CN114679356B

CN114679356B - Channel full-dimension parameter extraction method, device and storage medium independent of likelihood function

Info

Publication number: CN114679356B
Application number: CN202210266504.2A
Authority: CN
Inventors: 张阳; 屈阳; 李媛; 宋宇晨; 李迪
Original assignee: Xidian University
Current assignee: Xidian University
Priority date: 2022-03-17
Filing date: 2022-03-17
Publication date: 2023-04-28
Anticipated expiration: 2042-03-17
Also published as: CN114679356A

Abstract

The invention discloses a channel full-dimensional parameter extraction method, a device and a storage medium which do not depend on likelihood functions, wherein signal data are received through multiple channels; preprocessing the signal data to obtain a time delay peak value of the signal data; taking the time delay peak value as input information, and calculating by adopting a forward and backward airspace smoothing MUSIC algorithm to obtain azimuth angles and elevation angles corresponding to each sub-path in the time delay peak value; calculating the complex amplitude of each sub-path according to the azimuth angle and the elevation angle corresponding to the sub-path; collecting time delay peak values, azimuth angles and elevation angles corresponding to each sub-path and complex amplitudes to obtain a channel full-dimensional parameter set; the method can reduce the influence of Doppler frequency shift on the complex amplitude estimation of the sub-path by preprocessing the signals, so that the estimated complex amplitude is more accurate, and compared with a likelihood function-based parameter estimation algorithm which introduces EM iteration such as SAGE, the method does not need iteration, has shorter time, and has no problem of converging on a local optimal solution caused by improper initial value setting so as to estimate the false path.

Description

Channel full-dimension parameter extraction method, device and storage medium independent of likelihood function

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 likelihood functions.

Background

In order to meet the demands of future wireless communication networks (increasing data rates, reducing delays, energy and costs), the ability to design and evaluate various advanced wireless communication technologies in different communication systems, and to capture the characteristics exhibited by the technologies on the corresponding channels, is needed.

The geometric-based statistical ray-tracing channel modeling approach of the accurate qualitative radio channel generator (Quasi Deterministic Radio Channel Generator, quaDRiGa) is widely accepted by the industry, but needs to be adapted to the specific application scenario, and various size-scale channel parameters of the scenario need to be input for the model, and these channel parameters can only be obtained from a large amount of actual channel measurement data.

In terms of parameter extraction, to comprehensively extract parameters of each dimension of a channel, a space alternation generalized expectation maximization (SAGE) algorithm is most widely used at present. But since SAGE is a likelihood function-based parameter estimation algorithm that introduces iterations of a Expectation-Maximization (EM) algorithm to reduce the complexity of the maximum likelihood (Maximum Likelihood, ML) algorithm, each iteration searches the dimension parameters of the sub-paths to meet the maximum likelihood condition, and is therefore time consuming when the number of sub-paths is large. And because of the characteristics of the EM algorithm, when a sub-path with some similar parameters exists or the initial parameter value is not properly set, the result is easily converged to a local optimal solution, and the false path is estimated.

Disclosure of Invention

The invention aims to provide a channel full-dimensional parameter extraction method which does not depend on likelihood functions, so as to improve the accuracy of channel parameter extraction.

The invention adopts the following technical scheme: a method of channel full-dimensional parameter extraction independent of likelihood functions, comprising the steps of:

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;

taking the time delay peak value as input information, and calculating by adopting a forward and backward airspace smoothing MUSIC algorithm to obtain azimuth angles and elevation angles corresponding to each sub-path in the time delay peak value;

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 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 sequences are subjected to sliding correlation.

Preferably, the CFR data is pre-processed further comprising:

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 a cyclic prefix length;

determining a first noise threshold according to the noise section, and selecting a first delay position of an effective signal section according to the first noise threshold;

determining a union of first delay positions of CIR data of the same time slot received by different receiving channels to obtain a first delay position set;

acquiring intersections of a plurality of first time delay position sets of different time slots to obtain a second time delay position set;

calculating covariance matrixes corresponding to each element in the second time delay position set, and carrying out eigenvalue decomposition on the covariance matrixes to obtain a maximum eigenvalue and a minimum eigenvalue;

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, calculating the complex amplitude of each sub-path according to the azimuth angle and the elevation angle corresponding to the sub-path further comprises:

calculating the phase difference of different time slots of each sub-path;

determining Doppler shift of the sub-path according to the phase difference;

constructing a local PN sequence based on Doppler frequency shift;

and adopting the local PN sequence to carry out sliding correlation on the PN sequence, and continuing to execute until the complex amplitude of each sub-path is obtained again.

