Method and system for dynamically adjusting network data transmission bandwidth

Abstract

The invention provides a network data transmission bandwidth dynamic adjustment method and system, and the method comprises the steps: enabling a plurality of mobile terminals to transmit a data uploading demand signal to a data storage terminal, and enabling the data storage terminal to transmit a receiving signal to the plurality of mobile terminals; the ith mobile terminal receives the kth receiving signal sent by the data storage terminal at the t moment; calculating a total signal amount complex envelope signal transmitted to the ith mobile terminal by the data storage terminal; filtering and de-noising processing is carried out to obtain a restored real signal; and dynamically adjusting the bandwidth allocation coefficient of the data storage end, and dynamically uploading the data value to the data storage end in real time by the ith mobile end according to the adjusted bandwidth allocation coefficient. According to the invention, data filtering reduction is carried out according to the signal receiving and transmitting of the simultaneous multipath data transmission between the data transmission end and the plurality of mobile ends needing to upload the data, and real-time dynamic bandwidth adjustment is carried out according to the data filtering reduction, so that the data packet loss rate is kept below a threshold value, and the data is transmitted to the data storage end in a multipath manner.

Description

Technical Field

[0001] The present invention belongs to the technical field of network data transmission, and in particular relates to a method and system for dynamically adjusting network data transmission bandwidth. Background Art

[0002] As communication networks continue to transform and upgrade towards digitalization and intelligence, business diversification and network heterogeneity continue to deepen and strengthen. Many new business applications continue to emerge, such as Internet of Vehicles and remote control. These new businesses have put forward higher and higher requirements for service quality assurance. Their key business data is extremely sensitive to latency, and it is necessary to control the end-to-end latency to milliseconds or even microseconds, the latency jitter to microseconds, and the reliability to above 99.99%. Industrial services require intelligent digital networks to provide deterministic service guarantees, but traditional network technologies are difficult to meet this requirement. Emerging businesses not only require communication networks to ensure that services have low latency to meet the requirement of latency sensitivity, but also require high bandwidth requirements. That is, the network needs to ensure dynamic bandwidth adjustment of services during network data transmission under the premise of ensuring low latency for services, so as to meet the fastest upload speed to the data storage end.

[0003] In the prior art, a Chinese patent with application number 202010838169.X discloses a system and method for realizing fast data transmission between network devices, which monitors the amount of data to be transmitted by the interconnected interactive network devices and the channel capacity of the access channel. The theoretical maximum transmission rate analysis module of the access channel is used to determine the maximum amount of data transmitted by the current access channel within a limited time, and compare the maximum amount of data with the amount of data to be transmitted between the current devices. The access channel increases the channel bandwidth analysis module for analyzing and regulating with the bandwidth of the access channel, and the preferred channel secondary data transmission marking module is used to mark the channel inside the increased bandwidth, monitor the parameters of channel transmission between interactive network devices, and the real-time transmission scheduling module of the interconnected devices is used to monitor the status of the devices connected to each other in real time, and respond to the successfully sent data in real time. However, it does not perform data filtering and restoration based on the signal reception of simultaneous multipath data transmission between the data transmission end and the multiple mobile ends that need to upload data, and further performs real-time dynamic bandwidth adjustment based on this, so that the data packet loss rate is kept below the threshold, and the data is transmitted to the data storage end with the maximum bandwidth and other mobile ends at the same time. Therefore, there is an urgent need for a method and system for dynamic adjustment of network data transmission bandwidth. Summary of the invention

[0004] In view of the above-mentioned defects, the present invention provides a method and system for dynamically adjusting the bandwidth of network data transmission. The method provided by the present invention performs data filtering and restoration based on the signal reception of simultaneous multipath data transmission between a data transmission end and multiple mobile ends that need to upload data, and further performs real-time dynamic bandwidth adjustment based on the signal reception, so that the data packet loss rate is kept below a threshold, and the data is transmitted to the data storage end simultaneously with other mobile ends in multipath transmission with the maximum bandwidth.

