CN114679356A - Channel full-dimensional parameter extraction method independent of likelihood function - Google Patents
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Abstract
The invention discloses a channel full-dimensional parameter extraction method independent of a likelihood function, which receives signal data through multiple channels; preprocessing the signal data to obtain a time delay peak value of the signal data; calculating to obtain an azimuth angle and an elevation angle corresponding to each sub-path in the time delay peak value by adopting a forward and backward airspace smoothing MUSIC algorithm by taking the time delay peak value as input information; calculating the complex amplitude of each sub-path according to the azimuth angle and the elevation angle corresponding to the sub-path; collecting the time delay peak value, the azimuth angle and the elevation angle corresponding to each sub-path and the complex amplitude to obtain a channel full-dimensional parameter set; the method can reduce the influence of Doppler frequency shift on estimation of the sub-path complex amplitude by preprocessing the signal, so that the estimated complex amplitude is more accurate.
Description
Technical Field
The invention belongs to the technical field of wireless channel parameter extraction, and particularly relates to a channel full-dimensional parameter extraction method independent of a likelihood function.
Background
In order to meet the requirements of future wireless communication networks (increase data rates, decrease delays, energy and costs), the design and evaluation of various advanced wireless communication technologies in different communication systems requires the ability to capture the characteristics exhibited by the above technologies on the corresponding channels.
A geometric-based statistical ray tracing Channel modeling method, such as a precise qualitative Radio Channel Generator (QuaDRiGa), is generally accepted in the industry, but it needs to be adapted to a specific application scenario, and various Channel parameters with different sizes and dimensions of the scenario need to be input for a model, and these Channel parameters can only be obtained from a large amount of actual Channel measurement data.
In the aspect of parameter extraction, to extract parameters of each dimension of a channel comprehensively, the most widely used algorithm is Space Alternating Generalized Expectation-maximization (SAGE) algorithm. However, SAGE is a Likelihood function-based parameter estimation algorithm which introduces an iteration of Expectation-Maximization (EM) to reduce the complexity of a Maximum Likelihood (ML) algorithm, and each iteration needs to search each dimension parameter of a sub-path to enable the parameter to meet the Maximum Likelihood condition, so that time is consumed when the number of the sub-paths is large. Due to the characteristics of the EM algorithm, when a plurality of sub-paths with similar parameters exist or initial parameter values are not properly set, the result is easily converged to a local optimal solution, and a virtual false path is estimated.
Disclosure of Invention
The invention aims to provide a channel full-dimensional parameter extraction method independent of a likelihood function so as to improve the accuracy of channel parameter extraction.
The invention adopts the following technical scheme: a channel full-dimensional parameter extraction method independent of a likelihood function comprises the following steps:
receiving signal data over multiple channels; wherein the signal data is PN sequence or CFR data;
preprocessing the signal data to obtain a time delay peak value of the signal data;
calculating to obtain an azimuth angle and an elevation angle corresponding to each sub-path in the time delay peak value by adopting a forward and backward airspace smoothing MUSIC algorithm by taking the time delay peak value as input information;
calculating the complex amplitude of each sub-path according to the azimuth angle and the elevation angle corresponding to the sub-path;
and (4) collecting the time delay peak value, the azimuth angle and the elevation angle corresponding to each sub-path and the complex amplitude to obtain a channel full-dimensional parameter set.
Preferably, when the signal data is a PN sequence, the preprocessing is:
the PN sequence is subjected to sliding correlation.
Preferably, the preprocessing of the CFR data further comprises:
and performing IFFT on the CFR data to obtain CIR data corresponding to the CFR data.
Preferably, when the signal data is CFR data, the preprocessing is:
Dividing CIR data into a noise section and an effective signal section by using the length of the cyclic prefix;
determining a first noise threshold according to the noise section, and selecting a first time delay position of the effective signal section according to the first noise threshold;
determining a union set of first time delay positions of CIR data of the same time slot received by different receiving channels to obtain a first time delay position set;
taking intersection of a plurality of first sets of different time slots to obtain a second time delay position set;
calculating a covariance matrix corresponding to each element in the second time delay position set, and performing eigenvalue decomposition on the covariance matrix to obtain a maximum eigenvalue and a minimum eigenvalue;
and calculating the ratio of the maximum characteristic value to the minimum characteristic value, selecting elements with the ratio larger than a second noise threshold from the second time delay position set to form a third time delay position set, and taking the third time delay position set as the time delay peak value of the signal data.
Preferably, when the signal data is a PN sequence, after calculating the complex amplitude of each sub-path according to the azimuth and elevation corresponding to the sub-path, the method further includes:
calculating the phase difference of different time slots of each sub-path;
determining the Doppler frequency shift of the sub-path according to the phase difference;
constructing a local PN sequence based on the Doppler frequency shift;
And performing sliding correlation on the PN sequence by adopting the local PN sequence, and continuously executing until the complex amplitude of each sub-path is obtained again.
Preferably, when the doppler shift difference between the respective sub-paths is smaller than the difference threshold:
calculating the average Doppler frequency shift of each time delay cluster by adopting a weighted average method;
a local PN sequence is generated based on the average doppler shift.
