CN114844793B - A system and method for improving the success rate of frame structure preamble detection in the Internet of Things - Google Patents

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

A system and method for improving the success rate of frame structure preamble detection in the Internet of Things

Technical field

The invention belongs to the field of Internet of Things communication, relates to the implementation of a frame structure preamble search algorithm, and specifically relates to a system and method for improving the success rate of frame structure preamble detection in the Internet of Things.

Background technique

In the communication process of the Internet of Things, there is no strict timing and resource allocation like the public network. The sending and receiving of data in the Internet of Things is implemented in burst mode. The burst structure consists of a preamble, frame control and payload. The preamble consists of a fixed structure and is known to both the receiving end and the transmitting end. It is used for the receiving end to perform automatic gain (AGC) adjustment of the received signal, timing and frequency domain synchronization adjustment. , according to different system design requirements, it can be used for channel estimation to provide channel equalization information for frame control and load reception.

In IoT systems, frame structure leader search usually uses two methods. The first method is relatively simple, that is, searching for the received signal (Received Signal Strength Indication, RSSI) strength. The baseband part of the receiving end first performs RSSI calculation on the received data. If the calculated RSSI value is greater than a certain threshold, it is determined that there is a valid frame burst preamble. , otherwise there is no leader. Another way is to use the correlation calculation method, which is to perform correlation calculations on the received data and the local preamble sequence. If the correlation peak value is greater than a certain threshold, it is determined that there is a valid frame burst preamble. This method is also called the filter check method.

In actual engineering, although the RSSI method is simple, its performance is the worst. Especially in scenarios with large interference, the RSSI calculation value is very large, but it distinguishes the noise power and the effective preamble signal power, so it is only used for preliminary purposes in actual engineering. Decision or AGC adjustment is not used for the final decision of the leader.

In actual projects, the frame burst preamble is mainly determined by correlation between the received sequence and the local sequence. This method will greatly improve the accuracy and is also widely used in actual projects. When the noise floor of the receiving channel is large, it can also be determined whether there is a valid frame burst preamble based on the signal correlation characteristics. However, this method also has some problems. Determining whether there is a valid frame structure burst is based on the relevant power threshold. When the noise floor increases, the relevant power will also rise, and the noise may be misjudged. The preamble of the framed structure burst.

In the broadband micropower wireless power meter reading system, the linear frequency modulation (Chirp) modulation method is used for frame bursts. The preamble is composed of multiple uplink Chirp symbols and downlink Chirp symbols. This frame burst structure is known in advance at both the sending end and the receiving end.

The receiving end will receive wireless data from the sending end in real time, assuming it is receive_data. After receiving the data, it will perform related calculations with the local upChirp in real time, and the calculated correlation value is xcor_upChirp. If xcor_upChirp is greater than the fixed threshold delatValue, it is determined that there is a valid upChirp signal, and then the search for other upChirp symbols continues until all downChirp signals are searched. Finally determine the leading end position.

As described above, the xcor_upChirp value is calculated above. This is closely related to the noise floor of received receive_Data. If the noise floor increases, xcor_upChirp will also increase, so it will be very difficult to determine a reasonable DelatValue value. If delatValue is defined too large, leading errors are likely to occur; if delatValue is defined too small, leading errors are likely to occur.

Therefore, there is an urgent need for a method that can improve the accuracy of preamble search in the IoT frame structure while avoiding missed or false detection of preambles.

Contents of the invention

In view of this, the purpose of the present invention is to provide a system and method for improving the success rate of frame structure preamble detection in the Internet of Things, improve the frame structure preamble search accuracy, and avoid missed or false detection of the preamble.

In order to achieve the above objects, the present invention provides the following technical solutions:

Solution 1: A system to improve the success rate of preamble detection of the Internet of Things frame structure. As shown in Figure 1, the system includes a receiving module, a local positive sequence generation module, a local reverse sequence generation module, a positive sequence correlation module, and a reverse sequence correlation module. , Decision threshold calculation module and leading decision module;

The receiving module is used to complete the frame structure data on the transmission medium;

The local positive sequence generation module is used to complete data of the same nature as the sequence sent by the sending end, which is called a positive sequence;

The local desequence generation module is used to complete data with the opposite nature of the sequence sent by the sending end, which is called desequence. According to the characteristics of the preamble sequence, the desequence of the preamble sequence can exist in different forms;

The positive sequence correlation module is used to complete the correlation calculation between the received frame structure data and the positive sequence, and the calculation result is called the positive sequence correlation value;

The desequence correlation module is used to complete the reception of frame structure data and desequence correlation calculation, which is called the desequence correlation value;

The decision threshold calculation module is used to complete the calculation of the decision threshold. The calculation method is the absolute value of the positive sequence correlation value minus the inverse sequence correlation value;

The leading decision module is used to complete the final determination of whether it is leading data. If the decision threshold value is greater than a fixed decision threshold value, it means that it is valid leading data. Otherwise, it is not leading data. The fixed decision threshold value comes from system simulation and Actual test results.

