CN116319225A - Lead mode identification method and device and electronic equipment - Google Patents
Lead mode identification method and device and electronic equipment Download PDFInfo
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Abstract
The invention belongs to the technical field of wireless communication, and particularly relates to a preamble pattern recognition method and device and electronic equipment. Firstly, receiving a baseband sampling signal, and carrying out cross-correlation calculation on a symbol sequence corresponding to the baseband sampling signal and a local preamble sequence corresponding to a set time-frequency code when judging that an effective signal arrives; then, carrying out delay autocorrelation calculation on the obtained cross correlation calculation result and calculating the energy value of the delay autocorrelation calculation; if the maximum value of the energy value is larger than the preset peak threshold value, judging that the preamble mode corresponding to the set time-frequency code is the correct preamble mode. The method can find the correct leading mode only by executing the scanning processing process of half times of the total number of the time-frequency codes at most, has higher recognition efficiency, and particularly has higher accuracy of time-frequency code detection and recognition under the conditions of low signal-to-noise ratio and large frequency offset, small time delay expense, low realization complexity, low power consumption and strong noise and frequency offset resistance, and does not influence the speed of adding equipment into a piconet.
Description
Technical Field
The invention belongs to the technical field of wireless communication, and particularly relates to a preamble pattern recognition method and device and electronic equipment.
Background
Ultra Wideband (UWB) based on MB-OFDM is a short-distance wireless communication technology, and has the characteristics of low power consumption and high data transmission rate, and the maximum data transmission rate can reach 480Mbps. UWB is a wireless personal area network, so that neighboring devices may combine into a network, which is called a piconet. In an MB-OFDM UWB system, channelization of different Piconets (Piconets) is achieved by using different Time-Frequency Codes (TFCs) for the different Piconets. Different time-frequency codes correspond to different preamble patterns (Preamble Patterns). When a new device wants to join a current piconet, it needs to first detect the time-frequency code of the piconet, i.e., identify and determine the preamble pattern used by the piconet.
Due to the characteristics of extremely small symbol interval, extremely high transmission rate (53.3-480 Mbps), frequency hopping, dense multipath channels, large signal-to-noise ratio variation range (-8.4-24 dB) and the like of the MB-OFDM UWB system, the requirements on the speed and time of signal processing of a receiving end are met. The recognition method in the prior art is mainly based on two algorithms of auto-correlation (AC) of received signals and cross-correlation (CC) of received signals and local preamble sequences. The complexity of the AC algorithm is relatively low, but the AC algorithm is greatly influenced by noise, the AC algorithm is not ideal in performance under the condition of low signal to noise ratio, and the identification accuracy is required to be improved; the CC algorithm has strong noise immunity, but has relatively higher complexity and is greatly influenced by frequency offset. Furthermore, these approaches are mostly focused on optimizing the implementation complexity or performance of the individual functions, without optimizing the power consumption of the overall synchronization process. Moreover, a major consideration of design is the complexity of implementation. Lower implementation complexity typically results in some degree of power consumption reduction, but this is not equivalent to low power consumption. For example, a major consideration for low complexity approaches is the hardware cost of operation. However, in the low power consumption design, not only the hardware cost of the operation but also the number of times of performing the operation needs to be reduced. Therefore, the preamble is required to be identified with low power consumption and high efficiency, the identification algorithm is required to be not too complex, the execution times are less, and the noise immunity is high.
Disclosure of Invention
The invention aims to provide a preamble pattern recognition method, a preamble pattern recognition device and electronic equipment, which are used for solving the problems that the power consumption of the prior art method needs to be reduced and the recognition accuracy needs to be improved.
In order to solve the technical problems, the invention provides a preamble pattern recognition method, which comprises the following steps:
1) Receiving a baseband sampling signal, and judging whether an effective signal arrives or not;
2) When judging that the effective signal arrives, performing cross-correlation calculation on a symbol sequence corresponding to the baseband sampling signal and a local preamble sequence corresponding to the set time-frequency code;
3) Performing delay autocorrelation calculation on the cross correlation calculation result obtained in the step 2) and calculating the energy value of the delay autocorrelation calculation;
4) If the maximum value of the energy value is larger than the preset peak threshold value, judging that the preamble mode corresponding to the set time-frequency code is the correct preamble mode.