Preferably, when the signal data is a PN sequence, the set of full-dimensional channel parameters further includes:
doppler shift of each sub-path.
The other technical scheme of the invention is as follows: a full-dimensional channel parameter extraction device independent of likelihood functions, comprising:
a receiving module for receiving signal data through multiple channels; wherein the signal data is PN sequence or CFR data;
the preprocessing module is used for preprocessing the signal data to obtain a time delay peak value of the signal data;
the first calculation module is used for calculating and obtaining the azimuth angle and the elevation angle corresponding to each sub-path in the time delay peak value by adopting a forward and backward airspace smoothing MUSIC algorithm by taking the time delay peak value as input information;
the second calculation module is used for calculating the complex amplitude of each sub-path according to the azimuth angle and the elevation angle corresponding to the sub-path;
And the aggregation module is used for aggregating the time delay peak value, the azimuth angle and the elevation angle corresponding to each sub-path and the complex amplitude to obtain a channel full-dimensional parameter set.
The other technical scheme of the invention is as follows: a device for extracting channel full-dimensional parameters independent of likelihood functions comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the computer program to realize the channel full-dimensional parameter extraction method independent of likelihood functions.
The other technical scheme of the invention is as follows: a computer-readable storage medium, in which a computer program is stored, which, when being executed by a processor, implements a method for extracting full-dimensional parameters of a channel independent of likelihood functions as described above.
The invention has the beneficial effects that: the invention can reduce the influence of Doppler frequency shift on the estimation of the complex amplitude of the sub-path by preprocessing the signal, so that the estimated complex amplitude is more accurate.
Drawings
Fig. 1 is a flowchart of a channel full-dimensional parameter extraction method independent of a likelihood function according to an embodiment of the present invention;
fig. 2 is a schematic diagram of a frame format of a transmitting end of a channel measurement system in an embodiment of the present invention;
fig. 3 is a schematic diagram of a frame format of a transmitting end of an NR system according to an embodiment of the present invention;
FIG. 4 is a flowchart illustrating a processing procedure of the channel parameter extraction method for input data according to an embodiment of the present invention;
FIG. 5 is a schematic diagram illustrating sub-array selection for forward and backward spatial domain smoothing according to an embodiment of the present invention;
fig. 6 is a schematic diagram of a feature value assistance-based delay location selection provided in an embodiment of the present invention;
FIG. 7 is a diagram comparing the results of process estimation with SAGE runtime in an embodiment of the present invention;
FIG. 8 is an angle power spectrum plotted by parameters obtained by processing base station real-time acquisition data by the method and forward and backward airspace smoothing MUSIC algorithm in the embodiment of the present invention;
FIG. 9 is an angle power spectrogram reconstructed after the data acquired by the base station acquires the angle domain parameters by using the method in the single-user line-of-sight scenario in the embodiment of the present invention;
FIG. 10 is a comparison graph of the beam received power and the original beam received power of the parameter reconstruction obtained by the method and forward and backward spatial domain smoothing MUSIC algorithm processing the data actually acquired by the base station in the embodiment of the present invention;
Fig. 11 is a schematic structural diagram of a device for extracting full-dimensional parameters of a channel independent of a likelihood function according to an embodiment of the present invention.
Detailed Description
The invention is described in detail below with reference to the drawings and the detailed description.
The current 5G New Radio (NR) system usually uses beamforming to improve the system capacity, so the acquisition of the angle domain parameters is particularly important. The NR system uses Sounding Reference Signal (SRS) to probe a Channel, but at present, it mainly uses the SRS to obtain a Frequency Response (CFR) of the Channel, and it has practical significance to obtain effective angle information from the existing CFR for configuring the beam resources of the base station.
In practical applications, the delay estimation usually adopts sliding correlation based on Pseudo-Noise (PN) or constant Amplitude Zero Auto-correlation (CAZAC) sequence, the resolution depends on the chip width, and the chip width can be correspondingly reduced along with the increasing of the bandwidth of the signal which can be transmitted by the current wireless transmitting device, so the delay resolution based on the method is continuously improved.
In estimating angles, a feature structure algorithm of Multiple Signal Classification (MUSIC) not only has shorter estimation time and higher resolution in angle estimation, but generally requires that the known number of incoming waves is irrelevant, while the number of paths in a channel is often unknown and the received signals of different paths are coherent because the same probe Signal is on each path.
In the aspect of beam deployment of a base station, most of the conventional NR systems only perform eigenvalue decomposition processing on the obtained multi-channel CFR data, and roughly deploy beams and resource allocation by using eigenvalue information, or directly bring the CFR into an angle estimation algorithm to only distinguish sub-paths from a space domain and obtain angles of the sub-paths.
In fact, by performing Inverse Fast Fourier Transform (IFFT) on a frequency domain CFR to obtain a time domain Channel Impulse Response (CIR), a time delay cluster can be obtained by preliminarily separating paths by using a system time domain resolution, and further separating the paths by using a space domain to extract finer angle information.