Preferably, when the doppler shift difference between the individual sub-paths is less than a 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 channel full-dimensional parameter set further includes:

doppler shift for each sub-path.

Another technical scheme of the invention is as follows: a channel full-dimensional parameter extraction apparatus 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 azimuth angles and elevation angles corresponding to each sub-path in the delay peak value by using the delay peak value as input information and adopting a forward and backward airspace smoothing MUSIC algorithm;

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.

Another technical scheme of the invention is as follows: a channel full-dimensional parameter extraction device independent of likelihood functions 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 channel full-dimensional parameter extraction method independent of the likelihood functions when executing the computer program.

Another technical scheme of the invention is as follows: a computer readable storage medium storing a computer program which when executed by a processor implements a method of channel full-dimensional parameter extraction independent of likelihood functions as described above.

The beneficial effects of the invention are as follows: the method can reduce the influence of Doppler frequency shift on the complex amplitude estimation of the sub-path by preprocessing the signals, so that the estimated complex amplitude is more accurate, and compared with a likelihood function-based parameter estimation algorithm which introduces EM iteration such as SAGE, the method does not need iteration, has shorter time, and has no problem of converging on a local optimal solution caused by improper initial value setting so as to estimate the false path.

Drawings

FIG. 1 is a flow chart of a method for extracting channel full-dimension parameters independent of likelihood functions 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 according to 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 flow chart illustrating a method for extracting channel parameters according to an embodiment of the present invention;

FIG. 5 is a schematic diagram of sub-array selection for forward and backward spatial smoothing in an embodiment of the present invention;

FIG. 6 is a schematic diagram of feature-based assisted time delay position selection according to an embodiment of the present invention;

FIG. 7 is a graph comparing the method estimation results with SAGE run time in an embodiment of the present invention;

fig. 8 is an angular power spectrum diagram drawn by parameters obtained by processing data acquired by a base station by a method and a forward-backward airspace smoothing MUSIC algorithm in the embodiment of the invention;

FIG. 9 is a graph of angular power reconstructed from data collected by a base station in a single-user line-of-sight scene using the proposed method to obtain angular domain parameters in an embodiment of the present invention;

fig. 10 is a diagram showing a comparison between a beam receiving power and an original beam receiving power of parameter reconstruction obtained by processing data acquired by a base station by a method and a forward-backward spatial smoothing MUSIC algorithm in an embodiment of the present invention;

fig. 11 is a schematic structural diagram of a full-dimensional channel parameter extraction device independent of likelihood functions according to an embodiment of the present invention.

Detailed Description

The invention will be described in detail below with reference to the drawings and the detailed description.

Current 5G New Radio (NR) systems often use beamforming to increase system capacity, and thus acquisition of angular domain parameters is particularly important. The uplink of the NR system adopts a sounding reference signal (Sounding Reference Signal, SRS) to detect a channel, but the frequency response (Channel Frequency Response, CFR) of the channel is mainly obtained by the uplink of the NR system, and the effective angle information obtained from the existing CFR has practical significance for the beam resource allocation of the base station.

In practical applications, the delay estimation usually adopts sliding correlation based on Pseudo-Noise (PN) or constant envelope zero auto-correlation (CAZAC) sequences, the resolution depends on the chip width, and with the increasing of the transmittable signal bandwidth of the current wireless transmitting device, the chip width can be correspondingly reduced, so that the delay resolution based on the method is continuously improved.

In terms of estimating angles, this feature structure algorithm of multi-signal classification (Multiple Signal Classification, MUSIC) not only estimates for a shorter time and has a higher resolution in terms of angle estimation, but generally requires that it knows the number of incoming waves and that the incoming waves are uncorrelated, whereas the number of paths in the channel is often unknown and because each path is the same probe signal, the received signals of different paths are coherent.

In the aspect of beam deployment of a base station, most NR systems at present only perform eigenvalue decomposition processing on the obtained multichannel CFR data, and utilize eigenvalue information to coarsely deploy beams and resource allocation, or directly bring CFR into an angle estimation method to only divide sub-paths from a space domain and obtain angles of the sub-paths.

