CN114844793B - System and method for improving preamble detection success rate of frame structure of Internet of things - Google Patents
System and method for improving preamble detection success rate of frame structure of Internet of things Download PDFInfo
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Abstract
The invention relates to a system and a method for improving the preamble detection success rate of an Internet of things frame structure, and belongs to the field of Internet of things communication. The system comprises a receiving module, a local positive sequence generating module, a local negative sequence generating module, a positive sequence correlation module, a negative sequence correlation module, a decision threshold value calculating module and a leading decision module. The method adopts the same method of a transmitting end to generate a positive sequence and a negative sequence at a receiving end, firstly uses the received data to be correlated with the positive sequence, then correlates with the negative sequence, and finally adopts the absolute value of the difference value of the correlation results of the received data and the positive sequence and the negative sequence as the basis of a judging threshold of a frame structure preamble. The invention can improve the searching accuracy and avoid the lead missing detection or false detection.
Description
Technical Field
The invention belongs to the field of communication of the Internet of things, relates to implementation of a frame structure preamble search algorithm, and particularly relates to a system and a method for improving the success rate of frame structure preamble detection of the Internet of things.
Background
In the communication process of the Internet of things, strict timing and resource allocation are not similar to the public network, and data receiving and sending in the Internet of things are realized in a burst mode. The burst structure consists of a preamble, a frame control and a load, the preamble consists of a fixed structure, and the receiving end and the transmitting end are both known and used for the receiving end to carry out Automatic Gain (AGC) adjustment of a received signal, timing and frequency domain synchronous adjustment, and the burst structure can be used for channel estimation and provides channel equalization information for frame control and load reception according to different system design requirements.
In the internet of things system, frame structure preamble searching generally adopts two modes. The first way is simpler, namely, the intensity of a received signal (Received Signal Strength Indication, RSSI) is searched, the receiving end baseband part firstly calculates the RSSI of the received data, if the RSSI calculated value is larger than a certain threshold, the existence of a valid frame burst preamble is judged, and otherwise, no preamble exists. In another way, a correlation calculation method is adopted, that is, the received data and the local preamble sequence are subjected to correlation calculation, and if the correlation peak value is greater than a certain threshold, it is determined that a valid frame burst preamble exists, and the method is also called a filter checking method.
In actual engineering, the RSSI method is simple, but the performance is worst, and particularly in a scene of large interference, the calculated value of the RSSI is large, but the noise power and the effective preamble power are distinguished, so that in actual engineering, the method is only used for preliminary judgment or AGC adjustment, and is not used for final judgment of the preamble.
In actual engineering, the frame burst preamble is judged by mainly adopting the correlation between a receiving sequence and a local sequence, so that the accuracy of the mode is greatly improved, and the mode is widely used in the actual engineering. In the case of large noise of the receiving channel, whether an effective frame burst preamble exists can be judged according to the characteristics of signal correlation. However, this method also has some problems, and the determination of whether there is a valid burst of the frame structure is determined according to the threshold of the relevant power, and the situation that the noise floor increases, the relevant power will also have a lifting phenomenon, and there will also be a preamble that erroneously determines the noise to be the burst of the frame structure.
In the broadband micropower wireless power meter reading system, a frame burst adopts a linear frequency modulation (Chirp) modulation mode. The preamble is composed of a plurality of uplink Chirp symbols and downlink Chirp symbols, and the frame burst structure is known in advance at both the transmitting end and the receiving end.
And the receiving end receives the wireless data from the transmitting end in real time, the wireless data is assumed to be the received_data, and after the wireless data is received, the wireless data and the local upChirp are subjected to correlation calculation, so that the correlation value is calculated to be xcor_upChirp. If the xcor_upChirp is larger than the fixed threshold delatValue, the valid upChirp signal is judged to exist, and then other upChirp symbols are continuously searched until all the down Chirp signals are searched. And finally judging the preamble end position.
As described above, the value of xcor_upChirp is calculated, and there is a great correlation with the background noise of the received receiver_data, and if the background noise increases, xcor_upChirp also increases, thus making it difficult to determine a reasonable DelatValue value. If the delatValue definition is too large, the preamble missing detection is easy to exist, and if the delatValue definition is too small, the preamble false detection is easy to exist.
Therefore, a method for improving the accuracy of the preamble search of the frame structure of the internet of things and avoiding the preamble missing detection or false detection is needed.
Disclosure of Invention
Accordingly, the present invention is directed to a system and a method for improving the success rate of preamble detection of a frame structure of the internet of things, so as to improve the accuracy of preamble search of the frame structure and avoid preamble missing detection or false detection.