[0005] The present invention provides the following technical solution: a method for dynamically adjusting the bandwidth of network data transmission, wherein the method dynamically adjusts the bandwidth after processing the signal in the MIMO system based on an adaptive method, so as to ensure that the dynamic flow demand is met during the network data transmission process, and comprises the following steps:

[0006] S1: Multiple mobile terminals send data upload request signals to the data storage terminal, and the data storage terminal sends receiving signals to multiple mobile terminals;

[0007] S2: The i-th mobile terminal receives the k-th receiving signal sent by the data storage terminal at time t;

[0008] S3: Calculate the total amount of complex envelope signal transmitted by the data storage end to the i-th mobile end;

[0009] S4: filtering and denoising the total amount complex envelope signal transmitted by the data storage end to the i-th mobile phone end obtained by calculation in step S3 to obtain a restored real signal;

[0010] S5: The real signal obtained by restoration The bandwidth allocation coefficient of the data storage end is dynamically adjusted, and the i-th mobile end dynamically uploads data values ​​to the data storage end in real time according to the adjusted bandwidth allocation coefficient.

[0011] Furthermore, the S3 step includes:

[0012] S31: Calculate the kth received signal transmitted by the base station received by the i-th mobile terminal at time t

[0013]

[0014] Among them, t i The signal is received by the i-th mobile terminal The delay, A(tt i )for The amplitude of φ(tt i )for The phase, Δf iis the difference between the frequencies of the signals sent and received by the i-th mobile terminal, T is a sampling period, t∈[(i-1)T,iT], t i ∈[(i-1)T,iT], for The reception coefficient, for phase shift; i = 1, 2, ..., N; k = 1, 2, ... K; K is the total number of data storage terminals participating in network data transmission, N is the total number of mobile terminals participating in network data transmission; f0 is the transmission frequency of the data storage terminal transmitting and receiving signals;

[0015] S32: Calculate the total amount s of signals transmitted by the kth data storage end to all mobile ends k The calculation formula of (t) is:

[0016] Among them, O k (t), Q k (t) are the zero-degree phase component and the ninety-degree phase component of the received signal transmitted by the k-th data storage end, respectively;

[0017] S33: Define S0(t) = A(t)exp[μφ(t)] as the complex baseband envelope signal of the data storage end transmitting and receiving the signal, where μ is an imaginary number, and then calculate s based on this. k The complex envelope signal S(t) of (t):

[0018] Among them, n(t) is the periodic interference at time t, and ∈ is Gaussian white noise.

[0019] Furthermore, in the step S32, the kth data storage terminal transmits the zero-degree phase component O of the received signal. k (t) and the ninety degree phase component Q k The calculation formulas for (t) are as follows:

[0020]

[0021] Furthermore, in the step S31 The reception coefficient The calculation formula is as follows:

[0022] Where Δf k is the frequency difference between the transmitted and received signals of the kth data storage terminal, It is the phase shift of the received signal emitted by the data storage end.

[0023] Furthermore, the S4 step includes the following steps:

[0024] S41: Calculate the periodic interference n(t) at time t in step S33:

[0025] in, is the amplitude of the harmonic in the signal when the kth data storage terminal transmits and receives the signal at time t, η k The weight for calculating the periodic interference when the kth data storage terminal transmits and receives the signal, Re{} is the real part function of the independent variable; ω0 is the angular frequency of the data storage terminal transmitting and receiving the signal, ω0 = 2πf0;

[0026] S42: Building η k Minimize and solve the model:

[0027] Among them, Ω is the error minimization mean;

[0028] S43: continuously iteratively updating the solution result of step S42;

[0029] S44: The qth generation optimal periodic interference calculation weight is calculated by Substitute it into the formula for calculating the complex envelope signal S(t) in S33, calculate the signal-to-noise ratio at this time to determine whether it is less than the signal-to-noise ratio threshold, if so, stop the iteration; otherwise, repeat the continuous iteration of step 3.3.

[0030] Furthermore, in the step S44, the weight is calculated based on the qth generation optimal periodic interference obtained by solving The formula for calculating the signal-to-noise ratio is as follows:

[0031] Among them, SNR q is the signal-to-noise ratio of the qth generation result, Indicates that when the periodic interference calculation weight η k is the optimal periodic interference weight obtained by the qth generation iterative optimization The complex envelope signal S(t) at time ;

[0032] Signal-to-noise ratio threshold SNR Thr The calculation formula is as follows:

[0033] Where N0 is the power spectrum density of the periodic interference signal, B noise is the bandwidth of the periodic interference.

