CN110380821B - RFID response signal decoding system and method based on machine learning - Google Patents

RFID response signal decoding system and method based on machine learning Download PDF

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CN110380821B
CN110380821B CN201910636561.3A CN201910636561A CN110380821B CN 110380821 B CN110380821 B CN 110380821B CN 201910636561 A CN201910636561 A CN 201910636561A CN 110380821 B CN110380821 B CN 110380821B
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彭琪
林祥川
李小明
包军林
刘伟峰
庄奕琪
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Abstract

The invention discloses a machine learning-based RFID (radio frequency identification) response signal decoding system, which relates to the technical field of RFID and comprises a decision device, a decision device and a decoding device, wherein the decision device is used for forming a decided vector by an RFID response signal paragraph and a response signal amplitude, decoding is carried out according to the product of the decided vector and a decoding weight vector, and the adjustment which is required when the next response signal paragraph is intercepted is obtained according to the product of the decided vector and an adjusting weight vector; the parameter trainer is used for training and updating the weight vector according to the decoding result, the adjusting result and the judged vector; the main controller is used for controlling the components, and the invention has the advantages that: the decoding parameters trained by the invention are more in accordance with the signal characteristics of the RFID response signals, and the influence of channel interference and frequency offset can be resisted during decoding.

Description

RFID response signal decoding system and method based on machine learning
Technical Field
The invention relates to the technical field of RFID, in particular to a RFID response signal decoding system and method based on machine learning.
Background
The Radio Frequency Identification (RFID) technology is a non-contact automatic identification technology, and performs non-contact bidirectional data communication by a radio frequency method to identify a target and acquire related data.
The RFID system is generally composed of an electronic tag, a reader and a host. The reader is generally composed of an antenna, a radio frequency module and a baseband module. An antenna is a device that transmits and receives radio frequency carrier signals. The radio frequency module can transmit and receive a radio frequency carrier. The radio frequency module demodulates the carrier waves which are received by the antenna and transmitted/reflected back from the label and then transmits the demodulated carrier waves to the baseband module. The baseband module generally comprises an amplifier, a decoding and error correcting circuit, a microprocessor, a clock circuit, a standard interface and a power supply, can receive and decode signals transmitted by the radio frequency module to obtain information in the label, can encode the information sent to the label and then transmit the encoded information to the radio frequency module, and can transmit the content of the label and other information to a host through the standard interface.
The basic communication flow of the RFID system is as follows: the reader transmits a challenge signal → the tag returns a response signal → the reader receives and processes the response signal. The reply signal is demodulated, amplified and filtered in the reader and then converted into a digital signal by an analog-to-digital converter (ADC) having a high sampling frequency for synchronization and decoding. The reply signal may have the effect of wireless channel and hardware imperfections which degrade the synchronization and decoding performance of the reader. The reply signal in a passive RFID system also carries a frequency offset. Because in a passive RFID system, the tag is powered from the continuous carrier wave transmitted by the reader and transmits a response signal to the reader through its embedded oscillator, the output frequency of the embedded oscillator is usually determined by the base current generated by its internal bandgap, and the variation of the internal bandgap causes the frequency deviation of the oscillator. The reader is therefore required to be able to decode the symbols with the frequency offset.
The decoding method adopted at present has two methods, namely a direct hard decision method and a correlation method. The direct hard decision method completes decoding according to the interval time of the differential peak of the response signal, but the method is susceptible to burst interference. The correlation method decodes according to the correlation value of the answer signal segment and the reference signal, wherein the reference signal is a standard symbol, the method reduces the influence of burst interference, but the reference signal is difficult to define to equalize and decode the answer signal covered with frequency offset.
Based on this, the application provides a RFID response signal decoding system and method based on machine learning.
Disclosure of Invention
The present invention is directed to a system and a method for decoding RFID response signals based on machine learning, so as to solve the problems in the background art.
