CN109672635B

CN109672635B - Time domain correlation estimation method, device and equipment

Info

Publication number: CN109672635B
Application number: CN201710965874.4A
Authority: CN
Inventors: 金晓成; 徐兵
Original assignee: China Academy of Telecommunications Technology CATT
Current assignee: China Academy of Telecommunications Technology CATT; Datang Mobile Communications Equipment Co Ltd
Priority date: 2017-10-17
Filing date: 2017-10-17
Publication date: 2020-07-31
Anticipated expiration: 2037-10-17
Also published as: WO2019076210A1; CN109672635A

Abstract

The invention provides a time domain correlation estimation method, a device and equipment, which relate to the technical field of communication and are used for improving channel estimation performance.

Description

Time domain correlation estimation method, device and equipment

Technical Field

The present invention relates to the field of communications technologies, and in particular, to a method, an apparatus, and a device for estimating time domain correlation.

Background

Under high-speed rails, multiple antennas in the same cell are generally deployed along the high-speed rails by means of a Remote Radio Unit (RRH), so that cell coverage is increased, and switching frequency is reduced to improve network performance. In general, a plurality of RRHs are installed in a high-speed rail environment.

In the prior art, a high-speed rail model under a single RRH and a high-speed rail model under 4RRH are given, and in general, a power spectrum of rayleigh fading is assumed to be a Jake's spectrum, in practical situations, a UE (User Equipment) under a high-speed rail is also influenced by a part of strong Non-direct paths, namely L OS (L ine of Sight) path + N L OS (Non L ine of Sight) path, and in general, an N L OS path is rayleigh fading.

The existing time domain correlation estimation method aims at a Rayleigh fading model or a high-speed rail model with only L OS path, and under the high-speed rail scene with L OS path + N L OS path, the time domain correlation function calculated according to the existing method has errors, so that the channel estimation performance is reduced.

Disclosure of Invention

In view of the above, the present invention provides a time domain correlation estimation method, apparatus and device for improving channel estimation performance.

To solve the foregoing technical problem, in a first aspect, an embodiment of the present invention provides a time domain correlation estimation method, including:

respectively obtaining time domain channel estimation of an OS part of a direct path L of a pilot frequency position and time domain channel estimation of an OS part of a non-direct path N L;

obtaining a power spectrum offset and a maximum doppler spread of the N L OS portion;

obtaining a time-domain correlation function according to the time-domain channel estimation of the L OS part, the time-domain channel estimation of the N L OS part, the power spectrum offset and the maximum Doppler spread of the N L OS part;

and performing channel estimation by using the time domain correlation function.

The obtaining of the time domain channel estimation of the direct path L OS part of the pilot position and the time domain channel estimation of the non-direct path N L OS part of the pilot position respectively includes:

for any path, according to the estimated Doppler frequency offset on the path, taking the 0 th symbol as a reference, and performing phase derotation on the time domain channel estimation value of the pilot frequency position;

accumulating the time domain channel estimation values after the phase de-rotation within a preset time period to obtain an accumulated sum;

obtaining a time domain channel estimate of the L OS part from the accumulated sum;

obtaining a time domain channel estimate for the N L OS portion based on the accumulation and the time domain channel estimate for the L OS portion.

Wherein the obtaining of the power spectrum offset and the maximum Doppler spread of the N L OS part comprises:

performing sequence correlation estimation on the time domain channel estimation of the part N L OS to obtain a sequence correlation estimation value of the part N L OS;

determining a power spectrum offset and a maximum Doppler spread for the N L OS portion based on the sequence related estimates for the N L OS portion.

Wherein the method further comprises:

and acquiring the moving speed of the user equipment UE according to the maximum Doppler spread and the carrier frequency.

