CN107944316B - Multi-tag signal parallel coding/decoding method and system in a kind of backscattering agreement - Google Patents
Multi-tag signal parallel coding/decoding method and system in a kind of backscattering agreement Download PDFInfo
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Abstract
The invention discloses multi-tag signal parallel coding/decoding method and systems in a kind of backscattering agreement, method includes the following steps: to acquire the domain IQ signal sequence and is clustered to obtain multiple clusters to sampled point, and all neighbours' clusters of each cluster are identified according to the transition probability between any two cluster；According to neighbours' cluster of obtained all clusters and each cluster, the layering of cluster is obtained；Determine the corresponding level combinations of every layer of cluster；The corresponding level combinations sequence of the domain IQ signal sequence is identified according to cluster belonging to each signal, and the corresponding level of each label is obtained after level combinations sequence is decomposed and transmits sequence, each label is completed to decode.The present invention, which is realized, is decoded multiple collision labels in dynamic environment, is very suitable for back scattering system highly dynamic, highly unstable in practical application.Stability due to the present invention independent of signal does not need have any change in tab end, therefore reduces the energy consumption of tab end, improves the reliability and robustness of algorithm.
Description
Technical field
The present invention relates to internet of things field, and in particular to the multi-tag signal parallel solution into a kind of backscattering agreement
Code method and system are realized in the case where signal transmission is unstable and carry out parallel decoding to multiple RFID label tags.The technology is suitable
For bulk storage plant, shelf or need while reading in the wireless sensor networks of multiple RFID label tag signals to answer in Multi-target position
With.
Background technique
With the key technology that the fast development of Internet of Things recent years, radio frequency identification develop as Internet of Things, it has been subjected to
To the very big concern of academia and industry.In typical radio-frequency identification system, the high communication low efficiency energy of backscatter technique
The advantages that consumption, substantially increases the application that backscatter technique communicates between label and reader.But with wireless sense network
The development of network, the deployment of extensive label and a large amount of data transmission, and the communication distance of label and reader it is shorter and
Multiple labels communicate simultaneously causes the data of high-speed to transmit, so that backscatter technique is carried out while being solved to multiple label signals
When code, it is difficult not only to guarantee efficient data transmission but also realizes the energy consumption consumption of low-power.
In terms of carrying out extensive backscatter communication, parallel decoding technology can largely improve backscattering skill
The communication efficiency of art.Groundwork is divided into following two categories in terms of communicating decoding at present:
The first kind: the backscatter transmission decoding based on encoding mechanism.This method is each using the encoding mechanism of no rate code
Label carrys out coded data according to orthogonal code, each is converted into one long PN sequence, but the party is in the presence of decoded in tab end
The problem of cost prohibitive.
Second class: the IQ characteristic of field decoding based on label.Due to the decoded cost prohibitive of tab end, a kind of method is proposed
Reader end is decoded signal.It theoretically sees, the channel coefficient of collision labels is the line of these labels
Property combination, be in general it is stable, can have special feature in the domain IQ for the collision alarm of specific combination state, because
This reader can identify the signal of collision labels according to location information of the label in the domain IQ.
Third class: the temporal signatures information based on label is decoded.Due in a relatively-stationary time interval,
Identical label has the signal graph that is completely coincident, therefore this method is according to the signal cluster in temporal signatures and the domain IQ, according to
The signal graph that label signal generates identifies different labels to be decoded to collision labels.
Above-mentioned three classes method all relies on signal transmission stable between label, and in fact, for low-power consumption low overhead
Label, the signal transmission between label is mostly unstable, and vulnerable to ambient noise interference, therefore these three types of methods are for decoding more marks
It signs in parallel transmission signal, decoding error rate is very high, and performance is poor, largely influences the efficiency and network throughput of transmission
Amount.
Summary of the invention
For the problem that existing coding/decoding method is poor to the decoded performance of multi-tag signal parallel in backscatter communication,
The present invention proposes signal parallel coding/decoding method in a kind of backscattering agreement, comprising the following steps:
Multi-tag signal parallel coding/decoding method in a kind of backscattering agreement, includes the following steps:
Step 1, acquisition the domain IQ signal sequence simultaneously sampled point is clustered to obtain multiple clusters, according to any two cluster it
Between transition probability identify all neighbours' clusters of each cluster；
Step 2 carries out layered shaping to all clusters, obtains cluster according to neighbours' cluster of obtained all clusters and each cluster
Layering；
Step 3 determines the corresponding level combinations of every layer of cluster according to the layering of the level of root cluster and obtained cluster；
Step 4 identifies the domain IQ signal sequence pair according to cluster belonging to each signal in the signal sequence of the collected domain IQ
The level combinations sequence answered obtains the corresponding level of each label and transmits sequence, to each mark after decomposing level combinations sequence
Label complete decoding.