In order to achieve the purpose, the invention provides the following technical scheme:
an RFID response signal decoding system based on machine learning comprises a main controller, a decision device and a parameter trainer,
the decision device is used for forming a decided vector by the RFID response signal paragraph and the response signal amplitude, decoding the decided vector according to the product of the decided vector and the decoding weight vector, and obtaining the adjustment to be made when the next response signal paragraph is intercepted according to the product of the decided vector and the adjustment weight vector; the parameter trainer is used for training and updating the weight vector according to the decoding result, the adjusting result and the judged vector; the main controller is used for controlling the components.
As a still further scheme of the invention: initial values of the decoding weight vector and the adjusting weight vector are input from the outside and then updated by the training result of the parameter trainer.
As a still further scheme of the invention: the decision device comprises a subtracter, a register group, an inverter, a first data selector, a first vector multiplier, a first comparator, a second data selector, a second vector multiplier and a second comparator;
the subtracter is used for receiving the RFID response signal and the RFID response signal offset and outputting a signal without the offset to the register group; the register group is used for receiving the output of the subtracter and a control output signal section of the main controller, the signal section and the RFID response signal form a vector and are output to the inverter and the first data selector:
the inverter is used for receiving a vector formed by the output of the register group and the RFID response signal and inverting the vector, the output of the inverter is connected with the first data selector, the first data selector is used for selecting the inverted vector or the non-inverted vector as the output according to the output of the main controller, and the output vector is used as a judged vector for decoding judgment and adjustment judgment, namely the judged vector;
the first vector multiplier is used for calculating the product of the decoding weight vector and the judged vector and outputting the product to the first comparator; the first comparator gives a decoding result according to whether the product result is greater than zero or not:
the second data selector is used for inputting the adjusting weight vector to a second vector multiplier according to the input decoding result, the second vector multiplier is used for calculating the product of the judged vector and the adjusting weight vector and outputting the product to a second comparator, and the second comparator gives an adjusting result according to whether the product result is larger than zero or not and outputs the adjusting result to the main controller so as to control the generation of the next judged vector.
As a still further scheme of the invention: the parameter trainer comprises a data collector and an SVM trainer, wherein the data collector is used for receiving the decoding output validity, the judged vector, the decoding result and the adjustment result output by the decision device and generating data for training to the SVM trainer; the SVM trainer is used for training and updating the decoding weight vector and the adjusting weight vector.
As a still further scheme of the invention: the result checker is used for checking whether the decoding result is correct according to the cyclic redundancy check code, and if the decoding result is correct, the SVM trainer receives the data collected by the data collector through the control signal to train and update the decoding weight vector and the adjusting weight vector.
A RFID response signal decoding method based on machine learning comprises the following steps:
s100, forming a judged vector by the RFID response signal paragraph and the response signal amplitude, decoding according to the product of the judged vector and the decoding weight vector, introducing an adjusting weight vector, and obtaining the adjustment needed when the next response signal paragraph is intercepted according to the product of the judged vector and the adjusting weight vector;
s200, outputting a decoding result and an adjusting result;
and S300, checking the decoding result, and training and updating the decoding weight vector and the adjusting weight vector according to the decoding result, the adjusting result and the judged vector when the decoding result is correct.
As a further scheme of the invention: and the check mode is to check whether the decoding result is correct according to the cyclic redundancy check code.
As a still further scheme of the invention: the determined vector is generated by inverting or not inverting the vector formed by the RFID answering signal paragraph and the answering signal amplitude.
As a still further scheme of the invention: when the product of the decided vector and the decoding weight vector is less than zero, the decoding result is 0, and when the product is greater than zero, the decoding result is 1.
As a still further scheme of the invention: when the product of the judged vector and the adjusting weight vector is less than zero, the next judged vector is adjusted forwards in time, and when the product of the judged vector and the adjusting weight vector is more than zero, the next judged vector is adjusted backwards in time, and the main controller obtains an adjusting result and controls the generation of the next judged vector.