The invention discloses a channel full-dimensional parameter extraction method independent of a likelihood function, which comprises the following steps as shown in figure 1: step S110, receiving signal data through multiple channels; wherein the signal data is PN sequence or CFR data (i.e., channel frequency response data); step S120, preprocessing the signal data to obtain a time delay peak value of the signal data; step S130, calculating to obtain an azimuth angle and an elevation angle corresponding to each sub-path in the time delay peak value by using the time delay peak value as input information and adopting a forward and backward airspace smoothing MUSIC algorithm; step S140, calculating the complex amplitude of each sub-path according to the azimuth angle and the elevation angle corresponding to the sub-path; step S150, a time delay peak value, an azimuth angle and an elevation angle corresponding to each sub-path and a complex amplitude are collected to obtain a channel full-dimensional parameter set.
The invention can reduce the influence of Doppler frequency shift on the estimation of the complex amplitude of the sub-path by preprocessing the signal, so that the estimated complex amplitude is more accurate.
Specifically, in the channel measurement system, a transmitting end transmits a BPSK modulated PN sequence according to a certain frame format, and a receiving end completes multi-channel reception by an array with known arrangement and an antenna directional diagram; in the 5G-NR system, the UE acts as the transmitting end and modulates SRS (i.e. sounding reference signal) according to the protocol frame format, and the BS acts as the receiving end and processes the received SRS to obtain CFR data of multiple receiving channels.
In the embodiment of the present invention, the obtained mathematical model of the channel of the complete parameter is represented as:
where h (τ, t) is the time domain response, L and PlThe number of the time delay clusters and the number of sub-paths contained in the time delay cluster l are respectively, the time delay resolution of the system can only distinguish each time delay cluster actually but cannot distinguish the sub-paths in the cluster, and the time delay of each time delay cluster is represented as tau l. τ is a different description of the difference in time scale, τ being in units of PN chip width or NR system sampling interval, and t being in units of PN frame interval or NR system slot interval, δ (τ) being a unit impact function.
And fl,pRespectively corresponding to the complex amplitude and the Doppler frequency shift of the p-th sub-path in the l-th cluster.
A direction vector corresponding to the p-th sub-path in the l-th cluster, wherein thetal,pAnd
respectively its elevation and azimuth.
The baseband data processed by the receiving end is baseband data sampled and down-converted by a plurality of radio frequency channels, and includes array arrangement and antenna directional pattern information under a specified reference system, taking a uniform planar array placed on an XOZ plane as an example, a signal (i.e., a received PN sequence) received by each receiving channel is represented as:
wherein N ism(τ, t) is mth receptionThe method comprises the following steps that additive Gaussian noise on a channel is obtained, M and N are array element numbers of a uniform area array in the X-axis direction and the Y-axis direction respectively, a (tau) is a baseband signal expression of a transmitted signal, and tau is a unit of the size of a system sampling interval and the unit is a single chip width for a channel measurement system.
And for NR systems the inverse of the system bandwidth.
To be driven from
The mth element of the array steering vector of the incoming wave of the direction incidence, which contains array arrangement information and antenna directional pattern information, can be expanded as:
Wherein,
is the m-th array element directional diagram
Complex amplitude of (a)x(m)、az(m) is the coordinate of the m-th array element in the XOZ plane,
is the phase shift of the carrier caused by the distance of the m-th array element from the reference origin.
More specifically, as shown in fig. 2, in the channel measurement system, the transmitting end uses the full bandwidth in a certain frame format with a period TsCircularly transmitting BPSK modulated PN sequence, the number of PN sequence chips is K, the time length of a single chip is Tp. The receiving end completes multi-channel receiving by an array of known arrangement and antenna directional patterns. As shown in fig. 3, the sending end of the NR system is served by the UE, and the UE modulates the SRS according to the frame format specified by the protocol while continuously sending the radio frame, and the occupied time domain resource position is as shown in fig. 2As shown, the frequency domain uses the protocol to transmit in a 2-way comb manner as shown in fig. 3, the total bandwidth of the NR system includes 272 RBs, each RB includes 12 REs, and each RE corresponds to 1 subcarrier with a frequency interval of 30 kHz. And the receiving end acts as and processes the received SRS by the BS, and channel CFR data of a plurality of receiving channels is obtained after processing. Due to the limited processing capacity of the base station, each acquisition task can only acquire SRS of more than 40 slots in the time domain, each SRS of a slot can only acquire 68 continuous RBs in the frequency domain, and the base station needs to perform quarter down-sampling on CFR data when storing data, so that each acquisition task can only acquire CFR data of more than 40 slots on 102 REs.
Preferably, when the signal data is a PN sequence, the preprocessing is: the PN sequence is subjected to sliding correlation. Specifically, according to the description of the space-time characteristics of the channel in the QuaDRiGa channel model theory, the spatial domain scattering environment of the wireless channel between the transmitting end moving in a small range and the receiving end which is static hardly changes. Therefore, multiple snapshots (different snapshots) are used for receiving PN sequence data or SRS data of multiple slots to complete channel exploration or angle domain information acquisition. And carrying out sliding correlation on the exploration signals received in the channel measurement system in each snapshot by using a local PN sequence to obtain a time delay peak value of each section of PN sequence. And (3) converting the CFR of each slot obtained by the BS in the NR system into a time domain channel impact response CIR by using Inverse Fast Fourier Transform (IFFT).
