CN115225434A

CN115225434A - Large-scale MIMO satellite mobile communication channel estimation method and system

Info

Publication number: CN115225434A
Application number: CN202210872352.0A
Authority: CN
Inventors: 高西奇; 李科新; 尤力; 王闻今; 仲文
Original assignee: Southeast University
Current assignee: Southeast University
Priority date: 2022-07-20
Filing date: 2022-07-20
Publication date: 2022-10-21

Abstract

The invention discloses a large-scale MIMO satellite mobile communication channel estimation method and a system. The satellite or the gateway station takes the sequence of the basic pilot modulated by different phase modulation factors as a pilot set, and utilizes statistical channel information including space angle information and average channel energy to implement pilot allocation and determine the pilot sequence used by each user. The user terminal transmits a pilot signal using a pilot sequence allocated by the satellite or the gateway station. The satellite or the gateway station carries out two-stage channel estimation according to the received pilot signal, the channel estimation value is obtained by firstly carrying out subcarrier-by-subcarrier spatial processing on the received signal at the satellite side and then carrying out user-by-user frequency domain processing, the spatial processing is the same for all subcarriers, and the user-by-user frequency domain processing can be quickly realized by utilizing a Toeplitz system solver. The two-stage channel estimation method can achieve near-optimal performance and greatly reduce the implementation complexity.

Description

Large-scale MIMO satellite mobile communication channel estimation method and system

Technical Field

The present invention relates to a method and a system for estimating a satellite mobile communication channel configured with an antenna array, and more particularly, to a method and a system for estimating a satellite mobile communication channel using a large-scale MIMO technique.

Background

Satellite communication is considered one of the key technologies to achieve global seamless network coverage. Existing satellite communications mostly employ a multi-beam transmission scheme, wherein a beam former on the satellite side is usually fixed, which limits the transmission capability of the satellite communications to a certain extent. As an important technology of land 5G, large-scale multiple-input multiple-output (MIMO) can support tens of users to communicate with a base station on the same time-frequency resource by generating a large number of dynamic beams using a large-scale antenna array on the base station side. The large-scale MIMO technology is expanded and applied to the satellite mobile communication system, and the spectrum efficiency and the power efficiency of the satellite mobile communication system can be obviously improved.

Orthogonal Frequency Division Multiplexing (OFDM) has become one of the key technologies for realizing high-rate communication in broadband transmission, which can not only resist frequency selective fading, but also have an efficient implementation. The large-scale MIMO and OFDM are combined to form a large-scale MI MO OFDM system, which is a core enabling technology of a 5G mobile communication system and is continuously evolved and developed in 5G evolution and 6G systems. Most of the past work mainly focuses on massive MIMO OFDM technology in terrestrial wireless networks, wherein the massive MIMO OFDM channel estimation technology is also widely researched and applied, but does not consider the particularity of satellite channels. Therefore, the method has very important significance in developing research on the channel estimation problem in the satellite large-scale MIMO OFDM system. To the best of our knowledge, no literature on this aspect is known.

Disclosure of Invention

The purpose of the invention is as follows: the invention aims to overcome the defects of the prior art, improve the channel estimation performance of a satellite mobile communication system and reduce the implementation complexity.

The technical scheme is as follows: in order to realize the purpose of the invention, the invention adopts the following technical scheme:

a large-scale MIMO OFDM satellite mobile communication channel estimation method is applied to a satellite mobile communication system, and is characterized in that: the satellite configuration antenna array is communicated with a user terminal which is provided with a plurality of antennas or a single antenna in the coverage area; taking a sequence of the basic pilot modulated by different phase modulation factors as a pilot set; the satellite or the gateway station uses the statistical channel information including the space angle information and the average channel energy to implement pilot frequency distribution, determines the pilot frequency sequence of each user and sends the serial number to each user; the user sends pilot signal, the satellite or the gateway station carries out channel estimation according to the received pilot signal, and the estimated value of the channel parameter is obtained by adopting a space-frequency two-stage channel estimation method.

In a preferred embodiment, the statistical channel information is obtained by an uplink sounding procedure or by feedback information of each user terminal; in the uplink detection process, each user periodically sends a detection signal, and the satellite estimates the spatial angle information and the average channel energy of each user according to the received detection signal; the feedback information of each user terminal is the geographical position information, the spatial angle information and the average channel energy of the user.

