Disclosure of Invention
The invention aims at the defects and provides a method and a system for dynamically adjusting network data transmission bandwidth. The method provided by the invention carries out data filtering reduction according to the signal receiving and receiving of the simultaneous multipath data transmission between the data transmission end and a plurality of mobile ends needing to upload data, and further carries out real-time dynamic bandwidth adjustment according to the data filtering reduction, so that the data is transmitted to the data storage end simultaneously in multipath with the maximum bandwidth and other mobile ends under the condition that the data packet loss rate is kept below a threshold value.
The invention provides a method for dynamically adjusting the bandwidth of network data transmission, which is based on the self-adaptive method to dynamically adjust the bandwidth after processing signals in a MIMO system, and ensures that the network data transmission meets the dynamic flow demand, and comprises the following steps:
S1, a plurality of mobile terminals send out a signal for requiring data uploading to a data storage terminal, and the data storage terminal sends out a receiving signal to the plurality of mobile terminals;
s2, the ith mobile terminal receives the kth receiving signal sent by the data storage terminal at the time t;
s3, calculating a signal total complex envelope signal emitted by the data storage end to the ith opposite mobile end;
s4, filtering and denoising the signal total complex envelope signal transmitted from the data storage end to the mobile end of the ith mobile phone, which is obtained by the step S3, to obtain a restored real signal;
S5, according to the real signal obtained by restorationAnd 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.
Further, the step S3 includes:
s31, calculating the kth received signal transmitted by the base station at the time t of the ith mobile terminal
Wherein ti is the signal received by the ith mobile terminalA (t-ti) isPhi (t-ti) isΔfi is the difference between the frequencies of the receiving and transmitting signals of the ith mobile terminal, T is a sampling period, T is E [ (i-1) T, iT ], Ti is E [ (i-1) T, iT ],Is thatIs used for the reception coefficient of the (c),Is thatI=1, 2..n, k=1, 2..k, K being the total number of data storage terminals involved in the network data transmission, N being the total number of mobile terminals involved in the network data transmission, f0 being the transmission frequency of the data storage terminals transmitting the received signal;
S32, calculating a calculation formula of the k data storage end for the total amount Sk (t) of signals transmitted by all mobile ends:
Wherein, Ok(t)、Qk (t) is the zero degree phase component and ninety degree phase component of the transmitting and receiving signals of the kth data storage end respectively;
S33, defining S0 (t) =A (t) exp [ mu phi (t) ] as a complex baseband envelope signal of a data storage end transmitting and receiving signal, wherein mu is an imaginary number, and further calculating a complex envelope signal S (t) of Sk (t) according to the complex baseband envelope signal:
Where n (t) is the periodic disturbance at time t and ε is Gaussian white noise.
Further, in the step S32, the calculation formulas of the zero degree phase component Ok (t) and the ninety degree phase component Qk (t) of the transmission and reception signal at the kth data storage terminal are as follows:
Further, in the step S31Is of the reception coefficient of (a)The calculation formula of (2) is as follows:
wherein Deltafk is the difference between the frequencies of the transmission and reception signals of the kth data storage terminal,For phase shifting of the received signal transmitted from the data storage terminal.
Further, the step S4 includes the steps of:
s41, calculating periodic interference n (t) at t time in the step S33:
Wherein,For the amplitude of harmonic wave in a signal when a kth data storage end transmits a received signal at a moment t, etak is the periodic interference calculation weight when the kth data storage end transmits the received signal, re { } is a real part function of an independent variable, omega0 is the angular frequency of the data storage end transmitting the received signal, omega0＝2πf0;
s42, constructing an etak minimization solution model:
wherein Ω is the error minimization mean;
s43, continuously iteratively updating the solving result of the step S42;
s44, calculating the weight of the q-th generation optimal periodic interference obtained by solvingAnd (3) carrying out the step (3) into the formula for calculating the complex envelope signal S (t) by the S33, calculating the signal-to-noise ratio at the moment, judging whether the signal-to-noise ratio is smaller than a signal-to-noise ratio threshold value, if so, stopping iteration, and otherwise, repeating the continuous iteration of the step (3.3).