In a channel measurement system, received signals on NM receive channels are correlated with a local PN sequence sliding:
wherein,<y(τ,t),a(τ)>indicating that a sliding correlation is made with a (τ) for each received channel data y (τ, t) of the t-th slot, which represents a convolution operation,
Tpis the time width of a single chip, K is the code length of the PN code, and N' (tau, t) represents the receiving arrayThe noise on the PN signal is a result of sliding correlation due to KP bSo large that the influence of the noise N' (τ, t) can be neglected later. The delay peak value corresponding to the delay cluster l is represented as:
in the NR system, a base station receives and processes SRS signals received by all channels according to an OFDM architecture, and operations corresponding to sliding correlations are to perform IFFT on the obtained CFR data to obtain baseband CIR data per slot, where the expression is as follows:
wherein Y (k, t) is the frequency domain received data of the t slot,
Tsis a system sampling period when
When not an integer, the corresponding delay is τlThe power component of the delay cluster of (2) will leak to all delay positions. N is the number of subcarriers in the system, and is also the number of sample points in a single slot.
Is the angle-independent component of each sub-way expression. Phil,p(t) is an extra phase difference caused by Doppler shift of a sub-path p in a time delay cluster l at the t slot, and since the application scenarios of the NR system are mostly low-speed moving scenarios such as urban macro cells, the system is assumed to be quasi-static in the derivation, that is, phi isl,p(t) it does not vary with n.
For the NR system, since the channel CIR obtained by IFFT of the CFR data of the base station has an obvious peak leakage phenomenon, the channel CIR is first divided into a noise segment and an effective signal segment by using the Cyclic Prefix (CP) length, and the maximum amplitude value of the noise segment is used as the noise threshold η. Selecting a delay position omega of an effective signal segment by utilizing a threshold eta, and taking a union set of a delay position set on a plurality of receiving channels to resist spatial fading caused by multipath on an array:
Of different slots
Then, the intersection is taken to reduce the noise interference. Obtaining a new time delay position set:
since the leaked delay power is less or there are multiple paths in some delay positions, the angular information of a large number of sub paths is mixed and difficult to distinguish by MUSIC. In order to obtain correct and reliable angle domain information, the power of a small part of sub-path angle information is lost only by selecting and discarding CIR peak values at the time delay positions, but the adverse effect of noise on a ZF algorithm is reduced, and the subsequent amplitude estimation can be guaranteed. The effective time delay position selection method is based on the assistance of characteristic values and is used for any time delay position
The CIR peak at all channels calculates the covariance matrix at all slots:
wherein,
is connected with the next pair
And (3) carrying out characteristic value decomposition to obtain the maximum and minimum characteristic values:
when lambda ismax/λmin＞η2Reserving the delay position
To a collection
Otherwise, abandoning the time delay position, and only using the time delay position when extracting angle and amplitude information subsequently
The inner delay position corresponds to the CIR peak.
In one embodiment, a forward-backward spatial domain smoothing MUSIC algorithm is used for processing a plurality of peak values of snapshot/slot, distinguishing sub-paths in each time delay cluster and obtaining the azimuth angle and the elevation angle of the sub-paths. First, the peaks of multiple channels are vectorized:
Then selecting a subarray of a forward and backward spatial smoothing algorithm, wherein M rows of array elements comprise p which are mutually staggeredxEach of the N rows of the isomorphic subarrays includes p elements which are staggered with each otherzAnd (4) forming isomorphic submatrices. The two-dimensional planar array is divided into px×pzA sub-area array of size Ms＝M+1-pxColumn, Ns＝N+1-pzAnd (6) rows. V using T snapshot/slotl(t) obtaining a covariance matrix after forward and backward airspace smoothing
Comprises the following steps:
wherein,
represents the Kronecker product (.)HThe representation is taken of the conjugate transpose,
is Ms×MsThe identity matrix of (1);
is Ms×MsIn a deviceAnd (3) changing the matrix, wherein the elements on the anti-diagonal line of the matrix are 1, and the other elements are 0.
Then it is paired with
Decomposing the characteristic value, and setting a threshold xi according to the modulus of the minimum characteristic value and the signal-to-noise ratio of the receiving channellP with absolute value greater than thresholdlEach eigenvalue corresponds to P in a time delay cluster llPath of strips, feature vector v corresponding to feature value less than thresholdi,i＝PlN m structure orthogonal space
P within a delay cluster llArray steering vectors corresponding to respective strip paths
Are all reacted with B⊥Are orthogonal. MUSIC pseudo spectrum constructed for time delay cluster l
And two-dimensional search is carried out on the peak value:
recording the azimuth angle and elevation angle position after each peak position is obtained
And will be
The radius delta around the position is set to zero, and the next peak value is searched until P is obtained lElevation and azimuth of the sliver path. The value of Δ determines how large an angle range is to be madeThe synthesis of the sub-paths in the periphery is a path, the value of which is selected according to the size of the sub-array, the number of snapshots/slots and noise, and can be 1-5 degrees under the general application condition that the angle estimation precision is not high.