[0034] Furthermore, the step S5 includes:

[0035] S51: Calculate the bandwidth allocation coefficient ω for the i-th mobile terminal to transmit data to the data storage terminal after receiving the k-th receiving signal sent by the data storage terminal. i,k : Among them, B total The total bandwidth of the data storage end receiving uploaded data;

[0036] S52: During data transmission based on the TCP protocol, the bandwidth allocation coefficient is continuously increased under the bandwidth allocation restriction condition:

[0037] The bandwidth allocation restriction conditions are: σ is the bandwidth allocation increase coefficient, ω i,k+1 is the bandwidth allocation coefficient for transmitting data to the data storage end by the i-th mobile end after receiving the k+1-th receiving signal sent by the data storage end;

[0038] S53: After increasing the bandwidth allocation coefficient, calculate the data packet loss rate l when the i-th mobile terminal receives the k+1-th receiving signal sent by the data storage terminal and uploads data to the data storage terminal. i,k+1 :

[0039]

[0040] S54: Judgment l i,k+1 Is it less than or equal to the data packet loss rate threshold l? thr , if yes, repeat the steps S51-S52 to upload the data of the ith mobile terminal to the data storage terminal, otherwise the bandwidth allocation coefficient ω for the ith mobile terminal to upload data to the data storage terminal when receiving the k+1th receiving signal sent by the data storage terminal i,k+1 The bandwidth allocation coefficient after reduction is ω′ i,k+1 Continue uploading the data; the packet loss rate threshold l thr for:

[0041] Among them, β i,k+1 is the bandwidth allocation coefficient ω i,k+1 The reduction weight coefficient is:

[0042] Furthermore, the bandwidth allocation increase coefficient σ is calculated using the following calculation method:

[0043] Among them, RTT i,k The time it takes for the i-th mobile terminal to upload data to the data storage terminal and obtain its confirmation after receiving the k-th reception signal sent by the data storage terminal, 8ms≤RTT i,k ≤15ms; max is the maximum value function.

[0044] The beneficial effects of the present invention are:

[0045] 1. The method provided by the present invention decomposes the received signal sent by the data storage end into zero-degree phase components and ninety-degree phase components, and then calculates the complex envelope signal. The components can respectively describe the amplitude and phase of the signal, so that the receiving end can accurately restore the original signal, avoiding the defect that some key information of the signal may be lost, and at the same time reducing the envelope signal restoration distortion caused by noise, fading, and interference to which the transmission signal may be subjected during network data transmission in the wireless channel. The use of zero-degree and ninety-degree phase components and complex envelope signals helps to improve the accuracy of signal restoration. When using the complex envelope signal for restoration, the mobile terminal can detect and compensate for the phase change caused by channel fading to ensure signal quality.

[0046] 2. In the process of filtering and denoising the periodic interference in the envelope signal, the present invention iteratively updates the calculation weights of the periodic interference, and constructs The calculation model calculates the weights based on the mutual correlation matrix C, self-compensating matrix P and double conjugate matrix D of errors and samples, and the weights can be adaptively adjusted according to real-time data. This adaptive capability is very important for communication systems such as MIMO systems or beamforming where channel conditions change rapidly. The optimal periodic interference calculation weights calculated are dynamically adjusted in real time in an adaptive manner to cope with environmental changes and improve system flexibility. In adaptive filtering and MIMO systems, channel changes can be quickly tracked and errors can be reduced. The self-compensating matrix and double conjugate matrix that support the processing of multi-dimensional signals are suitable for processing multi-dimensional signals in complex form, such as multi-input and multi-output signals in MIMO systems. The mutual correlation matrix can capture the correlation between signal samples and is used for optimization processing between multiple signal sources (such as beamforming and array signal processing). Therefore, the optimal periodic interference calculation weights are finally dynamically adjusted by the method provided by the present invention. It supports multi-dimensional signal optimization and is suitable for data transmission in complex network communication systems such as MIMO communication systems, and can achieve optimal network signal transmission restoration.

[0047] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings.

[0048] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The present invention will be described in more detail below based on embodiments and with reference to the accompanying drawings, wherein:

[0050] Figure 1 A schematic diagram of data transmission between a data storage terminal and multiple mobile terminals in a method for dynamically adjusting network data transmission bandwidth of the present invention;

[0051] Figure 2 The complex envelope signal S(t) of the total amount of the transmitted signal and the zero-degree phase component I obtained by reverse calculation and reconstruction in step S3 in the method provided by the present invention are: g (t) and the ninety degree phase component Q g (t) Schematic diagram of the variation of the amplitude with the emission distance;

[0052] Figure 3 A schematic diagram showing a comparison of a fluctuation curve and a signal-to-noise ratio threshold value during the iterative optimization of a complex envelope signal in step S4 of the method provided by the present invention;

[0053] Figure 4 A comparison chart of the dynamic bandwidth adjustment effect of the method provided by the present invention and comparative examples 1-3. DETAILED DESCRIPTION