Furthermore, the positive sequence correlation module adopts upChirp time domain filter.

Further, the desequence correlation module uses a downChirp time domain filter.

Option 2: A method to improve the success rate of IoT frame structure preamble detection, specifically including the following steps:

S1: First, the forward and reverse sequence data of a symbol are generated locally at the receiving end, which are recorded as Position_sequences array and Negative_sequence array respectively; then the receiving end receives the data on the receiving medium and saves it in the Receive_data array. The length of the received data is one symbol. length unit; step 1 in Figure 2.

S2: Use the Position_sequences array and the Receive_data array to perform correlation calculations, recorded as the positive sequence correlation value P_xcor; the formula is expressed as: P_xcor=xcorr (Receive_data, Position_sequences), where xcorr represents the correlation calculator; step 2 in Figure 2.

S3: Use the Negative_sequences array and the Receive_data array to perform related calculations, recorded as the reverse sequence correlation value N_xcor; the formula is expressed as: N_xcor=xcorr (Receive_data, Negative_sequence); step 3 in Figure 2.

S4: Calculate the leading symbol decision threshold value R_thresholdValue of the received signal. Its value is the absolute value of the difference between the positive sequence correlation value and the inverse sequence correlation value. The expression is: R_thresholdValue=abs(P_xcor–N_xcor), where abs means taking Absolute value calculator; step 4 in Figure 2.

S5: Determine the fixed decision threshold value Preamblea_thresholdValue, which is determined by system simulation and actual testing; if R_thresholdValue is greater than Preamblea_thresholdValue, it indicates that a valid preamble symbol is received; otherwise, it indicates that noise is received, which is not a valid preamble symbol; as shown in Figure 2 5 steps.

S6: If a valid preamble symbol is received in step S5, the receiving end starts the preamble reception process, otherwise it continues to receive data on the receiving medium. As shown in step 6 in Figure 2.

Further, in step S2, the received Receive_data is passed through the local upChirp time domain filter, and the positive sequence correlation value P_xcor is output.

Further, in step S3, the received Receive_data is passed through the local downChirp time domain filter, and the inverse sequence correlation value N_xcor is output.

The beneficial effect of the present invention is that: the present invention divides the preamble into two parts. The front preamble symbol is composed of a positive sequence, and the subsequent preamble symbol is composed of a reverse sequence. When determining the effective preamble symbol, not only the correlation calculation is performed with the forward sequence, but also the reverse sequence is performed. When the method of the present invention is subject to strong noise interference or signal saturation, both the forward sequence correlation value and the reverse sequence correlation value will increase. , then the absolute values of their difference values are relatively small, which is very good at avoiding the probability of misjudgment.

Other advantages, objects, and features of the present invention will, to the extent that they are set forth in the description that follows, and to the extent that they will become apparent to those skilled in the art upon examination of the following, or may be derived from This invention is taught by practicing it. The objects and other advantages of the invention may be realized and obtained by the following description.

Description of the drawings

In order to make the purpose, technical solutions and advantages of the present invention clearer, the present invention will be described in detail below in conjunction with the accompanying drawings, in which:

Figure 1 is a frame structure preamble structure diagram of the present invention;

Figure 2 is a flow chart of frame structure preamble decision making according to the present invention;

Figure 3 is a structural diagram of a broadband micro-power wireless frame in Embodiment 1;

Figure 4 is a preamble structure diagram of the broadband micro-power wireless frame structure in Embodiment 1;

Figure 5 is a time domain decision block diagram of the preamble upChirp symbol of the broadband micro-power wireless communication frame structure in Embodiment 1;

Figure 6 is a flow chart of time domain determination of frame preamble symbols in the broadband micro-power wireless communication system in Embodiment 1;

Figure 7 is a schematic diagram of the output value of the upChirp time domain filter module in Embodiment 1.

Detailed ways

The following describes the embodiments of the present invention through specific examples. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments. Various details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments only illustrate the basic concept of the present invention in a schematic manner. The following embodiments and the features in the embodiments can be combined with each other as long as there is no conflict.

The drawings are only for illustrative purposes, and represent only schematic diagrams rather than actual drawings, which cannot be understood as limitations of the present invention. In order to better illustrate the embodiments of the present invention, some components of the drawings will be omitted. The enlargement or reduction does not represent the size of the actual product; it is understandable to those skilled in the art that some well-known structures and their descriptions may be omitted in the drawings.

