CN114501344B - Massive LoRa node rapid ad hoc network communication method based on wireless ranging technology - Google Patents
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Abstract
A wireless ranging technology-based massive LoRa node rapid ad hoc network communication method is applied to the technical field of wireless communication of seismic exploration nodes, and relates to equipment comprising: the system comprises a gateway and a terminal node, wherein the gateway is used for collecting data of the seismic exploration nodes in a centralized mode, and the seismic exploration nodes are used for collecting and transmitting required data. The method comprises the following steps: networking and communication are carried out between the LoRa gateway and the seismic exploration node, and quick networking is completed by adopting a wireless ranging technology, an improved K-Means unsupervised clustering grouping technology and a conflict back-off and frequency hopping mechanism; the LoRa terminal node enters a listening mode to wait for a gateway call. Each LoRa end node is identified by a mac address to facilitate point-to-point communication. The invention has the characteristics of networking grouping automation, networking rapidness and low power consumption of the seismic exploration nodes, and is very suitable for quality control detection of mass seismic exploration nodes.
Description
Technical Field
The invention belongs to the technical field of LoRa wireless communication, and particularly relates to a rapid self-networking communication method for massive LoRa nodes based on a wireless ranging technology.
Background
In the field of wireless communication technology, loRa wireless communication is one of the important technologies. LoRa refers to long-distance radio, is a linear frequency modulation spread spectrum modulation technology, and has the advantages of long transmission distance, low power consumption, flexible networking and the like, so that the linear frequency modulation spread spectrum modulation technology is widely applied to some industries. In the field of seismic exploration, traditional wired exploration is gradually banned by wireless exploration, while LoRa is also a preliminary corner in the field due to its advantages. A LoRa network system generally comprises a server, a gateway and terminal nodes, wherein the gateway and the server are generally connected through 5G/4G/3G/GPRS, the gateway and the terminal nodes are generally connected through a star network structure, and the LoRa gateway collects seismic exploration data collected by mass terminal nodes and reports the seismic exploration data to the server, so that how to efficiently networking and communicate the gateway and the terminal nodes is particularly important. For networking and communication of massive LoRa terminal nodes, the problems of high power consumption of the terminal nodes, long networking time consumption and the like often exist.
Chinese patent CN111107674a discloses a method for communication in a LoRa time packet network based on field animal monitoring equipment, which uses a time-sharing broadcasting mechanism to perform network communication, thereby implementing network communication of the LoRa. However, in the above method, each terminal node is connected to the network, the LoRa gateway needs to broadcast once, and each broadcast wakes up all terminal nodes to increase power consumption, and when a certain terminal node transmits data to the gateway, other irrelevant terminal nodes are waken up at the same time to further increase power consumption; and the terminal nodes are awakened to carry out networking in the monitoring mode for a certain period of time, when the number of the terminal nodes is large, the awakening time of each terminal node is accumulated, and the networking time consumption is greatly increased.
Therefore, in the prior art, a processing method for reducing the large-area wake-up terminal node is needed to reduce the power consumption of the LoRa terminal node, and a method for improving the networking communication speed of massive LoRa terminal nodes is needed to improve the networking efficiency.
Disclosure of Invention
In order to solve the problems, the invention provides a wireless ranging technology-based massive LoRa node rapid ad hoc network communication method which is suitable for quality control detection of massive seismic exploration nodes, realizes rapid automation of a networking process and easy operation of network management, and reduces node power consumption.
A wireless ranging technology-based massive LoRa node rapid ad hoc network communication method comprises the following steps:
step 1: the gateway and the terminal node utilize wireless signals to measure distance based on a mixed filtering method and a fitting method;
Step 2: the terminal nodes carry out self-adaptive grouping based on a K-Means unsupervised clustering improvement method, and the same group of terminal nodes are marked by the same group number;
Step 3: the gateway and the terminal node group the network based on the self-adaptive grouping technology, the conflict back-off and the frequency hopping mechanism of the step 2;
Step 4: the gateway and terminal internode functions include: when no operation is performed, the terminal node enters a monitoring mode; during point-to-point communication, the terminal node transmits the acquired data by using a short preamble sequence; broadcasting or point-to-point communication modes, the gateway changes the working state of a LoRa module of the terminal node; the gateway automatically ages the end node.