[0054] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0055] The present invention provides a method for dynamically adjusting the bandwidth of network data transmission. The method dynamically adjusts the bandwidth after processing the signal in the MIMO system based on an adaptive method, so as to ensure that the dynamic flow demand is met during the network data transmission process, such as Figure 1 As shown, the method provided by the present invention performs network dynamic adjustment on the data transmission end and the data transmission between multiple mobile ends. Figure 1 User1 is the first mobile terminal of the MIMO system, User2 is the second mobile terminal, Useri is the i-th mobile terminal, and UserN is the N-th mobile terminal. They all perform data network transmission with the data storage terminal. The data network method provided by the present invention includes the following steps:

[0056] S1: Multiple mobile terminals send data upload request signals to the data storage terminal, and the data storage terminal sends receiving signals to multiple mobile terminals;

[0057] S2: The i-th mobile terminal receives the k-th receiving signal sent by the data storage terminal at time t;

[0058] S3: Calculate the total amount of complex envelope signal transmitted by the data storage end to the i-th mobile end;

[0059] S4: filtering and denoising the total complex envelope signal of the signal transmitted from the data storage end to the i-th mobile phone end calculated in step S3 to obtain a restored real signal;

[0060] S5: The real signal obtained by restoration The bandwidth allocation coefficient of the data storage end is dynamically adjusted, and the i-th mobile end dynamically uploads data values ​​to the data storage end in real time according to the adjusted bandwidth allocation coefficient.

[0061] The S3 steps include:

[0062] S31: Calculate the kth received signal transmitted by the base station received by the i-th mobile terminal at time t

[0063]

[0064] Among them, t i The signal is received by the i-th mobile terminal The delay, A(tt i )for The amplitude of φ(tt i )for The phase, Δf i is the difference between the frequencies of the signals sent and received by the i-th mobile terminal, T is a sampling period, t∈[(i-1)T,iT], t i ∈[(i-1)T,iT], for The reception coefficient, for phase shift; i = 1, 2, ..., N; k = 1, 2, ... K; K is the total number of data storage terminals participating in network data transmission, N is the total number of mobile terminals participating in network data transmission; f0 is the transmission frequency of the data storage terminal transmitting and receiving signals;

[0065] In data transmission and wireless communication, the data storage end sends signals to multiple mobile ends, and the mobile ends need to process the received signals to restore the accurate original signals. It is of great significance and necessity to decompose the signal by the zero-degree phase component and the ninety-degree phase component, and further restore the complex envelope signal of the transmitted signal.

[0066] S32: Calculate the total amount s of signals transmitted by the kth data storage end to all mobile ends k The calculation formula of (t) is:

[0067] Among them, O k (t), Q k(t) are the zero-degree phase component and the ninety-degree phase component of the received signal transmitted by the k-th data storage end, respectively;

[0068] S33: Define S0(t) = A(t)exp[μφ(t)] as the complex baseband envelope signal of the data storage end transmitting and receiving the signal, where μ is an imaginary number, and then calculate s based on this. k The complex envelope signal S(t) of (t):

[0069] Among them, n(t) is the periodic interference at time t, and ∈ is Gaussian white noise. Figure 2 As shown in FIG. 1 , the total amount of signals s emitted by the kth data storage end to all mobile ends calculated by steps S31-S33 in the method provided by the present invention is k The complex envelope signal S(t) of the k-th data storage terminal and the zero-degree phase component O of the received signal sent by the k-th data storage terminal in step S32 k (t) and the ninety degree phase component Q k (t) The change of amplitude with the launch distance (horizontal axis) in the same coordinate system. Figure 2 As shown, the zero-degree phase component O k (t) represents the part of the signal that is in phase with the carrier, the ninety-degree phase component Q k (t) represents the part of the signal that is 90 degrees out of phase with the carrier. Since S(t) is the complex envelope signal of the received signal transmitted by K data storage terminals, S(t) is also equal to the total amount of the received signal transmitted by the kth data storage terminal calculated based on the zero-degree and ninety-degree phase components of step S32, that is, Therefore, if Figure 2 As shown, the total amount of the signal is decomposed in step S32, and the complex envelope of the zero-degree phase component and the ninety-degree phase component is again performed in step S33. The decomposition of the two components ensures that the phase and amplitude information of the signal are completely preserved, avoiding information loss due to carrier aliasing. In addition, the decomposition of the two components maps the signal to the complex plane, so that the signal model represented by complex numbers can be used for more efficient processing.

