Quality evaluation method and system of Bluetooth adaptive frequency hopping channel, and terminal equipment

Abstract

The invention discloses a quality evaluation method and system of a Bluetooth adaptive frequency hopping channel, terminal equipment and a computer readable storage medium, and the quality evaluation method of the Bluetooth adaptive frequency hopping channel comprises the steps: obtaining RSSI of each Bluetooth channel for multiple times, and obtaining each group of RSSI; determining a current channel parameter of each Bluetooth channel according to M groups of RSSIs with the latest acquisition time; determining a quality factor of each pair of Bluetooth channels according to the current channel parameter of each Bluetooth channel; and marking the G pair Bluetooth channel with the lowest quality factor value as a clean channel. According to the method and the device, the G pair Bluetooth channel with the relatively low quality factor value is selected as the clean channel in a sorting mode, so that clean channel assessment is realized, the method and the device can be suitable for interference environments with different intensities and complex interference environments with multiple interferences coexistence, the clean channel can be accurately detected under the interference intensity in a great range, and the method and the device are suitable for popularization and application. The problems that interference cannot be effectively distinguished in a large range and a small number of clean channels in different strong and weak multi-interference mixed environments are difficult to assess by other schemes are solved.

Description

Technical Field

[0001] The present application relates to the field of wireless communication technology, and in particular to a quality assessment method and system for a Bluetooth adaptive frequency hopping channel, a terminal device, and a computer-readable storage medium. Background Art

[0002] With the popularization of wireless video surveillance, True Wireless Stereo (TWS) Bluetooth headsets and various Internet of Things (IoT) devices, the 2.4G Industrial, Scientific and Medical (ISM) band has become increasingly crowded. This congestion has led to competition for spectrum resources, which in turn has caused problems such as signal interference, reduced data transmission rate and fluctuations in communication quality. Especially in densely populated urban environments, such as commercial centers, stations and airports, interference between multiple wireless networks has become more significant. In order to avoid interference, TWS Bluetooth headsets use adaptive frequency hopping to avoid interference. Adaptive frequency hopping can reduce the probability of collision with interference. However, especially in crowded environments with 2 to 3 wireless LAN hotspots (Wireless Fidelity, WiFi), since a 2.4G WiFi can occupy 20MHz to 40MHz channel bandwidth, there are usually only 20 or fewer clean channels left in the 79 Bluetooth channels. If adaptive frequency hopping cannot be effectively limited to relatively clean channels, the packet loss caused by high interference collisions will cause the TWS Bluetooth headset to freeze, seriously affecting the user experience.

[0003] The key to the performance of adaptive frequency hopping to avoid interference depends on how to accurately evaluate the quality of different channels, so that the adaptive frequency hopping communication channel is limited to switching in relatively clean channels. The existing solution to determine whether there is interference in the channel is usually to set one or more thresholds or thresholds, and to evaluate whether the channel is an interference channel by judging the energy of the scanned channel and the size of the threshold. When the energy of the channel exceeds one or more specified thresholds, the channel is determined to be an interference channel, otherwise the channel is determined to be a clean channel that can be used for communication.

[0004] When identifying a single interference of a specific size in the environment, the above-mentioned channel quality assessment scheme based on setting one or more thresholds can achieve better results. However, since there are usually multiple interference sources in the 2.4GISM band, such as different WiFi routers located at different frequencies and different distances, it is difficult for the existing scheme to accurately evaluate the appropriate channel for communication. When the threshold is too large, it is easy to misidentify the clean channel, and when the threshold is too small, it is easy to miss the clean channel. In order to optimize the shortcomings of fixed thresholds, some manufacturers or researchers have proposed some solutions for dynamically changing thresholds, but the adjustment of dynamic thresholds always has the disadvantage of lag and is difficult to be well applied to complex environments where multiple interferences coexist. In addition, for TWS Bluetooth headsets, the received signal strength (Received Signal Strength Indicator, RSSI) can usually vary in a large range of about -10dBm to -95dBm. Then, WiFi broadband interference with a strength range of -20dBm / MHz to -105dBm / MHz in different usage scenarios may cause communication failures and cause jams. It is difficult for existing technical solutions to accurately identify clean channels for communication within such a large signal range. Summary of the invention

[0005] In view of this, the present application provides a quality assessment method and system for a Bluetooth adaptive frequency hopping channel, a terminal device, and a computer-readable storage medium to enhance the anti-interference performance of a Bluetooth channel quality assessment solution.