In a preferred embodiment, the satellite or gateway station uses a graph-based pilot allocation algorithm for pilot allocation. The graph-based pilot allocation algorithm divides a set of users into S groups, where S represents the number of available pilots, such that users in the same group use the same pilots and users in different groups use different pilots. In the pilot frequency distribution algorithm based on the graph, the vertex set of the graph represents the user set, and the weight between the vertices of the graph represents the interference between the users. The weight between the vertices is calculated from the spatial angle information and the average channel energy. The map-based pilot allocation algorithm comprises the following steps:

initializing a user set with allocated pilot frequency and a user set without allocated pilot frequency;

allocating a pilot frequency which enables the sum of the weights between any two vertexes in the group to be minimum to each user which is not allocated with the pilot frequency, and updating a user set which is allocated with the pilot frequency and a user set which is not allocated with the pilot frequency;

in a preferred embodiment, in the space-frequency two-stage channel estimation method, the channel estimation value is obtained by performing subcarrier-by-subcarrier space domain processing and user-by-user frequency domain processing on a satellite-side received signal. The spatial processing is the same for all subcarriers. The user-by-user frequency domain processing can be quickly implemented using a Toeplitz system solver.

A large-scale MIMO OFDM satellite mobile communication channel estimation method is applied to a user terminal and is characterized in that:

the user terminal periodically sends a detection signal to the satellite, or feeds back the geographical position information, the spatial angle information and the average channel energy of the user to the satellite, and the user terminal is used for the satellite or the gateway station to implement pilot frequency allocation and channel estimation;

the user terminal performs frequency and time compensation on the uplink transmission signal by using Doppler frequency shift caused by satellite movement and minimum propagation delay of long-distance propagation;

each user terminal transmits a pilot signal using a pilot sequence assigned by the satellite or gateway station.

In a preferred embodiment, the doppler shift caused by the satellite movement and the minimum propagation delay of long-distance propagation are estimated by the user terminal according to the received synchronization signal, or calculated by the user terminal and the satellite position information; the Doppler shift and minimum propagation delay information are dynamically updated as the satellite or user terminal moves, and the frequency and time compensation amount is adaptively changed.

Massive MIMO OFDM satellite mobile communication channel estimation satellite-side apparatus comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that: the computer program, when loaded into a processor, implements the massive MIMO OFDM satellite mobile communication channel estimation method.

A massive MIMO OFDM satellite mobile communications channel estimation user terminal device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that: the computer program, when loaded into a processor, implements the massive MIMO OFDM satellite mobile communication channel estimation method.

The large-scale MIMO OFDM satellite mobile communication channel estimation system comprises a satellite and a user terminal, and is characterized in that: the satellite configuration antenna array is communicated with a user terminal which is provided with a plurality of antennas or a single antenna in the coverage area; the satellite or a gateway station associated therewith is adapted to:

taking a sequence of the basic pilot modulated by different phase modulation factors as a pilot set; the satellite or the gateway station implements pilot frequency distribution by utilizing statistical channel information including space angle information and average channel energy, and feeds back a pilot frequency distribution result to each user; a user sends a pilot signal, and a satellite or a gateway station carries out channel estimation according to the received pilot signal;

the satellite or gateway station uses a graph-based pilot allocation algorithm for pilot allocation. The graph-based pilot allocation algorithm divides a set of users into S groups, where S represents the number of available pilots, such that users in the same group use the same pilots and users in different groups use different pilots. In the pilot frequency distribution algorithm based on the graph, the vertex set of the graph represents the user set, and the weight between the vertices of the graph represents the interference between the users. The weight between the vertexes is obtained by calculating space angle information and average channel energy;

the satellite or the gateway station adopts a space-frequency two-stage channel estimation method to carry out channel estimation according to the received pilot signal. In the space-frequency two-stage channel estimation method, a channel estimation value is obtained by firstly carrying out subcarrier-by-subcarrier space domain processing on a satellite side receiving signal and then carrying out user-by-user frequency domain processing. The spatial processing is the same for all subcarriers. The user-by-user frequency domain processing can be quickly realized by using a Toeplitz system solver;

in the moving process of the satellite or each user terminal, the channel estimation result is dynamically updated along with the change of the statistical channel information;

the user terminal is configured to: periodically sending a detection signal to a satellite, or feeding back the geographical position information, the spatial angle information and the average channel energy of a user to the satellite, wherein the geographical position information, the spatial angle information and the average channel energy are used for the satellite or a gateway station to implement pilot frequency allocation and channel estimation; performing frequency and time compensation on an uplink transmission signal by using Doppler frequency shift caused by satellite movement and minimum propagation delay of long-distance propagation; the pilot signal is transmitted using a pilot sequence assigned by a satellite or a gateway station.