In practice, the time domain channel impulse response (Channel Impulse Response, CIR) is obtained by performing inverse fast fourier transform (Inverse Fast Fourier Transform, IFFT) on the frequency domain CFR, so that the time delay cluster can be obtained by performing primary separation on the paths by using the system time domain resolution, and finer angle information can be extracted by further separation with the airspace, but due to the existence of the leakage mechanism, the angle domain information of different paths can leak to different time delay positions, so that some preprocessing operations are required to ensure the quality and quantity of the extracted angle information.

The invention discloses a channel full-dimensional parameter extraction method independent of likelihood functions, which is shown in fig. 1 and comprises the following steps: 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 azimuth angles and elevation angles 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; and step S150, collecting the time delay peak value, the azimuth angle and 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 the complex amplitude estimation of the sub-path by preprocessing the signals, so that the estimated complex amplitude is more accurate, and compared with a likelihood function-based parameter estimation algorithm which introduces EM iteration such as SAGE, the method does not need iteration, has shorter time, and has no problem of converging on a local optimal solution caused by improper initial value setting so as to estimate the false path.

Specifically, in the channel measurement system, a transmitting end transmits a PN sequence modulated by BPSK according to a certain frame format, and a receiving end completes multichannel reception by an array of known arrangement and antenna patterns; the 5G-NR system is similar, in that a transmitting end acts as a UE and modulates an SRS (i.e., a sounding reference signal) in a protocol frame format, and a receiving end acts as a BS and processes the received SRS to obtain channel CFR data of multiple receiving channels.

In the embodiment of the invention, the obtained channel mathematical model of the complete parameter is expressed as:

wherein, h (τ, t) is the time domain response, L and P _l The number of delay clusters and the number of sub-paths contained in the delay cluster are respectively, the delay resolution of the system can only actually distinguish each delay cluster but not the sub-paths in the cluster, and the delay of each delay cluster is expressed as tau _l . τ and t are different descriptions of time scale, τ is in units of PN chip width or NR system sampling interval, and t is in units of PN frame interval or NR system slot interval, δ (τ) is a unit impact function.

And f _l,p Respectively corresponding to the complex amplitude and doppler shift of the p-th sub-path in the first cluster.

Is the direction vector corresponding to the p-th sub-path in the first cluster, wherein theta _l,p And->

Respectively its elevation and azimuth.

The receiving end processes the baseband data which are sampled and down-converted by a plurality of radio frequency channels and comprises array arrangement and antenna pattern information under a specified reference system, taking a uniform plane array placed on an XOZ plane as an example, and signals (namely received PN sequences) received by each receiving channel are expressed as:

wherein N is _m (τ, t) is additive Gaussian noise on the mth receive channel, M and N are the number of array elements of the uniform planar array in the X-axis and Y-axis directions, respectively, a (τ) is the baseband signal expression of the transmit signal, where τ is in units of the system sampling interval size, which is a single chip width for the channel measurement system.

And for NR systems the inverse of the system bandwidth.

To be from->

The m element of the array steering vector of the incident incoming wave comprises array arrangement information and antenna pattern information, and can be unfolded as follows:

wherein,,

is the m-th array element directional diagram is +.>

Complex amplitude at a _x (m)、a _z (m) is the coordinate of the m-th element in the XOZ plane,/th element>

Is the phase shift caused by the distance of the carrier wave at the mth 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 T _s Cyclically transmitting PN sequence modulated by BPSK, the number of PN sequence chips is K, and the duration of single chip is T _p . The receiving end performs multi-channel reception by an array of known arrangements and antenna patterns. As shown in fig. 3, the transmitting end of the NR system is served by the UE, while continuously transmitting the radio frame, the UE modulates the SRS according to the frame format specified by the protocol, where the occupied time domain resource position is shown in fig. 2, and the frequency domain is transmitted in a comb-divided manner as shown in fig. 3 in the frequency domain using protocol, where 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. The receiving end is served by the BS and processes the received SRS, and channel CFR data of a plurality of receiving channels are obtained after the processing. Because the processing capability of the base station is limited, each acquisition task can acquire more than 40 slots of SRS only in the time domain, each slot of SRS can acquire 68 continuous RBs only in the frequency domain, and the base station needs to perform quarter downsampling on CFR data when storing data, so that each acquisition task can only acquire more than 40 slots of channel CFR data on 68 x 12/2/4=102 REs.

