CN109526012A - A kind of LoRaWAN network spreading factor distribution method based on reliability - Google Patents
A kind of LoRaWAN network spreading factor distribution method based on reliability Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
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- H—ELECTRICITY
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- 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
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Abstract
The LoRaWAN network spreading factor distribution method based on reliability that the present invention relates to a kind of, belongs to low-power consumption wide area network wireless technical field.This method is lost packet-dropping model, initializes each node spreading factor, obtain spreading factor initial proportion collection M according to the receiving sensitivity threshold value and path loss characteristics of LoRa node, build pathinit；Secondly, analysis LoRa Data Transmission Feature, introduces spreading factor accounting Ps, establish data transmission success, spreading factor and PsRelational model, determine optimization spreading factor proportion set Mfair；Finally, according to MinitUsing the spreading factor of LoRa-FDF Developing Tactics difference node, improve data transfer success rate increases the reliability of network.
Description
Technical field
The invention belongs to low-power consumption wide area network wireless technical fields, are related to a kind of LoRaWAN network expansion based on reliability
Frequency factor distribution method.
Background technique
LoRa low-power consumption wan technology has the characteristics that low in energy consumption, long transmission distance.LoRaWAN agreement supports a variety of speed
Rate selection, communication distance and transmission rate are inversely, that is to say, that the distance of the faster communication of the rate of selection is also more
It is short.Simultaneously because use spread spectrum, due to the spreading factor used under different rates be it is mutually orthogonal, so each data
Data transmission between transmission rate will not conflict mutually.According to LoRa characteristic it is found that when one timing of bandwidth and code rate, LoRa's
Transmission rate is determined by spreading factor, and gateway can receive the data of different spreading factors simultaneously.But different spread spectrums are always
Between rate great disparity it is larger, when transmit equal length data when, Channel holding time also differs larger.If being only difference
Spreading factor distributes the node of identical quantity, then can generate the difference of different rates collision probability and cause to transmit inequitable existing
As.And this unjustness will lead to low rate (high spreading factor) and cause a large amount of packet losses because of higher collision probability, shadow
Node is also added while ringing network stabilization because the increase of bring node power consumption is retransmitted repeatedly, to spreading factor
Allocation strategy research it is very significant.
Summary of the invention
In view of this, the purpose of the present invention is to provide a kind of, the LoRaWAN network spreading factor based on reliability is distributed
Method, this method are mainly executed by LoRa gateway, final to improve in conjunction with the spreading factor of LoRaWANMAC agreement setting node
The reliability of LoRaWAN network.
In order to achieve the above objectives, the invention provides the following technical scheme:
A kind of LoRaWAN network spreading factor distribution method based on reliability, this method specifically includes the following steps:
S1: according to the receiving sensitivity threshold value and path loss characteristics of LoRa node, packet-dropping model is lost in build path, just
The each node spreading factor of beginningization obtains spreading factor initial proportion collection Minit；
S2: by LoRa Data Transmission Feature and spreading factor accounting P is introduceds, establish data transmission success, spreading factor
And PsRelational model；
S3: by the relational model of S2, the spreading factor allocation strategy of optimization is established, the spreading factor proportion set optimized
Mfair；
S4: the proportion set obtained in conjunction with S1 and S3, using the spreading factor of LoRa-FDF Developing Tactics difference node, to mention
High data transmission success.