In another embodiment, when the signal data is CFR data, the preprocessing is: dividing CIR data into a noise section and an effective signal section by using the length of the cyclic prefix; determining a first noise threshold according to the noise section, and selecting a first time delay position of the effective signal section according to the first noise threshold; determining a union set of first time delay positions of CIR data of the same time slot received by different receiving channels to obtain a first time delay position set; taking intersection of a plurality of first sets of different time slots to obtain a second time delay position set; calculating a covariance matrix corresponding to each element in the second time delay position set, and performing eigenvalue decomposition on the covariance matrix to obtain a maximum eigenvalue and a minimum eigenvalue; and calculating the ratio of the maximum characteristic value to the minimum characteristic value, selecting elements with the ratio larger than a second noise threshold from the second time delay position set to form a third time delay position set, and taking the third time delay position set as the time delay peak value of the signal data.
And receiving data by using a plurality of PN sequences of snapshots or SRS data of a plurality of slots to finish channel exploration or angle domain information acquisition. Survey signals received in the channel measurement system are subjected to sliding correlation in each snapshot by using a local PN sequence. The channel CFR of each slot processed by the BS in the NR system is converted into a time-domain CIR using IFFT.
The system time delay resolution is used for distinguishing time delay clusters, and the distinguishing of sub paths in the clusters and the estimation of azimuth angles and elevation angles of the sub paths are completed by a forward and backward airspace smoothing MUSIC algorithm aiming at a uniform planar array, wherein the sub array selection mode of the uniform planar array is shown in figure 5. Partitioning an array of size N M into px×pzSize of NS×MSA sub-array of (a). And finally, calculating the complex amplitude of each sub-path by adopting a ZF algorithm, wherein the phase difference between the complex amplitudes of the sub-paths obtained by different snapshots or slots is used for estimating the Doppler frequency shift of the sub-paths.
When analyzed by using known sub-path angle and ZF algorithmIn l cluster of PlThe complex amplitude and Doppler shift of the sliver path, V is first shiftedl(t) the noise-free part is converted into a matrix product form:
can be obtained by using the angle estimation result of the sub-path in the cluster I
Then using ZF algorithm to obtain 
Least squares estimation of (c):
using T snapshots/slots
Calculating the Doppler shift estimate of the sub-path in the cluster I:
where κ (t) is a factor used to cancel the 2 π periodicity of the phase, and is calculated by the expression:
obtain
And
later, it can easily count on the basis of the existing timing synchronization of the transmitting and receivingCalculating out
Thereby obtaining a complex amplitude estimate
In addition, whether channel measurement or NR system, when estimating the sub-path Doppler shift, the interval between slots or the frame interval T between different PN framesfAll need to satisfy:
wherein f isdThe maximum doppler shift that exists for the channel in the application scenario.
The system delay resolution can only distinguish delay clusters, and the sub-paths in the clusters all bear the same signal, so that the received signals of the sub-paths are coherent. The forward and backward airspace smoothing MUSIC algorithm aiming at the uniform plane array is required to complete the differentiation and calculate the azimuth angle and the elevation angle. And then, the discrimination is completed by aiming at a forward and backward airspace smoothing MUSIC algorithm of the uniform plane array, and the azimuth angle and the elevation angle of the uniform plane array are calculated. The phase difference between the complex amplitudes of the sub-paths derived by the different snapshots or slots is used for estimation of the doppler shift of the sub-paths.
More specifically, for the application of channel measurement in a high-speed moving scene, since the doppler shift on the sub-path is not negligible, only the time of a single PN chip will cause a relatively obvious phase change, so that the autocorrelation peak of the PN sliding correlation is reduced, and a relatively large error will occur in the complex amplitude calculated by using the correlation peak.
Therefore, the channel model per snapshot is first adjusted as follows:
after obtaining the sub-path Doppler shift estimate, the result can be used to construct a local PN sequence containing Doppler shift
And it is used to make sliding correlation with the received signal to cancel the effect of doppler shift.
This is divided into two specific cases, when the doppler shift difference between the sub-paths in the cluster is large (special scene), the doppler shift of each sub-path can be used to construct a corresponding local sequence to extract the complex amplitude of each sub-path without the influence of doppler shift. For example, when the p-th sub-path in the ith cluster is to be extracted, sliding correlation is performed first to obtain a peak value corresponding to the delay cluster i:
wherein N ″ (τ, t) is noise and
a is the interference of other sub-paths in the time delay cluster l to the sliding correlation peak of the p sub-path, and when the doppler shift between the sub-paths is large, the interference decreases as the length of the PN sequence increases. Then, the complex amplitude after Doppler frequency shift is eliminated is calculated according to the estimated sub-path angle and the peak vector of the time delay l:
wherein,
and estimating a steering vector corresponding to the p-th sub-path in the l-th cluster.