The beneficial effects are as follows: the invention realizes the identification of the correct preamble pattern through the matched filter based on the cross correlation, particularly carries out the cross correlation calculation on the symbol sequence corresponding to the baseband sampling signal and the local preamble sequence corresponding to the set time-frequency code when judging that the effective signal arrives, further carries out the delay self-correlation calculation on the cross correlation calculation result and calculates the energy value, when the maximum value of the energy value is larger than the preset peak threshold value, judges that the preamble pattern corresponding to the set time-frequency code is the correct preamble pattern, otherwise carries out the cross correlation calculation on the symbol sequence corresponding to the baseband sampling signal and the local preamble sequence corresponding to other time-frequency codes, and repeats the process.
Further, the cross-correlation calculation formula in step 2) is:
wherein s (n+i) is a symbol sequence corresponding to the baseband sampling signal, and
r (N) is a received baseband sampling signal, N is a received sampling signal index, n=0, 1, & i is a correlation window data index, i=0, 1, & N-1, N is a correlation window length; c (i) is a local preamble sequence corresponding to a set time-frequency code, Q c (i) For the quantized value of the local preamble sequence c (i), Q c (i) Round (c (i)), round (·) is rounded; sign (·) represents a signed function; |. | represents taking absolute value; f (n) is the cross-correlation calculation result.
Further, the calculation formula of the energy value is:
E(n)＝|F(n)·F * (n-M·L)| 2
wherein E (n) is the calculated energy value; f (n) is the cross-correlation calculation result; f (F) * (n) is the conjugate of F (n); l is the time domain point number of one leading OFDM symbol; m is the number of OFDM symbols at intervals.
Further, in step 1), signal power calculation is performed on the received baseband sampling signal, and whether the effective signal arrives is judged according to the power change condition.
The beneficial effects are as follows: whether the effective signal arrives or not can be effectively and accurately identified by utilizing the power change condition.
Further, the following method is adopted to judge whether the effective signal arrives:
(1) comparing the product of the detected current power and the previous power with a preset threshold: if the current power is greater than the product, adding 1 to the power increment sub-value and updating the previous power; if the current power is less than or equal to the product, adding 1 to the power reduction sub-value and updating the previous power;
setting the power decrease number value to 0 when the power decrease number value is larger than a preset power decrease number threshold value, setting the power decrease number value to 0 when the power decrease number is larger than the preset power decrease number threshold value, and adding 1 when the power decrease number is smaller than or equal to the preset power decrease number threshold value and the power decrease number value is larger than the preset power increase number threshold value;
(2) and (3) repeating the process of the step (1), and judging that the effective signal arrives when the power increase number value is equal to the preset signal detection threshold value.
Further, the update formula of the previous power is:
P_last(n)＝P(n)*α+P_last(n-1)*(1-α)
where P_last (n) is the updated previous power; p_last (n-1) is the previous power before update; p (n) is the current power; alpha is a smoothing factor, and alpha is more than 0 and less than or equal to 1.
Further, the calculation formula of the power is:
wherein P (n) is the calculated power; r (N) is the received baseband sampled signal, N is the index of the received sampled signal, n=0, 1,2,.. p For power calculation window length, k is the data index in the calculation window, k=0, 1.. p -1。
Further, when the time-frequency code is 1 or 2, m=3; when the time-frequency code is 3, 4, 5, 6 or 7, m=1; when the time-frequency code is 8, 9 or 10, m=2.
In order to solve the technical problem, the invention also provides a preamble pattern recognition device, which comprises a signal detection module, a correlation calculation module and a recognition module:
and the signal detection module is used for: the device is used for receiving the baseband sampling signal and judging whether the effective signal arrives or not;
and a correlation calculation module: when the effective signal is judged to arrive, performing cross-correlation calculation on a symbol sequence corresponding to the baseband sampling signal and a local preamble sequence corresponding to the set time-frequency code, and further performing delay autocorrelation calculation on a cross-correlation calculation result and calculating an energy value of the delayed autocorrelation calculation result;
and an identification module: and the method is used for judging whether the maximum value of the energy value is larger than a preset peak threshold value, and judging that the preamble mode corresponding to the set time-frequency code is the correct preamble mode when the maximum value of the energy value is larger than the preset peak threshold value.
The beneficial effects are as follows: the identification device can ensure that the preamble pattern identification method operates effectively and reliably.
To solve the above technical problem, the present invention further provides an electronic device, which includes a memory and a processor, where the processor is configured to execute the computer program instructions stored in the memory to implement the preamble pattern recognition method described above.