Wherein the obtaining a time-domain correlation function based on the time-domain channel estimate of the L OS part, the time-domain channel estimate of the N L OS part, the power spectrum offset of the N L OS part, and the maximum Doppler spread comprises:

obtaining a time-domain correlation function for the L OS part based on the time-domain channel estimate for the L OS part and the estimated Doppler shift for the L OS part;

obtaining a time-domain correlation function for the N L OS part based on the time-domain channel estimate for the N L OS part, the power spectrum offset and the maximum Doppler spread for the N L OS part;

determining L OS power ratio and N L OS power ratio on all paths from the time domain channel estimate of the L OS part;

and acquiring a final time domain correlation function according to the time domain correlation function of the L OS part, the L OS power ratio of all paths, the time domain correlation function of the N L OS part and the N L OS power ratio.

In a second aspect, an embodiment of the present invention provides a time domain correlation estimation apparatus, including:

a first obtaining module, configured to obtain time domain channel estimation of a direct path L OS part of a pilot position and time domain channel estimation of a non-direct path N L OS part of the pilot position, respectively;

a second obtaining module for obtaining a power spectrum offset and a maximum doppler spread of the N L OS part;

a third obtaining module, configured to obtain a time-domain correlation function according to the time-domain channel estimation of the L OS part, the time-domain channel estimation of the N L OS part, the power spectrum offset of the N L OS part, and a maximum doppler spread;

and the channel estimation module is used for carrying out channel estimation by utilizing the time domain correlation function.

Wherein the first obtaining module comprises:

the phase derotation rotor module is used for carrying out phase derotation on the time domain channel estimation value of the pilot frequency position by taking the 0 th symbol as a reference according to the estimated Doppler frequency offset on any path;

the accumulation submodule is used for accumulating the time domain channel estimation value after the phase de-rotation in a preset time period to obtain an accumulated sum;

a first obtaining sub-module, configured to obtain a time domain channel estimate of the L OS portion according to the accumulated sum;

a second obtaining sub-module, configured to obtain a time domain channel estimate for the N L OS portion according to the accumulated sum and the time domain channel estimate for the L OS portion.

Wherein the second obtaining module comprises:

the obtaining submodule is used for carrying out sequence correlation estimation on the time domain channel estimation of the N L OS part to obtain a sequence correlation estimation value of the N L OS part;

a determining submodule for determining a power spectrum offset and a maximum Doppler spread for the N L OS portion based on the sequence correlation estimate for the N L OS portion.

Wherein the apparatus further comprises:

and the speed determining module is used for acquiring the moving speed of the user equipment UE according to the maximum Doppler spread and the carrier frequency.

Wherein, the third acquisition module comprises:

a first obtaining sub-module, configured to obtain a time-domain correlation function of the L OS part according to the time-domain channel estimation of the L OS part and the estimated doppler frequency offset of the L OS part;

a second obtaining sub-module, configured to obtain a time-domain correlation function of the N L OS portion according to the time-domain channel estimation of the N L OS portion, the power spectrum offset of the N L OS portion, and the maximum doppler spread;

a first determining submodule for determining L OS power ratios and N L OS power ratios on all paths based on a time domain channel estimate of the L OS part;

and a third obtaining submodule, configured to obtain a final time-domain correlation function according to the time-domain correlation function of the L OS part, the L OS power ratios on all paths, the time-domain correlation function of the N L OS part, and the N L OS power ratio.

In a third aspect, an embodiment of the present invention provides a time domain correlation estimation apparatus, including: a memory, a processor, and a computer program stored on the memory and executable on the processor; the processor is used for reading the program in the memory and executing the following processes:

Wherein the processor is further configured to read the program in the memory and execute the following processes:

In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium for storing a computer program, which when executed by a processor implements the steps in the method according to the first aspect.

The technical scheme of the invention has the following beneficial effects:

in the embodiment of the invention, the time domain correlation function under the condition of the high-speed rail L OS path + N L OS path can be accurately estimated, so that the channel estimation result can be optimized by utilizing the accurate time domain correlation, and the channel estimation performance is improved by utilizing the scheme of the embodiment of the invention.