[0070] In step S32, the kth data storage terminal transmits the zero-degree phase component O of the received signal. k (t) and the ninety degree phase component Q k The calculation formulas for (t) are as follows:

[0071]

[0072] In step S31 The reception coefficient The calculation formula is as follows:

[0073] Where Δf k is the frequency difference between the transmitted and received signals of the kth data storage terminal, It is the phase shift of the received signal emitted by the data storage end.

[0074] In order to filter and reduce noise on the complex envelope signal and improve the accuracy of signal restoration of multipath propagation during mobile communication, as another preferred embodiment of the present invention, step S4 includes the following steps:

[0075] S41: Calculate the periodic interference n(t) at time t in step S33:

[0076] in, is the amplitude of the harmonic in the signal when the kth data storage terminal transmits and receives the signal at time t, η k The weight is calculated for the periodic interference when the kth data storage terminal transmits and receives the signal, Re{} is the real part function of the independent variable, that is, To take the independent variable The real part result of ω0 is the angular frequency of the signal transmitted and received by the data storage end, ω0=2πf0;

[0077] S42: Building η k Minimize and solve the model:

[0078]

[0079] S43: continuously iteratively update the solution result of step S42;

[0080] S44: The qth generation optimal periodic interference calculation weight is calculated by Substitute it into the formula for calculating the complex envelope signal S(t) in S33, calculate the signal-to-noise ratio at this time to determine whether it is less than the signal-to-noise ratio threshold, if so, stop the iteration; otherwise, repeat the continuous iteration of step 3.3.

[0081] In step S44, the weight is calculated based on the qth generation optimal periodic interference obtained by solving The formula for calculating the signal-to-noise ratio is as follows:

[0082] in, Indicates that when the periodic interference calculation weight η k is the optimal periodic interference weight obtained by the qth generation iterative optimization The complex envelope signal S(t) at Figure 3 Represented by the light blue curve; Figure 3 The light yellow curve in the figure represents the weight coefficient η of the proportion of S(t) that has not undergone the periodic interference n(t) of step S44. kThe signal situation under the optimization iteration is that after only 50 generations of iteration, the signal-to-noise ratio is always greater than the signal-to-noise ratio threshold (about 13dB);

[0083] The calculation formula of the signal-to-noise ratio threshold is as follows:

[0084] Where N0 is the power spectrum density of the periodic interference signal, B noise is the bandwidth of the periodic interference.

[0085] In order to improve η k To minimize the accuracy of the complex envelope signal obtained by solving, the present invention further optimizes the calculation result in step S43. Preferably, in step S43, the qth generation optimal periodic interference calculation weight obtained by solving the model constructed in step S42 is continuously iteratively optimized, including the following steps:

[0086] S431: Calculate the estimated value of the qth generation complex envelope signal S(t) obtained in the iterative process

[0087] Where q∈{1,2,…,H}, h∈{1,2,…,H}; H is the total number of iterations, S h (t) is the true value of the h-th generation complex envelope signal S(t) obtained in the iterative process, S q (t) is the true value of the qth generation complex envelope signal S(t) obtained in the iterative process;

[0088] S432: Calculate the estimated value of the qth generation complex envelope signal S(t) The deviation from the mean of the total samples of the H-generation iteration is

[0089] in, Calculate the weight for the hth generation of periodic interference; is the total sample mean of H generations of iterations

[0090] S433: Build Deviation The complex conjugate of The cross-correlation vector c uh :

[0091]

[0092] And construct the cross-correlation vector matrix C: The element cross-correlation vector c in the cross-correlation vector matrix C uh Provides sample estimates and the complex conjugate of the error The correlation between them makes it possible to more accurately describe the relationship between signal and noise when calculating weights. The process of minimizing errors can effectively eliminate the influence of noise on the iteration results, making the final calculated weights more accurate.

[0093] S434: Calculate self-compensation vector p ih :

[0094] And construct the self-complementing matrix P:

[0095] S435: Calculate the biconjugate vector d ih :

[0096] And construct the biconjugate matrix D:

[0097] S436: The η constructed in step S42 k The minimization solution model is converted into matrix form:

[0098]

[0099] S437: Obtain the optimal periodic interference calculation weight according to the matrix form converted in step 3.36