Further, the step 1 includes the following steps:
Step S11 reads the domain the IQ signal sequence that label is sent as reader using USRP equipment；
Step S12 calculates the local density of each sampling point sampling；
Step S13, identification and removal noise spot: it is lower than the sampled point of threshold value for local density, is regarded as noise section
It puts and removes, the domain the IQ signal sequence after being denoised；
Step S14, clusters sampled point, obtains different clusters, and the cluster identified is numbered；
Step S15 calculates the transition probability between any two cluster；
Step S16 identifies neighbours' cluster of each cluster according to transition probability, specifically will be with either cluster CiTransition probability is most
Q high cluster is as CiNeighbours' cluster Cnei(Ci), wherein Q is the label number of concurrent transmission.
Further, the step 2 includes the following steps:
Step S21 identifies root cluster, by root cluster CrootIt has been layered as the 0th layer of cluster, and by root cluster mark；Specifically: working as institute
When some labels do not have information to need to send all in sleep state, that is, label, if all signals fall in cluster CrIn, then will
Cluster CrIt is identified as root cluster Croot, root cluster CrootLevel combinations be [L, L ..., L], wherein L indicate low level, the level of root cluster
The number of L is equal to the number Q of label in combination；
Other clusters except root cluster are layered by step S22；Specifically: by root cluster CrootAll neighbours' clusters be denoted as the 1st layer
Cluster, and the 1st layer of cluster is identified and has been layered；The each layer of cluster started for the 2nd layer, takes the union of neighbours' cluster of this layer of cluster and removes
The cluster for going mark to be layered has been layered by remaining cluster as next layer of cluster of current layer cluster until all clusters identify.
Further, the step 3 includes the following steps:
Step S31 obtains the 1st layer of corresponding level combinations of cluster；Specifically: the level combinations of each cluster are not in the 1st layer of cluster
Together, and the level combinations of each cluster with root cluster CrootLevel combinations number it is identical, and differ a high level；
Step S32 obtains the level group of the 2nd layer of each cluster to n-th layer according to the level combinations of itself upper layer neighbours' cluster
It closes；Specifically:
For any one cluster in pth layer (2≤p≤N) clusterIts level combinations is according to its all neighbour at -1 layer of pth
The level combinations of cluster are occupied to determine；Specifically:There is m neighbours' cluster at -1 layer of pthWherein, m≤Q；ForIn -1 layer of pth any one neighbours' clusterIts
In, j is 1 any into m, and all positions for being identified as H level or position grouping are denoted as in corresponding level combinations
Highj, then clusterAll level for being identified as H position grouping be High1∪High2∪…∪HighmI.e. by cluster's
The level of corresponding position sets H in level combinations, and remaining level is set L, while guaranteeing clusterThe electricity of corresponding level combinations
Flat number is equal to label number Q.
Further, the step 4 includes the following steps:
Each signal in the collected domain the IQ signal sequence of step 1 is replaced with cluster belonging to the signal by step S41
Number, obtain the sequence of the corresponding cluster of the domain IQ signal sequence；
Each cluster in the sequence of the obtained cluster of step S41 is replaced with the level combinations of the cluster, obtains IQ by step S42
The corresponding level combinations sequence of domain signal sequence；Wherein, all level signals in the level combinations of each cluster and all labels
The signal of transmission corresponds；
Step S43 resolves into any level combinations in level combinations sequence that step S42 is obtained each in Q label
The signal of label obtains the corresponding level of each label in Q label and transmits sequence after all level combinations decompose；
Step S44 is decoded the level transmission sequence that each label is sent.
It is a further object of the invention to provide multi-tag signal parallels in a kind of backscattering agreement to decode system,
Including being sequentially connected the module connect as follows:
Signal acquisition module, for acquiring the domain IQ signal sequence and being clustered to obtain multiple clusters to sampled point, according to appoint
The transition probability between two clusters of anticipating identifies all neighbours' clusters of each cluster；
Cluster hierarchical block carries out at layering all clusters for neighbours' cluster according to obtained all clusters and each cluster
Reason, obtains the layering of cluster；
Cluster level combinations computing module determines every layer of cluster pair for the layering according to the level and obtained cluster of root cluster
The level combinations answered；
Label signal decomposing module is identified for the cluster according to belonging to each signal in the signal sequence of the collected domain IQ
Signal sequence corresponding level combinations sequence in the domain IQ obtains the corresponding level of each label and transmits after decomposing level combinations sequence
Sequence is completed to decode to each label.
