for the applications with high requirements on stability, so that the applications can quickly converge to a stable transmission speed; for the application with high requirement on the speed, a speed regulation scheme from high to low is adopted, so that the application converges to a high transmission speed as soon as possible.
2. The invention integrates the estimation of the collision probability into the rate self-adaptive scheme, compares the collision probability of the target rate before adjusting the rate to balance the collision probability of different rates and improve the reliability.
Additional advantages, objects, and features of the invention will be set forth in part in the description which follows and in part will become apparent to those having ordinary skill in the art upon examination of the following or may be learned from practice of the invention. The objectives and other advantages of the present invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
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In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be further described in detail with reference to the accompanying drawings, in which:
FIG. 1 is an overall architecture of the present invention;
fig. 2 shows a LoRa packet structure, and the flag bits used in the present invention are located in the MAC header;
Detailed Description
Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. It should be understood that the preferred embodiments are illustrative of the invention only and are not limiting upon the scope of the invention.
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The invention adopts the LoRa wireless technology which is a low-power local area network wireless standard established by semtech company, the low power consumption is generally difficult to cover a long distance, and the long distance is generally high in power consumption. The Long Range Radio (Long Range Radio) is named as the Long Range Radio, and has the greatest characteristic that the Long Range Radio is longer than the propagation distance of other Radio modes under the same power consumption condition, the unification of low power consumption and Long Range is realized, and the Long Range Radio is 3-5 times longer than the traditional Radio frequency communication distance under the same power consumption condition.
Fig. 1 is a block diagram of a system architecture provided by the present invention. As shown in fig. 1, the terminal node of the power grid is connected to the LoRa gateway through a wireless network. The terminal node sends a data packet to the LoRa gateway, if the data packet is sent for the first time, the application type is marked by a one-bit flag bit, and SF12 is selected to send the data packet; if not, selecting the corresponding rate to send according to the indication in the received ACK. After receiving the data packet, if the data packet is the first packet of the node, the gateway firstly infers a rate SF primarily through an SNR (signal to noise ratio), and then selects the rate to be SF +1 or SF-1 by combining with an application type; if the data packet is not the first data packet, firstly judging whether the rate needs to be adjusted according to the packet receiving condition, then judging the conflict probability of the target rate, and if the conflict probability is low, adjusting the rate to the target rate.
The invention provides a rate self-adaptive transmission method based on LoRa transmission for a power grid, which comprises the following steps:
s1, classifying the application type transmitted by a terminal node into a biased stable application or a biased rate application by the terminal node, and representing by using a flag bit;
fig. 2 shows a packet structure of LoRa. Wherein, the 2 to 4 bits in the MAC header are reserved bits, no information is transmitted, and the default is set to zero. Therefore, the invention uses the information and uses the fourth bit in the MAC header as a flag bit to make the terminal node indicate the application type, thereby not increasing extra throughput overhead. In this embodiment, the bias-stable application flag is set to 0, and the bias-rate application flag is set to 1.
S2, the terminal node transmits first frame data to the LoRa gateway through SF 12;
s3, the LoRa gateway estimates SNR (Signal to NOISE RATIO) according to the received data packet, selects a rate SF B for the node by combining the SNR and the application type, and sends the rate SF B to the terminal node through ACK (acknowledgement character);
in this embodiment, a preliminary inferred rate SF a is obtained according to SNR estimation, if the application type is biased towards stable application, the rate SF B is conservatively selected to be SF a +1, and if the packet rate of the rate SF B is higher, the rate SF a is tried to be used again. If the application type is biased rate type application, a higher rate SF B is selected as SF a-1, and if the packet rate of rate SF B is higher, rate SF a is not tried.
S4, the terminal node selects a corresponding rate to transmit the next frame of data according to the ACK information, wherein M is 1; m is maintained by the terminal node and is used for storing the number of packets sent by the node, and the gateway calculates the packet receiving rate according to the value of M.
S5, the LoRa gateway counts the number N of received data packets of the node, if N is greater than 20, the packet receiving rate N/M of the node is calculated, if the packet receiving rate of the current rate is greater than 90%, the rate SF C is planned to be increased to be SF B-1, and if the current packet receiving rate is less than 60%, the rate SF C is planned to be decreased to be SF B + 1;
s6, estimating the collision probability of the rate SF C by the LoRa gateway for the rate SF C to be selected, if the collision probability of the rate SF C is judged to be higher and the node number ratio of the rate SF C is larger than a threshold value, not changing the rate, and continuously using the rate SF B; if the collision probability is judged to be low, changing the rate, selecting the rate SF C, sending the selected rate to the terminal node through ACK, and enabling N and M to return to zero;
s7, the terminal node selects a corresponding rate to transmit the next frame data according to the ACK information, wherein the rate is M + 1;
s8, repeating the steps S6-S7 until the terminal node is disconnected.
Since the packet loss rate is determined by both the channel quality and the collision probability, the channel quality and the collision probability need to be considered comprehensively for adjusting the rate. For the ALOHA protocol adopted by LoRaWAN, the collision probability calculation formula is
Wherein N is the number of nodes using rate C, Nc is the number of sub-channels, lambda is the number of packets sent in unit time of node, T is the transmission time of data packet, and the calculation formula is
Wherein, BW is bandwidth, generally takes 125k/250k/500k, and Nsymbol is the number of symbols in the data packet.