[0100] The self-complementing vector p in the self-complementing matrix P ih Includes the estimated value of the qth generation complex envelope signal S(t) The deviation and its conjugate complex number The product of the biconjugate matrix D and the biconjugate vector d ih Including conjugate complex numbers The use of the self-compensating matrix P and the double conjugate matrix D takes into account the phase information of the signal, which is particularly effective for processing complex signals such as wireless communication signals. The cross-correlation vector matrix C can capture the relationship between different signals and improve the stability of the system in complex environments such as multipath propagation and interference. Finally, the optimal periodic interference weight is obtained by re-conjugating the matrices, subtracting and multiplying the inverse matrices. It can ensure phase adaptation in the case of channel distortion, thereby ensuring the calculation weight of periodic interference. The robustness and stability of the algorithm make it suitable for complex environments such as multipath and non-ideal channels. Figure 3As shown, in mobile communications, the decomposition of the zero-degree phase component and the ninety-degree phase component and the complex envelope processing can effectively compensate for the superposition distortion of the received signal caused by multipath propagation. The decomposition of the zero-degree phase component and the ninety-degree phase component enables the mobile terminal to demodulate the signal more efficiently, reduce the bit error rate (BER), and ensure the stability of communication. At the same time, through multiple iterations of optimization, the true state of the signal is restored, the harmonic noise in the signal is reduced, and the signal-to-noise ratio SNR is lower than the signal-to-noise ratio threshold, thereby improving the accuracy of demodulation.

[0101] The dynamic allocation of bandwidth is a key mechanism for flow control in the TCP protocol for network data transmission. The bandwidth allocation coefficient determines how much data the sender can send before receiving an acknowledgment to avoid network congestion. It determines the transmission speed of data when it is uploaded to the data storage end. Therefore, as another preferred embodiment of the present invention, step S5 includes:

[0102] S51: Calculate the bandwidth allocation coefficient ω for transmitting data from the i-th mobile terminal to the data storage terminal after receiving the k-th receiving signal from the data storage terminal. i,k : Among them, B total The total bandwidth of the data storage end receiving uploaded data;

[0103] S52: In the process of data transmission based on the TCP protocol, under the limitation of bandwidth allocation limiting conditions, the bandwidth allocation coefficient is continuously increased to improve bandwidth utilization and quickly transmit real signals:

[0104] The bandwidth allocation restriction conditions are: σ is the bandwidth allocation increase coefficient, ω i,k+1 is the bandwidth allocation coefficient for transmitting data to the data storage end by the i-th mobile end after receiving the k+1-th receiving signal sent by the data storage end;

[0105] The bandwidth allocation increase coefficient σ is calculated as follows:

[0106] Among them, RTT i,k The time it takes for the i-th mobile terminal to upload data to the data storage terminal and obtain its confirmation after receiving the k-th receiving signal sent by the data storage terminal, 8ms≤RTT i,k ≤15ms; max is the maximum value function;

[0107] S53: After increasing the bandwidth allocation coefficient, calculate the data packet loss rate l when the i-th mobile terminal receives the k+1-th receiving signal sent by the data storage terminal and uploads data to the data storage terminal. i,k+1 :

[0108]

[0109] S54: Judgment l i,k+1 Is it less than or equal to the data packet loss rate threshold l? thr , if yes, then repeat steps S51-S52 to upload the data of the ith mobile terminal to the data storage terminal, otherwise the bandwidth allocation coefficient ω for the ith mobile terminal to upload data to the data storage terminal when receiving the k+1th receiving signal sent by the data storage terminal i,k+1 The bandwidth allocation coefficient after reduction is ω′ i,k+1 Continue uploading data; packet loss rate threshold I thr for

[0110] Among them, β i,k+1 is the bandwidth allocation coefficient ω i,k+1 The reduction weight coefficient of

[0111] Comparative Example 1

[0112] This comparative example is substantially the same as the method provided by the present invention, except that in step S3, when calculating the complex envelope signal of the total amount of the signal transmitted by the data storage end to the i-th mobile end, the zero-degree phase component and the ninety-degree phase component are not decomposed, but the inverse Fourier transform is directly performed to solve the complex envelope signal.

[0113] Comparative Example 2

[0114] This comparative example is substantially the same as the method provided by the present invention, except that after calculating the total complex envelope signal of the signal transmitted by the data storage end to the i-th mobile end in step S3, in the filtering and denoising process of step S4, the signal-to-noise ratio threshold of the filtered signal is not limited and solved, and the cross-correlation vector matrix C, the self-compensation matrix P and the double conjugate matrix D are not constructed, and the optimal periodic interference calculation weight is performed. The solution is directly based on the least squares method.