Drawings

Fig. 1(a) and 1(b) are power spectra of a single RRH and multiple RRHs, respectively;

FIG. 2 is a Jake's power spectrum;

FIGS. 3(a) and 3(b) are power spectra of single and multiple RRHs at L OS path + N L OS path, respectively;

FIG. 4 is a flowchart of a time domain correlation estimation method according to an embodiment of the present invention;

FIG. 5 is a diagram of an L TE CRS pattern;

FIG. 6 is a flow process diagram of an embodiment of the present invention;

FIG. 7 is an offset N L OS power spectrum;

FIG. 8 is a comparison of throughput at the L OS path for a prior art scheme and a scheme of an embodiment of the present invention;

FIG. 9 is a diagram illustrating throughput comparison at the L OS + N L OS path for a prior art scheme and a scheme of an embodiment of the present invention;

FIG. 10 is a diagram illustrating a time-domain correlation estimation apparatus according to an embodiment of the present invention;

FIG. 11 is a block diagram of a time domain correlation estimation apparatus according to an embodiment of the present invention;

fig. 12 is a schematic diagram of a time domain correlation estimation apparatus according to an embodiment of the present invention.

Detailed Description

The following detailed description of embodiments of the present invention will be made with reference to the accompanying drawings and examples. The following examples are intended to illustrate the invention but are not intended to limit the scope of the invention.

However, in these models, the signals from each RRH are assumed to have only a direct path (L OS) and no non-direct path (N L OS), and the power spectrum is as shown in FIG. 1(a) and FIG. 1 (b). fig. 1(a) is the power spectrum for a single RRU, and fig. 1(b) is the power spectrum for multiple RRUs.

In general, the power spectrum of rayleigh fading is assumed to be a Jake's spectrum, as shown in fig. 2. in practice, a mobile device (UE) in a high-speed rail may also receive a portion of stronger non-direct path influence, i.e., L OS path + N L OS path, and in general, the N L OS path is rayleigh fading, so the power spectrum is as shown in fig. 3(a) and 3 (b).

In the prior art, according to the wiener-cinching theorem, the power spectral density of the wide stationary random process is the fourier transform of the self-correlation function thereof, and then the time-domain correlation function can be obtained by the inverse fourier transform of the power spectrum.

Under the condition of non-high speed rail, the general power spectrum meets the classic Jake's spectrum, and the corresponding time domain correlation function is a first class zero-order Bessel function, namely

In the 3GPP multi-RRH high-speed rail model, the method comprises

Calculating to obtain a time domain correlation function, wherein delta f_pDenotes the frequency deviation in the P path, P (Δ f)_p) Representing frequency deviation deltaf in the p path_pThe probability of (c).

However, when the power spectrum under the actual high-speed rail is as shown in fig. 3(a) and fig. 3(b), since the existing time-domain correlation estimation method is directed to the rayleigh fading model or the high-speed rail model with only L OS path, and under the high-speed rail scenario with L OS path + N L OS path, the time-domain correlation function calculated by the existing method is obviously no longer suitable.

To this end, as shown in fig. 4, the time domain correlation estimation method according to the embodiment of the present invention includes:

step 401, obtaining the time domain channel estimation of the pilot position L OS part and the time domain channel estimation of the N L OS part, respectively.

In this step, for any path, according to the estimated doppler frequency offset on the path, with the 0 th symbol as the reference, the time domain channel estimation value of the pilot frequency position is phase derotated, and the time domain channel estimation value after phase derotation is accumulated in a predetermined time period to obtain an accumulated sum, then, according to the accumulated sum, the time domain channel estimation of the L OS part is obtained, and according to the accumulated sum and the time domain channel estimation of the L OS part, the time domain channel estimation of the N L OS part is obtained.

Assuming a single RRH, the power spectrum is shown in fig. 3 (a); at multiple RRHs, the power spectrum is shown in fig. 3 (b). Multiple RRH power spectra can be viewed as being superimposed from multiple single RRH power spectra.

Taking L TE (L ong Term Evolution ) as an example, the pilot positions are scattered in the time domain, as shown in fig. 5.