Has the beneficial effects that: compared with the prior art, the invention has the following advantages:

(1) The large-scale MIMO technology is expanded and applied to the satellite mobile communication system, and the spectrum efficiency and the power efficiency of the satellite mobile communication system are improved.

(2) The characteristics of the satellite mobile communication channel are fully utilized, a complete channel estimation method is designed, and the calculation complexity is greatly reduced.

(3) The channel estimation method is suitable for time division duplex and frequency division duplex satellite mobile communication systems.

(4) Each user terminal performs frequency and time compensation on the transmitted signal, so that the system design is simplified, and the communication method is suitable for satellite mobile communication by using a high-orbit satellite, a medium-orbit satellite and a low-orbit satellite.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description only illustrate some embodiments of the present invention, and it is obvious for those skilled in the art to obtain drawings of other embodiments without creative efforts.

Fig. 1 is a schematic diagram of a large-scale MIMO satellite mobile communication channel estimation method.

FIG. 2 is a diagram of a massive MIMO satellite mobile communication system.

Fig. 3 is a comparison graph of large-scale MIMO satellite mobile communication channel estimation performance.

Fig. 4 is a schematic structural diagram of a massive MIMO satellite mobile communication channel estimation satellite-side device.

Fig. 5 is a schematic structural diagram of a massive MIMO satellite mobile communication channel estimation user terminal device.

FIG. 6 is a schematic diagram of a massive MIMO satellite mobile communication channel estimation system.

Detailed Description

In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

As shown in fig. 1, the massive MIMO OFDM satellite mobile communication channel estimation system disclosed by the embodiment of the present invention includes a satellite and a user terminal, and is characterized in that: the satellite configuration antenna array is communicated with a user terminal which is provided with a plurality of antennas or a single antenna in the coverage area; the satellite or a gateway station associated therewith is adapted to:

in the moving process of the satellite or each user terminal, dynamically updating a channel estimation result along with the change of the statistical channel information;

the invention discloses a large-scale MIMO OFDM satellite mobile communication channel estimation method, which is applied to a user terminal and is characterized in that:

the user terminal compensates the frequency and time of the uplink transmission signal by using the Doppler frequency shift caused by satellite movement and the minimum propagation delay of long-distance propagation;

each user terminal transmits pilot signals by using pilot sequences distributed by satellites or gateway stations;

the Doppler frequency shift caused by satellite movement and the minimum propagation delay of long-distance propagation are estimated by a user terminal according to received synchronous signals, or calculated by the position information of the user terminal and the satellite; the Doppler shift and minimum propagation delay information are dynamically updated as the satellite or user terminal moves, and the frequency and time compensation amount is adaptively changed.

The method according to the embodiment of the present invention is further described below with reference to specific implementation scenarios, the method according to the present invention is not limited to the specific scenarios, and for other implementations other than the exemplary scenarios of the present invention, those skilled in the art can make adaptive adjustments according to the technical idea of the present invention and using the existing knowledge according to the specific scenarios.

(1) System configuration

Considering the case of a single satellite (which may be a low-orbit satellite, a medium-orbit satellite, or a high-orbit satellite), the satellite side is equipped with an antenna array (which may be a one-dimensional or two-dimensional array, with the number of antennas being tens to hundreds). The antenna array or the large-scale antenna array can be arranged into different shapes according to the requirements of quantity, easy installation and the like. The most basic is a Uniform Planar Array (UPA) in two dimensions, i.e. the antenna elements are arranged uniformly in the transverse and longitudinal directions, and the distance between adjacent antenna elements can be λ/2 or

Where alpha is the carrier wavelength.