[0115] Comparative Example 3

[0116] During the process of dynamic bandwidth adjustment, no packet loss rate is calculated. i,k+1 Less than or equal to the packet loss rate threshold l thr The limit is not within the packet loss rate l i,k+1 Greater than the packet loss rate threshold l thr In the case of i,k+1The weight of the k+1th signal is used to reduce the bandwidth allocation coefficient of the transmission. It is only determined whether each signal transmission exceeds the bandwidth limit of the data storage end when it is synchronized with the signals of other mobile ends and transmitted to the data storage end, and whether to perform the signal transmission of the mobile end or reduce the data throughput setting of the signal transmission.

[0117] like Figure 4 As shown, it is a bar chart comparing the throughput of a mobile terminal when the data storage terminal and multiple mobile terminals perform multipath transmission in the method of the present invention and the methods of Comparative Examples 1 to 3. The horizontal axis is the number of mobile terminals. The blue column is the method provided by the present invention, the yellow column is the method of Comparative Example 1, the green column is the method of Comparative Example 2, and the red column is the method of Comparative Example 3. Figure 4 As shown, the method provided by the present invention performs data filtering and restoration according to the signal reception of simultaneous multipath data transmission between the data transmission end and multiple mobile ends that need to upload data, and further performs real-time dynamic bandwidth adjustment based on this, so that the data packet loss rate is kept below the threshold, and the data is transmitted to the data storage end with the maximum bandwidth and other mobile ends at the same time in multipath transmission, so that the original receiving signal sent by the data storage end can be accurately restored at the multiple mobile ends, and the throughput of the data storage end during the multipath transmission between the multiple mobile ends and the data storage end can be effectively improved, and the data of multiple mobile ends can be uploaded and stored with the maximum allowable receiving bandwidth.

[0118] The network data transmission bandwidth dynamic method provided in the present application may be in the form of a computer program product implemented on one or more storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing program code. Machine-readable storage media include permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. Information can be a computer-readable instruction, a data structure, a module of a program, or other data. Examples of machine-readable storage media include but are not limited to: phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, read-only compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device.

[0119] It should be noted that the serial numbers of the above-mentioned embodiments of the present invention are only for description and do not represent the advantages and disadvantages of the embodiments. In this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. And the terms "include", "comprise" or any other variants thereof in this article are intended to cover non-exclusive inclusion, so that a process, device, article or method including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, device, article or method. In the absence of further restrictions, an element defined by the sentence "including a..." does not exclude the existence of other identical elements in the process, device, article or method including the element.

[0120] The above are only specific embodiments of the present disclosure, so that those skilled in the art can understand or implement the present disclosure. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present disclosure. Therefore, the present disclosure will not be limited to these embodiments herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for dynamically adjusting the bandwidth of network data transmission, wherein the method dynamically adjusts the bandwidth after processing the signal in the MIMO system based on an adaptive method, so as to ensure that the dynamic flow demand is met during the network data transmission process, and is characterized in that: The following steps are involved: S1: Multiple mobile terminals send data upload request signals to the data storage terminal, and the data storage terminal sends receiving signals to multiple mobile terminals; S2: The i-th mobile terminal receives the k-th receiving signal sent by the data storage terminal at time t; S3: Calculate the total amount of complex envelope signal transmitted by the data storage end to the i-th mobile end; S4: filtering and denoising the total amount complex envelope signal transmitted by the data storage end to the i-th mobile phone end obtained by calculation in step S3 to obtain a restored real signal; S5: The real signal obtained by restoration The bandwidth allocation coefficient of the data storage end is dynamically adjusted, and the i-th mobile end dynamically uploads data values ​​to the data storage end in real time according to the adjusted bandwidth allocation coefficient.

2. The method for dynamically adjusting network data transmission bandwidth according to claim 1, characterized in that: The S3 step includes: S31: Calculate the kth received signal transmitted by the base station received by the i-th mobile terminal at time t Among them, t i The signal is received by the i-th mobile terminal The delay, A(tt i )for The amplitude of φ(tt i )for The phase, Δf i is the difference between the frequencies of the signals sent and received by the i-th mobile terminal, T is a sampling period, t∈[(i-1)T,iT], t i ∈[(i-1)T,iT], for The reception coefficient, for phase shift; i = 1, 2, ..., N; k = 1, 2, ... K; K is the total number of data storage terminals participating in network data transmission, N is the total number of mobile terminals participating in network data transmission; f0 is the transmission frequency of the data storage terminal transmitting and receiving signals; S32: Calculate the total amount s of signals transmitted by the kth data storage end to all mobile ends k The calculation formula of (t) is: Among them, O k (t), Q k (t) are the zero-degree phase component and the ninety-degree phase component of the received signal transmitted by the k-th data storage end, respectively; S33: Define S0(t) = A(t)exp[μφ(t)] as the complex baseband envelope signal of the data storage end transmitting and receiving the signal, where μ is an imaginary number, and then calculate s based on this. k The complex envelope signal S(t) of (t): Among them, n(t) is the periodic interference at time t, and ∈ is Gaussian white noise.