Preferably, when the signal data is a PN sequence, the preprocessing is: the PN sequences are subjected to sliding correlation. Specifically, according to the description of the space-time characteristics of the channel in the QuaDRiGa channel model theory, the space-domain scattering environment of the wireless channel between the transmitting end and the receiving end which move in a small range hardly changes. Therefore, PN sequence data or SRS data of multiple slots are received by using multiple snapshot (different snapshots), and channel exploration or angle domain information acquisition is completed. And carrying out sliding correlation on the exploration signals received in the channel measurement system by using local PN sequences in each snapshot to obtain a time delay peak value of each PN sequence. The CFR of each slot obtained by BS processing in the NR system is converted into a time domain channel impulse response CIR by using Inverse Fast Fourier Transform (IFFT).

In a channel measurement system, a received signal on an NM reception channel is correlated with a local PN sequence sliding:

wherein,,<y(τ,t),a(τ)>indicating that the sliding correlation is performed with a (τ) for each received channel data y (τ, t) of the t-th slot, +.,

T _p for a single chip time width, K is the code length of the PN code, N' (τ, t) represents the result of the sliding correlation of noise on the receive array with the PN signal due to KP _b Is large, so that the influence of noise N' (τ, t) is negligible later. The delay peak corresponding to the delay cluster l is expressed as:

in an NR system, a base station receives and processes SRS signals received by all channels according to an OFDM architecture, and the operation corresponding to sliding correlation is to perform IFFT on the acquired CFR data to obtain baseband CIR data of each slot, wherein the expression is as follows:

where Y (k, t) is the frequency domain received data of the t-th slot,

T _s for the system sampling period, when ∈>

When the time delay is not an integer, the corresponding time delay is tau _l The power component of the delay cluster of (c) leaks to all delay locations. N is the number of subcarriers in the system and is also the number of sampling points within a single slot.

The angle independent components in each sub-path expression. Phi _l,p (t) is the extra phase difference of the sub-path p in the delay cluster l caused by Doppler shift at the t slot, and since the application scene of the NR system is mostly a low-speed moving scene such as a city macro cell, the system is assumed to be quasi-static in deduction, namely phi _l,p (t) it does not vary with n.

For the NR system, since the channel CIR obtained by the IFFT of the channel 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 of the noise segment is used as the noise threshold η. Selecting a delay position omega of an effective signal segment by using a threshold eta, and taking the union of the delay position sets on a plurality of receiving channels to resist the space fading caused by multipath on an array:

from different slots

And then taking the intersection to reduce noise interference. Obtaining a new time delay position set:

the angle information of a large number of sub-paths is difficult to distinguish by MUSIC due to the fact that the leaked delay power is small or the leaked power of a plurality of paths exists at some delay positions. In order to obtain correct and reliable angle domain information, the CIR peak values at the time delay positions are selected to be discarded, so that only the power of small sub-path angle information is lost, but the adverse effect of noise on a ZF algorithm is reduced, and the guarantee can be provided for subsequent amplitude estimation. The effective time delay position selection method is assisted based on characteristic values, and is used for any time delay position

The CIR peak values of all channels are used for calculating covariance matrixes under all slots:

wherein,,

next pair->

And decomposing the characteristic value to obtain the maximum and minimum characteristic values of the characteristic value:

when lambda is _max /λ _min ＞η ₂ Preserving the time delay position

To the collection->

Otherwise discarding the delay position, and using only +.>

And CIR peak value corresponding to the inner time delay position.

In one embodiment, the peaks of a plurality of snapshot/slots are processed by a forward-backward spatial smoothing MUSIC algorithm, and sub-paths in each time delay cluster are distinguished and the azimuth and elevation angles of the sub-paths are obtained. First, the peaks of the multiple channels are vectorized:

then selecting subarrays of forward and backward airspace smoothing algorithm, wherein M rows of array elements comprise p mutually staggered _x The array elements of N rows comprise p mutually staggered _z And the isomorphic subarrays. The two-dimensional planar array is divided into p _x ×p _z A sub-area array with a size of M _s ＝M+1-p _x Columns, N _s ＝N+1-p _z And (3) row. V using T snapshot/slot _l (t) obtaining the covariance matrix after the forward and backward airspace smoothing

The method comprises the following steps:

wherein,,

represent Kronecker product, (. Cndot.) ^H Representing the conjugate transpose>

Is M _s ×M _s Is a matrix of units of (a);

Is M _s ×M _s Is 1 for the element on the opposite corner line and 0 for the remaining elements.