The beneficial effects are as follows: the electronic equipment can ensure that the preamble pattern recognition method operates effectively and reliably.
Drawings
Fig. 1 is a schematic diagram of a band allocation of the present invention;
FIG. 2 is a diagram of a physical layer frame structure in accordance with the present invention;
fig. 3 is a block diagram of the receiver system of the present invention;
FIG. 4 is a flow chart of a preamble pattern recognition method of the present invention;
FIG. 5 is a block diagram of a preamble pattern recognition scheme of the present invention;
fig. 6 is a block diagram of a preamble pattern recognition apparatus according to the present invention.
Detailed Description
In an ultra wideband system based on MB-OFDM, each transmitted OFDM symbol is frequency hopped for transmission over a different frequency band depending on the time-frequency code employed. Before synchronization is achieved, the receiver scans all the frequency bands contained in the frequency band group and monitors a possible incoming preamble signal on a certain frequency band. If no information data packet is detected within a certain period, the receiver is switched to other frequency bands to continue monitoring. For reasons of frequency hopping, only the frequency band symbols that the receiver is listening to can be monitored for any upcoming information data packet. For example, for TFC1, one symbol will be heard every three symbol periods. To obtain the time-frequency code employed for the current signal transmission, the most common approach is to identify the preamble pattern of the frame signal, which can be achieved by using a cross-correlation based matched filter. If the received signal uses the same preamble pattern as the matched filter, the calculated value will produce a peak from which the time-frequency code can be determined. Since there are 10 time-frequency codes in total, the whole time-frequency code detection process is performed for 5 times at most, and the processing process of each scanning is identical. Based on the thought, the preamble pattern recognition method, the preamble pattern recognition device and the electronic equipment can be realized. The present invention will be described in further detail with reference to the drawings and examples.
Preamble pattern recognition method embodiment:
the following Ultra-wideband (UWB) system based on MB-OFDM adopts the combination of OFDM modulation and frequency hopping technology for data transmission. As shown in fig. 1. In the system, a spectrum bandwidth of 7.5GHz (3.1-10.6 GHz) is divided into 14 frequency bands, each band having a bandwidth of 528MHz. The first 12 bands are divided into 4 groups, each group containing 3 bands; the last 2 bands form the 5 th Band Group (Band Group). In addition, 3 frequency bands are defined as a 6 th frequency band group. According to the communication environment, the system can flexibly select a certain frequency band group. In an MB-OFDM UWB system, one symbol contains N FFT =128 IFFT samples and N ZPS =37 zero-filled suffixes. MB-OFDM UWB enables Time-frequency interleaved (Time-Frequency Interleaved, TFI) transmissions of OFDM symbols over the frequency bands comprised by the band group, with only one frequency band operating for the duration of one OFDM symbol. The system realizes the Frequency hopping switching of the Frequency band according to a Time-Frequency Code (TFC). ECMA (European Computer Manufacturers Association, european international computer manufacturers association) defines 10 time-frequency codes TFC1 to TFC10, and a Preamble Pattern (Preamble Pattern) corresponds to the time-frequency codes. Data can be transmitted on different frequency bands by using time-frequency codesAnd the frequency diversity gain and the multiple access capability of the system are improved. For example, TFC and preamble pattern for band group # 1 are shown in table 1 below:
TABLE 1
In the above table, the frequency band sequence number corresponding to each TFC represents the frequency band sequence number occupied by the hopping transmission in turn. In addition, when the system uses different TFCs, the preamble sequences applied are also different. ECMA-368 defines a unique set of 128 long preamble sequences for each TFC.
A schematic diagram of the physical frame structure defined by the MB-OFDM UWB system is shown in fig. 2, which contains three parts: preamble, header and payload data. The preamble precedes the preamble and serves primarily to aid the receiver in time synchronization, carrier offset recovery and channel estimation. The preamble is again composed of two parts: a packet/frame synchronization sequence and a channel estimation sequence. The identification of the time-frequency code or preamble pattern is based mainly on the packet/frame synchronization sequence.
The preamble pattern and the time-frequency code play an important role in the transmission of UWB system symbols based on MB-OFDM. As shown in fig. 3. At the receiving end, if correct reception is to be achieved, the time-frequency code adopted by the transmitting end must be accurately known. The invention provides a simple and efficient method for identifying and judging a preamble pattern by utilizing the characteristic of a preamble, the whole flow is shown in a figure 4, and the specific process is as follows:
step one, a receiver receives a baseband sampling signal and performs small-section signal power calculation on the received baseband sampling signal.