[0006] The present application provides a method for evaluating the quality of a Bluetooth adaptive frequency hopping channel, comprising the following steps:

[0007] Obtain the RSSI of each Bluetooth channel multiple times to obtain each group of RSSI;

[0008] Determine the current channel parameters of each of the Bluetooth channels according to the M groups of RSSIs with the most recent acquisition time;

[0009] Determining the quality factor of each pair of the Bluetooth channels according to the current channel parameters of each of the Bluetooth channels;

[0010] The G pair of Bluetooth channels with the lowest quality factor value is marked as clean channels.

[0011] Optionally, the RSSI acquisition process of each group includes: scanning each Bluetooth channel to obtain the initial signal reception strength of each Bluetooth channel; filtering the initial signal reception strength of each Bluetooth channel according to the initial signal reception strength of an adjacent Bluetooth channel to obtain the RSSI of each Bluetooth channel.

[0012] Optionally, the filtering process of the initial signal reception strength of each Bluetooth channel includes: rssi_ch_avg[i]=w11*rssi[i-1]+w12*rssi[i]+w13*rssi[i+1]); wherein rssi_ch_avg[i] represents the RSSI of the i+1th Bluetooth channel, rssi[i] represents the initial signal reception strength of the i+1th Bluetooth channel, and rssi[i-1] represents the i-th Bluetooth channel. Initial signal reception strength, rssi[i+1] represents the initial signal reception strength of the i+2th Bluetooth channel, rssi_ch_avg[0]=(rssi[0]+rssi[1]) / 2, rssi_ch_avg[N-1]=(rssi[N-2]+rssi[N-1]) / 2, 1≤i≤N, N is the total number of Bluetooth channels, w11, w12 and w13 are preset smoothing filter coefficients, w11+w12+w13=1.

[0013] Optionally, the method of determining the current channel parameters of each of the Bluetooth channels based on the M groups of RSSIs with the most recent acquisition time includes: writing each group of the RSSI into a row in a data table with M rows and N columns in sequence, wherein the newly written row of data overwrites the original data at the corresponding position in the data table; and determining the current channel parameters of the N Bluetooth channels respectively according to the N columns of data in the data table with M rows and N columns.

[0014] Optionally, determining the current channel parameters of the N Bluetooth channels respectively according to the N columns of data in the M-row-N-column data table includes: Wherein, R_time_avg[i-1] represents the current channel parameter of the i-th Bluetooth channel, R[j-1][i-1] represents the data in the j-th row and i-th column in the M-row and N-column data table, 1≤j≤M, 1≤i≤N, and N is the total number of Bluetooth channels.

[0015] Optionally, the process of determining the quality factor of each pair of Bluetooth channels includes: Q_ch[a]=(R_time_avg[2a-1-1]+R_time_avg[2a-1]) / 2; wherein, Q_ch[a] represents the quality factor of the ath pair of Bluetooth channels, R_time_avg[2a-1-1] represents the current channel parameter of the 2a-1th Bluetooth channel, R_time_avg[2a-1] represents the current channel parameter of the 2ath Bluetooth channel, 1≤a≤N / 2, N is the total number of Bluetooth channels, if N is an odd number, the quality factor of the last pair of Bluetooth channels is the current channel parameter of the Nth Bluetooth channel.

[0016] Optionally, the value of M is 8.

[0017] Optionally, the value of G is 10.

[0018] The present application also provides a quality assessment system for a Bluetooth adaptive frequency hopping channel, comprising:

[0019] The first acquisition module is used to acquire the RSSI of each Bluetooth channel multiple times to obtain each group of RSSI;

[0020] A second acquisition module is used to determine the current channel parameters of each Bluetooth channel according to the M groups of RSSI with the latest acquisition time;

[0021] A determination module, configured to determine the quality factor of each pair of the Bluetooth channels according to the current channel parameters of each of the Bluetooth channels;

[0022] The marking module is used to mark the G pair of Bluetooth channels with the lowest quality factor value as clean channels.