In the drawings of the embodiments of the present invention, the same or similar numbers correspond to the same or similar components; in the description of the present invention, it should be understood that if there are terms "upper", "lower", "left" and "right" The orientation or positional relationship indicated by "front", "rear", etc. is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the present invention and simplifying the description, and does not indicate or imply that the device or element referred to must be It has a specific orientation and is constructed and operated in a specific orientation. Therefore, the terms describing the positional relationships in the drawings are only for illustrative purposes and cannot be understood as limitations of the present invention. For those of ordinary skill in the art, they can determine the specific position according to the specific orientation. Understand the specific meaning of the above terms.

Example 1:

In order to illustrate the use of the present invention in actual scenarios, this embodiment uses a broadband micro-power wireless communication system for explanation. In this embodiment, the broadband micropower wireless communication system is mainly used for power meter reading, which is a typical Internet of Things application. Since the wireless channel is relatively poor, the system uses Chirp modulation. The system frame structure definition is shown in Figure 3.

In the wireless frame structure, the preamble, frame control and payload are all composed of Chirp modulation. The preamble part consists of a fixed bandwidth, a fixed operating frequency point and a fixed symbol length. Both the sending end and the receiving end are completely aware of the status.

In this embodiment, the frame structure preamble adopts two Chirp modulation methods. One is the upChirp signal, and the other is the downChirp signal, as shown in Figure 4. There are also two filters at the receiving end, namely upChirp time domain filter and downChirp time domain filter.

In the process of searching the frame structure of the broadband micro-power wireless communication system, the content of the frame preamble is first searched. Currently, the method is usually used. After the receiving end receives the data, it detects it through the upChirp time domain filter, and determines whether it is based on the filter output peak value. The frame structure is preceded by upChirp symbols and the downChirp time domain filter will not be used during the inspection. However, in the present invention, upChirp and downChirp time domain filters will be used together to determine whether it is an upChirp leading symbol in the frame structure.

The present invention adopts the Chirp modulation method in this embodiment. In the frame structure, both the preamble and frame control adopt this modulation method. The preamble symbol decision function block diagram in the frame structure is shown in Figure 5. According to the description of the present invention, the frame structure preamble upChirp symbol function diagram can be calculated by the receiving module, the upChirp time domain filter, the downChirp time domain filter, and the decision threshold abs(P_xcor -N_xcor), and the leading decision module. The upChirp time domain filter is a forward sequence correlator, and the downChirp time domain filter is an inverse sequence correlator.

The specific operation process is shown in Figure 6.

Step 1: The receiving end receives the broadband micropower wireless signal from the wireless interface. It first performs down-conversion on the signal to convert the received signal from the carrier frequency to the baseband signal, which is recorded as Receive_data. The length of the received data is a standard symbol length. As shown in step 1 in Figure 6.

Step 2: Pass the received Receive_data through the local upChirp time domain filter, and then output a relevant power value from the filter, recorded as the P_xcor value. As shown in step 2 in Figure 6.

Step 3: Pass the received Receive_data through the local downChirp time domain filter, and then output a relevant power value from the filter, recorded as the N_xcor value. As shown in step 3 in Figure 6.

Step 4: Calculate the upChirp symbol decision value of the wireless channel received data Receive_data. upChirp_thresholdValue=abs(P_xcor-N_xcor). abs is the absolute value calculation symbol. As shown in step 4 in Figure 6.

Step 5: Compare upChirp_thresholdValue with the decision threshold preamble_upChirpThresholdValue. If upChirp_thresholdValue is greater than or equal to the preamble_upChirpThresholdValue value, it indicates that the receiving end has received a completed upChirp preamble symbol and continues to step 6. Otherwise it indicates that it is not a leading symbol in the frame structure or an incomplete leading upChirp symbol. As shown in step 5 in Figure 6.

Step 6: In the previous steps 1 to 5, if it is determined that a frame structure leading upChirp symbol has been received, then continue to search for other upChirp symbols. Later, determine the conversion positions of the upChirp symbol and downChirp symbol, as shown in step 6 in Figure 6.

In this embodiment, in order to facilitate frame structure preamble, the receiving end usually designs the upChirp time domain filter and downChirp time domain filter as an upChirp time domain filter module, as shown in Figure 5. The received signal directly outputs 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 it needs to constantly monitor the conversion point of the upChirp symbol and downChirp symbol in the frame structure.

In this embodiment, the received data is a set of moving sequence data. As shown in Figure 7, the data is sent from the receiving module to the upChirp time domain filter module. The receiving module receives the data and sends it to the step size of the upChirp time domain filter module. , which is to determine the upChirp symbol and downChirp symbol accuracy in the frame structure preamble, and also the preamble synchronization accuracy.

Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified. Modifications or equivalent substitutions without departing from the purpose and scope of the technical solution shall be included in the scope of 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.