Specific:
the method is adopted for calculation:
wherein P (n) is the calculated power; r (n) is the received baseband sampling signal; n is the index of the received sampled signal, n=0, 1,2. k is the data index in the calculation window, k=0, 1,.. p -1，N p For power calculation window length, N in this embodiment p ＝128。
Using an iterative calculation method for simplification, P (n) can be expressed as:
and step two, judging that the effective signal arrives according to the change condition of the signal power. The signal of the MB-ofdm uwb system is a burst frame signal. The digital-to-analog converter of the receiver outputs a background noise signal before the actual signal arrives. The noise floor signal power is typically maintained at a low level. When the useful signal arrives, the received signal power may rise to a certain level. Therefore, a power threshold is preset, and in a certain detection time, if the signal power continuously exceeds the preset threshold value and is maintained for a certain time, the arrival of the effective signal is judged. In addition, in order to prevent erroneous judgment due to interference such as a pulse or a tone, the signal power duration is counted. Thus, even if the signal power fluctuates instantaneously due to interference, the final decision result is not affected. The specific process is as follows:
1) Every time a sampling signal is received, if the current power P (n) is detected to be larger than the previous power P_last (n) and the preset threshold T 1 Where T is the product of 1 The range of the available value is (1.0,2.5)]Go to step 2), otherwise go to step 3).
2) The power increase sub-value pOnCnt is accumulated by 1. If the power increase count value pOnCnt is greater than the preset power increase count threshold T on Here T on And (3) setting the power reduction frequency value pOffCnt to be zero, and then turning to the step (4), otherwise, directly turning to the step (4).
3) The power reduction count value ploffcnt is accumulated by 1. If the power reduction number value pOffCnt is greater than the preset power reduction number threshold value T off Here T off Setting the power increase sub-value pOnCnt to be zero if the value is 2, and then turning to the step 4); if the power is reduced by a sub-value pOffCnt is less than or equal to a preset power reduction frequency threshold value T off And the power increase time value pOnCnt is larger than the preset power increase time threshold value T on Accumulating the power increment sub-value pOnCnt by 1, and then turning to the step 4); if the power reduction frequency value pOffCnt is less than or equal to the preset power reduction frequency threshold value T off And the power increase time value pOnCnt is smaller than or equal to a preset power increase time threshold value T on Then go directly to step 4).
4) Updating the previous power value p_last (n), i.e. p_last (n) =p (n) ×α+p_last (n-1) ×1- α, where α is a smoothing factor, 0 < α+.ltoreq.1.
5) If the power increase number value pOnCnt is equal to the preset signal detection threshold value T Det Here T Det And if the value is 120, judging that the effective signal arrives.
And thirdly, when the arrival of the effective signal is judged, carrying out cross-correlation calculation on a symbol sequence corresponding to the baseband sampling signal and a local preamble sequence corresponding to the set time-frequency code.
The formula for performing the cross-correlation calculation is:
wherein s (n+i) is the calculated symbol sequence, and
where r (N) is a received baseband sampling signal, N is a received sampling signal index, n=0, 1,..i is a correlation window data index, i=0, 1,..n-1, N is a correlation window length, where N takes a value of n=128; c (i) is a local preamble sequence corresponding to a set TFC, Q c (i) For the quantized value of the local preamble sequence c (i), Q c (i) Round (c (i)), round (·) is rounded; sign (·) represents a signed function; |. | represents taking absolute values.
And step four, judging the cross-correlation result, and identifying the correct preamble pattern.
1) F (n) obtained by the cross correlation calculation is subjected to delay autocorrelation and the energy value is calculated, wherein the calculation formula is as follows:
E(n)＝|F(n)·F * (n-M·L)| 2 (5)
wherein, L is the number of time domain points of a preamble OFDM symbol, and the value here is l=165; m is the number of the spaced OFDM symbols, the value of M is determined according to TFC, in MB-OFDM UWB system, M takes 3 when the time frequency code tfc=1 or 2, M takes 1 when tfc=3, 4, 5, 6 or 7, and M takes 2 when tfc=8, 9 or 10; f (F) * And (n) is the conjugate of F (n).
2) Peak search is performed based on the energy value E (n) to obtain E (n) maximum value E max If satisfy E max ≥T 2 And judging that the preamble pattern corresponding to the set TFC is the correct preamble pattern. Wherein T is 2 Is a preset peak threshold value, where T 2 The value of (2) is 8.