In order to achieve the above purpose, the present invention provides the following technical solutions:
scheme one: a system for improving the success rate of preamble detection of an Internet of things frame structure is shown in fig. 1, and comprises a receiving module, a local positive sequence generating module, a local negative sequence generating module, a positive sequence correlation module, a negative sequence correlation module, a decision threshold value calculating module and a preamble decision module;
the receiving module is used for finishing frame structure data on a transmission medium;
the local positive sequence generation module is used for completing the data with the same property as the sequence sent by the sending end, and is called positive sequence;
the local reverse sequence generation module is used for completing the data with the reverse property of the sequence sent by the sending end, which is called reverse sequence, and the reverse sequence of the preamble sequence can have different forms according to the characteristics of the preamble sequence;
the positive sequence correlation module is used for completing the correlation calculation between the received frame structure data and the positive sequence, and the calculation result is called a positive sequence correlation value;
the inverse sequence correlation module is used for completing the correlation calculation between the received frame structure data and the inverse sequence, and is called an inverse sequence correlation value;
the judgment threshold value calculation module is used for completing calculation of the judgment threshold value, and the calculation method is that the absolute value of the correlation value of the positive sequence minus the correlation value of the negative sequence;
the preamble judging module is used for finishing the final judgment of whether the preamble data is or not, if the judging threshold value is larger than a fixed judging threshold value, the preamble data is valid, otherwise, the preamble data is not, and the fixed judging threshold value sources the system simulation and actual test results.
Further, the positive sequence correlation module employs an upChirp time-domain filter.
Further, the inverse sequence correlation module employs a downChirp time-domain filter.
Scheme II: the method for improving the preamble detection success rate of the frame structure of the Internet of things specifically comprises the following steps:
s1: firstly, locally generating positive sequence data and Negative sequence data of a symbol at a receiving end, and respectively marking the positive sequence data and the Negative sequence data as a position_sequences array and a negative_sequences array; then the receiving end receives data on the receiving medium and stores the data in the receiving_data array, and the length of the received data is a length unit of one symbol; as shown in step 1 of fig. 2.
S2: performing correlation calculation by using a position_sequences array and a received_data array, and marking the correlation value as a positive sequence correlation value P_xcor; the formula is adopted as follows: p_xcor=xcorr (received_data, position_sequences), where xcorr represents a correlation calculator; as in step 2 of fig. 2.
S3: performing correlation calculation by using the negative_sequences array and the received_data array, and marking the result as an inverse sequence correlation value N_xcor; the formula is adopted as follows: n_xcor=xcorr (received_data, negative_sequence); as in step 3 of fig. 2.
S4: and calculating a preamble symbol judgment threshold value R_threshold value of the received signal, wherein the value is the absolute value of the difference value between the positive sequence correlation value and the negative sequence correlation value, and the expression is as follows: r_threshold value=abs (p_xcor-n_xcor), where abs represents an absolute value taking operator; as in step 4 of fig. 2.
S5: determining a fixed decision threshold value preambleathreshhold value, which is determined for system simulation and actual testing; if R_threshold is greater than Preamble_threshold, then a valid preamble symbol is received; otherwise, indicating that noise is received and is not a valid preamble symbol; as shown in step 5 of fig. 2.
S6: if a valid preamble symbol is received in step S5, the receiving end starts a preamble reception procedure, otherwise data is received on the receiving medium. As shown in step 6 of fig. 2.
Further, in step S2, the received receive_data is passed through a local upChirp time domain filter, and a positive sequence correlation value p_xcor is output.
Further, in step S3, the received received_data is passed through a local downChirp time domain filter, and an inverse sequence correlation value n_xcor is output.
The invention has the beneficial effects that: the invention divides the preamble into two parts, the front preamble symbol is composed of a positive sequence, and the rear preamble symbol is composed of a negative sequence. When the effective leading symbol is judged, the method not only carries out correlation calculation with the positive sequence, but also carries out correlation calculation with the negative sequence.
Additional advantages, objects, and features of the invention will be set forth in part in the description which follows and in part will become apparent to those having ordinary skill in the art upon examination of the following or may be learned from practice of the invention. The objects and other advantages of the invention may be realized and obtained by means of the instrumentalities and combinations particularly pointed out in the specification.
Drawings
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in the following preferred detail with reference to the accompanying drawings, in which:
FIG. 1 is a diagram of a frame structure preamble structure according to the present invention;
FIG. 2 is a flow chart of a frame structure preamble decision in accordance with the present invention;
fig. 3 is a diagram of a broadband micro power radio frame structure in embodiment 1;
fig. 4 is a preamble structure diagram of a wideband micro-power radio frame structure in embodiment 1;
FIG. 5 is a block diagram of a wideband micro-power wireless communication frame structure preamble upChirp symbol time domain decision in embodiment 1;
fig. 6 is a time domain decision flow chart of a frame preamble symbol of the wideband micro-power wireless communication system in embodiment 1;
fig. 7 is a schematic diagram of the output values of the upChirp time domain filter module in example 1.