Further, in the step S44, weights are calculated according to the q-th generation optimal periodic interference obtained by solvingThe formula for calculating the signal-to-noise ratio is as follows:
wherein SNRq is the q-th generation result signal-to-noise ratio,Represents the optimal periodic interference weight obtained when the periodic interference calculation weight etak is optimized for the q-th generation iterationA complex envelope signal S (t) at that time;
The calculation formula for the signal-to-noise threshold SNRThr is as follows:
where N0 is the power spectral density of the signal causing the periodic interference and Bnoise is the bandwidth of the periodic interference.
Further, the step S5 includes:
S51, after the ith mobile terminal receives the kth receiving signal sent by the data storage terminal, calculating a bandwidth allocation coefficient omegai,k for transmitting data to the data storage terminal: Wherein, Btotal is the total bandwidth of the data storage end for receiving the uploading data;
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:
wherein, the bandwidth allocation constraint is: Sigma is a bandwidth allocation increase coefficient, omegai,k+1 is a bandwidth allocation coefficient of transmitting data to a data storage end after the ith mobile end receives the (k+1) th receiving signal sent by the data storage end;
S53, after the bandwidth allocation coefficient is increased, calculating a data packet loss rate li,k+1 when the ith mobile terminal receives the (k+1) th receiving signal sent by the data storage terminal and uploads data to the data storage terminal:
S54, judging whether li,k+1 is smaller than or equal to a data packet loss rate threshold lthr, if yes, repeating the steps S51-S52 to upload the data of the ith mobile terminal to a data storage terminal, otherwise, reducing a bandwidth allocation coefficient omegai,k+1 when the ith mobile terminal receives the (k+1) th receiving signal sent by the data storage terminal and uploads the data to the data storage terminal, so as to continuously upload the data by the reduced bandwidth allocation coefficient omega'i,k+1, wherein the packet loss rate threshold lthr is as follows:
Wherein βi,k+1 is a cut-down weight coefficient of the bandwidth allocation coefficient ωi,k+1:
further, the bandwidth allocation increase coefficient sigma is calculated by adopting the following calculation method:
Wherein, RTTi,k is the time that the ith mobile terminal takes to upload data to the data storage terminal and obtain the acknowledgement thereof when receiving the kth receiving signal sent by the data storage terminal, RTTi,k is less than or equal to 8ms and less than or equal to 15ms, and max is the maximum function.
The beneficial effects of the invention are as follows:
1. The method provided by the invention calculates the complex envelope signal after the decomposition of the zero-degree phase component and the ninety-degree phase component for the received signal sent by the data storage end, and the components can describe the amplitude and the phase of the signal respectively, so that the receiving end can accurately recover the original signal, the defect that some key information of the signal is possibly lost is avoided, and meanwhile, the phenomenon of envelope signal reduction distortion caused by noise, fading and interference to the transmitted signal during network data transmission in a wireless channel is reduced. The use of zero and ninety degree phase components and complex envelope signals helps to improve the accuracy of the signal recovery. When complex envelope signals are restored, the mobile terminal can detect and compensate phase change caused by channel fading, and signal quality is ensured.
2. In the process of filtering and denoising periodic interference in an envelope signal, the invention constructs in the iterative updating process by carrying out iterative updating on the calculated weight of the periodic interferenceThe weight can be adaptively adjusted according to real-time data by calculating the weight based on the error and sample cross-correlation matrix C, the self-compensating matrix P, and the bi-conjugate matrix D. The self-adaptive capacity is very important for a communication system with rapid channel condition change such as a MIMO system or beam forming, and the optimal periodic interference calculation weight obtained by calculation is dynamically and in real time adjusted in an adaptive mode so as to cope with environmental change, thereby improving the flexibility of the system. In the self-adaptive filtering and MIMO system, the channel variation can be tracked quickly, and the error is reduced. The self-compensating matrix and the double conjugate matrix which simultaneously support the processing of multi-dimensional signals are suitable for processing multi-dimensional signals in complex forms, such as multi-input multi-output signals in a MIMO system. The cross-correlation matrix can capture correlations between signal samples for optimal processing (e.g., beamforming, array signal processing) between multiple signal sources. Therefore, the method provided by the invention finally and dynamically adjusts the obtained optimal periodic interference calculation weightThe multi-dimensional signal optimization is supported, the method is suitable for data transmission of complex network communication systems such as MIMO communication systems, and the optimal network signal transmission reduction degree can be realized.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims thereof as well as the appended drawings.