As shown in fig. 5, it is assumed that the system operates in band group # 1. If the presence of a valid signal is detected on the frequency band 1, setting the radio frequency to be fixed on the frequency band 1 to receive data, setting the TFC indexes or the preamble mode indexes corresponding to the correlators 1 to 3 to be 1, 3 and 8, respectively, and monitoring 4 OFDM symbol periods (the parameter refers to the duration of detection, and theoretically, the maximum OFDM symbol interval 3 under each TFC is set, but in order to shorten the time delay of the whole detection process as much as possible, the value is preferably 4). If the preamble pattern satisfying the condition is identified, stopping the detection process and outputting the corresponding TFC/preamble pattern index. If no preamble pattern is identified, then the TFC index or preamble pattern index corresponding to the correlators 1-3 are set to 2, 4 and 9, respectively, and the monitoring is continued for 4 OFDM symbol periods. If the preamble pattern satisfying the condition is identified, stopping the detection process and outputting the corresponding TFC/preamble pattern index. If no preamble pattern is identified, the TFC index or preamble pattern index corresponding to the correlator 2 is set to 5 and 2 OFDM symbol periods are monitored. If the preamble pattern recognition condition is satisfied, the TFC index or the preamble pattern index 5 is output. If no preamble pattern is still identified, the radio frequency is fixed to band 2, and similarly, after receiving data and detecting the arrival of a signal, the relevant identification of the preamble pattern is performed. I.e. the TFC index or preamble pattern index corresponding to correlators 2 and 3 are set to 6 and 10, respectively, 3 OFDM symbol periods are monitored. If the preamble pattern satisfying the condition is identified, stopping the detection process and outputting the corresponding TFC/preamble pattern index. If no preamble pattern is identified, the radio frequency is fixed to band 3, and after receiving data and detecting the arrival of a signal, the relevant identification preamble pattern 7 is performed. All TFC/preamble pattern recognition is completed so far.
In summary, the present invention performs cross-correlation computation on the received signal and the matched filter, performs delay autocorrelation computation on the cross-correlation computation result, and determines the energy value of the delayed autocorrelation computation result, and if the maximum value of the energy value is greater than a preset peak threshold value, determines that the preamble pattern corresponding to the set TFC is the correct preamble pattern. Since there are 10 time-frequency codes in total, only 5 scanning processes are needed to find the correct time-frequency code. The preamble pattern recognition method is low in time delay cost, low in implementation complexity, high in noise and frequency offset resistance, low in power consumption and high in application value in an MB-OFDM system.
Preamble pattern recognition apparatus embodiment:
an embodiment of a preamble pattern recognition apparatus of the present invention, as shown in fig. 6, includes a signal detection module, a correlation calculation module, and a recognition module (i.e., the TFC recognition module in fig. 6), where the apparatus can be applied to a server, a computer terminal, or various mobile devices, and functions and roles to be implemented by each module are as follows:
and the signal detection module is used for: the device is used for receiving the baseband sampling signal and judging whether the effective signal arrives or not;
and a correlation calculation module: when the effective signal is judged to arrive, performing cross-correlation calculation on a symbol sequence corresponding to the baseband sampling signal and a local preamble sequence corresponding to the set time-frequency code, and further performing delay autocorrelation calculation on a cross-correlation calculation result and calculating an energy value of the delayed autocorrelation calculation result;
TFC identification module: and the method is used for judging whether the maximum value of the energy value is larger than a preset peak threshold value, and judging that the preamble mode corresponding to the set time-frequency code is the correct preamble mode when the maximum value of the energy value is larger than the preset peak threshold value.
Electronic device embodiment:
the embodiment of the invention relates to an electronic device, which comprises a memory, a processor and an internal bus, wherein the processor and the memory are communicated with each other and data interaction is completed through the internal bus. The processor implements a preamble pattern recognition method as described in the preamble pattern recognition method embodiment of the present invention by running a software program stored in a memory. The processor can be a microprocessor MCU, a programmable logic device FPGA and other processing devices; the memory may be various types of memories for storing information by using electric energy, such as RAM, ROM, etc., or may be other types of memories.