Assuming that a plurality of RRH signals are a plurality of estimated paths, the time domain channel estimation value of the pilot frequency position on the known ith symbol and the pth path is expressed as

Estimated Doppler frequency offset delta f of p-th path_p。

In this embodiment, the pilot positions are required to be based on

And time domain correlation interpolation is carried out to obtain a channel estimation value on a non-pilot position. In addition, the time domain correlation can be used to align the pilot frequency position

Performing time-domain filtering to suppress noise and the like

The quality of the channel estimation value at the pilot frequency position is improved.

In conjunction with the flow chart process diagram shown in fig. 6, assume that the time domain channel estimation value of the pilot frequency position on the ith symbol and the pth path

Wherein the content of the first and second substances,

representing L a time domain channel estimate of an OS component and remaining unchanged for a period of time;

time domain channel representing N L OS componentEstimating;

indicates a frequency shift Δ f due to Doppler_pThe induced phase rotation; Δ t_lIndicating the time interval between the ith symbol and the 0 th symbol.

Then, based on the estimated Doppler shift Δ f_pAfter the phase de-rotation is performed with the 0 th symbol as the reference, the following results are obtained:

generally, the higher speed of movement under high-speed rail results in

Change rapidly with time, so assume a period of time

The cumulative sum of (1) is small; while

And remain unchanged for a period of time. That, satisfy:

therefore, the first and second electrodes are formed on the substrate,

namely use of

Estimated L OS components

Then, again by

Estimated to form part of N L OS

And step 402, obtaining the power spectrum offset and the maximum Doppler spread of the N L OS part.

Specifically, sequence correlation estimation is carried out on the time domain channel estimation of the N L OS part to obtain a sequence correlation estimation value of the N L OS part, and the power spectrum offset and the maximum Doppler spread of the N L OS part are determined according to the sequence correlation estimation value of the N L OS part.

In general rayleigh fading, assuming that an error of Automatic Frequency tracking (AFC) is small, a power spectrum is as shown in fig. 2, and the power spectrum is centrosymmetric about f being 0Hz, so that a time-domain correlation function is:

however, in case of multiple RRHs, the power spectrum corresponding to the N L OS part may not be symmetrical about the center where f is 0Hz any more but about a certain frequency f after automatic frequency tracking (AFC) due to the combined effect of doppler shifts of multiple L OS paths₀Centrosymmetric, as shown in fig. 7.

Then, the time-domain correlation function becomes:

assume that the time domain channel estimate for the N L OS component at a known pilot location is

Then can pass through the pair

Sequence correlation estimation is carried out to obtain a sequence correlation estimation value of an N L OS part

Due to J₀(2πf_d,maxτ) is a real number, so

Is in phase with

So that the power spectrum offset f can be estimated₀。

Due to the fact that

Therefore, it is not only easy to use

Thereby can utilize

Estimating the maximum Doppler spread f_d,max。

Further, here, the relative moving speed of the UE can also be estimated in combination with the carrier frequency, i.e. the relative moving speed of the UE is estimated

Wherein f is_cRepresenting the carrier frequency and c the speed of light.

In addition, the estimates of the multiple paths can be combined, assuming that the N L OS portions from each RRH all satisfy the same Jake's spectral power spectral distribution.

And step 403, obtaining a time domain correlation function according to the time domain channel estimation of the L OS part, the time domain channel estimation of the N L OS part, the power spectrum offset of the N L OS part and the maximum Doppler spread.

In this step, the following process may be included:

step 4031, obtaining a time domain correlation function of the L OS part according to the time domain channel estimation of the L OS part and the estimated doppler frequency offset of the L OS part;

step 4032, obtaining a time domain correlation function of the N L OS part according to the time domain channel estimation of the N L OS part, the power spectrum offset and the maximum Doppler spread of the N L OS part;

step 4033, according to the time domain channel estimation of the L OS part, L OS power ratio and N L OS power ratio on all paths are determined;

step 4034, according to the time domain correlation function of the L OS part, the L OS power ratios on all the paths, the time domain correlation function of the N L OS part, and the N L OS power ratio, a final time domain correlation function is obtained.