Further, the hybrid filtering method in the step 1 is to perform kalman filtering on the wireless signal and then perform mean filtering.
Further, in the fitting method in the step 1, a higher order polynomial is adopted to perform fitting solution on the test point data to obtain the optimized parameters.
Further, the K-Means unsupervised clustering improvement method in the step 2 is that the K value is dynamically controlled by the number of the terminal nodes, and the terminal nodes are divided into annular groups by adopting a one-dimensional K-Means clustering algorithm.
Further, in the step 3, the collision back-off method is to collect the instantaneous wireless signal intensity, if the instantaneous wireless signal intensity is greater than the specified threshold, the interference is judged to exist, and the random time delay back-off is performed, wherein the random number is constructed through the collected value of the wireless signal intensity.
Further, the frequency hopping mechanism method in the step 3 is to collect the instantaneous wireless signal intensity, if the instantaneous wireless signal intensity is larger than the specified threshold, the interference is judged, and random frequency conversion is carried out to enter the network, wherein the random number is constructed through the collected value of the wireless signal intensity.
Further, in the step 4, when no operation is performed, the terminal node enters a monitoring mode, specifically, enters a RxDutyCycle mode, and monitors the gateway call.
Further, in the step 4, during the peer-to-peer communication, the terminal internode transmits the collected data, specifically, the mac address of the terminal node is unique and the data is transmitted to the gateway by using the short preamble sequence.
Further, in the step 4, the gateway changes the working state of the LoRa module of the terminal node by broadcasting or in a peer-to-peer communication mode, specifically, the gateway modifies the parameters of the LoRa module of the terminal node by broadcasting or in a peer-to-peer wireless communication mode through a special frame format.
Further, in the step 4, the gateway automatically ages the terminal node, specifically, the terminal node uploads the heartbeat data packet to the gateway at regular time, and if the heartbeat data packet is overtime, the gateway performs aging treatment on the terminal node which does not upload the heartbeat data packet.
Compared with the prior art, the invention has the beneficial effects that at least:
1) And multiple gateways with different frequencies are adopted for networking in groups, so that the networking speed is increased, the networking time is reduced, and the rapid automation of the networking process is realized.
2) The networking process generates a lookup table of the mac address-distance correspondence of the terminal node, so that the terminal node can be aged, and the management of the lora network is facilitated.
3) In the networking process, the gateway only performs broadcast for several times, so that the number of times of waking up the terminal node is reduced, and the power consumption is reduced; when the terminal node communicates with the gateway, the probability of waking up the irrelevant node can be greatly reduced by adopting the short preamble sequence, thereby further reducing the power consumption.
4) The gateway can modify the relevant parameters of the terminal node through the lora wireless communication, thereby facilitating the user to change the working state of the terminal node.
Drawings
Fig. 1 is a block diagram of the gateway and end node architecture in an embodiment of the invention.
Fig. 2 is a graph of a polynomial algorithm fit in an embodiment of the present invention.
Fig. 3 is a simulation diagram of a LoRa networking site situation in an embodiment of the present invention.
Fig. 4 is a flow chart of end node networking communications in an embodiment of the invention.
Fig. 5 is a gateway networking communication flow diagram in an embodiment of the invention.
Detailed Description
The technical scheme of the invention is further described in detail below with reference to the attached drawings.
Fig. 1 shows a block diagram of the gateway and the terminal node structure of the present invention, in which the gateway is composed of five sub-gateways with different frequencies, the default sub-gateway communication frequency is freq1, and sub-gateways with other frequencies are all applied to frequency hopping communication. Default relevant parameters burnt in the terminal node equipment comprise: communication frequency, spreading factor, bandwidth, mac address, etc., wherein the communication frequency defaults to freq1.
The temporary site situation for the LoRa networking is: and a gateway and a large number of terminal nodes, wherein the terminal nodes are arranged in the range of the interception gateway according to actual measurement.
The invention relates to a wireless ranging technology-based massive LoRa node rapid ad hoc network communication method, which comprises the steps of ranging, networking, communication and the like, and specifically comprises the following steps:
step 1: and (5) ranging. The ranging process specifically comprises the following steps:
s1: establishing a ranging model:
the ranging model adopts a logarithmic attenuation model of wireless signal propagation:
Pr (d) is the power of the received signal obtained by the receiving end with the distance d of the transmitting end, and is generally replaced by Rssi value-Rc of the current position; pr (d 0) is usually taken as the power of a received signal obtained by a receiving end at a distance of 1m from the transmitting end, and is generally replaced by an Rssi value-R 1m at a distance of 1m from the transmitting end; n is a propagation factor and an environmental factor; xσ is a gaussian random variable with an average value of 0.