Compared with the prior art, the invention has the beneficial effects that: forming a judged vector by the RFID response signal paragraph and the response signal amplitude, decoding according to the product of the judged vector and the decoding weight vector, and obtaining the adjustment to be made when the next response signal paragraph is intercepted according to the product of the judged vector and the adjusting weight vector; and then training and updating the weight vector by using the decoding result, the adjusting result and the judged vector, wherein the decoding parameter trained by the invention is more in accordance with the signal characteristic of the RFID response signal, and can resist the influence of channel interference and frequency offset during decoding.
Drawings
Fig. 1 is a control schematic diagram of a machine learning-based RFID response signal decoding system.
Fig. 2 is a control schematic diagram of an arbiter in a machine learning-based RFID reply signal decoding system.
Fig. 3 is a control schematic diagram of a parameter trainer in a machine learning-based RFID response signal decoding system.
In the figure: 1-a main controller, 2-a subtracter, 3-a register group, 4-an inverter, 5-a first data selector, 6-a first vector multiplier, 7-a first comparator, 8-a second data selector, 9-a second vector multiplier, 10-a second comparator, 11-a data collector, 12-a result checker and 13-an SVM trainer.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the exemplary embodiments below are not intended to represent all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.
Example 1
Referring to fig. 1 to 3, in an embodiment of the present invention, an RFID response signal decoding system based on machine learning includes a main controller 1, a decision device, and a parameter training device.
In this embodiment, the determiner is configured to combine the RFID reply signal segment and the reply signal amplitude into a determined vector, decode the determined vector according to a product of the determined vector and a decoding weight vector, and obtain an adjustment to be performed when a next reply signal segment is intercepted according to a product of the determined vector and an adjusting weight vector, where initial values of the decoding weight vector and the adjusting weight vector are input from the outside and then updated by a training result of the parameter trainer; the parameter trainer is used for training and updating the weight vector according to the decoding result, the adjusting result and the judged vector (the weight vector is the decoding weight vector and the adjusting weight vector); the main controller 1 is used to control the above components.
Specifically, the decision device includes a subtractor 2, a register group 3, an inverter 4, a first data selector 5, a first vector multiplier 6, a first comparator 7, a second data selector 8, a second vector multiplier 9, and a second comparator 10.
The subtracter 2 is used for receiving the RFID response signal and the RFID response signal offset and outputting the signal without the offset to the register group 3; the register group 3 is used for receiving the output of the subtracter 2 and a control output signal section of the main controller 1, the signal section and the RFID response signal form a vector to be output to the inverter 4 and the first data selector 5, and preferably, the register group 3 is composed of multidimensional shift registers:
here, the inverter 4 is configured to receive a vector formed by the output of the register group 3 and the RFID response signal and invert the vector, the output of the inverter 4 is connected to the first data selector 5, and the first data selector 5 is configured to select an inverted vector or an un-inverted vector as an output according to the output of the main controller 1, where the main controller 1 determines whether inversion is required according to a coding method and a previous decoding result, for example, when FM0 is coded, if the previous decoding result is 0, it is consistent with the inversion or non-inversion processing of the decided vector last time, and if the previous decoding result is 1, it is opposite to the inversion or non-inversion processing of the decided vector last time; the vector output by the first data selector 5 is used as a decided vector for decoding decision and adjustment decision, namely the decided vector;
the first vector multiplier 6 is used for calculating the product of the decoding weight vector and the decided vector and outputting the product to a first comparator 7; the first comparator 7 gives a decoding result according to whether the product result is greater than zero or not, if the product result is greater than zero, the decoding result is 1, and if the product result is less than zero, the decoding result is 0;
the second data selector 8 is configured to input the adjustment weight vector to the second vector multiplier 9 according to the input decoding result, the second vector multiplier 9 is configured to calculate a product of the determined vector and the adjustment weight vector and output the product to the second comparator 10, and the second comparator 10 gives an adjustment result according to whether the product result is greater than zero or not and outputs the adjustment result to the main controller 1 to control generation of a next determined vector.