When the doppler shift between the sub-paths is small, for example, in a general scenario such as an urban macro cell, the influence of the factor a is not negligible, and thus it is not possible to individually cancel the influence of the doppler shift for each path, but to cancel the influence of the doppler shift on the sub-path in each delay cluster as much as possible. To ensure large amplitude The average Doppler frequency shift on the time delay cluster l is determined by adopting a weighted average mode
Followed by adopting
Performing sliding correlation on the received sequence to obtain
And according to the previous complex amplitude estimation processing flow, completing the estimation of the sub-path complex amplitude of partial Doppler frequency shift elimination by using the obtained sub-path angle and peak vector.
As shown in fig. 4, for channel sounding application based on PN sequence, the doppler shift estimation result of the sub-path is used to eliminate the influence of doppler shift on the sub-path complex amplitude estimation. For the NR system, since the channel data estimated by the LS has a power leakage phenomenon in the time domain as shown in fig. 6, the delay position selection method based on the eigenvalue assistance is used for preprocessing to determine a delay position where the signal-to-noise ratio is high and the angle information is easy to extract, thereby reducing adverse effects caused by the CIR leakage phenomenon.
Specifically, when the signal data is a PN sequence, after calculating the complex amplitude of each sub-path according to the azimuth and elevation angles corresponding to the sub-path, the method further includes: calculating the phase difference of different time slots of each sub-path; determining the Doppler frequency shift of the sub-path according to the phase difference; constructing a local PN sequence based on the Doppler frequency shift; and performing sliding correlation on the PN sequence by adopting the local PN sequence, and continuously executing until the complex amplitude of each sub-path is obtained again.
In one embodiment, when the doppler shift difference between the respective sub-paths is less than the difference threshold: calculating the average Doppler frequency shift of each time delay cluster by adopting a weighted average method; a local PN sequence is generated based on the average doppler shift.
Finally, according to the channel parameter estimation results obtained from a plurality of snapshots/slots, the channel parameters with the large and small scales and the probability statistical distribution thereof are calculated, and spectrograms such as Power Angular Spectrum (PAS) shown in fig. 8 and fig. 9 are drawn. When the signal data is a PN sequence, the set of full-dimensional channel parameters further includes: doppler shift of each sub-path.
In summary, the method provided by the invention distinguishes each sub-path in the channel by utilizing the space-time separable characteristic of the channel and further extracts parameters, adopts PN sliding correlation or IFFT to distinguish the path and obtain the time delay information of the path in a time delay domain, and adopts MUSIC algorithm based on forward and backward airspace smoothing to distinguish the sub-path in the path and obtain the azimuth angle and the pitch angle of the sub-path in the airspace. And finally, estimating corresponding Doppler frequency shift according to the phase difference of the sub-path complex amplitude in different snapshots (snapshot)/time slots (slot). In addition, Doppler frequency shift elimination is introduced into the complex amplitude estimation module, so that more accurate complex amplitude can be obtained in a high-speed moving scene. In a time delay estimation module, a time delay position selection preprocessing method based on characteristic value assistance is introduced, so that the method can more effectively extract angle domain information in NR system channel data. Moreover, the high efficiency of the method is verified through simulation, and the processing result of the measured data shows the effectiveness of the angle domain information extracted by the method.
The following is the simulation verification of the method of the present invention. The channel parameter table shown in table 1 is set to simulate the parameters of each sub-path in the wireless multi-path channel, and the channel parameters are extracted separately using SAGE and the proposed method, respectively. Both methods use PN sequences of length K511 and each chip width dt 3.69 x 10-6And s. The azimuth angle and the elevation angle of the sub-path are randomly selected between 1 degree and 180 degrees. According to the description of QuaDRiGa, the doppler shift and the angle of the sub-paths in the same cluster are mostly relatively close, so that the same delay path is considered when setting the path. In addition, the number of paths is known by default SAGE, and the proposed method defaults to variousThe threshold is set appropriately and the remaining relevant configurations are shown in table 2.
TABLE 1
TABLE 2
The paths are added in sequence, the running results of the algorithm and SAGE are recorded, the running time of the two algorithms and the iteration times of the SAGE are shown in FIG. 7 when the number of the paths is different, the specific estimation condition is recorded in Table 3, and the estimated time delay deviation of each path is considered to be less than dt, the angle deviation is less than 1 degree, the Doppler frequency shift is less than 1Hz, and the estimation is error-free when the amplitude estimation error is less than 0.01.
As can be seen from FIG. 7, the proposed algorithm and SAGE estimation perform comparably but at shorter run times when the number of paths is small. The convergence condition of SAGE depends on the constitution of sub-paths thereof, the iteration number required by convergence cannot be determined in advance, when the paths arrive at the same time, the estimation effect on the paths is not good, the paths are easy to converge on the local optimal solution, and the failure of estimation which is not accordant with the actual condition is caused. The running time of SAGE algorithm initialization increases along with the increase of the number of paths, while the running time of the method provided by the invention mainly increases along with the increase of the number of clusters, and the time of SAGE algorithm iteration is mainly related to the number of iterations and the number of paths.