3. The method for dynamically adjusting network data transmission bandwidth according to claim 2, characterized in that: In the step S32, the kth data storage terminal transmits the zero-degree phase component O of the received signal. k (t) and the ninety degree phase component Q k The calculation formulas for (t) are as follows:

4. The method for dynamically adjusting network data transmission bandwidth according to claim 2, characterized in that: In the step S31 The reception coefficient The calculation formula is as follows: Where Δf k is the frequency difference between the transmitted and received signals of the kth data storage terminal, It is the phase shift of the received signal emitted by the data storage end.

5. The method for dynamically adjusting network data transmission bandwidth according to claim 2, characterized in that: The S4 step includes the following steps: S41: Calculate the periodic interference n(t) at time t in step S33: in, is the amplitude of the harmonic in the signal when the kth data storage terminal transmits and receives the signal at time t, η k The weight for calculating the periodic interference when the kth data storage terminal transmits and receives the signal, Re{} is the real part function of the independent variable; ω0 is the angular frequency of the data storage terminal transmitting and receiving the signal, ω0 = 2πf0; S42: Building η k Minimize and solve the model: Among them, Ω is the error minimization mean; S43: continuously iteratively updating the solution result of step S42; S44: The qth generation optimal periodic interference calculation weight is calculated by Substitute it into the formula for calculating the complex envelope signal S(t) in S33, calculate the signal-to-noise ratio at this time to determine whether it is less than the signal-to-noise ratio threshold, if so, stop the iteration; otherwise, repeat the continuous iteration of step 3.

3.

6. The method for dynamically adjusting network data transmission bandwidth according to claim 5, characterized in that: In the step S44, the weight is calculated based on the qth generation optimal periodic interference obtained by solving The formula for calculating the signal-to-noise ratio is as follows: Among them, SNR q is the signal-to-noise ratio of the qth generation result, Indicates that when the periodic interference calculation weight η g is the optimal periodic interference weight obtained by the qth generation iterative optimization The complex envelope signal S(t) at time ; Signal-to-noise ratio threshold SNR Thr The calculation formula is as follows: Where N0 is the power spectrum density of the periodic interference signal, B noise is the bandwidth of the periodic interference.

7. The method for dynamically adjusting network data transmission bandwidth according to claim 1, characterized in that: The S5 step includes: S51: Calculate the bandwidth allocation coefficient ω for the i-th mobile terminal to transmit data to the data storage terminal after receiving the k-th receiving signal sent by the data storage terminal. i,k : Among them, B total The total bandwidth of the data storage end receiving uploaded data; S52: During data transmission based on the TCP protocol, the bandwidth allocation coefficient is continuously increased under the bandwidth allocation restriction condition: The bandwidth allocation restriction conditions are: σ is the bandwidth allocation increase coefficient, ω i,k+1 is the bandwidth allocation coefficient for transmitting data to the data storage end by the i-th mobile end after receiving the k+1-th receiving signal sent by the data storage end; S53: After increasing the bandwidth allocation coefficient, calculate the data packet loss rate l when the i-th mobile terminal receives the k+1-th receiving signal sent by the data storage terminal and uploads data to the data storage terminal. i,k+1 : S54: Judgment l i,k+1 Is it less than or equal to the data packet loss rate threshold l? thr , if yes, repeat the steps S51-S52 to upload the data of the ith mobile terminal to the data storage terminal, otherwise the bandwidth allocation coefficient ω for the ith mobile terminal to upload data to the data storage terminal when receiving the k+1th receiving signal sent by the data storage terminal i,k+1 The bandwidth allocation coefficient after reduction is ω′ i,k+1 Continue uploading the data; the packet loss rate threshold l thr for: Among them, β i,k+1 is the bandwidth allocation coefficient ω i,k+1 The reduction weight coefficient is:

8. The method for dynamically adjusting the network data transmission bandwidth according to claim 7, characterized in that: The bandwidth allocation increase coefficient σ is calculated using the following calculation method: Among them, RTT i,k The time it takes for the i-th mobile terminal to upload data to the data storage terminal and obtain its confirmation after receiving the k-th reception signal sent by the data storage terminal, 8ms≤RTT i,k ≤15ms; max is the maximum value function.

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