Further, in the step S1, according to the receiving sensitivity threshold value and path loss characteristics of LoRa node, road is constructed
Packet-dropping model is lost in diameter, initializes each node spreading factor, obtains spreading factor initial proportion collection Minit, include the following:
The minimum receiving sensitivity S of different spreading factorsSF[i]For threshold value, only in received signal strength Pr(d)=Ptx+G-
Lpl(d) it is greater than SSF[i]Shi Caineng is unpacked；The packet loss as caused by path loss is expressed as follows:
Pper(d, S)=P { Pr(d) > SSF[i]i∈{7,8,9,...,12}}
=P { Ptx+G-Lpl(d) > SSF[i]i∈{7,8,9,...,12}}
Wherein, SSF[i]For the receiving sensitivity threshold value of spreading factor i, G is antenna gain, PtxFor transimission power, Lpl(d)
Indicate Lognormal shadowing path loss, the distance of d node to gateway；
Spreading factor original allocation is carried out as restrictive condition according to path loss packet loss condition, steps are as follows:
S11: node is initialized with highest spreading factor, i.e. SF [m]=12, m ∈ [1, N], wherein N indicates network node
Total quantity；
S12: for a period of time after stablizing, gateway saves the RSSI value information of node, and presses descending row for the network operation
Sequence is put into set RSSI []；
S13: judged according to path loss packet loss, i.e. Ptx+G-Lpl(d) > SSF[j], wherein j ∈ { y7,8,9 ..., 12 },
Circulation j=7:1:12 is executed, if RSSI [m] > SSF[j], then SF [m]=j；
S14: counting each spreading factor number of nodes, obtains spreading factor ratio set Minit={ Minit|Minit,i=Pi,i
∈ { 7,8,9 ..., 12 } }, wherein PiIndicate the ratio for the total node of node Zhan that spreading factor is i in original allocation.
Further, in the step S2, by LoRa Data Transmission Feature and spreading factor accounting P is introduceds, establish data biography
Defeated success rate, spreading factor and PsRelational model, include the following:
Assuming that network node is evenly distributed in gateway areas, on this basis, LoRa spreading factor S and spread spectrum are introduced
Factor accounting PsAs new variable, the node-node transmission success rate that spreading factor is S is obtained according to Poisson distribution are as follows:
Wherein S indicates that spreading factor, L indicate that data length, BW indicate bandwidth, and N indicates node total number amount, TiIndicate data
Transmission Time Interval, PsIndicate that spreading factor is the ratio of the total node of node Zhan of S.
Further, in the step S2, by the relational model of S2, the spreading factor pro rate strategy of optimization is established, is obtained
To the spreading factor proportion set M of optimizationfair, include the following:
(a) spreading factor best proportion distributes: being defined as when being disposed using the distribution of spreading factor best proportion, no
It is identical with the data transmission success of spreading factor node, it indicates are as follows:
Wherein, PiAnd PjIndicate the ratio of total node shared by spreading factor i and j, Pder(i,Pi) and Pder(j,Pi) difference table
Show their data transmission success；When spreading factor allocation proportion collection is equal to MfairWhen, belong to best proportion distribution:
Best proportion distributes Rule of judgment: according to MfairWith MinitBetween proportional difference K between each spreading factormCome
Judge whether original allocation can be converted into best proportion distribution:
Km={ mi|mi=Minit,i-Mfair,i,i∈{7,8,9,...,12}}
When the condition 1 of satisfaction, then original allocation can not be converted into best proportion distribution:
Condition 1
Condition 1 indicates that there are a spreading factor j, so that in the sum of [j, 12] section proportional difference less than zero or m7It is small
In the case where zero, then it cannot be distributed by initial proportion and be converted into best proportion distribution；
(b) spreading factor suboptimum pro rate: the target of suboptimum pro rate becomes finding most data transmission success
Equal spreading factor group, and and the data transmission success of non-guaranteed all spreading factors be equal, it may be assumed that
max∑H(Pder(i,Pi)=Pder(j,Pj)),i,j∈{7,8,9,...,12},i≠j
Wherein, H is indicator function, and bracket conditional is if true, be 1, vacation is 0；
It allows spreading factor primary election ratio set and Optimal Distribution ratio set to be compared, is greater than or equal to optimum allocation plan
Slightly proportion set shares CbIt indicates:
Cb=b | Minit,b≥Mfair,bor Minit,b=0 }
Belong to set CbSpreading factor optimize processing again, for CbIn each spreading factor b for, institute
The ratio summation of the total node N of Zhan is set asSo to belonging to CbIn spreading factor optimize and handle according to (a):
Wherein S expression meets CbSpreading factor；
So suboptimum allocation proportion collection are as follows:
Further, in the step S3, in conjunction with the proportion set that S1 and S3 are obtained, using LoRa-FDF Developing Tactics difference section
Point spreading factor include the following: with improve data transfer success rate
S31: spreading factor ratio distribution M is obtained according to spreading factor original allocation firstinit={ Minit{Minit=Pi,i
∈{7,8,9,...,12}}；
S32: compare initial proportion distribution MinitM is distributed with best proportionfairIn each spreading factor accounting, if the expansion of primary election
Frequency Factor minute cloth meets Optimal Distribution network Rule of judgment Mfair_condition, then spreading factor is distributed according to this distribution；If no
Meet, then judge whether it can be converted into Optimal Distribution, Rule of judgment is as follows:
Condition 1
S33: if best proportion distribution can be converted to, gateway collect again and save the RSSI value information of node in
It in RSSI [], sorts again to set RSSI [], is distributed M according to best proportionfairAnd according to high RSSI value using low spread spectrum because
Son, low RSSI value are redistributed using high spreading factor principle.