Further, the signal acquisition module includes following submodule:
Submodule S11, for reading the domain the IQ signal sequence that label is sent as reader using USRP equipment；
Submodule S12, for calculating the local density of each sampling point sampling；
Submodule S13 for identification and removes noise spot: being lower than the sampled point of threshold value for local density, be regarded as
Noise node simultaneously removes, the domain the IQ signal sequence after being denoised；
Submodule S14 obtains different clusters, and the cluster identified is numbered for clustering to sampled point；
Submodule S15, for calculating the transition probability between any two cluster；
Submodule S16 specifically will be with either cluster C for identifying neighbours' cluster of each cluster according to transition probabilityiTransfer
The highest Q cluster of probability is as CiNeighbours' cluster Cnei(Ci), wherein Q is the label number of concurrent transmission.
Further, the cluster hierarchical block includes following submodule:
Submodule S21, root cluster for identification, by root cluster CrootIt has been layered as the 0th layer of cluster, and by root cluster mark；Specifically
Be: when all labels all in sleep state i.e. label does not have information to need to send when, if all signals fall in cluster Cr
In, then by cluster CrIt is identified as root cluster Croot, root cluster CrootLevel combinations be [L, L ..., L], wherein L indicate low level, root cluster
Level combinations in L number be equal to label number Q；
Submodule S22, for being layered other clusters except root cluster；Specifically: by root cluster CrootAll neighbours' clusters note
For the 1st layer of cluster, and the 1st layer of cluster is identified and has been layered；The each layer of cluster started for the 2nd layer, takes neighbours' cluster of this layer of cluster
Union simultaneously removes the cluster that mark has been layered, by remaining cluster as next layer of cluster of current layer cluster, until all clusters identify
Layering.
Further, the cluster level combinations computing module includes following submodule:
Submodule S31, for obtaining the 1st layer of corresponding level combinations of cluster；Specifically: the level of each cluster in the 1st layer of cluster
Combination is different, and the level combinations of each cluster with root cluster CrootLevel combinations number it is identical, and differ a high level；
Submodule S32 obtains the 2nd layer of each cluster to n-th layer for the level combinations according to itself upper layer neighbours' cluster
Level combinations；Specifically:
For any one cluster in pth layer (2≤p≤N) clusterIts level combinations is according to its all neighbour at -1 layer of pth
The level combinations of cluster are occupied to determine；Specifically:There is m neighbours' cluster at -1 layer of pthWherein, m≤Q；ForIn -1 layer of pth any one neighbours' clusterIts
In, j is 1 any into m, and all positions for being identified as H level or position grouping are denoted as in corresponding level combinations
Highj, then clusterAll level for being identified as H position grouping be High1∪High2∪…∪HighmI.e. by cluster's
The level of corresponding position sets H in level combinations, and remaining level is set L, while guaranteeing clusterThe electricity of corresponding level combinations
Flat number is equal to label number Q.
Further, the label signal decomposing module includes following submodule:
Submodule S41, for each signal in the collected domain the IQ signal sequence of signal acquisition module to be replaced with this
The number of cluster belonging to signal obtains the sequence of the corresponding cluster of the domain IQ signal sequence；
Submodule S42, each cluster in the sequence of the cluster for obtaining submodule S41 replace with the level group of the cluster
It closes, obtains the corresponding level combinations sequence of the domain IQ signal sequence；Wherein, all level signals in the level combinations of each cluster with
The signal that all labels are sent corresponds；
Submodule S43, any level combinations resolve into Q mark in the level combinations sequence for obtaining submodule S42
The signal of each label in label obtains the corresponding level of each label in Q label and transmits after all level combinations decompose
Sequence；
Submodule S44, the level transmission sequence for sending to each label are decoded.
The present invention is suitable for Internet of Things passive RFID tags, can be realized and carries out in dynamic environment to multiple collision labels
Decoding, especially suitable for back scattering system highly dynamic, highly unstable in practical application.Compared to the prior art, originally
Invention has the following beneficial effects:
1, do not need have any change in tab end.
Existing many methods need to change the coding mode of tab end, and new more complicated coding mode is often
What the hardware configuration of existing label was unable to reach.In order to realize that new coding mode, label manufacturer need to recall all portions
The label affixed one's name to away is changed label hardware, so that new coding method is able to use.In view of 2010 Nian Yinian, entirely
The deployment amount of ball range interior label arrived 33,000,000,000, and recalling all labels and being modified undoubtedly will lead to huge manpower
Material resources expense.And concurrent coding/decoding method proposed by the invention does not need to make label any change, label can continue to follow
Original coding mode carries out Signal coding.Therefore this method largely reduces manpower costs.
2, the energy consumption of tab end is reduced.
The present invention does not need to do tab end any change, that is, does not need complicated coding mode, do not need accurately yet
It is synchronous between label, any medium access control technique is not needed more.Label only needs to carry out simple " acquisition Data Transfer "
Operation, greatly reduce the energy expense of tab end.The design of this low energy consumption is very suitable for passive radio frequency identification system
System.