From the ranging model and the parameter simplification formula:
Rc＝R1m-10·n·log10d (2)
Further simplifying the distance d between the terminal node and the gateway:
s2: and (3) mixing and filtering:
The mean filtering refers to a process that a terminal node receives multiple Rssi values and calculates an arithmetic average value of the multiple Rssi values as a filtering result, so as to reduce errors caused by unstable factors, and for N sampling values, the following formula is given:
Kalman filtering is a recursive state space model based on an estimation algorithm, and is an optimal recursive data processing algorithm, which can reduce the influence of noise and interference in an observation data including a system.
The Kalman filtering algorithm abstract formula is as follows:
Pk＝APk-1AT+Q (6)
Kk＝PkHT(HPkHT+R)-1 (7)
P'k＝(I-KkH)Pk (9)
wherein, For the state value at time K, u k-1 is the control variable for the system at time K-1, P k is the error covariance at time K, Q is the process noise covariance, K k is the Kalman gain at time K, R is the measurement noise covariance,/>To correct the updated state value, y k is the measurement at time k, P' k is the corrected updated error covariance, I is the identity matrix, A, B and H are system parameters.
And (3) embodying abstract parameters by combining the ranging model established in the step (S1): no system control variable exists in the ranging model, and Bu k-1 =0; under the condition of no system control variable, as the measured variable is the instantaneous Rssi value, the Rssi value is unchanged at the previous moment and the next moment, and a=1; h=1. After simplification, the Kalman filtering algorithm formula is as follows:
Kk＝(Pk-1+Q)(Pk-1+Q+R)-1 (10)
P'k＝(1-Kk)(Pk-1+Q) (12)
wherein, Specifically, the updated Rssi value, and y k is specifically the current Rssi value, i.e., R c.
The Kalman algorithm comprises the following specific implementation steps: first initialize P 0(P0 +.0) andPredicting the Rssi value at the k moment by the optimal Rssi value at the k-1 moment, predicting the error covariance at the k moment by the error covariance at the k-1 moment and the error covariance at the k moment by the process noise, calculating the Kalman gain, and finally correcting and updating the predicted Rssi value.
Step of mixed filtering: the acquired instantaneous Rssi value is subjected to Kalman filtering, then the result of the Kalman filtering is subjected to average filtering, and the result of the average filtering is output as the result of the mixed filtering.
S3: parameter optimization:
in the formula (3), R 1m can be obtained through actual measurement; n can be obtained by two known sets of R c and d, but R 1m and n will change with the surrounding environment, in order to make the ranging more accurate, it is necessary to perform on-site measurement and fit in combination with a fitting algorithm to obtain more appropriate parameters, and the fitting algorithm adopts a polynomial regression algorithm.
After simplifying the formula (2), carrying out N-order Taylor expansion:
Then there are fitting parameters:
The specific steps of parameter optimization are as follows:
1) Samples are collected every 2m within 100 m; samples are collected every 100m from 100m to 3000 m.
2) And carrying out mixed filtering on the instantaneous Rssi sample values at different distances to obtain a filtered stable value.
3) The values of R 1m and n are calculated using a polynomial regression algorithm: r 1m = -32.121, n= 3.029. The fitted curve is shown in figure 2.
S4: substituting the value after parameter optimization into the formula (3), and finally simplifying the ranging formula into:
S5: the specific implementation steps of the ranging are as follows:
1) The sub-gateway 1 with frequency freq1 continuously broadcasts for the terminal node to range.
2) The terminal node samples the instantaneous Rssi value, the output result after mixed filtering is substituted into a ranging formula (16), and the distance between the terminal node and the gateway is calculated.
Step 2: grouping. The grouping process specifically comprises the following steps:
The K-Means method is one of ten classic algorithms in clustering, data mining. The algorithm accepts the parameter k and then divides the n data objects input in advance into k clusters so that the obtained clusters satisfy that the object similarity in the clusters is higher, while the object similarity in the different clusters is smaller.