The technical scheme of the invention is further described in detail through the drawings and the embodiments.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The invention provides a dynamic adjustment method of network data transmission bandwidth, which is based on a self-adaptive method to dynamically adjust bandwidth after signal processing in MIMO system, so as to ensure that dynamic flow demand is met in the process of network data transmission, as shown in figure 1, the method provided by the invention dynamically adjusts the network for data transmission between a data transmission end and a plurality of mobile ends, the User1 in figure 1 is the 1 st mobile end of the MIMO system, the User2 is the 2 nd mobile end, useri is the i mobile end and UserN is the N mobile end, and the data network performs data network transmission with a data storage end, and the method provided by the invention comprises the following steps:
S1, a plurality of mobile terminals send out a signal for requiring data uploading to a data storage terminal, and the data storage terminal sends out a receiving signal to the plurality of mobile terminals;
s2, the ith mobile terminal receives a kth receiving signal sent by the data storage terminal at the time t;
S3, calculating a signal total complex envelope signal emitted from the data storage end to the ith opposite mobile end;
s4, filtering and denoising the complex envelope signal of the total signal quantity transmitted from the data storage end to the mobile end of the ith mobile phone obtained in the step S3 to obtain a restored real signal;
S5, according to the real signal obtained by restorationAnd dynamically adjusting the bandwidth allocation coefficient of the data storage end, and dynamically uploading the data value data storage end in real time by the ith mobile end according to the adjusted bandwidth allocation coefficient.
The step S3 comprises the following steps:
s31, calculating the kth received signal transmitted by the base station at the time t of the ith mobile terminal
Wherein ti is the signal received by the ith mobile terminalA (t-ti) isPhi (t-ti) isΔfi is the difference between the frequencies of the receiving and transmitting signals of the ith mobile terminal, T is a sampling period, T is E [ (i-1) T, iT ], Ti is E [ (i-1) T, iT ],Is thatIs used for the reception coefficient of the (c),Is thatI=1, 2..n, k=1, 2..k, K being the total number of data storage terminals involved in the network data transmission, N being the total number of mobile terminals involved in the network data transmission, f0 being the transmission frequency of the data storage terminals transmitting the received signal;
In data transmission and wireless communication, a data storage end transmits signals to a plurality of mobile ends, and the mobile ends need to process the received signals to restore accurate original signals. The signal is decomposed through the zero-degree phase component and the ninety-degree phase component, and the complex envelope signal of the transmitted signal is further restored, so that the method has important significance and necessity.
S32, calculating a calculation formula of the k data storage end for the total amount Sk (t) of signals transmitted by all mobile ends:
Wherein, Ok(t)、Qk (t) is the zero degree phase component and ninety degree phase component of the transmitting and receiving signals of the kth data storage end respectively;
S33, defining S0 (t) =A (t) exp [ mu phi (t) ] as a complex baseband envelope signal of a data storage end transmitting and receiving signal, wherein mu is an imaginary number, and further calculating a complex envelope signal S (t) of Sk (t) according to the complex baseband envelope signal:
Where n (t) is the periodic disturbance at time t and ε is Gaussian white noise. As shown in fig. 2, the k-th data storage end calculated in steps S31-S33 in the method provided by the present invention is used to calculate the complex envelope signal S (t) of the total signal Sk (t) transmitted by all mobile ends, and the amplitude variation condition of the zero-degree phase component Ok (t) and ninety-degree phase component Qk (t) of the received signal transmitted by the k-th data storage end in step S32 along with the transmission distance (horizontal axis) in the same coordinate system. As shown in fig. 2, the zero-degree phase component Ok (t) represents the portion of the signal that is in phase with the carrier, and the ninety-degree phase component Qk (t) represents the portion of the signal that is 90 degrees out of phase with the carrier. Since S (t) is the complex envelope signal of the K data storage terminals transmitting the received signal, S (t) is also equal to the total amount of the received signal transmitted by the kth data storage terminal calculated from the zero degree and ninety degree phase components of the S32 step, i.eAs shown in fig. 2, the total signal is decomposed in step S32, and the complex envelopes of the zero-degree phase component and the ninety-degree phase component are further processed in step S33, so that the decomposition of the two components ensures the complete preservation of the phase and amplitude information of the signal, and the information loss caused by carrier aliasing is avoided. Furthermore, the decomposition of the two components maps the signal onto the complex plane, allowing more efficient processing using a complex representation of the signal model.