3, the reliability and robustness of algorithm are improved.
The most important advantage of the present invention is exactly its stability independent of signal.Due to a large amount of portions of labeling requirement
Administration, hardware design and coding method design must obey the principle of " low energy consumption, low overhead ".On the one hand the two principles make
Label can only the extremely low OOK of Energy in use monitor coding mode, and this coding mode is very poor to the robustness of interference, causes
Serious swinging of signal is qualitative.On the other hand, " low energy consumption, low overhead " principle use label can only very cheap hard
Part, and the unstability of inexpensive hardware (for example the frequency deviation of the usually used cheap crystal oscillator of label is about in 50000ppm) is directly led
The unstability of signal is caused.And existing concurrent decoding technique can only signal and its it is unstable in the case where concurrently solved
Code greatly enhances decoding stability and robustness.
Detailed description of the invention
Fig. 1 is the work flow diagram of method of the invention；
Fig. 2 is that cluster collides planisphere.Wherein, (a) is two tag-collision exemplary diagrams；It (b) is caused under dynamic environment
The collision labels signal cluster of two sequence packets；It (c) is the collision alarm cluster of two labels of non-linear dependence；It (d) is expression weight
Folded cluster exemplary diagram；
Fig. 3 is sub-clustering step schematic diagram.Wherein, the sampled point that (a) is received；(b) the cluster central point identified；(c) it is
Easily obscuring sampled point schematic diagram (d) is result schematic diagram of the sampled point final classification to each cluster；
Fig. 4 is the relation schematic diagram of each algorithm throughput and concurrent label number；
Fig. 5 is the relation schematic diagram of each algorithm throughput and tag bits rate；
Fig. 6 is the relationship of each algorithm throughput and channel quality.
Specific embodiment
Multi-tag signal in backscatter communication is carried out simultaneously for existing coding/decoding method the performance of parallel decoding compared with
The problem of difference, the invention proposes signal parallel coding/decoding method and systems in a kind of backscattering agreement, realize in dynamic ring
Multiple collision labels are decoded in border, are mainly used in highly dynamic back scattering system.Specifically includes the following steps:
Step 1, acquisition the domain IQ signal sequence simultaneously sampled point is clustered to obtain multiple clusters, according to any two cluster it
Between transition probability identify all neighbours' clusters of each cluster.Include the following steps:
Step S11 reads the domain the IQ signal sequence that label is sent as reader using USRP equipment, and generates constellation
Figure.I-th of signal sampling point is denoted as (Ii,Qi).Wherein, IiIndicate that i-th of signal I in the domain IQ sits target value, QiIndicate the
I signal Q in the domain IQ sits target value.These sampled points will form different clusters (as shown in Figure 2) in the domain IQ.
Step S12 calculates the local density of each sampling point sampling.For ith sample point, the local density of sampling
Are as follows: with i-th of signal sampling point (Ii,Qi) centered on, d is the number for the sampled point for including in the circle of radius, wherein d is truncation
Radius:
Wherein, ImaxAnd IminRepresent maximum value and minimum value that sampled point I reference axis in IQ coordinate domain is got；QmaxWith
QminRepresent maximum value and minimum value that sampled point Q reference axis in IQ coordinate domain is got.
Step S13, identification and removal noise spot.Due to that can adopt many noise spots in sampling process, these points are usual
It is not belonging to any cluster, therefore needs to get rid of noise spot before being clustered.Threshold value T h is lower than for local densityDAdopt
Sampling point is regarded as noise node and removes, the domain the IQ signal sequence after being denoised.Here T hD=20.
Step S14, clusters sampled point, obtains different clusters.It is specifically that the domain the IQ signal sequence after denoising is defeated
Enter into dbscan clustering algorithm, N number of cluster is identified by dbscan clustering algorithm, and the N number of cluster identified is numbered；
Step S15 calculates the transition probability between any two cluster.Any two cluster CiAnd CjBetween transition probability
Ptrans(Ci,Cj) are as follows:
In formula,Indicate CiAnd CjBetween transfer number；Indicate CiWith it is every other
The sum of transfer number between cluster.
Step S16 identifies neighbours' cluster of each cluster according to transition probability.It specifically will be with either cluster CiTransition probability is most
Q high cluster is as CiNeighbours' cluster Cnei(Ci), wherein Q is the label number of concurrent transmission.If CiAnd CjNeighbours each other
Cluster, then < Ci,Cj> ∈ E, E indicate that neighbours' gathering is closed each other.The purpose of the step is the neighbours' cluster for obtaining each cluster, for subsequent
Step is layered all clusters, obtains level combinations corresponding to each cluster, to realize the standard of final multi-tag collision alarm
Really decoding.