[0023] The present application also provides a terminal device, including: a memory and a processor, wherein the memory stores a quality assessment program for a Bluetooth adaptive frequency hopping channel, and when the quality assessment program for the Bluetooth adaptive frequency hopping channel is executed by the processor, the steps of any of the above-mentioned quality assessment methods for the Bluetooth adaptive frequency hopping channel are implemented.

[0024] The present application also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of any of the above methods for evaluating the quality of a Bluetooth adaptive frequency hopping channel are implemented.

[0025] The quality assessment method and system, terminal device, and computer-readable storage medium of the Bluetooth adaptive frequency hopping channel of the present application obtain RSSI of each Bluetooth channel multiple times to obtain each group of RSSI, determine the current channel parameters of each Bluetooth channel according to the M groups of RSSI with the most recent acquisition time, determine the quality factor of each pair of Bluetooth channels according to the current channel parameters of each Bluetooth channel, and select G pairs of Bluetooth channels with relatively low quality factor values ​​as clean channels by sorting, so as to achieve clean channel assessment, which can be applicable to interference environments with different strengths and complex interference environments with multiple interferences coexisting, and can accurately detect clean channels under a wide range of interference intensities, thereby solving the problem that other solutions cannot effectively distinguish interference over a large range and it is difficult to assess a small number of clean channels in a mixed environment with different strengths and multiple interferences.

[0026] Furthermore, the quality assessment method of the above-mentioned Bluetooth adaptive frequency hopping channel can also perform frequency domain smoothing and time domain two-dimensional smoothing on the channel parameters of each Bluetooth channel. On the one hand, it can improve the situation where WiFi-type broadband interference is not transmitted and affects the assessment result during channel scanning. On the other hand, it can improve the situation where other frequency hopping Bluetooth signals that may exist in the environment are misjudged as fixed channel interference.

[0027] It can be seen that the present application can improve the anti-interference performance in the Bluetooth channel quality assessment process from many aspects and enhance the reliability of the Bluetooth channel quality assessment process. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0029] Figure 1 It is a schematic diagram of a quality assessment method for a Bluetooth adaptive frequency hopping channel according to an embodiment of the present application;

[0030] Figure 2 This is a schematic diagram of M rows and N columns of data representation in one embodiment of the present application;

[0031] Figure 3 It is a schematic diagram of the structure of a quality assessment system for a Bluetooth adaptive frequency hopping channel according to an embodiment of the present application. DETAILED DESCRIPTION

[0032] The technical solutions in the embodiments of the present application are clearly and completely described below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present application. In the absence of conflict, the following embodiments and their technical features can be combined with each other.

[0033] In a first aspect, the present application provides a method for evaluating the quality of a Bluetooth adaptive frequency hopping channel. The method for evaluating the quality of a Bluetooth adaptive frequency hopping channel can be performed by a terminal device such as a Bluetooth device that needs to perform Bluetooth channel quality evaluation. Figure 1 As shown, the quality assessment method of the Bluetooth adaptive frequency hopping channel includes the following steps S110 to S140.

[0034] S110, acquiring RSSI (received signal strength) of each Bluetooth channel multiple times to obtain each group of RSSI.

[0035] Optionally, the above step S110 can obtain the RSSI of each Bluetooth channel by scanning each Bluetooth channel, for example, there are 79 Bluetooth channels, and all 79 channels can be scanned one by one at a time to obtain a group of RSSI. Optionally, after obtaining a group of RSSI, the above step S110 can also perform filtering and other interference removal and / or noise processing on the group of RSSI to obtain a group of RSSI after interference removal and / or noise processing, thereby improving the effectiveness of the final group of RSSI. Furthermore, by repeatedly performing the above operation of scanning all 79 channels one by one to obtain a group of RSSI, and performing interference removal and / or noise processing on the obtained RSSI, multiple groups of required RSSI can be obtained successively.

[0036] S120: Determine the current channel parameters of each Bluetooth channel according to the M groups of RSSIs acquired most recently.