S34: being that node distributes spreading factor according to suboptimum allocation strategy, secondary if Optimal Distribution can not be converted into
In excellent allocation strategy, the node that spreading factor is i is rejected, optimum allocation is carried out to remaining node, specific strategy is as follows:
(1) if mi< 0, i ∈ { 7,8,9 ..., 12 }, then re-start S32 to i+1, Rule of judgment becomes:
Condition 2Wherein k ∈ { i+1 ..., 12 }, mk∈Km
(2) if meeting condition 2, to i+1 and thereafter spreading factor, recalculate its optimum allocation ratio and according to
S33 distributes spreading factor.
The beneficial effects of the present invention are: network spreading factor is obtained by comprehensively considering path loss packet loss appraising model
Initial distribution, and LoRa spreading factor accounting and accordingly is introduced in the data transmission success relational model based on Poisson distribution
It is proposed spreading factor pro rate strategy and spreading factor allocation algorithm.The present invention can be realized the spread spectrum of LoRaWAN network because
Son distribution, improves the reliability of network.
Detailed description of the invention
In order to keep the purpose of the present invention, technical scheme and beneficial effects clearer, the present invention provides following attached drawing and carries out
Illustrate:
Fig. 1 is system global structure figure of the invention；
Fig. 2 is original allocation strategic process figure of the invention；
Fig. 3 is LoRa-FDF spreading factor allocation strategy flow chart.
Specific embodiment
Below in conjunction with attached drawing, a preferred embodiment of the present invention will be described in detail.
As shown in Fig. 1 system global structure figure of the present invention, it is broadly divided into following steps: S1: according to the reception of LoRa node
The threshold of sensitivity and path loss characteristics, build path are lost packet-dropping model, initialize each node spreading factor, spread
Factor initial proportion collection Minit；S2: by LoRa Data Transmission Feature and spreading factor accounting P is introduceds, establish data transmission success
Rate, spreading factor and PsRelational model；S3: by the relational model of S2, the spreading factor allocation strategy of optimization is established, is obtained excellent
The spreading factor proportion set M of changefair；S4: the proportion set obtained in conjunction with S1 and S3, using LoRa-FDF Developing Tactics difference node
Spreading factor, with improve data transfer success rate.
S1: according to the receiving sensitivity threshold value and path loss characteristics of LoRa node, packet-dropping model is lost in build path, just
The each node spreading factor of beginningization obtains spreading factor initial proportion collection Minit, include the following:
According to LoRa practical application scene and network large scale deployment feature, consider using consideration large-scale fading Pp(d)
With shadow effect PsLognormal shadowing path loss model Lpl(d), free space loss model, the loss model energy are compared
Enough more accurately reaction Actual path losses, are expressed as follows:
Lpl(d)=Lpl(d0)+10γl
Wherein, d is distance of the terminal node to gateway, d0For reference distance, Lpl(d0) damaged for the path under reference distance
Consumption, γ is path loss index, X0Indicate that mean value is 0, standard deviation is the normal distribution of δ.
According to transmission power PtxRecipient's received signal strength P is obtained with antenna gain Gr(d):
Pr(d)=Ptx+G-Lpl(d)
With the minimum receiving sensitivity S of receiving end under different spreading factorsSF[i]For threshold value, signal only is received in recipient
Intensity Pr(d) it is greater than SSF[i]Shi Caineng is unpacked；So the drop probabilities as caused by path loss are expressed as follows:
Pper(d, S)=P { Pr(d) > SSF[i]}
=P { Ptx+G-Lpl(d) > SSF[i]}
Wherein, SSF[i]Meet following relationship:
SSF[i]=-174+10log (BW)+NF+SNRSF[i]
Wherein, NF is the noise coefficient of recipient, and BW is bandwidth, and SNR is the modulated letter under different spreading factor SF [i]
It makes an uproar ratio.