Next, to

Performing eigenvalue decomposition, and setting threshold xi according to the module of the minimum eigenvalue and the signal-to-noise ratio of the receiving channel _l P with absolute value greater than threshold _l The characteristic values correspond to P in the delay cluster l _l A strip path for a feature vector v corresponding to a feature value smaller than a threshold _i ,i＝P _l +1..NM construction orthogonal space +.>

P within delay cluster l _l Array guide vectors corresponding to the strip paths respectively +.>

Are all with B _⊥ Orthogonal. MUSIC pseudospectrum constructed for delay cluster l

And two-dimensional searching is carried out on the peak value:

after each peak position is obtained, the azimuth and elevation positions are recorded

And will->

The radius delta around the position is set to zero, and the next peak value is searched until P is obtained _l Elevation and azimuth of the sliver path. The value of delta determines how large an angle range the sub-paths are to be combined into one path, which is chosen depending on the sub-array size, the number of snapshot/slots and noise, and can be 1-5 deg. in the case of general applications where the accuracy of the angle estimation 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 a cyclic prefix length; determining a first noise threshold according to the noise section, and selecting a first delay position of an effective signal section according to the first noise threshold; determining a union of first delay positions of CIR data of the same time slot received by different receiving channels to obtain a first delay position set; acquiring intersections of a plurality of first time delay position sets of different time slots to obtain a second time delay position set; calculating covariance matrixes corresponding to each element in the second time delay position set, and carrying out eigenvalue decomposition on the covariance matrixes to obtain a maximum eigenvalue and a minimum eigenvalue; 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 (3) receiving data by using PN sequences of a plurality of snapshot or SRS data of a plurality of slots to finish channel exploration or angle domain information acquisition. The received survey signals in the channel measurement system are slip correlated in each snapshot with 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 by IFFT.

The system time delay resolution is used for distinguishing time delay clusters, the distinction of sub-paths in the clusters and the estimation of azimuth angles and elevation angles of the sub-paths are finished by means of a front-back 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. Dividing an array of original size N M into p _x ×p _z Scale N _S ×M _S Is a 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 snapshot or slot is used for estimating Doppler frequency shift of the sub-paths.

Resolving P in delay cluster l by using known sub-path angle and ZF algorithm _l Complex amplitude and doppler shift of the strip path, first V _l (t) converting the noise-free portion into a matrix product form:

the angle estimation result of the sub-paths in the cluster I can be utilized to obtain

Then using ZF algorithm to get +.>

Least squares estimation of (c):

using T snapshot/slots

Calculating Doppler shift estimates for sub-paths within cluster l:

where κ (t) is a factor to cancel out the 2π periodicity of the phase, the calculation expression is:

obtain the following steps of

And->

After that, the +.f can be easily calculated based on the existing timing synchronization of the transceiving>

And further to obtain a complex amplitude estimate +.>

In addition, whether it is a channel measurement or an NR system, when the sub-path Doppler shift is to be estimated, the interval between slots or the frame interval T between PN different frames _f All that is required is to satisfy:

wherein f _d Is the maximum doppler shift that a channel exists in the application scenario.

The system delay resolution can only distinguish delay clusters, and all the sub-paths in the clusters bear the same signal, so that the received signals of all the sub-paths are coherent. The front-to-back airspace smoothing MUSIC algorithm for the uniform planar array is required to complete the differentiation and calculate the azimuth and elevation angles thereof. And then the front-back airspace smooth MUSIC algorithm aiming at the uniform plane array is used for completing the distinction and calculating the azimuth angle and the elevation angle. The phase difference between the complex amplitudes of the sub-paths obtained by different snapshot or slot is used for the estimation of the doppler shift of the sub-paths.

More specifically, for the application of channel measurement in a high-speed mobile scenario, since the doppler shift on the sub-path is not negligible, the time of only a single PN chip will cause a significant phase change, so that the autocorrelation peak of the PN sliding correlation is reduced, and a larger error will occur in calculating the complex amplitude by using the correlation peak.