Time domain channel estimation assuming L OS components at pilot locations on the p-th path are known

Corresponding Doppler shift Δ f_pTime domain channel estimation of N L OS components

Corresponding power spectrum shift f₀Maximum Doppler spread f_d,max。

Then, the time-domain correlation function of the L OS part is expressed as:

wherein

The time-domain correlation function of the N L OS part is expressed as:

meanwhile, the L OS power ratio and the N L OS power ratio on all paths are respectively:

therefore, the final time-domain correlation function is expressed as: r_t(τ)＝P_LOS·R_t,LOS(τ)+P_NLOS·R_t,NLOS(τ)。

And step 404, performing channel estimation by using the time domain correlation function.

The method is not limited to L TE, and is also suitable for calculating the time-domain correlation function under all high-speed rails.

Taking the 4RRH model of L TE 3GPP 36.101 annex B.3A as an example, in the case that only L OS path exists, since N L OS part estimates P_NLOSAnd 0, the throughput performance is equal to the original, as shown in fig. 8.

When 8 additional N L OS paths are added based on the 4RRH model in annex b.3a of 3GPP 36.101, the relative delay and relative power of the total 9 paths are shown in table 1.

TABLE 1

Relative time delay [ ns ]]	Relative power [ dB ]]
		0	0.0(LOS)
9	-9.02(NLOS)
		18	-9.02(NLOS)
36	-15.73(NLOS)
		71	-19.43(NLOS)
179	-20.13(NLOS)
		286	-21.33(NLOS)
393	-23.63(NLOS)
		500	-25.03(NLOS)

As shown in fig. 10, the time domain correlation estimation apparatus according to the embodiment of the present invention includes:

a first obtaining module 1001, configured to obtain time domain channel estimation of an OS portion of a direct path L at a pilot position and time domain channel estimation of an OS portion of a non-direct path N L, respectively;

a second obtaining module 1002, configured to obtain a power spectrum offset and a maximum doppler spread of the N L OS part;

a third obtaining module 1003, configured to obtain a time-domain correlation function according to the time-domain channel estimation of the L OS part, the time-domain channel estimation of the N L OS part, the power spectrum offset of the N L OS part, and the maximum doppler spread;

a channel estimation module 1004, configured to perform channel estimation by using the time domain correlation function.

Wherein the first obtaining module 1001 includes:

the device comprises a phase derotation rotor module, an accumulation submodule, a first acquisition submodule and a second acquisition submodule, wherein the phase derotation rotor module is used for carrying out phase derotation on a time domain channel estimation value of a pilot frequency position by taking a 0 th symbol as a reference according to estimated Doppler frequency offset on any path, the accumulation submodule is used for accumulating the time domain channel estimation value after phase derotation in a preset time period to obtain an accumulated sum, the first acquisition submodule is used for obtaining the time domain channel estimation of the L OS part according to the accumulated sum, and the second acquisition submodule is used for obtaining the time domain channel estimation of the N L OS part according to the accumulated sum and the time domain channel estimation of the L OS part.

Wherein the second obtaining module 1002 comprises:

the device comprises an acquisition submodule and a determination submodule, wherein the acquisition submodule is used for carrying out sequence correlation estimation on the time domain channel estimation of the N L OS part to obtain a sequence correlation estimation value of the N L OS part, and the determination submodule is used for determining the power spectrum offset and the maximum Doppler spread of the N L OS part according to the sequence correlation estimation value of the N L OS part.

As shown in fig. 11, the apparatus further includes:

a speed determining module 1005, configured to obtain a moving speed of the user equipment UE according to the maximum doppler spread and the carrier frequency.

The third obtaining module 1003 includes a first obtaining sub-module configured to obtain a time-domain correlation function of the L0 OS part according to the time-domain channel estimation of the L OS part and the estimated doppler frequency offset of the L OS part, a second obtaining sub-module configured to obtain a time-domain correlation function of the N L OS part according to the time-domain channel estimation of the N L1 OS part, the power spectrum offset of the N L2 OS part, and the maximum doppler spread, a first determining sub-module configured to determine L OS power ratios and N L OS power ratios on all paths according to the time-domain channel estimation of the L OS part, and a third obtaining sub-module configured to obtain a final time-domain correlation function according to the time-domain correlation function of the L OS part, the time-domain L OS power ratios on all paths, the correlation function of the N L OS part, and the N L OS power ratio.