Detailed Description
Other advantages and effects of the present invention will become apparent to those skilled in the art from the following disclosure, which describes the embodiments of the present invention with reference to specific examples. The invention may be practiced or carried out in other embodiments that depart from the specific details, and the details of the present description may be modified or varied from the spirit and scope of the present invention. It should be noted that the illustrations provided in the following embodiments merely illustrate the basic idea of the present invention by way of illustration, and the following embodiments and features in the embodiments may be combined with each other without conflict.
Wherein the drawings are for illustrative purposes only and are shown in schematic, non-physical, and not intended to limit the invention; for the purpose of better illustrating embodiments of the invention, certain elements of the drawings may be omitted, enlarged or reduced and do not represent the size of the actual product; it will be appreciated by those skilled in the art that certain well-known structures in the drawings and descriptions thereof may be omitted.
The same or similar reference numbers in the drawings of embodiments of the invention correspond to the same or similar components; in the description of the present invention, it should be understood that, if there are terms such as "upper", "lower", "left", "right", "front", "rear", etc., that indicate an azimuth or a positional relationship based on the azimuth or the positional relationship shown in the drawings, it is only for convenience of describing the present invention and simplifying the description, but not for indicating or suggesting that the referred device or element must have a specific azimuth, be constructed and operated in a specific azimuth, so that the terms describing the positional relationship in the drawings are merely for exemplary illustration and should not be construed as limiting the present invention, and that the specific meaning of the above terms may be understood by those of ordinary skill in the art according to the specific circumstances.
Example 1:
to illustrate the method of using the present invention in a practical scenario, the present embodiment is illustrated using a broadband micro-power wireless communication system. The broadband micropower wireless communication system in the embodiment is mainly used for electric meter reading, belongs to a typical application of the Internet of things, and adopts a Chirp modulation mode due to the fact that a wireless channel is bad. The system frame structure definition is shown in fig. 3.
In the wireless frame structure, the preamble, the frame control and the load are all composed of Chirp modulation, wherein the preamble part is composed of a fixed bandwidth, a fixed working frequency point and a fixed symbol length, and the transmitting end and the receiving end are all in completely known states.
In this embodiment, the frame structure preamble adopts two Chirp modulation schemes. One is the upChirp signal and the other is the downChirp signal, as shown in FIG. 4. There are also two filters at the receiving end, an upChirp time-domain filter and a downChirp time-domain filter.
In the process of searching the frame structure of the broadband micropower wireless communication system, firstly, the content of a frame preamble part is searched, a method is generally adopted at present, after receiving data, a receiving end receives the data, the data is detected through an upChirp time domain filter, whether the data is the frame structure preamble upChirp symbol is judged according to the output peak value of the filter, and a down Chirp time domain filter is not used in the detection process. But in the present invention, upChirp and downChirp time domain filters are used in combination to determine whether it is the upChirp preamble symbol in the frame structure.
In this embodiment, the present invention adopts a Chirp modulation scheme, and in the frame structure, both the preamble and the frame control adopt the modulation scheme. The functional block diagram of the preamble symbol decision in the frame structure is shown in fig. 5, and according to the present invention, the frame structure preamble upChirp symbol functional pattern may be formed by a receiving module, an upChirp time domain filter, a downChirp time domain filter, a decision threshold calculation abs (p_xcor-n_xcor), and a preamble decision module. Wherein the upChirp time-domain filter is a positive sequence correlator and the downChirp time-domain filter is an inverse sequence correlator.
In particular, the operational flow is shown in FIG. 6.
Step 1: the receiving end receives the broadband micropower wireless signal from the wireless interface, firstly down-converts the signal, converts the received signal from carrier frequency to baseband signal, marks as received_data, and the received data length is a standard symbol length. As shown in step 1 of fig. 6.
Step 2: and (3) enabling the received received_data to pass through a local upChirp time domain filter, and outputting a relevant power value from the filter, and recording the relevant power value as a P_xcor value. As shown in step 2 in fig. 6.
Step 3: and (3) enabling the received received_data to pass through a local down Chirp time domain filter, outputting a relevant power value from the filter, and recording the relevant power value as an N_xcor value. As shown in step 3 of fig. 6.
Step 4: and calculating an upChirp symbol decision value of the received data received by the wireless channel. upchirp_threshold value=abs (p_xcor-n_xcor). abs is the absolute value taken calculation sign. As shown in step 4 of fig. 6.
Step 5: comparing the upChirp_threshold value with a decision threshold preamble_upChirpThreshold value, if the upChirp_threshold value is greater than or equal to the preamble_upChirpThreshold value, indicating that the receiving end receives a completed upChirp preamble symbol, and continuing with step 6. Otherwise, it means not a preamble symbol or an incomplete preamble upChirp symbol in the frame structure. As shown in step 5 of fig. 6.