Thus, the channel model for each snapshot is first adjusted as follows:

after the sub-path Doppler shift estimate is obtained, the result can be used to construct a local PN sequence with Doppler shift

And uses it to make a sliding correlation with the received signal to cancel the effect of doppler shift.

This is further divided into two specific cases, when the doppler shifts between sub-paths in a cluster are quite different (special scenario), 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 that is free of the influence of the doppler shift. For example, when the p-th sub-path in the first cluster is to be extracted, sliding correlation is performed first to obtain a peak value corresponding to the delay cluster l:

wherein N "(τ, t) is noise and

a is the interference of other sub-paths in the delay cluster l to the p sub-path sliding correlation peak, which decreases as the length of the PN sequence increases when the doppler shift between sub-paths is larger. The complex amplitude after the Doppler shift removal is then calculated from the estimated sub-path angle and the peak vector of the delay l:

wherein,,

and estimating the guiding vector corresponding to the p-th sub-path in the first cluster.

When the doppler shift between sub-paths differs less, for example in a general scenario like a urban macrocell, the effect of factor a is not negligible, so it is not possible to cancel the effect of the doppler shift for each path separately, but to cancel the effect of the doppler shift on the sub-paths within each delay cluster as much as possible. To ensure the path Doppler shift cancellation effect with large amplitude, the average Doppler shift on the delay cluster l is determined by adopting a weighted average mode

And then adopts

For receivingThe sequences are obtained by sliding correlation

And according to the previous complex amplitude estimation processing flow, completing the sub-path complex amplitude estimation of Doppler frequency shift part elimination by using the obtained sub-path angle and peak value vector.

As shown in fig. 4, for a PN sequence based channel sounding application, the doppler shift estimation results of the sub-paths are used to cancel the effect of doppler shift on the complex amplitude estimation of the sub-paths. For the NR system, because the channel data estimated by LS has the power leakage phenomenon shown in fig. 6 in the time domain, the characteristic value-assisted time delay position selection method is used for preprocessing, and the time delay position with high signal to noise ratio and easy extraction of angle information is determined, so that the adverse effect caused by CIR leakage phenomenon is reduced.

Specifically, when the signal data is a PN sequence, calculating the complex amplitude of each sub-path according to the azimuth angle and the elevation angle corresponding to the sub-path further includes: calculating the phase difference of different time slots of each sub-path; determining Doppler shift of the sub-path according to the phase difference; constructing a local PN sequence based on Doppler frequency shift; and adopting the local PN sequence to carry out sliding correlation on the PN sequence, and continuing to execute until the complex amplitude of each sub-path is obtained again.

In one embodiment, when the doppler shift difference between the sub-paths is less than a 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 channel parameter estimation results obtained by a plurality of snapshot/slots, calculating the size scale channel parameters and probability statistical distribution thereof, and drawing spectrograms such as power angle spectrums (Power Azimuth Spectrum, PAS) of fig. 8 and 9. When the signal data is a PN sequence, the channel full-dimensional parameter set further comprises: doppler shift for each sub-path.

In summary, the method provided by the invention utilizes the space-time separable characteristic of the channel to distinguish each sub-path in the channel and further extract parameters, adopts PN sliding correlation or IFFT to distinguish the paths and obtain the time delay information of the paths in the time delay domain, and adopts MUSIC algorithm introduced with forward and backward airspace smoothing to distinguish the sub-paths in the paths and obtain the azimuth angle and pitch angle thereof in the airspace. And then analyzing the sub-path complex amplitude by utilizing the angle information and the correlation peak values or CIR peak values of a plurality of receiving channels, and finally estimating corresponding Doppler frequency shift according to the phase difference of the sub-path complex amplitude in different snapshots (snapshot)/time slots (slots). In addition, the 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. And introducing a characteristic value-assisted time delay position selection preprocessing method into the time delay estimation module, so that the method can more effectively extract angle domain information in NR system channel data. In addition, the simulation verifies the high efficiency of the method, and the processing result of the measured data shows the effectiveness of the angle domain information extracted by the method.