TABLE 3
As shown in fig. 9, for data acquired by a base station in a single user Line of Sight (LOS) scene, an angle power spectrum reconstructed after obtaining angle domain parameters by using the proposed method is obtained, and circle positions with reference numbers represent directions of 32 beams formed by 32 receiving units on the base station side by using a Discrete Fourier Transform (DFT) codebook. As shown in fig. 8, the method is to directly bring the CFR data of each channel of the base station into the forward and backward spatial smoothing MUSIC algorithm to extract the angle spectrum reconstructed after the angle domain parameters are extracted. It can be seen that the method of the present invention constructs the same main power region of the angle spectrum as the latter, but the angle power spectrum constructed by the method of the present invention is more refined. In order to verify the effectiveness of the method, the power ratio of the received CFR on the 32 wave beams is respectively reconstructed by using the respectively extracted angle domain parameters and compared with the power ratio of the original 32 wave beams, and as a result, as shown in fig. 10, it can be seen that the recovered power ratio of the method of the present invention is closer to the original wave beam power ratio, and in addition, it can be seen that the reconstruction performance of the wave beam power with strong received power in the angle spectrum main power region is better, and the effectiveness of the method is verified.
Compared with a likelihood function-based parameter estimation algorithm which introduces EM iteration like SAGE, the method of the invention does not need iteration, needs shorter time, and has no problem that the initial value is improperly set to cause convergence to a local optimal solution so as to estimate the virtual false path. Compared with various estimation algorithms about channel parameters, the method can effectively distinguish the sub-paths in the time delay cluster and obtain the parameters of azimuth angle, elevation angle, complex amplitude and Doppler frequency shift of the sub-paths. The invention not only utilizes the characteristic of 5G large bandwidth, uses the high resolution capability of the time delay domain to distinguish the time delay clusters in the channel, but also utilizes the characteristic of 5G large-scale antenna, and uses the forward and backward space domain smoothing MUSIC algorithm with higher angle resolution capability to the coherent information source to distinguish the sub-paths in the clusters, thereby extracting a large number of sub-paths from the time domain and the space domain and accurately describing the channel by using the parameters thereof. In addition, a Doppler frequency elimination method is provided for the PN sequence-based 5G channel sounding application, and the influence of the Doppler frequency elimination method on the sub-path complex amplitude estimation is reduced. Aiming at the NR system, a preprocessing method for extracting angle domain parameters from channel CIR data by using the algorithm is provided, the effect is superior to that of processing CFR by using forward and backward airspace smooth MUSIC, and the obtained angle information is more complete and reliable.
The invention also discloses a device for extracting the channel full-dimensional parameters independent of the likelihood function, as shown in fig. 11, comprising: a receiving module 210 for receiving signal data through multiple channels; wherein the signal data is PN sequence or CFR data; the preprocessing module 220 is configured to preprocess the signal data to obtain a delay peak of the signal data; the first calculating module 230 is configured to calculate, by using the time delay peak value as input information and using a forward-backward airspace smoothing MUSIC algorithm, an azimuth angle and an elevation angle corresponding to each sub-path in the time delay peak value; a second calculating module 240, configured to calculate a complex amplitude of each sub-path according to the azimuth angle and the elevation angle corresponding to the sub-path; and an aggregation module 250, configured to aggregate the delay peak, the azimuth and elevation angle corresponding to each sub-path, and the complex amplitude to obtain a full-dimensional channel parameter set.
It should be noted that, for the information interaction, execution process, and other contents between the modules of the apparatus, the specific functions and technical effects of the embodiments of the method are based on the same concept, and thus reference may be made to the section of the embodiments of the method specifically, and details are not described here.
It will be clear to those skilled in the art that, for convenience and simplicity of description, the foregoing division of the functional modules is merely illustrated, and in practical applications, the above function distribution may be performed by different functional modules according to needs, that is, the internal structure of the apparatus is divided into different functional modules to perform all or part of the above described functions. Each functional module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional modules are only used for distinguishing one functional module from another, and are not used for limiting the protection scope of the application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
The invention also discloses a device for extracting the channel full-dimensional parameters independent of the likelihood function, which comprises a memory, a processor and a computer program which is stored in the memory and can run on the processor, wherein the processor realizes the method for extracting the channel full-dimensional parameters independent of the likelihood function when executing the computer program.
The device can be a desktop small computer, a notebook, a palm computer, a cloud server and other computing equipment. The apparatus may include, but is not limited to, a processor, a memory. Those skilled in the art will appreciate that the apparatus may include more or fewer components, or some components in combination, or different components, and may also include, for example, input-output devices, network access devices, etc.