Table 1 is the measured data of receiving sensitivity threshold value under different spreading factor/bandwidth, and table 2 is the relationship of SNR and SF,
Only in recipient's received signal strength Pr(d) it is greater than SSF[i]Shi Caineng is unpacked.
The minimum receiving sensitivity of spreading factor under 1 different bandwidth of table
The relationship of table 2 SNR and SF
| SF | 7 | 8 | 9 | 10 | 11 | 12 |
| SNR | -6 | -9 | -12 | -15 | -17.5 | -20 |
According to fig. 2 and path loss packet loss condition is combined to carry out spreading factor original allocation as restrictive condition, step is such as
Under:
STEP1: node is initialized with highest spreading factor, i.e. SF [m]=12, m ∈ [1, N], wherein N indicates network internal segment
Point total quantity；
STEP2: the network operation is for a period of time after stablizing, and gateway saves the RSSI value information of node, and by descending
Sequence is put into set RSSI []；
STEP3: judged according to path loss packet loss, i.e. Ptx+G-Lpl(d) > SSF[j], wherein j ∈ y7,8,9 ...,
12 }, circulation j=7:1:12 is executed, if RSSI [m] > SSF[j], then SF [m]=j；
STEP4: counting each spreading factor number of nodes, obtains spreading factor ratio set Minit={ Minit|Minit,i=
Pi,i∈{7,8,9,...,12}}。
S2: by LoRa Data Transmission Feature and spreading factor accounting P is introduceds, establish data transmission success, spreading factor
And PsRelational model, include the following:
Assuming that network node is evenly distributed in gateway areas, on this basis, LoRa spreading factor is introduced as new
Variable, first consider in network the case where there is only a kind of spreading factors, can be obtained according to Poisson distribution:
Wherein, GSGenerated in network during indicating to send the data packet that spreading factor is S have same spread because
The quantity P of subdata packetder(S,PS) indicate data packet transmission success rate in spreading factor S lower a period of time.The transmission of data packet
Time TSIt is expressed as follows:
TS=L/Rb
Wherein L indicates data packet length, RbIndicate bit rate,The flow generated in unit time
λ is as follows:
λ=N/Ti
ThereforeTherefore deduce that one data of spreading factor S transport are bundled into function
By the received probability of gateway:
Wherein S indicates that spreading factor, L indicate that data length, BW indicate bandwidth, and N indicates node total number amount, TiIndicate data
Transmission Time Interval, PsIndicate that spreading factor is the ratio of the total node of node Zhan of S.
S3: by the relational model of S2, the spreading factor pro rate strategy of optimization is established, the spreading factor ratio optimized
Example collection Mfair, include the following:
The distribution of spreading factor best proportion: being defined as when being disposed according to the distribution of spreading factor best proportion, different
The data transmission success of spreading factor node is identical, may be expressed as:
Wherein, PiAnd PjIndicate the ratio of total node shared by spreading factor i and j, Pder(i,Pi) and Pder(j,Pi) difference table
Show their data transmission success.
It can obtain:
Wherein i, j ∈ 7,8 ..., and 12 }, i ≠ j；
Wherein i, j ∈ 7,8 ..., and 12 }, i ≠ j；
As mono- timing of bandwidth BW and code rate CR, the transmission rate R of LoRabIt is determined by spreading factor.Spreading factor in network
The sum of shared total node ratio is constant, as constraint condition, is expressed as follows:
It can be obtained by deriving above, when spreading factor allocation proportion set meets following distribution, belong to optimal distribution strategy:
As data length L, number of nodes N, bandwidth BW and data transmission time intervals TiIn the case where certain,It is
One definite value.The data transmission success of different spreading factors is identical at this time, is expressed as follows:
According to path loss packet-dropping model, i.e. Ptx+G-Lpl(d) > SSF[i]I ∈ { 7,8,9 ..., 12 } is network internal segment
Point distribution spreading factor, it is as follows to obtain network original allocation ratio set:
Minit={ Minit|Minit,i=Pi,i∈{7,8,9,...,12}}
Best proportion distributes Rule of judgment: according to best proportion allocation proportion collection MfairWith MinitBetween each spreading factor
Between proportional difference KmTo judge that can initial proportion distribution be converted into best proportion distribution:
Km={ mi|mi=Minit,i-Mfair,i,i∈{7,8,9,...,12}}
When the condition 1 of satisfaction, then original allocation cannot achieve best proportion distribution:
Condition 1
Spreading factor suboptimum pro rate: the target of suboptimum pro rate becomes finding most data transmission success equal
Spreading factor group, and and the data transmission success of non-guaranteed all spreading factors be equal, it may be assumed that
max∑H(Pder(i,Pi)=Pder(j,Pj)),i,j∈{7,8,9,...,12},i≠j
Wherein, H is indicator function, and bracket conditional is if true, be 1, vacation is 0.