For example, a single satellite may communicate with multiple users, as shown in fig. 2. Assuming that the satellite side is equipped with UPA, the number of the antenna units in the x-axis and y-axis directions is M _x And M _y Then M = M _x M _y The total number of antennas provided for the satellite. Suppose that each user side is equipped with an omnidirectional antenna and the number of users is K. Recording the user index set as

It is considered that an Orthogonal Frequency Division Multiplexing (OFDM) is used for wideband data transmission, so that a frequency selective fading channel can be converted into a plurality of parallel flat fading channels. Count total number of subcarriers as N _c The adjacent subcarrier spacing is Δ f. The system sampling time is T _s ＝1/(N _c Δ f). Adding length N at the beginning of each OFDM symbol _g I.e. Cyclic Prefix (CP). The time length of CP is T _g ＝N _g T _s . The time lengths of the OFDM symbols not containing and containing CP are T respectively _c ＝N _c T _s And T = T _g +T _c 。

Consider that the massive MIMO satellite communication system operates in a Frequency Division Duplex (FDD) mode, i.e., the uplink and downlink occupy different frequency bands. The time resource of the uplink phase is divided into a plurality ofTime slots, each time slot containing N _S One OFDM symbol. The first OFDM symbol in each time slot is used for uplink channel estimation, and the rest N _S 1 OFDM symbol is used for uplink data transmission.

In training-based uplink channel estimation, multiple terrestrial mobile users transmit pilot sequences to a single satellite simultaneously. The pilot sequence is accurately known by both the satellite and the user side. After receiving the pilot sequence, the satellite estimates the channel parameters for all users.

Note the book

Representing a set of all n x m-dimensional complex (real) number matrices.

(2) Signal model

Received signal received by satellite at time t

Is composed of

Wherein

And

the channel impulse response and the transmit signal for user k,

is an additive gaussian noise signal on the satellite side. Channel impulse response

Can be expressed as

Where δ (x) is a Dirc delta function, Q _k For the number of multi-paths for user k,

v _k，q 、τ _k，q and g _k，q Channel gain, doppler shift, propagation delay, and satellite side array response vector for the q-th path of user k, respectively.

Doppler shift v for the qth path of user k _k，q Can be expressed as

Wherein

And

doppler shift due to satellite and user k movement, respectively. In addition to this, the present invention is,

the different multipaths for user k are approximately the same, i.e.

The minimum propagation delay of the user k channel is noted as

Note book

Respectively, the angle of arrival (AoA, angle-of-arrival) of the q-th path of the user k channel. Satellite side array response vector g _k，q Can be expressed as g _k，q ＝g(θ _k，q ). Vector g (θ) to arbitrary θ = (θ) _x ，θ _y ) Is defined as

Wherein

Representing the kronecker product of two vectors. In the formula (3), the reaction mixture is,

can be expressed as

Wherein

λ＝c/f _c C =3 × 10 for uplink carrier wavelength ⁸ m/s is the speed of light, f _c For uplink carrier frequency, d _v For v e { x, y } distance between adjacent antenna elements, (. Cndot.) ^T Representing a transpose of a vector or matrix. If the satellite side is provided with other antenna arrays, only the antenna array needs to be matched

And then the array response vector corresponding to the array response vector is replaced.

In satellite communication, since users are far away from the satellite, the departure angles corresponding to different multipath signals of the same user can be considered to be approximately the same, namely, θ _k，q ＝θ _k ，q＝1，...，Q _k . Thus, the array response vector g for the q-th path of user k channel _k，q Can be abbreviated as g _k，q ＝g _k ＝g(θ _k ) Wherein

Referred to as AoA for user k channel. Note the book

Is the spatial angle of the k channel of the user, wherein

And

the nadir angle of user k is noted

Having a maximum value of

Corner of sky and bottom

Sum spatial angle xi _k Satisfy the following relationship

Thus, the spatial angle ξ of user k _k Fall in a circular area

And (4) inside. Due to the far distance from the satellite, the space angle

The variation is slow and therefore accurate spatial angle information can be assumed to be known to the satellite and the user.