The following is a 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 multipath channel, and the channel parameters are extracted by SAGE and the proposed method, respectively. Both methods use a PN sequence of length k=511, each chip width dt=3.69×10 ^-6 s. The azimuth angle and the elevation angle of the sub-path are randomly selected between 1 DEG and 180 deg. According to the description of QuaDRiGa, the doppler shift and angle of sub-paths within the same cluster are mostly close, so this is considered when setting paths with the same delay. In addition, by default SAGE knows the number of paths, the proposed method defaults to appropriate various threshold settings, and the rest of the relevant configuration is shown in Table 2.

TABLE 1

TABLE 2

Paths are added in sequence, running results of the algorithm and SAGE are recorded, when the number of paths is different, running time of the algorithm and iteration times of the SAGE are shown in figure 7, specific estimation conditions are recorded in table 3, estimated delay deviation of each path is considered to be smaller than dt, angle deviation is considered to be smaller than 1 degree, doppler frequency shift is considered to be smaller than 1Hz, and estimation is correct when amplitude estimation error is considered to be smaller than 0.01.

As can be seen from fig. 7, the proposed algorithm and SAGE estimation perform quite well with a smaller number of paths but with a shorter run time. The convergence condition of SAGE depends on the sub-path composition, the iteration times required by convergence cannot be determined in advance, when paths arrive simultaneously, the estimation effect is not good, the SAGE is easy to converge on a local optimal solution, and the SAGE is not in accordance with the estimation failure with the actual condition, and the method provided by the invention is more in accordance with the actual condition for processing the problem. The operation time of SAGE algorithm initialization increases along with the increase of the number of paths, while the operation time of the method mainly increases along with the increase of the number of clusters, and the iteration time of the SAGE algorithm is mainly related to the iteration times and the number of paths.

TABLE 3 Table 3

As shown in fig. 9, for the angular power spectrum reconstructed after the data collected by the base station in the single user Line of Sight (LOS) scene is obtained by using the proposed method, the circle position with the label represents the direction of 32 beams formed by 32 receiving units on the base station side using the discrete fourier transform (Discrete Fourier Transform, DFT) codebook. As shown in fig. 8, the CFR data of each channel of the base station is directly carried into the front-back airspace smoothing MUSIC algorithm to extract the angle domain parameters and then reconstruct the angle spectrum. It can be seen that the inventive method is identical to the main power region of the angular spectrum that the latter individually constructs, but the angular power spectrum that the inventive method constructs is finer. In order to verify the effectiveness, the power duty 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 duty ratio on the original 32 wave beams, and as shown in the result of fig. 10, the recovered power duty ratio of the method is more similar to the power duty ratio of the original wave beams, in addition, the beam power reconstruction performance of the main power area of the angle spectrum, which is strong in the received power, can be better, and the effectiveness is verified.

Compared with a likelihood function-based parameter estimation algorithm which introduces EM iteration, the method of the invention does not need iteration, has shorter time, and does not have the problem of converging to a local optimal solution to estimate the false path caused by improper initial value setting. Compared with various estimation algorithms about channel parameters, the method can effectively distinguish sub-paths in the time delay cluster and obtain the parameters of azimuth angle, elevation angle, complex amplitude and Doppler frequency shift. The invention not only utilizes the characteristic of 5G large bandwidth, uses the high resolution capability of the time delay domain to distinguish time delay clusters in the channel, but also utilizes the characteristic of 5G large-scale antenna, and uses the forward and backward airspace smooth MUSIC algorithm with higher angle resolution capability to the coherent information source to distinguish sub-paths in the clusters, so that a large number of sub-paths can be extracted from the time domain and the airspace and the parameters can be used for accurately describing the channel. In addition, for 5G channel sounding applications based on PN sequences, doppler frequency cancellation methods are provided that reduce their impact on sub-path complex amplitude estimation. Aiming at an NR system, the preprocessing method for extracting the angle domain parameters from the channel CIR data by using the algorithm is provided, the effect is better than that of processing CFR by using forward and backward airspace smoothing MUSIC, and the acquired angle information is more complete and reliable.

The invention also discloses a channel full-dimensional parameter extraction device which does not depend on likelihood functions, 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 value of the signal data; the first calculation module 230 is configured to calculate, using the time delay peak value as input information, an azimuth angle and an elevation angle corresponding to each sub-path in the time delay peak value by using a forward and backward spatial domain smoothing MUSIC algorithm; a second calculation module 240, configured to calculate a complex amplitude of each sub-path according to the azimuth and elevation corresponding to the sub-path; the aggregation module 250 is configured to aggregate 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.