[0037] The most recent M groups of RSSI refer to the RSSI of each Bluetooth channel obtained M times most recently, where M may be a natural number greater than or equal to 2, so as to determine the channel parameters that can accurately characterize the quality of each current Bluetooth channel according to the M groups of RSSI.

[0038] Optionally, the step S120 may pre-construct a data storage structure for storing each group of RSSIs, and store each group of RSSIs in chronological order, so that the M groups of RSSIs that are most recent in time may be efficiently and accurately obtained from the data storage structure.

[0039] S130: Determine a quality factor of each pair of the Bluetooth channels according to current channel parameters of each of the Bluetooth channels.

[0040] The above step S130 can determine two adjacent Bluetooth channels as a pair of Bluetooth channels. If the total number of Bluetooth channels is an odd number, the last Bluetooth channel can form a pair of Bluetooth channels alone. Optionally, the quality factor of a pair of Bluetooth channels can be determined based on the current channel parameters of each Bluetooth channel in the pair of Bluetooth channels. For example, a current channel parameter with higher accuracy can be selected from the current channel parameters of each Bluetooth channel as the quality factor of the pair of Bluetooth channels, etc.

[0041] S140, marking the G pair Bluetooth channel with the lowest quality factor value as a clean channel, so as to be used by terminal devices such as Bluetooth devices when performing adaptive frequency hopping communication.

[0042] The lower the quality factor of a pair of Bluetooth channels, the cleaner the pair of Bluetooth channels is. The above step S140 can sort each pair of Bluetooth channels from low to high according to the quality factor value, and select G pairs of Bluetooth channels with relatively low quality factor values ​​as clean channels. The relatively preferred clean channels can be selected by sorting, which can be applicable to interference environments of different strengths and complex interference environments with multiple interferences. Clean channels can be accurately detected under a wide range of interference intensities, such as WiFi interference environments with intensities as high as -20dBm / MHz and as low as -105dBm / MHz. The interference channels can be accurately distinguished, which solves the problem that other solutions cannot effectively distinguish interference over a large range and it is difficult to evaluate a small number of clean channels in a mixed environment with different strengths and multiple interferences. Optionally, the value of G can be set according to the relevant provisions in the Bluetooth communication standard; for example, if the Bluetooth communication standard requires that the frequency of the frequency hopping sequence is greater than or equal to 20, the value of G can be 10 or other values ​​that meet the corresponding standards; when facing other provisions, G can also be set to other values.

[0043] Specifically, the process of determining the quality factor of each pair of Bluetooth channels includes: Q_ch[a]=(R_time_avg[2a-1-1]+R_time_avg[2a-1]) / 2; wherein Q_ch[a] represents the quality factor of the ath pair of Bluetooth channels, R_time_avg[2a-1-1] represents the current channel parameter of the 2a-1th Bluetooth channel, R_time_avg[2a-1] represents the current channel parameter of the 2ath Bluetooth channel, 1≤a≤N / 2, and N is the total number of Bluetooth channels. If N is an odd number, the quality factor of the last pair of Bluetooth channels is the current channel parameter of the Nth Bluetooth channel. For example, if N=79, then: Q_ch

[40] =R_time_avg

[78] , Q_ch[a] represents the quality factor of the 40th pair of Bluetooth channels, and R_time_avg

[78] represents the current channel parameter of the 79th Bluetooth channel.

[0044] The above-mentioned quality assessment method of the Bluetooth adaptive frequency hopping channel obtains each group of RSSI by acquiring the RSSI of each Bluetooth channel multiple times, determines the current channel parameters of each Bluetooth channel according to the M groups of RSSI with the most recent acquisition time, determines the quality factor of each pair of Bluetooth channels according to the current channel parameters of each Bluetooth channel, and selects G pairs of Bluetooth channels with relatively low quality factor values ​​as clean channels by sorting, so as to realize clean channel assessment. It can be applied to interference environments with different strengths and complex interference environments with multiple interferences. It can accurately detect clean channels under a wide range of interference intensities, and solves the problem that other solutions cannot effectively distinguish interference over a large range and it is difficult to evaluate a small number of clean channels in a mixed environment with different strengths and multiple interferences.