Note the book

The signal is transmitted in the frequency domain in the s-th OFDM symbol for user k. The time domain of user k sends a signal of

Note the book

And

by using the Doppler frequency shift and time delay compensation method, the time domain transmission signal of the user k after compensation is

The received signal of the satellite at the s-th OFDM symbol is

Wherein z is _s (t) is an additive gaussian noise signal. Here, the first and second liquid crystal display panels are,

for equivalent channel impulse response

Wherein

And

respectively the equivalent channel gain and the propagation delay of the q-th path of the user k channel. In OFDM systems, to avoid inter-symbol interference, N _g Should satisfy

In addition, note h _k (t, f) is the equivalent channel frequency response of user k, which can be expressed as

Wherein

The received signal of the satellite on the r sub-carrier of the s OFDM symbol is

Wherein

Is the channel vector of user k, z _s，r Is additive noise on the satellite side. (11) Channel vector h in _k，s，r Can be expressed as

h _k，s，r ＝h _k (sT，rΔf)＝d _k，s，r g _k ， (12)

Wherein d is _k，s，r ＝d _k (sT, r.DELTA.f). Since the doppler shift and propagation delay have been compensated, the frequencies and times on the satellite side and the user side can be considered perfectly synchronized after that.

(3) Channel model

This subsection analyzes the channel characteristics over the OFDM symbol where the pilot is located. The subscript s of the OFDM symbol is omitted hereinafter for convenience. The channel vector of user k on the r-th subcarrier of the OFDM symbol is

h _k，r ＝d _k，r g _k ， (13)

Wherein

a _k，q The equivalent channel gain of the q path of the k channel of the user. Suppose N _p The sub-carriers are used for channel estimation and the corresponding index set is

Note the book

For user k in N _p Frequency domain channel of subcarriers, which may be denoted as

Wherein

Will H _p，k Referred to as the space-frequency domain channel (SFC) of user k. In addition, d _p，k Can be further expressed as

Wherein

Is composed of

Note that the equivalent propagation delay of each user is satisfied

The interval [0,T _g ) Is divided into the following intervals

Wherein

τ _l ＝lT _d /(N _d N _p Δ f) is the l grid point, where

And is

Record mu _d ＝N _d /L _d A time delay refinement factor. Utilizing N in (17) _d Sub-interval, d _p，k Can be re-represented as

Wherein

When N is present _d When large enough, satisfy

Is/are as follows

Can be approximated as p (tau) _l ) Then d is followed by _p，k Can be re-represented as

Wherein

Note that N _d To represent

Is approximately p (tau) _l ) To the degree of accuracy of the measurement. N is a radical of _d The larger the approximation, the more accurate the approximation. At this time, H _p，k Can be expressed as

Thereafter, d _t，k Referred to as the angle-delay domain channel (ADC) for user k.

Suppose alpha _k，e Can be modeled as

Wherein beta is _k Representing a large-scale fading parameter, η _k，l A small-scale fading parameter representing the ith path of user k. In addition, let η _k，l Obeying a Gaussian distribution

Wherein

Referred to as the power delay profile (PD P) of user k. And, α _k，l Independent of each other for different users k and multipaths i.e.

Time domain correlation matrix

Is composed of

Wherein

And omega _k，l ＝β _k γ _k，l . It is assumed that the satellite and the user can accurately acquire slowly varying channel parameters

(3) Statistical channel information acquisition

The statistical channel information such as spatial angle information and average channel energy may be obtained by an uplink sounding procedure or by feedback information of each ue. In the uplink detection process, each user periodically transmits a detection signal, and the satellite estimates spatial angle information, average channel energy, and a mean vector and a variance matrix of user-side channel components of each user according to the received detection signal. In particular, spatial angle

The estimated value of (a) can be obtained by a classical arrival angle estimation algorithm, such as a MUSIC algorithm, an ESPRIT algorithm, a unity ESPRIT algorithm, and the like; average channel energy w _k，l Can be obtained by the following method

Wherein

Is a vector alpha _k，l Estimated value of the nth time, N _L Is the estimated number of times.

The feedback information of each user terminal is the geographical position information, the spatial angle information and the average channel energy of the user. The feedback information of each user terminal can be obtained by a channel parameter estimation method by using an uplink synchronization signal or a detection signal, wherein the geographical position information can also be obtained by a global positioning system. And under the condition that the terminal feeds back the geographical position information, the satellite side obtains the spatial angle information of each user by using the geographical position information of the terminal and the position information of the satellite.