It should be noted that, because the content of information interaction and execution process between modules of the above apparatus is based on the same concept as the method embodiment of the present application, specific functions and technical effects thereof may be referred to in the method embodiment section, and details are not repeated herein.

It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional modules is illustrated, and in practical application, the above-described functional allocation may be performed by different functional modules according to needs, i.e. the internal structure of the apparatus is divided into different functional modules to perform all or part of the above-described functions. The functional modules in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit, where the integrated units may be implemented in a form of hardware or a form of a software functional unit. In addition, the specific names of the functional modules are only for distinguishing from each other, and are not used for limiting the protection scope of the application. The specific working process of the units and modules in the above system may refer to the corresponding process in the foregoing method embodiment, which is not described herein again.

The invention also discloses a channel full-dimensional parameter extraction device 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 channel full-dimensional parameter extraction method independent of the likelihood function when executing the computer program.

The device can be a computing device such as a desktop small computer, a notebook computer, a palm computer, a cloud server and the like. The means 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 certain components may be combined, or different components, for example, may also include input-output devices, network access devices, etc.

The processor may be a central processing unit (Central Processing Unit, CPU), which may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), off-the-shelf programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.

The memory 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 in other embodiments also be an external storage device of the apparatus, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash Card (Flash Card) or the like, which are 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 to store an operating system, application programs, boot loader (BootLoader), data, and other programs, etc., such as program code for the computer program, etc. 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 realizes the channel full-dimension parameter extraction method independent of likelihood functions when being executed by a processor.

The computer readable medium may include at least: any entity or device capable of carrying computer program code to a photographing device/terminal apparatus, recording medium, computer Memory, read-Only Memory (ROM), random access Memory (RAM, random Access Memory), electrical carrier signals, telecommunications signals, and software distribution media. Such as a U-disk, removable hard disk, magnetic or optical disk, etc. In some jurisdictions, computer readable media may not be electrical carrier signals and telecommunications signals in accordance with legislation and patent practice.

Claims

1. A method for extracting channel full-dimensional parameters independent of likelihood functions, comprising the steps of:

when the signal data is PN sequence, the preprocessing is as follows: performing sliding correlation on the PN sequence;

when the signal data are CFR data, performing IFFT on the CFR data to obtain CIR data corresponding to the CFR data; the pretreatment is as follows:

dividing the CIR data into a noise section and an effective signal section by using a cyclic prefix length;

determining a first noise threshold according to the noise section, and selecting a first delay position of the effective signal section according to the first noise threshold;

calculating a covariance matrix corresponding to each element in the second time delay position set, and carrying out eigenvalue decomposition on the covariance matrix to obtain a maximum eigenvalue and a minimum eigenvalue;

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 a time delay peak value of the signal data;

calculating to obtain azimuth angles and elevation angles 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;

2. The method of channel full-dimensional parameter extraction independent of likelihood functions of claim 1, wherein when said signal data is a PN sequence, calculating the complex amplitude of each of said sub-paths based on the corresponding azimuth and elevation angles further comprises:

calculating the phase difference of different time slots of each sub-path;

determining a Doppler shift of the sub-path based on the phase difference;

constructing a local PN sequence based on the Doppler shift;

and carrying out sliding correlation on the PN sequence by adopting the local PN sequence, and continuing to execute until the complex amplitude of each sub-path is obtained again.

3. A method of channel full-dimensional parameter extraction independent of likelihood functions as claimed in claim 2, wherein when the doppler shift difference between each of said sub-paths is less than a difference threshold:

a local PN sequence is generated based on the average doppler shift.

4. The method of channel full-dimensional parameter extraction independent of likelihood functions of claim 1, wherein when said signal data is a PN sequence, said channel full-dimensional parameter set further comprises:

doppler shift for each of the sub-paths.

5. A channel full-dimensional parameter extraction apparatus independent of likelihood functions, comprising:

the first calculation module is used for calculating azimuth angles and elevation angles 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;

6. A likelihood function independent channel full-dimensional parameter extraction apparatus comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements a likelihood function independent channel full-dimensional parameter extraction method as claimed in any one of claims 1-4 when executing the computer program.

7. A computer readable storage medium storing a computer program, wherein the computer program when executed by a processor implements a method for extracting channel full-dimensional parameters independent of likelihood functions as claimed in any one of claims 1-4.