Step 6: and (5) in the previous steps 1-5, if the fact that the upChirp symbol of the preamble of one frame structure is received is determined, the other upChirp symbols are continuously searched. The upChirp symbol and downChirp symbol transition positions are then determined, step 6 in FIG. 6.
In this embodiment, for convenience in frame structure preamble, the receiving end generally regards the upChirp time domain filter and the downChirp time domain filter design as one upChirp time domain filter module, as shown in fig. 5. The received signal is directly output with a correlation peak after passing through the upChirp time-domain filter module. However, the receiving end cannot determine the starting position of each symbol in the frame structure preamble, so that it is necessary to constantly monitor the switching points of the upChirp symbol and the downChirp symbol in the frame structure.
In this embodiment, the received data is a set of moving sequence data, and as shown in fig. 7, the data is sent from the receiving module to the upChirp time domain filter module, and the step length of the receiving module for receiving the data sent to the upChirp time domain filter module is the step length for determining the accuracy of the upChirp symbol and the downChirp symbol in the preamble of the frame structure, which is also the preamble synchronization accuracy.
Finally, it is noted that the above embodiments are only for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made thereto without departing from the spirit and scope of the present invention, which is intended to be covered by the claims of the present invention.
Claims (6)
1. The system for improving the success rate of the preamble detection of the frame structure of the Internet of things is characterized by comprising a receiving module, a local positive sequence generating module, a local negative sequence generating module, a positive sequence correlation module, a negative sequence correlation module, a judgment threshold value calculating module and a preamble judging module;
the receiving module is used for completing the receiving of the frame structure data on the transmission medium;
the local positive sequence generation module is used for completing generation of data with the same properties as the sequence sent by the sending end, and is called positive sequence;
the local reverse sequence generation module is used for completing generation of data with reverse properties of a sequence sent by a sending end, and is called reverse sequence;
the positive sequence correlation module is used for completing the correlation calculation of the received frame structure data and the positive sequence, and the calculation result is called a positive sequence correlation value;
the inverse sequence correlation module is used for completing the correlation calculation of the received frame structure data and the inverse sequence, and is called an inverse sequence correlation value;
the judgment threshold value calculation module is used for completing calculation of the judgment threshold value, and the calculation method is that the absolute value of the correlation value of the positive sequence minus the correlation value of the negative sequence;
and the preamble judging module is used for finishing the final judgment of whether the preamble data is or not, if the judging threshold value is larger than a fixed judging threshold value, the preamble data is valid, and otherwise, the preamble data is not valid.
2. The system for improving the preamble detection success rate of an internet of things frame structure according to claim 1, wherein the positive sequence correlation module adopts an upChirp time domain filter.
3. The system for improving the preamble detection success rate of an internet of things frame structure according to claim 1, wherein the inverse sequence correlation module adopts a downChirp time domain filter.
4. The method for improving the success rate of the preamble detection of the frame structure of the Internet of things is characterized by comprising the following steps of:
s1: firstly, locally generating positive sequence data and Negative sequence data of a symbol at a receiving end, and respectively marking the positive sequence data and the Negative sequence data as a position_sequences array and a negative_sequences array; then the receiving end receives data on the receiving medium and stores the data in the receiving_data array, and the length of the received data is a length unit of one symbol;
s2: performing correlation calculation by using a position_sequences array and a received_data array, and marking the correlation value as a positive sequence correlation value P_xcor; the formula is adopted as follows: p_xcor=xcorr (received_data, position_sequences), where xcorr represents a correlation calculator;
s3: performing correlation calculation by using the negative_sequences array and the received_data array, and marking the result as an inverse sequence correlation value N_xcor; the formula is adopted as follows: n_xcor=xcorr (received_data, negative_sequence);
s4: and calculating a preamble symbol judgment threshold value R_threshold value of the received signal, wherein the value is the absolute value of the difference value between the positive sequence correlation value and the negative sequence correlation value, and the expression is as follows: r_threshold value=abs (p_xcor-n_xcor), where abs represents an absolute value taking operator;
s5: determining a fixed decision threshold value preambiea_threshold value; if R_threshold is greater than Preamble_threshold, then a valid preamble symbol is received; otherwise, indicating that noise is received and is not a valid preamble symbol;
s6: if a valid preamble symbol is received in step S5, the receiving end starts a preamble reception procedure, otherwise continues to receive data on the receiving medium.
5. The method for improving the preamble detection success rate of the frame structure of the internet of things according to claim 4, wherein in step S2, the received receive_data is passed through a local upChirp time domain filter to output a positive sequence correlation value p_xcor.
6. The method for improving the preamble detection success rate of an Internet of things frame structure according to claim 4, wherein in step S3, and outputting the received data through a local down Chirp time domain filter to obtain an inverse sequence correlation value N_xcor.
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