(4) Pilot multiplexing and pilot allocation

The available pilot number is recorded as S, and the pilot set is

In satellite communication, the number of available conductors is much smaller than the number of users, i.e., S < K. Therefore, the pilots need to be multiplexed among different users. Note that the s-th pilot X is used _p，s Is recorded as

Wherein

Note the book

For satellites in N _p The uplink received signal of the sub-carrier, which can be expressed as

Wherein p is _P For user k, s _k Indicating the pilot index used by user k. In addition to this, the present invention is,

is additive complex Gaussian noise, and each element of the additive complex Gaussian noise follows independent same distribution

Using the property of phase-shifted pilot, the s-th pilot X _p，s Can be expressed as

Wherein

Satisfy the requirement of

Further, X _c ＝diag{x _c Is a common pilot with a unit modulus value element and satisfies

For example, X _c May be constructed based on Zadoff-Chu sequences. In addition, the maximum number of pilots satisfies

Since the satellite side accurately knows the space angle

I.e. the known array direction vector

Estimation of SFC

Can be converted into a vector

Is estimated. Furthermore, since the ADC can better describe the SFC with fewer parameters, the following considerations first estimate the estimated ADC

Note the book

And

can be obtained by the following formula (24),

in which the following equation is used

Wherein

Is composed of

z _p Obedience distribution

When the vector d is obtained _t After estimation, the vector

Is estimated as

d _t Is estimated as the Minimum Mean Square Error (MMSE)

Wherein

Corresponding channel estimation error

Obedience distribution

Wherein

Is composed of

The MMSE of the channel estimation can be expressed as

When N is present _p When approaching infinity, the MMSE of the channel estimation approaches J → J _asy Wherein J _asy Is composed of

Wherein

When the following conditions are satisfied

J _asy Can reach the following minimum value

It can be found that when N is present _p Tending to infinity, the interference between users using different pilots will disappear so that there is only interference from the multiplexed pilots. In other words, collections

The pilots in the inner tend to be phase shifted orthogonally. Furthermore, if the array direction vectors of users using the same pilots are orthogonal to each other, the interference generated by the multiplexed pilots also disappears and the progressive MMSE reaches its minimum.

It can be seen that the MMSE performance of the channel estimation depends on the pilot allocation. In order to further improve the performance of channel estimation, pilot frequency needs to be allocated reasonably. From the above analysis, users whose array direction vectors are close to orthogonal should use the same pilot, while users whose array direction vectors are highly linearly related should use different pilots. That is, the inner product of the array direction vectors of any two users using the same pilot should be as close to zero as possible. Intuitively, the pilot allocation problem can be established as an optimization problem as follows

Wherein

Note that the problem in (36) can be represented as a max-S-cut problem on the graph. Recording picture

Wherein

A set of vertices is represented that is,

is a set of weights. Specifically, an edge between any pair of vertex i and vertex k has a weight W _i，k And satisfy W _i，k ＝W _k，i And write W _i，i And =0. It can be seen that the problem (36) is actually to divide the vertex set into S disjoint subsets

So that the sum of the weights of the edges connecting vertices within the same subset is minimized.

Note the following equations

The problem (36) can be equivalently converted into the following problem

It is noted that problem (38) is the figure

max-S-cut problem in (1). Specifically, the problem (38) attempts to find a set of vertices

Is used to maximize the sum of the weights of the endpoints falling within the different subsets. Based on the inspiration, an efficient pilot frequency allocation algorithm based on a graph is designed.

The pilot frequency allocation algorithm based on the graph comprises the following specific steps:

inputting: angle of space

And average channel energy

And (3) outputting: pilot allocation results

Step 1: initialization

And

step 2: for any purpose

S is calculated as follows _k

And step 3: updating

And

and 4, step 4: if it is

If the set is an empty set, exiting the executing step; if it is

And if not, continuing to execute the step 2.

(5) Space-frequency two-stage channel estimation method

The channel estimation is obtained by firstly carrying out subcarrier-by-subcarrier spatial processing on a satellite side received signal and then carrying out user-by-user frequency domain processing, wherein the spatial processing is the same for all subcarriers. And obtaining an optimal linear subcarrier-by-subcarrier spatial processing vector by minimizing and gradually MMSE. By using a fast Toeplitz system solver, user-by-user frequency domain processing can be quickly realized.

To simplify the analysis, assume R for each user _t，k Can be expressed as

R _t，k ＝β _k Γ， (39)

Where Γ = diag { γ },

satisfy the requirement of

This means that the PDP is the same for all users. Therefore, the satellite only needs to obtain large-scale fading parameters

And PDP of all users

This may significantly reduce the overhead of statistical channel information acquisition.