The working principle of the device according to the invention can be referred to the description of the method embodiment described above.

As shown in fig. 12, the time domain correlation estimation apparatus according to the embodiment of the present invention includes:

a processor 1200 for reading the program in the memory 1220 and executing the following processes:

performing channel estimation by using the time domain correlation function;

a transceiver 1210 for receiving and transmitting data under the control of the processor 1200.

In fig. 12, among other things, the bus architecture may include any number of interconnected buses and bridges, with one or more processors represented by processor 1200 and various circuits of memory represented by memory 1220 being linked together. The bus architecture may also link together various other circuits such as peripherals, voltage regulators, power management circuits, and the like, which are well known in the art, and therefore, will not be described any further herein. The bus interface provides an interface. The transceiver 1210 may be a plurality of elements, including a transmitter and a transceiver, providing a means for communicating with various other apparatus over a transmission medium. The processor 1200 is responsible for managing the bus architecture and general processing, and the memory 1220 may store data used by the processor 1200 in performing operations.

The processor 1200 is responsible for managing the bus architecture and general processing, and the memory 1220 may store data used by the processor 1200 in performing operations.

The processor 1200 is further configured to read the computer program and execute the following steps:

Furthermore, a computer-readable storage medium of an embodiment of the present invention stores a computer program executable by a processor to implement:

Wherein the method further comprises:

In the several embodiments provided in the present application, it should be understood that the disclosed method and apparatus may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.

In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be physically included alone, or two or more units may be integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.

The integrated unit implemented in the form of a software functional unit may be stored in a computer readable storage medium. The software functional unit is stored in a storage medium and includes several instructions to enable a computer device (which may be a personal computer, a server, or a network device) to execute some steps of the transceiving method according to various embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.

The foregoing is a preferred embodiment of the present invention, and it should be noted that it is obvious to those skilled in the art that various modifications and improvements can be made without departing from the principle of the present invention, and these modifications and improvements should be construed as the protection scope of the present invention.

Claims

1. A method for time-domain correlation estimation, comprising:

performing channel estimation by using the time domain correlation function;

obtaining a time-domain correlation function based on the time-domain channel estimate of the L OS part, the time-domain channel estimate of the N L OS part, the power spectrum offset of the N L OS part, and the maximum Doppler spread, comprising:

2. The method of claim 1, wherein obtaining the time domain channel estimate for the direct path L OS part and the time domain channel estimate for the non-direct path N L OS part separately comprises:

3. The method of claim 1, wherein said obtaining a power spectrum shift and a maximum doppler spread of said N L OS portion comprises:

4. The method according to claim 1 or 3, characterized in that the method further comprises:

5. A time-domain correlation estimation apparatus, comprising:

a second obtaining module for obtaining a power spectrum offset and a maximum doppler spread of the N L OS portion;

a channel estimation module, configured to perform channel estimation by using the time domain correlation function;

wherein the third obtaining module comprises:

6. The apparatus of claim 5, wherein the first obtaining module comprises:

7. The apparatus of claim 5, wherein the second obtaining module comprises:

8. The apparatus of claim 5 or 7, further comprising:

9. A time-domain correlation estimation apparatus, comprising: a memory, a processor, and a computer program stored on the memory and executable on the processor; it is characterized in that the preparation method is characterized in that,

the processor is used for reading the program in the memory and executing the following processes:

performing channel estimation by using the time domain correlation function;

the processor is also used for reading the program in the memory and executing the following processes:

10. The apparatus of claim 9, wherein the processor is further configured to read a program in the memory and perform the following:

11. The apparatus of claim 9, wherein the processor is further configured to read a program in the memory and perform the following:

12. The apparatus of claim 9 or 11, wherein the processor is further configured to read a program in the memory and perform the following process:

13. A computer-readable storage medium for storing a computer program, wherein the computer program, when executed by a processor, implements the steps in the method of any one of claims 1 to 4.