In the step S32, the calculation formulas of the zero-degree phase component Ok (t) and the ninety-degree phase component Qk (t) of the transmission and reception signal of the kth data storage terminal are as follows:
In the S31 stepIs of the reception coefficient of (a)The calculation formula of (2) is as follows:
wherein Deltafk is the difference between the frequencies of the transmission and reception signals of the kth data storage terminal,For phase shifting of the received signal transmitted from the data storage terminal.
In order to filter and reduce noise of the complex envelope signal and improve the accuracy of signal recovery of multipath propagation in the mobile communication process, as another preferred embodiment of the present invention, the step S4 includes the steps of:
S41, calculating periodic interference n (t) at t time in the step S33:
Wherein,For the amplitude of the harmonic in the signal when the kth data storage end transmits the received signal at the moment t, etak is the periodic interference calculation weight when the kth data storage end transmits the received signal, re { } is the real part function of the taken independent variable, namelyTo take independent variablesOmega0 is the angular frequency of the data storage terminal transmitting and receiving signal, omega0＝2πf0;
s42, constructing an etak minimization solution model:
s43, continuously and iteratively updating the solving result of the step S42;
s44, calculating the weight of the q-th generation optimal periodic interference obtained by solvingAnd (3) carrying out S33 in a formula for calculating the complex envelope signal S (t), calculating the signal-to-noise ratio at the moment to judge whether the signal-to-noise ratio is smaller than a signal-to-noise ratio threshold, if so, stopping iteration, otherwise, repeating the continuous iteration of the step (3.3).
In the S44 step, the weight is calculated according to the q-th generation optimal periodic interference obtained by solvingThe formula for calculating the signal-to-noise ratio is as follows:
Wherein,Represents the optimal periodic interference weight obtained when the periodic interference calculation weight etak is optimized for the q-th generation iterationThe complex envelope signal S (t) is represented by a light blue curve in the graph in FIG. 3, the light yellow curve in the graph in FIG. 3 represents the signal condition of the S (t) under the optimized iteration condition of the weight coefficient etak without the periodic disturbance n (t) of the proportion of the step S44, and the signal to noise ratio is always larger than the signal to noise ratio threshold (about 13 dB) after only 50 generations of iteration;
the signal to noise ratio threshold is calculated as follows:
where N0 is the power spectral density of the signal causing the periodic interference and Bnoise is the bandwidth of the periodic interference.