It allows spreading factor original allocation proportion set to be compared with best proportion collection, is greater than or equal to optimal distribution strategy ratio
Example collection shares CbIt indicates:
Cb=b | Minit,b≥Mfair,bor Minit,b=0 }
Belong to set CbSpreading factor optimize processing again, for CbIn each spreading factor b for, institute
The ratio summation of the total node N of Zhan is set asSo to belonging to CbIn spreading factor optimize and handle according to (a):
Wherein S expression meets CbSpreading factor；
So suboptimum allocation proportion collection are as follows:
S4:LoRa-FDF spreading factor allocation strategy includes the following:
STEP 1: spreading factor ratio distribution M is obtained according to spreading factor original allocation firstinit={ Minit|Minit,i=
Pi,i∈{7,8,9,...,12}}；
STEP2: compare initial proportion distribution MinitM is distributed with best proportionfairIn each spreading factor accounting, if primary election
Spreading factor distribution meets Optimal Distribution network Rule of judgment Mfair_condition, then spreading factor is distributed according to this distribution；If
It is unsatisfactory for, then judges whether it can be converted into Optimal Distribution, Rule of judgment is as follows:
Condition 1
STEP3: if best proportion distribution can be converted to, gateway collect again and save the RSSI value information of node in
It in RSSI [], sorts again to set RSSI [], is distributed M according to best proportionfairAnd according to high RSSI value using low spread spectrum because
Son, low RSSI value are redistributed using high spreading factor principle.
STEP4: being that node distributes spreading factor according to suboptimum allocation strategy if Optimal Distribution can not be converted into,
In suboptimum allocation strategy, the node that spreading factor is i is rejected, optimum allocation is carried out to remaining node, specific strategy is as follows:
(1) if mi< 0, i ∈ { 7,8,9 ..., 12 }, then re-start S32 to i+1, Rule of judgment becomes:
Condition 2Wherein k ∈ { i+1 ..., 12 }, mk∈Km
(2) if meeting condition 2, to i+1 and thereafter spreading factor, recalculate its optimum allocation ratio and according to
S33 distributes spreading factor.
Fig. 3 indicates LoRa-FDF allocation strategy execution flow chart.
Finally, it is stated that preferred embodiment above is only used to illustrate the technical scheme of the present invention and not to limit it, although logical
It crosses above preferred embodiment the present invention is described in detail, however, those skilled in the art should understand that, can be
Various changes are made to it in form and in details, without departing from claims of the present invention limited range.
Claims (5)
1. a kind of LoRaWAN network spreading factor distribution method based on reliability, it is characterised in that: this method specifically include with
Lower step:
S1: according to the receiving sensitivity threshold value and path loss characteristics of LoRa node, packet-dropping model, initialization is lost in build path
Each node spreading factor obtains spreading factor initial proportion collection Minit；
S2: by LoRa Data Transmission Feature and spreading factor accounting P is introduceds, establish data transmission success, spreading factor and Ps
Relational model；
S3: by the relational model of S2, establishing the spreading factor allocation strategy of optimization, the spreading factor proportion set M optimizedfair；
S4: the proportion set obtained in conjunction with S1 and S3, using the spreading factor of LoRa-FDF Developing Tactics difference node, to improve number
According to transmission success rate.