Claims (10)
1. A preamble pattern recognition method, comprising the steps of:
1) Receiving a baseband sampling signal, and judging whether an effective signal arrives or not;
2) When judging that the effective signal arrives, performing cross-correlation calculation on a symbol sequence corresponding to the baseband sampling signal and a local preamble sequence corresponding to the set time-frequency code;
3) Performing delay autocorrelation calculation on the cross correlation calculation result obtained in the step 2) and calculating the energy value of the delay autocorrelation calculation;
4) If the maximum value of the energy value is larger than the preset peak threshold value, judging that the preamble mode corresponding to the set time-frequency code is the correct preamble mode.
2. The preamble pattern recognition method according to claim 1, wherein the cross-correlation calculation formula in step 2) is:
wherein s (n+i) is a symbol sequence corresponding to the baseband sampling signal, and
r (N) is a received baseband sampling signal, N is a received sampling signal index, n=0, 1, & i is a correlation window data index, i=0, 1, & N-1, N is a correlation window length; c (i) is a local preamble sequence corresponding to a set time-frequency code, Q c (i) For the quantized value of the local preamble sequence c (i), Q c (i) Round (c (i)), round (·) is rounded; sign (·) represents a signed function; |. | represents taking absolute value; f (n) is the cross-correlation calculation result.
3. The preamble pattern recognition method according to claim 1, characterized in that the calculation formula of the energy value is:
E(n)＝|F(n)·F * (n-M·L)| 2
wherein E (n) is the calculated energy value; f (n) is the cross-correlation calculation result; f (F) * (n) is the conjugate of F (n); l is the time domain point number of one leading OFDM symbol; m is the number of OFDM symbols at intervals.
4. The preamble pattern recognition method as claimed in claim 1, wherein the step 1) is performed by performing signal power calculation on the received baseband sampling signal, and determining whether the effective signal arrives according to the power variation condition.
5. The preamble pattern recognition method as claimed in claim 4, wherein the determination as to whether the valid signal has arrived is performed by:
(1) comparing the product of the detected current power and the previous power with a preset threshold: if the current power is greater than the product, adding 1 to the power increment sub-value and updating the previous power; if the current power is less than or equal to the product, adding 1 to the power reduction sub-value and updating the previous power;
setting the power decrease number value to 0 when the power decrease number value is larger than a preset power decrease number threshold value, setting the power decrease number value to 0 when the power decrease number is larger than the preset power decrease number threshold value, and adding 1 when the power decrease number is smaller than or equal to the preset power decrease number threshold value and the power decrease number value is larger than the preset power increase number threshold value;
(2) and (3) repeating the process of the step (1), and judging that the effective signal arrives when the power increase number value is equal to the preset signal detection threshold value.
6. The preamble pattern recognition method as claimed in claim 5, wherein the update formula of the previous power is:
P_last(n)＝P(n)*α+P_last(n-1)*(1-α)
where P_last (n) is the updated previous power; p_last (n-1) is the previous power before update; p (n) is the current power; alpha is a smoothing factor, and alpha is more than 0 and less than or equal to 1.
7. The preamble pattern recognition method according to claim 4 or 5, characterized in that the power calculation formula is:
wherein P (n) is the calculated power; r (N) is the received baseband sampled signal, N is the index of the received sampled signal, n=0, 1,2,.. p For power calculation window length, k is the data index in the calculation window, k=0, 1.. p -1。
8. A preamble pattern recognition method according to claim 3, characterized in that M = 3 when the time-frequency code is 1 or 2; when the time-frequency code is 3, 4, 5, 6 or 7, m=1; when the time-frequency code is 8, 9 or 10, m=2.
9. The preamble pattern recognition device is characterized by comprising a signal detection module, a correlation calculation module and a recognition module:
and the signal detection module is used for: the device is used for receiving the baseband sampling signal and judging whether the effective signal arrives or not;
and a correlation calculation module: when the effective signal is judged to arrive, performing cross-correlation calculation on a symbol sequence corresponding to the baseband sampling signal and a local preamble sequence corresponding to the set time-frequency code, and further performing delay autocorrelation calculation on a cross-correlation calculation result and calculating an energy value of the delayed autocorrelation calculation result;
and an identification module: and the method is used for judging whether the maximum value of the energy value is larger than a preset peak threshold value, and judging that the preamble mode corresponding to the set time-frequency code is the correct preamble mode when the maximum value of the energy value is larger than the preset peak threshold value.
10. An electronic device comprising a memory and a processor for executing computer program instructions stored in the memory to implement the preamble pattern recognition method as claimed in any one of claims 1 to 8.
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