[0045] In some embodiments, the RSSI acquisition process for each group includes steps S111 to S112.

[0046] S111, scanning each of the Bluetooth channels to obtain an initial signal reception strength of each of the Bluetooth channels.

[0047] Specifically, the above step S111 can scan and obtain the RSSI (ie, initial signal reception strength) of each Bluetooth channel, and the initial signal reception strengths of N Bluetooth channels can be recorded as rssi[0] to rssi[N-1].

[0048] Optionally, step S111 may scan all N Bluetooth channels one by one at a time to obtain initial signal reception strengths of the N Bluetooth channels.

[0049] Optionally, step S111 may also scan some channel frequencies in an interval scanning manner, and then obtain the initial signal reception strength of all N Bluetooth channels by interpolation. For example, only odd-numbered channels or even-numbered channels are scanned once at intervals to obtain the initial signal reception strength of the corresponding channels, and the initial signal reception strength of other channels is obtained by interpolation, thereby obtaining the initial signal reception strength of N Bluetooth channels.

[0050] S112: Filter the initial signal reception strength of each Bluetooth channel according to the initial signal reception strength of the adjacent Bluetooth channel to obtain the RSSI of each Bluetooth channel.

[0051] The above step S112 filters the initial signal reception strength of each Bluetooth channel according to the initial signal reception strength of the adjacent Bluetooth channel. For wideband interference, the fluctuation effect of high peak-to-average ratio interference scanning can be reduced. For narrowband interference, the adjacent frequency points on both sides of the interference can be avoided from being selected as clean channels as much as possible.

[0052] Optionally, the above step S112 may implement filtering by smoothing between adjacent channels in the frequency domain, or may implement filtering by other frequency domain smoothing filtering methods.

[0053] In some examples, the filtering process of the initial signal reception strength of each of the Bluetooth channels includes: rssi_ch_avg[i]=w11*rssi[i-1]+w12*rssi[i]+w13*rssi[i+1]);

[0054] Wherein, rssi_ch_avg[i] represents the RSSI of the i+1th Bluetooth channel, rssi[i] represents the initial signal receiving strength of the i+1th Bluetooth channel, rssi[i-1] represents the initial signal receiving strength of the i-th Bluetooth channel, rssi[i+1] represents the initial signal receiving strength of the i+2th Bluetooth channel, 1≤i≤N, N is the total number of Bluetooth channels. w11, w12 and w13 are preset smoothing filter coefficients respectively. Specifically, w11 is the smoothing filter coefficient corresponding to rssi[i-1], w12 is the smoothing filter coefficient corresponding to rssi[i], w13 is the smoothing filter coefficient corresponding to rssi[i+1], w11+w12+w13=1, for example, w11=w12=w13=1 / 3, etc., and the symbol * represents multiplication.

[0055] In addition, the filtering processing of the initial signal reception strength of the Bluetooth channels at both ends (such as the first and last Bluetooth channels) can be flexibly adjusted according to needs. For example, the frequency domain smoothing filtering process corresponding to the first Bluetooth channel may include: rssi_ch_avg[0]=(rssi[0]+rssi[1]) / 2; the frequency domain smoothing filtering process corresponding to the last Bluetooth channel may include: rssi_ch_avg[N-1]=(rssi[N-2]+rssi[N-1]) / 2.

[0056] Optionally, the frequency domain smoothing filtering process can also be flexibly adjusted by transforming the number of smoothed data and / or the weighted coefficient of the smoothing calculation to improve the filtering quality.

[0057] In some embodiments, determining the current channel parameters of each of the Bluetooth channels according to the M groups of RSSIs acquired most recently includes steps S121 to S122.

[0058] S121, write each group of RSSI into a row in the M-row and N-column data table in sequence, wherein the newly written row of data overwrites the original data at the corresponding position in the data table, that is, write each group of RSSI into the M-row and N-column data table in sequence in a cyclic manner, wherein a row of data corresponds to a group of RSSI obtained at one time, and a column of data corresponds to the latest M groups of RSSI of a Bluetooth channel.