The self-adaptive grouping adopts an improved algorithm of K-Means, and the LoRa node is divided into annular groups by utilizing a one-dimensional K-Me ans algorithm, and the specific steps are as follows:
S1: determining a K value;
s2: selecting K points from the original data set as initial mean points;
S3: sequentially taking out data from the original data set, respectively calculating distances (Euclidean distances among default calculation points) between each data and K mean points when one data is taken out, and classifying a mean point as a cluster where the mean point is located when the mean point is closer;
S4: after the step S3 is finished, calculating the current mean value points of each cluster (namely, calculating the mean value of all points in the cluster);
s5: comparing whether the current mean point is the same as the mean point obtained in the last step, if so, ending the K-Means algorithm, otherwise, replacing the current mean point with the previous mean point, and repeating the step S3.
Clustering the terminal nodes by using the distance measured in the step 1 and the self-adaptive grouping algorithm (k=4) in the step 2, and clustering the terminal nodes into four groups according to the LoRa networking field situation simulation diagram shown in fig. 3: a first group: 0 to L1, second group: l1 to L2, third group: l2 to L3, fourth group: L3-L4, wherein 0< L1 < L2 < L3 < L4. After the clustering grouping is completed, the nodes of the group are marked, and if the group number of all the terminal nodes of the first group is marked as 1. The correspondence between nodes and packets is shown in the following table:
step 3: networking. The networking process specifically comprises the following steps:
s1: the sub-gateway 1 with frequency freq1 broadcasts a networking request packet.
S2: and the terminal nodes start to access the network from the near to the far according to the self-adaptive grouping, and if one group of terminal nodes are accessing the network, the other groups of terminal nodes enter a low-power consumption monitoring mode and wait for the last group to finish accessing the network again. The network access process specifically comprises the following steps:
1) The first group of terminal nodes are accessed to the network preferentially, and other groups of terminal nodes enter a low-power consumption monitoring mode. When terminal nodes in the first group access the network, channel conflict detection is firstly carried out, if other terminal nodes are accessing the network, namely, the instantaneous Rssi value is larger than a specified threshold value, random back-off collision prevention is carried out, wherein the random back-off times are fixed, and the random numbers are constructed through the instantaneous Rssi value.
2) And if the limit number of the back-off times is reached, frequency hopping is carried out, and after the frequency hopping, the anti-collision step of the step 1) is repeated until the network access of all the terminal nodes in the first group is successful.
3) The gateway broadcasts again, the second group of terminal nodes access the network, and the steps 1) and 2) are repeated until all terminal nodes access the network successfully.
Step 4: in the process from the start of networking to the completion of networking, the terminal node enters the network with the local mac address and the distance measured in the step 1, and the gateway finally generates a lookup table of the mac address-distance correspondence of the terminal node.
Step 5: after networking is completed, when no operation is performed, the terminal node enters RxDutyCycle mode to monitor gateway call and wait for point-to-point communication request; the terminal node transmits the heartbeat data packet to the gateway at regular time, otherwise, the timeout gateway can age the terminal node, namely deleting the related lookup table information of the terminal node; when the terminal node performs point-to-point communication to the gateway, a short preamble sequence is adopted for communication, and the probability of waking up other irrelevant nodes can be greatly reduced.
According to step 4, the gateway has stored the mac address-distance correspondence associated with the terminal node, which correspondence is also stored in the terminal node. When the gateway has operation, namely point-to-point communication is carried out, the gateway broadcasts a communication data packet which contains the corresponding relation of mac address-distance, the terminal node compares the mac address of the terminal with the communication data packet, if the mac address of the terminal node is different from the communication data packet, the communication data packet is ignored, and then the gateway enters RxDutyCycle mode immediately to monitor the gateway call; and if the data packet is the same, the terminal node receives the communication data packet and analyzes the content of the communication data packet, and performs related acquisition operation.
When the terminal node communicates with the gateway, the terminal node sets a short preamble sequence, then transmits a communication data packet, wherein the communication data packet comprises the updated mac address-distance correspondence, and after the gateway receives the communication data packet, the gateway analyzes the data packet content and updates the corresponding lookup table content.
And (3) automatically aging the terminal nodes of the gateway, uploading the heartbeat data packets to the gateway by the terminal nodes at regular time, and aging the terminal nodes which do not upload the heartbeat data packets by the gateway when the heartbeat data packets are overtime.