And if p is greater than 15%, judging that the collision probability is higher, further comparing the node number ratio of the using rate C, and if the ratio is greater than a threshold value, determining that the collision probability of the node using the rate C is higher than the average value, selecting the rate C at the moment, and continuing to use the rate B without changing the rate. If p is less than or equal to 15%, the collision probability of the rate C is judged to be low, and the rate C can be selected.
When considering that collision probabilities are equal, the number of nodes at each rate is 45.6%, 25.5%, 14.6%, 7.4%, 4.6%, and 2.3% in the threshold ratios from SF7 to SF12, respectively. For the same packet length, the lower the rate, the longer the transmission duration, and the higher the collision probability, so if the collision probabilities are equal, the rate SF12 supports the lowest nodes. The invention adopts the LoRa technology, and realizes the adoption of flexible speed selection and speed self-adaptive adjustment modes for different power grid application requirements by adjusting different SF (six adjustable speeds of SF7-SF12 are available in LoRa).
It should be noted that any process or method descriptions in flow charts of the present invention or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and that the scope of the preferred embodiments of the present invention includes additional implementations in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present invention.
The logic and/or steps represented in the flowcharts or otherwise described herein, such as an ordered listing of executable instructions that can be considered to implement logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.
It should be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, and the program may be stored in a computer readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.
In addition, functional units in the embodiments of the present invention may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a stand-alone product, may also be stored in a computer readable storage medium.
The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
Finally, the above embodiments are only intended to illustrate the technical solutions of the present invention and not to limit the present invention, and although the present invention has been described in detail with reference to the preferred embodiments, it will be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions, and all of them should be covered by the claims of the present invention.
Claims (8)
1. A rate adaptation method for power grid based on LoRa transmission, the method comprising:
s1: the terminal node classifies the application type transmitted by the terminal node and uses a flag bit to represent the application type;
s2: the terminal node transmits first frame data to the LoRa gateway by using SF 12;
s3: the LoRa gateway estimates SNR according to the received data packet, selects a rate SF B for the node by combining the SNR and the application type, and sends the rate SF B to the terminal node through ACK;
s4: the terminal node selects a corresponding rate to transmit the next frame data according to the ACK information, wherein M = 1;
s5: the LoRa gateway counts the number N of received data packets of the node, if the N is greater than 20, the packet receiving rate N/M of the node is calculated, if the packet receiving rate of the current rate is greater than 90%, the rate is planned to be increased SF C = SF B-1, and if the current packet receiving rate is less than 60%, the rate is planned to be decreased SF C = SF B + 1;
s6: the LoRa gateway pre-estimates the collision probability of the speed SF C for the speed SF C to be selected, and judges that the collision probability is higher if p is more than 15 percent according to the calculated collision probability p; if p is less than or equal to 15%, judging that the collision probability is lower; if the collision probability of the rate SF C is judged to be higher and the node number ratio of the rate SF C is larger than the threshold value, the rate is not changed, and the rate SF B is continuously used; if the collision probability is judged to be low, changing the rate, selecting the rate SF C, sending the selected rate to the terminal node through ACK, and returning N and M to zero;
s7: the terminal node selects a corresponding rate to transmit the next frame data, M +1, according to the ACK information;
s8: the steps S6-S7 are repeated until the end node is disconnected.
2. The rate adaptation method for electric grid based on LoRa transmission according to claim 1, wherein: in step S1, the application type is classified as either a biased-stable type application or a biased-rate type application.
3. Rate adaptation method for electric networks based on LoRa transmission according to claim 1 or 2, characterized by: in step S1, the one-bit flag is embedded in the MAC header of the data frame, and the fourth bit of the MAC header is reserved as the flag.
4. The rate adaptation method for electric grid based on LoRa transmission according to claim 2, wherein: in step S3, selecting a rate SF for the node in combination with the SNR and the application type, first obtaining a rate a corresponding to the SNR according to the SNR, and if the gateway learns from the flag bit that the application type is a biased-to-stable application, selecting a rate B as a +1 for the terminal node; if the gateway knows that the application type is the biased rate application from the zone bit, the gateway selects a rate B as A-1 for the terminal node.
5. The rate adaptation method for electric grid based on LoRa transmission according to claim 1, wherein: in step S6, the collision probability of the rate C is estimated, and the formula is p = e -2NTλ/Nc Where N is the number of nodes using the rate C, Nc is the number of subchannels, T is the transmission duration of the data packet, and λ is the number of packets sent in a unit time of the node.
6. The rate adaptation method for electric grid based on LoRa transmission according to claim 1, wherein: in step S6, the threshold values of the ratio of the number of nodes of the rate SF C from SF7 to SF12 are 45.6%, 25.5%, 14.6%, 7.4%, 4.6%, and 2.3%, respectively, and when the ratio of the number of nodes of each rate meets the threshold values, the collision probabilities of the nodes are equal.
7. A computer apparatus comprising a memory, a processor, and a computer program stored on the memory and capable of running on the processor, wherein: the processor, when executing the computer program, implements the method of any of claims 1-6.
8. A computer-readable storage medium having stored thereon a computer program, characterized in that: the computer program, when executed by a processor, implements the method of any one of claims 1-6.
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