In order to improve accuracy of a complex envelope signal obtained by performing a minimized solution on etak, the invention further optimizes a calculation result in the step S43, preferably, the method comprises the following steps of:
S431 calculating the estimated value of the q-th generation complex envelope signal S (t) obtained in the iterative process
Wherein, q is {1,2,.. H }, H is {1,2,.. H }, H is the total number of iterations, Sh (t) is the true value of the H-th generation complex envelope signal S (t) obtained in the iteration process, and Sq (t) is the true value of the q-th generation complex envelope signal S (t) obtained in the iteration process;
s432, calculating the estimated value of the q-th generation complex envelope signal S (t)Deviation difference of the mean value of the middle relative to the total sample of the H-generation iteration
Wherein,Calculating weights for the h-th generation periodic interference; for the H generation iteration total sample mean value
S433 constructionDeviation from the differenceComplex conjugate of (2)Is a cross-correlation vector cuh:
and constructing a cross-correlation vector matrix C: The element cross-correlation vector Cuh in the cross-correlation vector matrix C provides sample estimatesConjugate complex number of errorThe relevance between the two can describe the relation between the signal and the noise more accurately when the weight is calculated, the influence of the noise on the iteration result can be effectively eliminated in the process of minimizing the error, the finally calculated weight is more accurate,
S434, calculating a self-compensation vector pih:
and constructing a self-compensating matrix P:
s435, calculating a double conjugate vector dih:
and constructing a double conjugate matrix D:
s436, converting the etak minimization solution model constructed in the step S42 into a matrix form:
S437, obtaining the optimal periodic interference calculation weight according to the matrix form converted in the step 3.36
The self-compensating vector Pih in the self-compensating matrix P includes an estimated value of the q-th generation complex envelope signal S (t)Deviation difference of (2)Complex conjugate of the twoThe double conjugate vector Dih of the double conjugate matrix D includes the complex conjugateThe use of the self-compensating matrix P and the double conjugate matrix D considers the phase information of the signals, is particularly effective for processing complex signals such as wireless communication signals, the cross-correlation vector matrix C can capture the interrelation between different signals, the stability of the system in complex environments such as multipath propagation, interference and the like is improved, and finally the optimal periodic interference weight is obtained through the difference and the product between the re-conjugate matrix and the inverse matrixCan ensure phase adaptation under the condition of channel distortion, thereby ensuring the calculated weight of the solved periodic interferenceIs suitable for complex environments such as multipath, non-ideal channels and the like. As shown in fig. 3, in mobile communication, through the decomposition of the zero-degree phase component and the ninety-degree phase component and the complex envelope processing, the superposition distortion of the received signal caused by multipath propagation can be effectively compensated, the mobile terminal can more efficiently demodulate the signal through the decomposition of the zero-degree phase component and the ninety-degree phase component, the Bit Error Rate (BER) is reduced, the stability of communication is ensured, the real state of the restored signal is optimized through multiple iterations, the harmonic noise in the signal is reduced, the signal-to-noise ratio SNR is lower than the signal-to-noise ratio threshold, and the demodulation precision is improved.
Dynamic allocation of bandwidth is a key mechanism for flow control in the network data transmission TCP protocol. The bandwidth allocation factor determines how much data the sender can send at most before no acknowledgement is received, to avoid network congestion. It determines the transmission speed of data when it is uploaded at the data storage end. Thus, as another preferred embodiment of the present invention, the step S5 includes:
S51, calculating a bandwidth allocation coefficient omegai,k of the data transmitted to the data storage end by the ith mobile end after receiving the kth receiving signal sent by the data storage end: Wherein, Btotal is the total bandwidth of the data storage end for receiving the uploading data;
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 so as to improve the bandwidth utilization rate and rapidly transmit real signals:
wherein, the bandwidth allocation constraint is: Sigma is a bandwidth allocation increase coefficient, omegai,k+1 is a bandwidth allocation coefficient of transmitting data to a data storage end after the ith mobile end receives the (k+1) th receiving signal sent by the data storage end;
the bandwidth allocation increase coefficient sigma is calculated by the following calculation method:
Wherein, RTTi,k is the time that the ith mobile terminal takes to upload data to the data storage terminal and obtain the acknowledgement thereof in the receiving of the kth receiving signal sent by the data storage terminal, RTTi,k is more than or equal to 8ms and less than or equal to 15ms, and max is the maximum function;
S53, after the bandwidth allocation coefficient is increased, calculating a data packet loss rate li,k+1 when the ith mobile terminal receives the (k+1) th received signal sent by the data storage terminal and uploads data to the data storage terminal:
s54, judging whether li,k+1 is smaller than or equal to a data packet loss rate threshold lthr, if yes, repeating the steps S51-S52 to upload the ith mobile terminal data to a data storage terminal, otherwise, reducing the bandwidth allocation coefficient omegai,k+1 of the ith mobile terminal when the ith mobile terminal receives the (k+1) th receiving signal sent by the data storage terminal and uploads the data to the data storage terminal, and continuing uploading the data by the reduced bandwidth allocation coefficient omega'i,k+1, wherein the packet loss rate threshold Ithr is that
Wherein βi,k+1 is a cut-down weight coefficient of the bandwidth allocation coefficient ωi,k+1;
Comparative example 1
The comparison example is substantially the same as the method provided by the invention, and only in the process of calculating the complex envelope signal of the total signal amount transmitted from the data storage terminal to the i-th pair mobile terminal in step S3, the complex envelope signal is solved by directly performing inverse fourier transform without decomposing the zero-degree phase component and the ninety-degree phase component.