2. a kind of LoRaWAN network spreading factor distribution method based on reliability according to claim 1, feature exist
In: in the step S1, according to the receiving sensitivity threshold value and path loss characteristics of LoRa node, packet loss mould is lost in build path
Type initializes each node spreading factor, obtains spreading factor initial proportion collection Minit, include the following:
The minimum receiving sensitivity S of different spreading factorsSF[i]For threshold value, only in received signal strength Pr(d)=Ptx+G-Lpl
(d) it is greater than SSF[i]Shi Caineng is unpacked；The packet loss as caused by path loss is expressed as follows:
Pper(d, S)=P { Pr(d) > SSF[i]i∈{7,8,9,...,12}}
=P { Ptx+G-Lpl(d) > SSF[i]i∈{7,8,9,...,12}}
Wherein, SSF[i]For the receiving sensitivity threshold value of spreading factor i, G is antenna gain, PtxFor transimission power, Lpl(d) it indicates
Lognormal shadowing path loss, the distance of d node to gateway；
Spreading factor original allocation is carried out as restrictive condition according to path loss packet loss condition, steps are as follows:
S11: node is initialized with highest spreading factor, i.e. SF [m]=12, m ∈ [1, N], wherein N indicates network node sum
Amount；
S12: for a period of time after stablizing, gateway saves the RSSI value information of node, and puts by descending sequence for the network operation
Enter in set RSSI []；
S13: judged according to path loss packet loss, i.e. Ptx+G-Lpl(d) > SSF[j], wherein j ∈ { y7,8,9 ..., 12 }, executes
J=7:1:12 is recycled, if RSSI [m] > SSF[j], then SF [m]=j；
S14: counting each spreading factor number of nodes, obtains spreading factor ratio set Minit={ Minit|Minit,i=Pi,i∈
{ 7,8,9 ..., 12 } }, wherein PiIndicate the ratio for the total node of node Zhan that spreading factor is i in original allocation.
3. a kind of LoRaWAN network spreading factor distribution method based on reliability according to claim 1, feature exist
In: in the step S2, by LoRa Data Transmission Feature and introduce spreading factor accounting Ps, establish data transmission success, expand
The frequency factor and PsRelational model, include the following:
Assuming that network node is evenly distributed in gateway areas, on this basis, LoRa spreading factor S and spreading factor are introduced
Accounting PsAs new variable, the node-node transmission success rate that spreading factor is S is obtained according to Poisson distribution are as follows:
Wherein S indicates that spreading factor, L indicate that data length, BW indicate bandwidth, and N indicates node total number amount, TiIndicate data transmission
Time interval, PsIndicate that spreading factor is the ratio of the total node of node Zhan of S.
4. a kind of LoRaWAN network spreading factor distribution method based on reliability according to claim 1, feature exist
In: in the step S2, by the relational model of S2, establish the spreading factor pro rate strategy of optimization, the spread spectrum optimized
Factor proportion set Mfair, include the following:
(a) spreading factor best proportion distributes: being defined as when being disposed using the distribution of spreading factor best proportion, difference expands
The data transmission success of frequency factor nodes is identical, indicates are as follows:
Wherein, PiAnd PjIndicate the ratio of total node shared by spreading factor i and j, Pder(i,Pi) and Pder(j,Pi) respectively indicate it
Data transmission success；When spreading factor allocation proportion collection is equal to MfairWhen, belong to best proportion distribution:
Best proportion distributes Rule of judgment: according to MfairWith MinitBetween proportional difference K between each spreading factormTo judge
Whether original allocation can be converted into best proportion distribution:
Km={ mi|mi=Minit,i-Mfair,i,i∈{7,8,9,...,12}}
When the condition 1 of satisfaction, then original allocation can not be converted into best proportion distribution:
Condition 1Or m7< 0
Condition 1 indicates that there are a spreading factor j, so that in the sum of [j, 12] section proportional difference less than zero or m7Less than zero