The Processor may be a Central Processing Unit (CPU), and the Processor may be other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The storage may in some embodiments be an internal storage unit of the device, such as a hard disk or a memory of the device. The memory may also be an external storage device of the apparatus in other embodiments, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), etc. provided on the apparatus. Further, the memory may also include both an internal storage unit and an external storage device of the apparatus. The memory is used for storing an operating system, application programs, a BootLoader (BootLoader), data, and other programs, such as program codes of the computer programs. The memory may also be used to temporarily store data that has been output or is to be output.
The invention also discloses a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to realize the channel full-dimensional parameter extraction method independent of the likelihood function.
The computer readable medium may include at least: any entity or device capable of carrying computer program code to a photographing apparatus/terminal apparatus, a recording medium, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), an electrical carrier signal, a telecommunications signal, and a software distribution medium. Such as a usb-disk, a removable hard disk, a magnetic or optical disk, etc. In certain jurisdictions, computer-readable media may not be an electrical carrier signal or a telecommunications signal in accordance with legislative and patent practice.
Claims (10)
1. A channel full-dimensional parameter extraction method independent of a likelihood function is characterized by comprising the following steps:
receiving signal data through multiple channels; wherein the signal data is PN sequence or CFR data;
preprocessing the signal data to obtain a time delay peak value of the signal data;
calculating to obtain an azimuth angle and an elevation angle corresponding to each sub-path in the time delay peak value by adopting a forward and backward airspace smoothing MUSIC algorithm by taking the time delay peak value as input information;
calculating the complex amplitude of each sub-path according to the azimuth angle and the elevation angle corresponding to the sub-path;
and collecting the time delay peak value, the azimuth angle and the elevation angle corresponding to each sub-path and the complex amplitude to obtain a channel full-dimensional parameter set.
2. The method for extracting channel full-dimensional parameters independent of likelihood functions according to claim 1, wherein when the signal data is a PN sequence, the preprocessing is:
and performing sliding correlation on the PN sequences.
3. A method as claimed in claim 1 or 2, wherein the preprocessing of the CFR data is preceded by:
and performing IFFT on the CFR data to obtain CIR data corresponding to the CFR data.
4. The method according to claim 3, wherein when the signal data is CFR data, the preprocessing is:
dividing the CIR data into a noise section and an effective signal section by using the length of a cyclic prefix;
determining a first noise threshold according to the noise section, and selecting a first time delay position of the effective signal section according to the first noise threshold;
determining a union set of first time delay positions of the CIR data of the same time slot received by different receiving channels to obtain a first time delay position set;
taking intersection of a plurality of first sets of different time slots to obtain a second time delay position set;
calculating a covariance matrix corresponding to each element in the second time delay position set, and performing eigenvalue decomposition on the covariance matrix to obtain a maximum eigenvalue and a minimum eigenvalue;
and calculating the ratio of the maximum characteristic value to the minimum characteristic value, selecting elements with the ratio larger than a second noise threshold from the second time delay position set to form a third time delay position set, and taking the third time delay position set as the time delay peak value of the signal data.
5. The method as claimed in claim 2, wherein when the signal data is a PN sequence, the calculating the complex amplitude of each sub-path according to the corresponding azimuth and elevation angle of the sub-path further comprises:
Calculating the phase difference of different time slots of each sub-path;
determining the Doppler frequency shift of the sub-path according to the phase difference;
constructing a local PN sequence based on the Doppler frequency shift;
and performing sliding correlation on the PN sequence by adopting the local PN sequence, and continuously executing until the complex amplitude of each sub-path is obtained again.
6. The method as claimed in claim 5, wherein when the doppler shift difference between each of the sub-paths is smaller than the difference threshold:
calculating the average Doppler frequency shift of each time delay cluster by adopting a weighted average method;
a local PN sequence is generated based on the average doppler shift.
7. The method as claimed in claim 1, wherein when the signal data is a PN sequence, the set of channel full-dimensional parameters further comprises:
a doppler shift of each of the sub-paths.
8. A device for extracting a channel full-dimensional parameter independent of a likelihood function, comprising:
a receiving module for receiving signal data through multiple channels; wherein the signal data is PN sequence or CFR data;
The preprocessing module is used for preprocessing the signal data to obtain a time delay peak value of the signal data;
the first calculation module is used for calculating and obtaining the azimuth angle and the elevation angle corresponding to each sub-path in the time delay peak value by adopting a forward and backward airspace smoothing MUSIC algorithm by taking the time delay peak value as input information;
the second calculation module is used for calculating the complex amplitude of each sub-path according to the azimuth angle and the elevation angle corresponding to the sub-path;
and the aggregation module is used for aggregating the time delay peak value, the azimuth angle and the elevation angle corresponding to each sub-path and the complex amplitude to obtain a channel full-dimensional parameter set.
9. A device for extracting channel full-dimensional parameters independent of likelihood functions, comprising a memory, a processor and a computer program stored in the memory and operable on the processor, wherein the processor executes the computer program to implement a method for extracting channel full-dimensional parameters independent of likelihood functions according to any one of claims 1 to 7.
10. A computer-readable storage medium, in which a computer program is stored, which, when being executed by a processor, implements a method for full-dimensional parameter extraction of a channel independent of a likelihood function according to any one of claims 1 to 7.
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