[0059] Specifically, N = 79, M rows and N columns data table can refer to Figure 2 As shown, the RSSI of 79 Bluetooth channels can be recorded as rssi_ch_avg[0:78], and each group of rssi_ch_avg[0:78] is cyclically overwritten and written into Figure 2In the data table with M rows and 79 columns shown, if the current result is the K-th scan calculation result (i.e., rssi_ch_avg[0:78] obtained for the K-th time), then the 79 values ​​corresponding to rssi_ch_avg[0:78] are written into the b+1th row of the data table, where b=mod(K, M), K represents the number of times a group of RSSI is obtained, which can be counted from 0 or 1, and mod() represents the remainder. In this way, the respective RSSIs recorded in the data table with M rows and N columns are the M groups of RSSIs with the most recent acquisition time. Figure 2 In the data table with M rows and 79 columns shown, R[j-1][i-1] represents the data in the j-th row and i-th column, 1≤j≤M, 1≤i≤79.

[0060] S122, determining current channel parameters of the N Bluetooth channels respectively according to the N columns of data in the M-row-N-column data table, so as to perform time domain filtering on the channel parameters of the N Bluetooth channels, and ensure the accuracy of the current channel parameters of the N Bluetooth channels finally determined.

[0061] Optionally, M takes a value such as 8, so that the M-row and N-column data table has an appropriate length, which can improve the efficiency of determining the current channel parameters of the N Bluetooth channels while ensuring the accuracy of determining the current channel parameters of the N Bluetooth channels based on the N columns of data.

[0062] Optionally, the above-mentioned step S122 can implement time domain filtering by smoothing the channel parameters of the corresponding Bluetooth channel according to the data in each column of the M-row and N-column data table; other filtering methods can also be used to implement time domain filtering, such as removing obviously abnormal RSSIs in each column (such as values ​​greater than the upper threshold and / or values ​​less than the lower threshold), and then determining the current channel parameters of the corresponding Bluetooth channel based on the average value of the remaining RSSI, etc.

[0063] In some examples, determining the current channel parameters of the N Bluetooth channels respectively according to the N columns of data in the M-row and N-column data table includes:

[0064]

[0065] Wherein, R_time_avg[i-1] represents the current channel parameter of the i-th Bluetooth channel, R[j-1][i-1] represents the data in the j-th row and i-th column in the M-row and N-column data table, 1≤j≤M, 1≤i≤N, and N is the total number of Bluetooth channels.

[0066] This example can implement two-dimensional time domain smoothing processing on the channel parameters of each Bluetooth channel. The time domain smoothing processing is combined with the frequency domain smoothing processing to improve the situation where WiFi-type broadband interference is not transmitted and affects the evaluation results during channel scanning, and can also improve the situation where other frequency hopping Bluetooth signals that may exist in the environment are misjudged as fixed channel interference.

[0067] The above-mentioned quality assessment method of the Bluetooth adaptive frequency hopping channel obtains each group of RSSI by acquiring the RSSI of each Bluetooth channel multiple times, determines the current channel parameters of each Bluetooth channel according to the M groups of RSSI with the most recent acquisition time, determines the quality factor of each pair of Bluetooth channels according to the current channel parameters of each Bluetooth channel, selects G pairs of Bluetooth channels with relatively low quality factor values ​​as clean channels by sorting, thereby realizing clean channel assessment, which can be applied to interference environments of different strengths and complex interference environments with multiple interferences, and can accurately detect clean channels under a wide range of interference intensities, solving the problem that other solutions cannot effectively distinguish interference over a large range and are difficult to assess a small number of clean channels in a mixed environment of different strengths and multiple interferences. In addition, the above-mentioned quality assessment method of the Bluetooth adaptive frequency hopping channel can also perform frequency domain smoothing and time domain two-dimensional smoothing on the channel parameters of each Bluetooth channel, which can improve the situation that WiFi-type broadband interference is not transmitted and affects the evaluation results during channel scanning, and can also improve the situation that other frequency hopping Bluetooth signals that may exist in the environment are misjudged as fixed channel interference. It can be seen that the above-mentioned Bluetooth adaptive frequency hopping channel quality assessment method can improve the anti-interference performance in the Bluetooth channel quality assessment process from many aspects and enhance the reliability of the Bluetooth channel quality assessment process.