Comparative example 2
The comparative example is substantially the same as the method provided by the present invention, and after calculating the complex envelope signal of the total amount of signals transmitted from the data storage terminal to the ith opposite mobile terminal in step S3, in the filtering denoising process of step S4, the defining solution of the signal-to-noise ratio threshold of the filtered signals is not performed, the construction of the cross-correlation vector matrix C, the self-compensation matrix P and the double conjugate matrix D is not performed, and the optimal periodic interference calculation weight is performedThe solution method is directly solved according to the least square method.
Comparative example 3
In the process of dynamically adjusting the bandwidth, the limitation of the data packet loss rate li,k+1 to be less than or equal to the packet loss rate threshold lthr is not carried out, and further, the bandwidth allocation coefficient of the transmission of the (k+1) th signal is reduced by the weight of the reduction weight coefficient betai,k+1 under the condition that the packet loss rate li,k+1 is greater than the packet loss rate threshold lthr, and only whether the bandwidth limitation of the data storage end is exceeded or not is judged when each signal transmission and the signal synchronous multipath transmission of other mobile ends are transmitted to the data storage end, so as to determine whether the signal transmission of the mobile end is carried out or the setting of the data throughput of the signal transmission is reduced
As shown in fig. 4, a bar graph of throughput of one mobile terminal when the data storage terminal of the method of the present invention and the methods of comparative examples 1 to 3 perform multipath transmission with a plurality of mobile terminals is shown, the abscissa is the number of mobile terminals, the blue bar is the method provided by the present invention, the yellow bar is the method of comparative example 1, the green bar is the method of comparative example 2, and the red bar is the method of comparative example 3. As shown in fig. 4, the method provided by the invention performs data filtering and restoration according to the signal receiving and receiving of the simultaneous multipath data transmission between the data transmission end and the plurality of mobile ends needing to upload data, and further performs real-time dynamic bandwidth adjustment according to the data filtering and restoration, so that the data is transmitted to the data storage end by the multipath transmission between the maximum bandwidth and other mobile ends under the condition that the data packet loss rate is kept below a threshold value, the original receiving signals sent by the data storage end can be accurately recovered at the plurality of mobile ends, the throughput of the data storage end in the multipath transmission process between the plurality of mobile ends and the data storage end is effectively improved, and the data of the plurality of mobile ends is uploaded and stored by the allowable maximum receiving bandwidth.
The network data transmission bandwidth dynamic methods provided by the present application may take the form of a computer program product embodied on one or more storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having program code embodied therein. Machine-readable storage media include both permanent and non-permanent, removable and non-removable media, and information storage may be implemented by any method or technology. The information may be computer readable instructions, data structures, modules 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 optical disk read only memory (CD-ROM), digital Versatile Disks (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device.
It should be noted that, the foregoing reference numerals of the embodiments of the present invention are merely for describing the embodiments, and do not represent the advantages and disadvantages of the embodiments. Relational terms such as "first" and "second", and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. And the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, apparatus, article, or method. Without further limitation, an element defined by the phrase "comprising one does not exclude the presence of other like elements in a process, apparatus, article, or method that comprises the element.
The above is merely a specific embodiment of the disclosure to enable one skilled in the art to understand or practice the disclosure. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the disclosure. Thus, the present disclosure is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.