In the case where, then it cannot be distributed by initial proportion and be converted into best proportion distribution；
(b) spreading factor suboptimum pro rate: the target of suboptimum pro rate becomes finding most data transmission success equal
Spreading factor group, and and the data transmission success of non-guaranteed all spreading factors be equal, it may be assumed that
max∑H(Pder(i,Pi)=Pder(j,Pj)),i,j∈{7,8,9,...,12},i≠j
Wherein, H is indicator function, and bracket conditional is if true, be 1, vacation is 0；
It allows spreading factor primary election ratio set and Optimal Distribution ratio set to be compared, is greater than or equal to optimal distribution strategy ratio
Example collection shares CbIt indicates:
Cb=b | Minit,b≥Mfair,b or Minit,b=0 }
Belong to set CbSpreading factor optimize processing again, for CbIn each spreading factor b for, it is shared total
The ratio summation of node N is set asSo to belonging to CbIn spreading factor optimize and handle according to (a):
Wherein S expression meets CbSpreading factor；
So suboptimum allocation proportion collection are as follows:
5. a kind of LoRaWAN network spreading factor distribution method based on reliability according to claim 1, feature exist
In: in the step S3, in conjunction with the proportion set that S1 and S3 are obtained, using LoRa-FDF Developing Tactics difference node spread spectrum because
Son includes the following: with improve data transfer success rate
S31: spreading factor ratio distribution M is obtained according to spreading factor original allocation firstinit={ Minit{Minit=Pi,i∈{7,
8,9,...,12}}；
S32: compare initial proportion distribution MinitM is distributed with best proportionfairIn each spreading factor accounting, if the spread spectrum of primary election because
Son distribution meets Optimal Distribution network Rule of judgment Mfair_condition, then spreading factor is distributed according to this distribution；If not satisfied,
Then judge whether it can be converted into Optimal Distribution, Rule of judgment is as follows:
Condition 1Or m7< 0
S33: if best proportion distribution can be converted to, gateway is collected again and saves the RSSI value information of node in RSSI []
In, it sorts again to set RSSI [], is distributed M according to best proportionfairAnd low spreading factors are used according to high RSSI value, it is low
RSSI value is redistributed using high spreading factor principle；
S34: being that node distributes spreading factor according to suboptimum allocation strategy, in secondary optimal sorting if Optimal Distribution can not be converted into
With the node that spreading factor is i in strategy, is rejected, optimum allocation is carried out to remaining node, specific strategy is as follows:
(1) if mi< 0, i ∈ { 7,8,9 ..., 12 }, then re-start S32 to i+1, Rule of judgment becomes:
Condition 2Wherein k ∈ { i+1 ..., 12 }, mk∈Km
(2) if meeting condition 2, spreading factor, recalculates its optimum allocation ratio and according to S33 points to i+1 and thereafter
With spreading factor.
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Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110267282A (en) * | 2019-06-24 | 2019-09-20 | 厦门大学 | A method of realizing LoRa network optimal throughput fairness |
| CN111080998A (en) * | 2019-12-11 | 2020-04-28 | 广西电网有限责任公司 | LoRa technology-based multi-meter centralized reading control method and system |
| CN111130715A (en) * | 2019-12-13 | 2020-05-08 | 西北大学 | Lora wireless network and parameter optimization and transmission method and device thereof |
| CN112020105A (en) * | 2020-08-26 | 2020-12-01 | 贵州电网有限责任公司 | LoRa transmission-based rate self-adaption method for power grid |
| CN113038541A (en) * | 2021-03-04 | 2021-06-25 | 重庆邮电大学 | Adaptive LoRaWAN network rate adjusting method based on conflict perception |
| CN113124878A (en) * | 2021-04-21 | 2021-07-16 | 哈尔滨工业大学 | Lunar surface large-range road topology network construction method, system and device |
| CN113395669A (en) * | 2020-03-11 | 2021-09-14 | 新开普电子股份有限公司 | LoRa networking method, node centralized reading method and network server |