[0068] The second aspect of the present application provides a quality assessment system for a Bluetooth adaptive frequency hopping channel, which can be provided in a terminal device such as a Bluetooth device that needs to perform Bluetooth channel quality assessment. Figure 3 As shown, the quality assessment system of the Bluetooth adaptive frequency hopping channel includes:

[0069] The first acquisition module 110 is used to acquire the RSSI of each Bluetooth channel multiple times to obtain each group of RSSI;

[0070] A second acquisition module 120, configured to determine the current channel parameters of each of the Bluetooth channels according to the M groups of RSSIs acquired most recently;

[0071] A determination module 130, configured to determine a quality factor of each pair of the Bluetooth channels according to current channel parameters of each of the Bluetooth channels;

[0072] The marking module 140 is used to mark the G pair of Bluetooth channels with the lowest quality factor value as clean channels.

[0073] For the specific definition of the quality assessment system of the Bluetooth adaptive frequency hopping channel, please refer to the definition of the quality assessment method of the Bluetooth adaptive frequency hopping channel in the above text, which will not be repeated here. Each module in the above-mentioned quality assessment system of the Bluetooth adaptive frequency hopping channel can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the operation module in the relevant computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the operation module can call and execute the operations corresponding to the above-mentioned units.

[0074] The present application also provides a terminal device, which may include: a memory and a processor, wherein the memory stores a quality assessment program for a Bluetooth adaptive frequency hopping channel, and when the quality assessment program for the Bluetooth adaptive frequency hopping channel is executed by the processor, the steps of the quality assessment method for the Bluetooth adaptive frequency hopping channel as described in any of the above embodiments are implemented.

[0075] The present application also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the quality assessment method for the Bluetooth adaptive frequency hopping channel as described in any of the above embodiments are implemented.

[0076] Although the present application has been shown and described with respect to one or more implementations, equivalent variations and modifications will occur to those skilled in the art based on reading and understanding of this specification and the accompanying drawings. The present application includes all such modifications and variations and is limited only by the scope of the appended claims. In particular, with respect to the various functions performed by the above-mentioned components, the terms used to describe such components are intended to correspond to any component (unless otherwise indicated) that performs the specified function of the component (e.g., it is functionally equivalent), even if it is not structurally equivalent to the disclosed structure that performs the functions in the exemplary implementation of this specification shown herein.

[0077] That is, the above description is only an embodiment of the present application, and does not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the description and drawings of the present application, such as the mutual combination of technical features between the embodiments, or direct or indirect application in other related technical fields, are also included in the patent protection scope of the present application.

[0078] In addition, in the description of the present application, it should be understood that the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more features. In the description of the present application, "plurality" means two or more, unless otherwise clearly and specifically defined.

[0079] In this application, the word "exemplary" is used to mean "used as an example, illustration or description". Any embodiment described as "exemplary" in this application is not necessarily to be construed as being more preferred or more advantageous than other embodiments. In order to enable any technician in the field to implement and use the present application, the present application provides the above description. In the above description, various details are listed for the purpose of explanation. It should be understood that a person of ordinary skill in the art can recognize that the present application can be implemented without using these specific details. In other embodiments, well-known structures and processes will not be elaborated in detail to avoid unnecessary details that make the description of the present application obscure. Therefore, the present application is not intended to be limited to the embodiments shown, but is consistent with the widest range of principles and features disclosed in the present application.

Claims

1. A quality assessment method for a Bluetooth adaptive frequency hopping channel, characterized in that: The quality assessment method includes: Obtain the RSSI of each Bluetooth channel multiple times to obtain each group of RSSI; Determine the current channel parameters of each of the Bluetooth channels according to the M groups of RSSIs with the most recent acquisition time; Determining the quality factor of each pair of the Bluetooth channels according to the current channel parameters of each of the Bluetooth channels; The G pair of Bluetooth channels with the lowest quality factor value is marked as clean channels.