According to the embodiment, the LoRa network can be quickly established, the networking process of the network is automatic, the aging treatment of old equipment is supported, the networking speed of the LoRa network is improved, and the operation difficulty is reduced; the terminal node transmits data through the short preamble sequence, so that the probability of waking up other irrelevant nodes is greatly reduced, and the power consumption of the terminal node is reduced; supporting the air awakening and wireless modification of the LoRa parameters of the terminal node, and facilitating the user to remotely change the working state of the terminal node through the gateway.
The above description is merely of preferred embodiments of the present invention, and the scope of the present invention is not limited to the above embodiments, but all equivalent modifications or variations according to the present disclosure will be within the scope of the claims.
Claims (7)
1. A wireless ranging technology-based massive LoRa node rapid ad hoc network communication method is characterized by comprising the following steps of: the method comprises the following steps:
Step 1: the gateway and the terminal node utilize wireless signals to measure distance based on a mixed filtering method and a fitting method; the mixed filtering method is that the wireless signal is firstly subjected to Kalman filtering and then is subjected to mean filtering; the fitting method is to adopt a higher order polynomial to carry out fitting solution on test point data to obtain an optimized parameter;
Step 2: the terminal nodes carry out self-adaptive grouping based on a K-Means unsupervised clustering improvement method, and the same group of terminal nodes are marked by the same group number; the K-Means unsupervised clustering improvement method is that the K value is dynamically controlled by the number of terminal nodes, and the terminal nodes are divided into annular groups by adopting a one-dimensional K-Means clustering algorithm;
Step 3: the gateway and the terminal node group the network based on the self-adaptive grouping technology, the conflict back-off and the frequency hopping mechanism of the step 2;
Step 4: the gateway and terminal internode functions include: when no operation is performed, the terminal node enters a monitoring mode; during point-to-point communication, the terminal node transmits the acquired data by using a short preamble sequence; broadcasting or point-to-point communication modes, the gateway changes the working state of a LoRa module of the terminal node; the gateway automatically ages the end node.
2. The rapid self-networking communication method of massive LoRa nodes based on the wireless ranging technology as set forth in claim 1, wherein the method comprises the following steps: in the step 3, the collision back-off method is to collect the instantaneous wireless signal intensity, if the instantaneous wireless signal intensity is larger than the appointed threshold, the interference is judged to exist, and the random time delay back-off is carried out, wherein the random number is constructed through the collected value of the wireless signal intensity.
3. The rapid self-networking communication method of massive LoRa nodes based on the wireless ranging technology as set forth in claim 1, wherein the method comprises the following steps: the frequency hopping mechanism method in the step 3 is to collect the instantaneous wireless signal intensity, if the instantaneous wireless signal intensity is larger than the appointed threshold value, the interference is judged, the random frequency conversion is carried out, and the random number is constructed through the collected value of the wireless signal intensity.
4. The rapid self-networking communication method of massive LoRa nodes based on the wireless ranging technology as set forth in claim 1, wherein the method comprises the following steps: in the step 4, when no operation is performed, the terminal node enters a monitoring mode, specifically, enters a RxDutyCycle mode, and monitors the gateway call.
5. The rapid self-networking communication method of massive LoRa nodes based on the wireless ranging technology as set forth in claim 1, wherein the method comprises the following steps: in the step 4, during the peer-to-peer communication, the terminal internode transmits the collected data, specifically, the mac address of the terminal node is unique and the data is transmitted to the gateway by using the short preamble sequence.
6. The rapid self-networking communication method of massive LoRa nodes based on the wireless ranging technology as set forth in claim 1, wherein the method comprises the following steps: in the step 4, the gateway changes the working state of the LoRa module of the terminal node by broadcasting or in a peer-to-peer communication mode, specifically, the gateway modifies the parameters of the LoRa module of the terminal node by broadcasting or in a peer-to-peer wireless communication mode through a special frame format.
7. The rapid self-networking communication method of massive LoRa nodes based on the wireless ranging technology as set forth in claim 1, wherein the method comprises the following steps: in the step 4, the gateway automatically ages the terminal node, specifically, the terminal node uploads the heartbeat data packet to the gateway at regular time, and if the heartbeat data packet is overtime, the gateway performs aging treatment on the terminal node which does not upload the heartbeat data packet.
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