Step 2, neighbours' cluster of all clusters and each cluster that are obtained according to step 1 carry out layered shaping to all clusters,
The layering of cluster is obtained, specific as follows:
Step S21 identifies root cluster, by root cluster CrootIt has been layered as the 0th layer of cluster, and by root cluster mark.Specifically: working as institute
When some labels do not have information to need to send all in sleep state, that is, label, if all signals fall in cluster CrIn, then will
Cluster CrIt is identified as root cluster Croot, root cluster CrootLevel combinations be obviously [L, L ..., L], wherein L indicate low level, root cluster
The number of L is equal to the number Q of label in level combinations；
Other clusters except root cluster are layered by step S22.Specifically: by root cluster CrootAll neighbours' clusters be denoted as the 1st layer
Cluster, and the 1st layer of cluster is identified and has been layered；The each layer of cluster started for the 2nd layer, takes the union of neighbours' cluster of this layer of cluster and removes
The cluster for going mark to be layered has been layered by remaining cluster as next layer of cluster of current layer cluster until all clusters identify.Example
Such as: taking in the 1st layer of cluster and be used as the 2nd layer of cluster after the union of neighbours' cluster of each cluster and the cluster of the 0th layer and the 1st layer of removing, take the 2nd layer
It the union of neighbours' cluster of each cluster and is removed after the cluster of layers 1 and 2 as the 3rd layer of cluster in cluster, and so on, until all
Cluster be all layered, obtain N+1 layers of cluster.
Step 3 determines the corresponding electricity of every layer of cluster according to the delamination for the cluster that the level of root cluster and step 2 obtain
Flat combination.Specifically comprise the following steps:
Step S31 obtains the 1st layer of cluster (i.e. root cluster CrootQ neighbours' cluster) corresponding level combinations.Specifically: the 1st layer
The level combinations of each cluster are different in cluster, and the level combinations of each cluster with root cluster CrootLevel combinations number it is identical, and
Differ a high level.For example, root cluster be [L, L ..., L], then the 1st layer of cluster be respectively as follows: [H, L ..., L], [L, H ...,
L],…,[L,L,…,H]；
Step S32 obtains the level group of the 2nd layer of each cluster to n-th layer according to the level combinations of itself upper layer neighbours' cluster
It closes.Specifically:
For any one cluster in pth layer (2≤p≤N) cluster(it indicates i-th of cluster of pth layer), level combinations
It is determined according to it in the level combinations of -1 layer of pth of all neighbours' clusters.Specifically:
There is m neighbours' cluster at -1 layer of pthWherein, m≤Q；For?
- 1 layer of pth any one neighbours' clusterWherein, j is 1 any into m, all in corresponding level combinations to be identified as
The position of H level or position grouping are denoted as Highj(for example, ifLevel combinations be [H, L, H, L], then H level
Position grouping Highj={ 1,3 }), then clusterAll level for being identified as H position grouping be High1∪High2∪…
∪HighmI.e. by clusterLevel combinations in the level of corresponding position set H, and remaining level is set into L, while guaranteeing clusterIt is right
The level number for the level combinations answered is equal to label number Q.
It is corresponding with level combinations to obtain cluster primarily to obtain the corresponding level combinations of each cluster for this step purpose
Table, it is subsequent each signal in the signal sequence of the domain IQ to be converted into level combinations sequence.
Step 4 identifies the domain IQ signal according to cluster belonging to each signal in the collected domain the IQ signal sequence of step 1
The corresponding level combinations sequence of sequence obtains the corresponding level of each label and transmits sequence after decomposing level combinations sequence, right
Each label completes decoding.
Each signal in the collected domain the IQ signal sequence of step 1 is replaced with cluster belonging to the signal by step S41
Number, obtain the sequence of the corresponding cluster of the domain IQ signal sequence；
Each cluster in the sequence of the obtained cluster of step S41 is replaced with the level combinations of the cluster, obtains IQ by step S42
The corresponding level combinations sequence of domain signal sequence.Wherein, all level signals in the level combinations of each cluster and all labels
The signal of transmission corresponds.
Step S43 resolves into any level combinations in level combinations sequence that step S42 is obtained each in Q label
The signal of label obtains the corresponding level of each label in Q label and transmits sequence after all level combinations decompose.Example
Such as, for Q=3 (i.e. three label concurrent transmissions) the case where, if the corresponding level combinations sequence of the level signal received is
{ [H, H, L], [L, H, L], [L, H, H] ... ... }, then the level transmission sequence of label 1 is { H, L, L ... ... }, the electricity of label 2
Defeated sequence of flating pass is { H, H, H ... ... }, and the level transmission sequence of label 3 is { L, L, H ... ... }.
Step S44 is decoded the level transmission sequence that each label is sent using traditional single tag decoder.