2. The quality assessment method of Bluetooth adaptive frequency hopping channel according to claim 1, characterized in that: The RSSI acquisition process of each group includes: Scan each of the Bluetooth channels to obtain an initial signal reception strength of each of the Bluetooth channels; The initial signal reception strength of each Bluetooth channel is filtered according to the initial signal reception strength of the adjacent Bluetooth channel to obtain the RSSI of each Bluetooth channel.

3. The quality assessment method of Bluetooth adaptive frequency hopping channel according to claim 2, characterized in that: The filtering process of the initial signal reception strength of each Bluetooth channel includes: rssi_ch_avg[i]=w11*rssi[i-1]+w12*rssi[i]+w13*rssi[i+1]); Wherein, rssi_ch_avg[i] represents the RSSI of the i+1th Bluetooth channel, rssi[i] represents the initial signal reception strength of the i+1th Bluetooth channel, rssi[i-1] represents the initial signal reception strength of the ith Bluetooth channel, rssi[i+1] represents the initial signal reception strength of the i+2th Bluetooth channel, rssi_ch_avg[0]=(rssi[0]+rssi[1]) / 2, rssi_ch_avg[N-1]=(rssi[N-2]+rssi[N-1]) / 2, 1≤i≤N, N is the total number of Bluetooth channels, w11, w12 and w13 are preset smoothing filter coefficients, w11+w12+w13=1.

4. The quality assessment method of Bluetooth adaptive frequency hopping channel according to claim 1, characterized in that: The determining the current channel parameters of each of the Bluetooth channels according to the M groups of RSSIs with the latest acquisition time includes: Write the RSSI of each group into a row in a data table with M rows and N columns in sequence, wherein the newly written row of data overwrites the original data at the corresponding position in the data table; The current channel parameters of the N Bluetooth channels are determined respectively according to the N columns of data in the M-row and N-column data table.

5. The quality assessment method of Bluetooth adaptive frequency hopping channel according to claim 4, characterized in that: The determining the current channel parameters of the N Bluetooth channels respectively according to the N columns of data in the M-row and N-column data table includes: Wherein, R_time_avg[i-1] represents the current channel parameter of the i-th Bluetooth channel, R[j-1][i-1] represents the data in the j-th row and i-th column in the M-row and N-column data table, 1≤j≤M, 1≤i≤N, and N is the total number of Bluetooth channels.

6. The quality assessment method of Bluetooth adaptive frequency hopping channel according to claim 1, characterized in that: The process of determining the quality factor of each pair of Bluetooth channels includes: Q_ch[a]=(R_time_avg[2a-1-1]+R_time_avg[2a-1]) / 2; Wherein, Q_ch[a] represents the quality factor of the a-th pair of Bluetooth channels, R_time_avg[2a-1-1] represents the current channel parameter of the 2a-1-th Bluetooth channel, R_time_avg[2a-1] represents the current channel parameter of the 2a-th Bluetooth channel, 1≤a≤N / 2, N is the total number of Bluetooth channels. If N is an odd number, the quality factor of the last pair of Bluetooth channels is the current channel parameter of the N-th Bluetooth channel.

7. The quality assessment method of Bluetooth adaptive frequency hopping channel according to claim 1, characterized in that: The value of M is 8; and / or the value of G is 10.

8. A quality assessment system for a Bluetooth adaptive frequency hopping channel, characterized in that: include: The first acquisition module is used to acquire the RSSI of each Bluetooth channel multiple times to obtain each group of RSSI; A second acquisition module is used to determine the current channel parameters of each Bluetooth channel according to the M groups of RSSI with the latest acquisition time; A determination module, configured to determine the quality factor of each pair of the Bluetooth channels according to the current channel parameters of each of the Bluetooth channels; The marking module is used to mark the G pair of Bluetooth channels with the lowest quality factor value as clean channels.

9. A terminal device, characterized in that: The terminal device may include: a memory and a processor, wherein the memory stores a quality assessment program for a Bluetooth adaptive frequency hopping channel, and when the quality assessment program for the Bluetooth adaptive frequency hopping channel is executed by the processor, the steps of the quality assessment method for the Bluetooth adaptive frequency hopping channel as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by the processor, the steps of the quality assessment method for the Bluetooth adaptive frequency hopping channel according to any one of claims 1 to 7 are implemented.

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