| CN113596921A (en) * | 2021-05-31 | 2021-11-02 | 国网江苏省电力有限公司电力科学研究院 | Fair adaptive data rate distribution and power control method and system |
| CN114173421A (en) * | 2021-11-25 | 2022-03-11 | 中山大学 | LoRa logic channel based on deep reinforcement learning and power distribution method |
| CN114222316A (en) * | 2021-11-25 | 2022-03-22 | 山东有人物联网股份有限公司 | LoRa parameter evaluation method, device, equipment and readable storage medium |
| CN114760709A (en) * | 2022-03-24 | 2022-07-15 | 中山大学 | LoRa node distribution model construction method, node distribution method and device |
| CN115767755A (en) * | 2022-11-23 | 2023-03-07 | 国网湖北省电力有限公司电力科学研究院 | Lightweight scheduling method and system suitable for LoRaWAN network terminal node and storage medium |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102868488A (en) * | 2012-09-13 | 2013-01-09 | 中国人民解放军理工大学 | Space time diversity-based reliable transmission method for low-spell wireless sensor |
| CN109040214A (en) * | 2018-07-25 | 2018-12-18 | 北京邮电大学 | A kind of service arrangement method that reliability enhances under cloud environment |
-
2019
- 2019-01-24 CN CN201910070021.3A patent/CN109526012A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102868488A (en) * | 2012-09-13 | 2013-01-09 | 中国人民解放军理工大学 | Space time diversity-based reliable transmission method for low-spell wireless sensor |
| CN109040214A (en) * | 2018-07-25 | 2018-12-18 | 北京邮电大学 | A kind of service arrangement method that reliability enhances under cloud environment |
Non-Patent Citations (1)
| Title |
|---|
| 赵菁菁: "LoRa协议公平与抗干扰传输研究", 《中国优秀硕士学位论文》 * |
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| CN110267282A (en) * | 2019-06-24 | 2019-09-20 | 厦门大学 | A method of realizing LoRa network optimal throughput fairness |
| CN111080998A (en) * | 2019-12-11 | 2020-04-28 | 广西电网有限责任公司 | LoRa technology-based multi-meter centralized reading control method and system |
| CN111130715A (en) * | 2019-12-13 | 2020-05-08 | 西北大学 | Lora wireless network and parameter optimization and transmission method and device thereof |
| CN113395669A (en) * | 2020-03-11 | 2021-09-14 | 新开普电子股份有限公司 | LoRa networking method, node centralized reading method and network server |
| CN112020105B (en) * | 2020-08-26 | 2022-08-12 | 贵州电网有限责任公司 | LoRa transmission-based rate self-adaption method for power grid |
| CN112020105A (en) * | 2020-08-26 | 2020-12-01 | 贵州电网有限责任公司 | LoRa transmission-based rate self-adaption method for power grid |
| CN113038541A (en) * | 2021-03-04 | 2021-06-25 | 重庆邮电大学 | Adaptive LoRaWAN network rate adjusting method based on conflict perception |
| CN113124878A (en) * | 2021-04-21 | 2021-07-16 | 哈尔滨工业大学 | Lunar surface large-range road topology network construction method, system and device |
| CN113124878B (en) * | 2021-04-21 | 2023-12-22 | 哈尔滨工业大学 | Moon surface large-scale road topology network construction method, system and device |
| CN113596921A (en) * | 2021-05-31 | 2021-11-02 | 国网江苏省电力有限公司电力科学研究院 | Fair adaptive data rate distribution and power control method and system |
| CN114173421A (en) * | 2021-11-25 | 2022-03-11 | 中山大学 | LoRa logic channel based on deep reinforcement learning and power distribution method |
| CN114173421B (en) * | 2021-11-25 | 2022-11-29 | 中山大学 | LoRa logic channel based on deep reinforcement learning and power distribution method |
| CN114222316A (en) * | 2021-11-25 | 2022-03-22 | 山东有人物联网股份有限公司 | LoRa parameter evaluation method, device, equipment and readable storage medium |
| CN114222316B (en) * | 2021-11-25 | 2024-01-26 | 山东有人物联网股份有限公司 | LoRa parameter evaluation method, device, equipment and readable storage medium |
| CN114760709A (en) * | 2022-03-24 | 2022-07-15 | 中山大学 | LoRa node distribution model construction method, node distribution method and device |
| CN115767755A (en) * | 2022-11-23 | 2023-03-07 | 国网湖北省电力有限公司电力科学研究院 | Lightweight scheduling method and system suitable for LoRaWAN network terminal node and storage medium |
| CN115767755B (en) * | 2022-11-23 | 2023-07-11 | 国网湖北省电力有限公司电力科学研究院 | Lightweight scheduling method, system and storage medium suitable for LoRaWAN network terminal node |
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