Two, the method for the present invention performance test and the comparative experiments with other algorithms
Get off the advantage that we verify this method relative to other methods by one group of experiment.Experiment is mainly to following three
The performance of kind algorithm is compared:
(1) FlipTracer: algorithm proposed by the present invention.
(2) Cluster-Based method (abbreviation CB): this method assumes that signal its channel parameter in transmission process is steady
It is fixed, therefore carry out using position of the cluster in IQ coordinate system the identification of each cluster level combinations.
(3) BiGroup: this method assumes that the bit length of all labels is fixed, therefore with the time of collision alarm
Characteristic of field is decoded as the level combinations identification according to progress cluster and concurrently.
Experiment mainly proves advantage of the invention from following several respects:
1. influence of the concurrency (participating in the number of concurrent label) to the throughput of three above method, 2. bit rate
Influence to the throughput of three above method, 3. influence of the channel quality to the throughput of three above method；
Experiment one: the influence that concurrency generates throughput
Experiment initialization:
We use a USRP N210 as reader to read the signal that label is sent.USRP has met two UBX RF
Daughter board and two 900MHz antennas.The sample rate of USRP is set as 20MHz, and antenna gain is set as 20dBm.Experiment uses 5
WISP is as passive label.We remove the part Slot Aloha of EPCglobal C1G2 agreement in label, and such label can
With concurrent transmission.
Experimentation:
In this experiment, concurrent label number is changed by we from 2 to 5, has carried out 4 groups of experiments in total.In order to protect
Real result is tested in confirmation, and for each algorithm, in every group of experiment, each label sends 100 packets.We observe receiving end
(USRP) to the decoding cases of collision data packet.
Experimental result:
Fig. 4 shows the relationship of each algorithm throughput Yu concurrent label number.It can be seen from the figure that FlipTracer
The throughput of algorithm is much higher than BiGroup algorithm and BC algorithm.When concurrent label number reaches 5, FlipTracer algorithm
Throughput reach 2.5 times, 17 times of BC algorithm of BiGroup algorithm.This is because FlipTracer algorithm is using between cluster
Transfer relationship carry out the identification of each cluster level.Even if transfer relationship in the case where concurrency is high, can also maintain higher
Stability.Therefore, FlipTracer can also reach higher in the very high situation of concurrency and be decoded into power, to reach
Higher throughput.
Experiment two: the influence that bit rate generates throughput
Experiment initialization: with experiment one.
Experimentation:
In this experiment, the bit rate of concurrent label is changed to 600kbps by 100kbps by us, has carried out 6 groups in total
Experiment.Since WISP platform only supports the bit rate of highest 256Kbps at present, we are tested each using emulation experiment
Performance of the algorithm when tag bits rate is 500~600Kbps.In order to guarantee experimental result authenticity, for each algorithm, often
In group experiment, each label sends 100 packets.We observe receiving end (USRP) to the decoding cases of collision data packet.
Experimental result:
Fig. 5 shows the relationship of each algorithm throughput and tag bits rate.It can be seen from the figure that FlipTracer can
To realize that 5 labels carry out concurrent data transfer with 500Kbps.Meanwhile BiGroup and FlipTracer is compared in different bits
The throughput for the 5 label concurrent transmissions realized under rate, it has been found that when BiGroup tag bits rate reaches 200Kbps, performance
Start decline rapidly.The maximum overall throughput of BiGroup is 300Kbps.And FlipTracer carries out high bit rate biography in label
Performance is higher when defeated: when label is transmitted with 500Kbps, FlipTracer throughput reaches 14 times of BiGroup.
Experiment three: the influence that channel quality generates throughput
Experiment initialization: with experiment one.
Experimentation:
In this experiment, the performance that we only compare FlipTracer and BiGroup (is being believed mainly due to BC algorithm
It can not work at all in the case that road is second-rate, therefore not consider that it is allowed to participate in comparison).During the experiment, we pass through
Channel quality is changed to the movement of label.Experiment uses 3 labels, and the transmission rate of each label is 100Kpbs.It is theoretical
On, label is remoter from reader, and channel quality is poorer between label and reader.Therefore, we are by label gradually far from readding
Device is read, and observes the variation of the throughput of each algorithm in this process.We have collected 3 groups of data in total, respectively represent
Channel quality " good ", " in ", " bad " when concurrent decoding cases.In order to guarantee experimental result authenticity, for each algorithm,
In every group of experimental data, each label sends 100 packets.We observe receiving end (USRP) to the decoding feelings of collision data packet
Condition.
Experimental result:
Fig. 6 shows the relationship of each algorithm throughput and channel quality.It can be seen from the figure that higher in channel quality
When, FlipTracer and BiGroup can realize good throughput.When channel quality is deteriorated, when noise frequently occurs,
BiGroup total throughout is remarkably decreased.This is because BiGroup algorithm signal cluster process robustness is lower, strong noise makes
There is large error in the cluster module of BiGroup algorithm, and in contrast, FlipTracer still has when channel condition is poor
There is higher robustness.