The parameter trainer comprises a data collector 11, a result checker 12 and an SVM trainer 13, wherein the data collector 11 is used for receiving the decoding output of the judger to be valid (the decoding output is valid as 1 to indicate that the data of the decoding result port at the current moment is useful and valid, and the decoding output is valid as 0 to indicate that the data of the decoding result port at the current moment is useless and invalid), the judged vector, the decoding result and the adjustment result, and generating the data for training to the SVM trainer 13; the SVM trainer 13 is used for training and updating the decoding weight vector and the adjusting weight vector; in addition, as a preferable mode, the embodiment further discloses a result checker 12, which is configured to check whether the decoding result is correct according to a cyclic redundancy check code (CRC), and if the decoding result is correct, the SVM trainer 13 receives the collected data of the data collector 11 through a control signal to perform training and updating of the decoding weight vector and the adjusting weight vector; if not, not training and not updating.
Example 2
In the embodiment of the invention, a machine learning-based RFID (radio frequency identification) response signal decoding method comprises the following steps:
s100, forming a judged vector by the RFID response signal paragraph and the response signal amplitude, decoding according to the product of the judged vector and the decoding weight vector, introducing an adjusting weight vector, and obtaining the adjustment needed when the next response signal paragraph is intercepted according to the product of the judged vector and the adjusting weight vector;
s200, outputting a decoding result and an adjusting result;
and S300, checking the decoding result, specifically, checking whether the decoding result is correct or not according to a cyclic redundancy check code (CRC) in a checking mode, and when the decoding result is correct, training and updating the decoding weight vector and the adjusting weight vector according to the decoding result, the adjusting result and the judged vector.
The determined vector is generated by inverting or not inverting the vector formed by the RFID response signal segment and the response signal amplitude, as described in the above embodiment, the signal segment output by the register group 3 and the RFID response signal form a vector to be output to the inverter 4, and the first data selector 5 is configured to select the inverted vector or the non-inverted vector as an output according to the output of the main controller 1.
Preferably, when the product of the decided vector and the decoding weight vector is less than zero, the decoding result is 0, and when the product is greater than zero, the decoding result is 1; when the product of the decided vector and the adjusting weight vector is less than zero, the next decided vector is adjusted forward in time, and when the product of the decided vector and the adjusting weight vector is more than zero, the next decided vector is adjusted backward in time, and the main controller 1 obtains an adjusting result and controls the generation of the next decided vector.
It should be particularly noted that, in the present technical solution, the RFID response signal segment and the response signal amplitude are combined into a determined vector, decoding is performed according to the product of the determined vector and the decoding weight vector, and the adjustment to be performed when the next response signal segment is intercepted is obtained according to the product of the determined vector and the adjustment weight vector; and then training and updating the weight vector by using the decoding result, the adjusting result and the judged vector, wherein the decoding parameter trained by the invention is more in accordance with the signal characteristic of the RFID response signal, and can resist the influence of channel interference and frequency offset during decoding.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
It will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims (8)

1. A machine learning based RFID reply signal decoding system, comprising:
the decision device is used for forming a decided vector by the RFID response signal paragraph and the response signal amplitude, decoding the decided vector according to the product of the decided vector and the decoding weight vector, and obtaining the adjustment to be made when the next response signal paragraph is intercepted according to the product of the decided vector and the adjustment weight vector;
the parameter trainer is used for training and updating the weight vector according to the decoding result, the adjusting result and the judged vector;
a main controller (1) for controlling the decision maker and the parameter trainer component;
the decision device comprises
The subtracter (2) is used for receiving the RFID response signal and the RFID response signal offset and outputting a signal without the offset to the register group (3);