Claims (6)
1. multi-tag signal parallel coding/decoding method in a kind of backscattering agreement, which comprises the steps of:
Step 1 acquires the domain IQ signal sequence and is clustered to obtain multiple clusters to sampled point, according between any two cluster
Transition probability identifies all neighbours' clusters of each cluster；
Step 2 carries out layered shaping to all clusters according to neighbours' cluster of obtained all clusters and each cluster, obtains point of cluster
Layer；
Step 3 determines the corresponding level combinations of every layer of cluster according to the layering of the level of root cluster and obtained cluster；Including as follows
Step:
Step S31 obtains the 1st layer of corresponding level combinations of cluster；Specifically: the level combinations of each cluster are different in the 1st layer of cluster, and
The level combinations of each cluster with root cluster CrootLevel combinations number it is identical, and differ a high level；
Step S32 obtains the level combinations of the 2nd layer of each cluster to n-th layer according to the level combinations of itself upper layer neighbours' cluster；
Specifically:
For any one cluster in pth layer (2≤p≤N) clusterIts level combinations is according to it in -1 layer of pth of all neighbours' clusters
Level combinations determine；Specifically:There is m neighbours' cluster at -1 layer of pthIts
In, m≤Q；ForIn -1 layer of pth any one neighbours' clusterWherein, j is 1, corresponding level any into m
All positions for being identified as H level or position grouping are denoted as High in combinationj, then clusterAll level for being identified as H
Position grouping be High1∪High2∪…∪HighmI.e. by clusterLevel combinations in the level of corresponding position set H, and
Remaining level is set into L, while guaranteeing clusterThe level number of corresponding level combinations is equal to label number Q；
Step 4 identifies that the domain IQ signal sequence is corresponding according to cluster belonging to each signal in the signal sequence of the collected domain IQ
Level combinations sequence obtains the corresponding level of each label and transmits sequence after decomposing level combinations sequence, complete to each label
At decoding；Include the following steps:
Each signal in the collected domain the IQ signal sequence of step 1 is replaced with the volume of cluster belonging to the signal by step S41
Number, obtain the sequence of the corresponding cluster of the domain IQ signal sequence；
Each cluster in the sequence of the obtained cluster of step S41 is replaced with the level combinations of the cluster by step S42, obtains the domain IQ letter
Number corresponding level combinations sequence of sequence；Wherein, all level signals in the level combinations of each cluster and all labels are sent
Signal correspond；
Any level combinations in level combinations sequence that step S42 is obtained are resolved into each label in Q label by step S43
Signal obtain the corresponding level of each label in Q label after all level combinations decompose and transmit sequence；
Step S44 is decoded the level transmission sequence that each label is sent.
2. multi-tag signal parallel coding/decoding method in backscattering agreement as described in claim 1, which is characterized in that the step
Rapid one includes the following steps:
Step S11 reads the domain the IQ signal sequence that label is sent as reader using USRP equipment；
Step S12 calculates the local density of each sampling point sampling；
Step S13, identification and removal noise spot: it is lower than the sampled point of threshold value for local density, is regarded as noise node simultaneously
Removal, the domain the IQ signal sequence after being denoised；
Step S14, clusters sampled point, obtains different clusters, and the cluster identified is numbered；
Step S15 calculates the transition probability between any two cluster；
Step S16 identifies neighbours' cluster of each cluster according to transition probability, specifically will be with either cluster CiThe highest Q of transition probability
A cluster is as CiNeighbours' cluster Cnei(Ci), wherein Q is the label number of concurrent transmission.
3. multi-tag signal parallel coding/decoding method in backscattering agreement as described in claim 1, which is characterized in that the step
Rapid two include the following steps:
Step S21 identifies root cluster, by root cluster CrootIt has been layered as the 0th layer of cluster, and by root cluster mark；Specifically: when all
When label does not have information to need to send all in sleep state, that is, label, if all signals fall in cluster CrIn, then by cluster CrKnow
It Wei not root cluster Croot, root cluster CrootLevel combinations be [L, L ..., L], wherein L indicates low level, L in the level combinations of root cluster
Number be equal to label number Q；
Other clusters except root cluster are layered by step S22；Specifically: by root cluster CrootAll neighbours' clusters be denoted as the 1st layer of cluster, and
1st layer of cluster is identified and has been layered；The each layer of cluster started for the 2nd layer, takes the union of neighbours' cluster of this layer of cluster and removes mark
Know the cluster being layered to be layered by remaining cluster as next layer of cluster of current layer cluster until all clusters identify.
4. multi-tag signal parallel decodes system in a kind of backscattering agreement, which is characterized in that connect including being sequentially connected as follows
Module:
Signal acquisition module, for acquiring the domain IQ signal sequence and being clustered to obtain multiple clusters to sampled point, according to any two
Transition probability between a cluster identifies all neighbours' clusters of each cluster；
Cluster hierarchical block carries out layered shaping to all clusters, obtains for neighbours' cluster according to obtained all clusters and each cluster
To the layering of cluster；
Cluster level combinations computing module determines that every layer of cluster is corresponding for the layering according to the level and obtained cluster of root cluster
Level combinations；The cluster level combinations computing module includes following submodule:
Submodule S31, for obtaining the 1st layer of corresponding level combinations of cluster；Specifically: the level combinations of each cluster in the 1st layer of cluster
Difference, and the level combinations of each cluster with root cluster CrootLevel combinations number it is identical, and differ a high level；
Submodule S32 obtains the level of the 2nd layer of each cluster to n-th layer for the level combinations according to itself upper layer neighbours' cluster
Combination；Specifically:
For any one cluster in pth layer (2≤p≤N) clusterIts level combinations is according to it in -1 layer of pth of all neighbours' clusters
Level combinations determine；Specifically:There is m neighbours' cluster at -1 layer of pthIts
In, m≤Q；ForIn -1 layer of pth any one neighbours' clusterWherein, j is 1, corresponding level any into m
All positions for being identified as H level or position grouping are denoted as High in combinationj, then clusterAll level for being identified as H
Position grouping be High1∪High2∪…∪HighmI.e. by clusterLevel combinations in the level of corresponding position set H, and
Remaining level is set into L, while guaranteeing clusterThe level number of corresponding level combinations is equal to label number Q；
Label signal decomposing module identifies the domain IQ for the cluster according to belonging to each signal in the signal sequence of the collected domain IQ
The corresponding level combinations sequence of signal sequence obtains the corresponding level of each label and transmits sequence after decomposing level combinations sequence
Column are completed to decode to each label；The label signal decomposing module includes following submodule:
Submodule S41, for each signal in the collected domain the IQ signal sequence of signal acquisition module to be replaced with the signal
The number of affiliated cluster obtains the sequence of the corresponding cluster of the domain IQ signal sequence；
Submodule S42, each cluster in the sequence of the cluster for obtaining submodule S41 replace with the level combinations of the cluster, obtain
To the corresponding level combinations sequence of the domain IQ signal sequence；Wherein, all level signals in the level combinations of each cluster and all
The signal that label is sent corresponds；
Submodule S43, any level combinations resolve into Q label in the level combinations sequence for obtaining submodule S42
The signal of each label obtains the corresponding level of each label in Q label and transmits sequence after all level combinations decompose
Column；
Submodule S44, the level transmission sequence for sending to each label are decoded.
5. multi-tag signal parallel decodes system in backscattering agreement as claimed in claim 4, which is characterized in that the letter
Number acquisition module includes following submodule:
Submodule S11, for reading the domain the IQ signal sequence that label is sent as reader using USRP equipment；
Submodule S12, for calculating the local density of each sampling point sampling；
Submodule S13 for identification and removes noise spot: being lower than the sampled point of threshold value for local density, be regarded as noise
Node simultaneously removes, the domain the IQ signal sequence after being denoised；
Submodule S14 obtains different clusters, and the cluster identified is numbered for clustering to sampled point；
Submodule S15, for calculating the transition probability between any two cluster；
Submodule S16 specifically will be with either cluster C for identifying neighbours' cluster of each cluster according to transition probabilityiTransition probability
Highest Q cluster is as CiNeighbours' cluster Cnei(Ci), wherein Q is the label number of concurrent transmission.
6. multi-tag signal parallel decodes system in backscattering agreement as claimed in claim 4, which is characterized in that the cluster
Hierarchical block includes following submodule:
Submodule S21, root cluster for identification, by root cluster CrootIt has been layered as the 0th layer of cluster, and by root cluster mark；Specifically: when
When all labels do not have information to need to send all in sleep state, that is, label, if all signals fall in cluster CrIn, then
By cluster CrIt is identified as root cluster Croot, root cluster CrootLevel combinations be [L, L ..., L], wherein L indicate low level, the electricity of root cluster
The number of L is equal to the number Q of label in flat combination；
Submodule S22, for being layered other clusters except root cluster；Specifically: by root cluster CrootAll neighbours' clusters be denoted as the 1st
Layer cluster, and the 1st layer of cluster is identified and has been layered；The each layer of cluster started for the 2nd layer, takes the union of neighbours' cluster of this layer of cluster simultaneously
The cluster that mark has been layered is removed to be layered by remaining cluster as next layer of cluster of current layer cluster until all clusters identify.
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