the register group (3) is used for receiving the output of the subtracter (2) and receiving a control output signal section of the main controller (1), the signal section and the RFID response signal form a vector to be output to the inverter (4) and the first data selector (5):
the inverter (4) is used for receiving the output vector of the register group (3) and inverting the vector, and the output of the inverter (4) is connected with the first data selector (5);
the first data selector (5) is used for selecting the inverted vector or the non-inverted vector as output according to the output of the main controller (1), and the output vector is used as a judged vector for decoding judgment and adjustment judgment, namely the judged vector;
the first vector multiplier (6) is used for calculating the product of the decoding weight vector and the judged vector and outputting the product to the first comparator (7), the first comparator (7) gives a decoding result according to whether the product result is greater than zero or not, if the product result is greater than zero, the decoding result is 1, and if the product result is less than zero, the decoding result is 0;
a second data selector (8) for inputting the adjustment weight vector to a second vector multiplier (9) according to the inputted decoding result;
the second vector multiplier (9) is used for calculating the product of the judged vector and the adjusting weight vector and outputting the product to the second comparator (10), the second comparator (10) gives an adjusting result according to whether the product result is larger than zero or not, and outputs the adjusting result to the main controller (1) so as to control the generation of the next judged vector;
when the product of the judged vector and the adjusting weight vector is less than zero, the next judged vector is adjusted forwards in time, and when the product of the judged vector and the adjusting weight vector is more than zero, the next judged vector is adjusted backwards in time, and the main controller obtains an adjusting result and controls the generation of the next judged vector.
2. The machine-learning-based RFID reply signal decoding system according to claim 1, wherein the initial values of the decoding weight vector and the adjusting weight vector are inputted from the outside and then updated by the training result of the parameter trainer.
3. A machine learning based RFID reply signal decoding system according to claim 1 or 2, wherein the parameter trainer comprises:
a data collector (11) for receiving the decoded output valid, the decided vector, the decoded result and the adjusted result output by the decider, and generating data for training to the SVM trainer (13);
the SVM trainer (13) is used for training and updating the decoding weight vector and the adjusting weight vector.
4. The RFID answer signal decoding system based on machine learning of claim 3, further comprising a result checker (12) for checking whether the decoding result is correct according to the cyclic redundancy check code, and if the decoding result is correct, the training and updating of the decoding weight vector and the adjusting weight vector are performed by the SVM trainer (13) through the control signal to receive the data collected by the data collector (11).
5. A RFID response signal decoding method based on machine learning is characterized by comprising the following steps:
s100, forming a judged vector by the RFID response signal paragraph and the response signal amplitude, decoding according to the product of the judged vector and the decoding weight vector, introducing an adjusting weight vector, and obtaining the adjustment needed when the next response signal paragraph is intercepted according to the product of the judged vector and the adjusting weight vector;
s200, outputting a decoding result and an adjusting result;
s300, checking the decoding result, and when the decoding result is correct, training and updating the decoding weight vector and the adjusting weight vector according to the decoding result, the adjusting result and the judged vector;
when the product of the judged vector and the adjusting weight vector is less than zero, the next judged vector is adjusted forwards in time, and when the product of the judged vector and the adjusting weight vector is more than zero, the next judged vector is adjusted backwards in time, and the main controller obtains an adjusting result and controls the generation of the next judged vector.
6. The machine-learning-based RFID reply signal decoding method according to claim 5, wherein the check manner is to check whether the decoding result is correct according to a cyclic redundancy check code.
7. The machine-learning-based RFID response signal decoding method of claim 5, wherein the determined vector is generated by inverting or not inverting a vector consisting of RFID response signal segments and response signal amplitudes.
8. The machine-learning-based RFID reply signal decoding method of claim 5, wherein the decoding result is 0 when the product of the decided vector and the decoding weight vector is less than zero and 1 when it is greater than zero.
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