In the space-frequency two-stage channel estimation method, the channel estimation can be obtained as follows

Wherein

And

respectively representing subcarrier-by-subcarrier spatial processing vectors and user-by-user frequency domain processing matrices. First, the satellite-side reception signal is subjected to the following spatial domain processing

Wherein

Obedience distribution

Then, d _t，k May be obtained by user-by-user frequency domain processing as follows

By minimizing

The optimal frequency domain processing matrix of user k is

Wherein

Is composed of

Diagonal matrix Λ _w，k Is composed of

MMSE matrix of

Wherein

Corresponding MMSE of

When N is present _p When it tends to be endless, J _w，k Tend to be

Wherein

Is composed of

Wherein A is _k，l ＝G _k γ _e +σ ² W _k ，

W _k ＝||w _k || ² And is

So that

The minimized spatial processing vector should satisfy

Wherein u is _k Satisfy the requirement of

It can be seen that the progressive optimal spatial processing vector should be in the form of a regularized zero-breaking process. Due to A _k，l And w _k In this connection, it is generally difficult to obtain v from the formula (50) _k Is a closed expression of (1). According to formula (50), v _k Is equal to equation F (v) _k ) Root of =0, wherein F (u) _k ) Is composed of

Equation F (u) _k ) The root of =0 can be obtained by newton method.

In the user-by-user frequency domain processing in equation (43), there is

Notice T _w，k Is a Toeplitz matrix, which is equivalent to solving the Toeplitz system T _w，k x _w，k ＝y _w，k . Here, the Toeplitz system is solved using the classical Levinson recursive algorithm. For an n-dimensional Toeplitz matrix, the multiplication times required by the Levinson algorithm are 4n ² . To solve for Toeplitz System T _n s = b is an example, wherein

Is a positive Toeplitz matrix, b = [ b ] ₁ …b _n ] ^T Is an arbitrary vector. The Levinson algorithm proceeds as follows.

Firstly, let T _n Is re-expressed as T _n ＝T ₀ L _n Wherein T is ₀ ＝[T _n ] _0，0 ，L _n Can be expressed as

Wherein r is _n-1 ＝[ρ ₁ ...ρ _n-1 ] ^T . For convenience, note r _m ＝[ρ ₁ ...ρ _m ] ^T . Variable alpha _m 、ζ _m 、

Are each alpha ₁ ＝-ρ ₁ 、ζ ₁ ＝1、x ₁ ＝b ₁ 、y ₁ ＝-ρ ₁ . M is more than or equal to 1 and less than or equal to n-1, zeta _m And x _m Is updated as follows

ζ _m+1 ＝(1-|α _m | ² )ζ _m ， (53)

Wherein

Representing the vector obtained by rearranging the elements in the vector x in the reverse order. For m is more than or equal to 1 and less than or equal to n-2, alpha _m And y _m Is updated as follows

In obtaining x _n Later, toeplitz System T _n The solution of s = b can be expressed as

When obtaining a solution

After that, (42) in the formula

Can be expressed as

Wherein

The IFFT (-) represents an inverse fast Fourier transform.

The specific steps of the space-frequency two-stage channel estimation algorithm are as follows.

Inputting: angle of space

Average channel energy

And a common PDP

And (3) outputting: channel estimation results

for

do

Calculating w according to equation (49) _k ；

Computing

Calculated according to the formulae (53) to (57)

Calculated according to equation (58)

end for

(6) Dynamic update

As the satellite or the user moves, channel information such as a spatial angle and average channel energy of each user is dynamically updated, pilot allocation and channel estimation values adaptively change accordingly, information such as doppler shift and minimum propagation delay, and frequency and time compensation amounts of a user terminal adaptively change accordingly.

Fig. 3 shows the channel estimation performance curves of the method of the present embodiment in different scenarios.

Based on the same inventive concept, as shown in fig. 4, a large-scale MIM O satellite mobile communication channel estimation satellite-side apparatus disclosed in the embodiment of the present invention includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the computer program is loaded into the processor, the large-scale MIMO satellite mobile communication channel estimation method applied to a satellite or a gateway station is implemented.

In a particular implementation, the device includes a processor, a communication bus, a memory, and a communication interface. The processor may be a general purpose Central Processing Unit (CPU), microprocessor, application Specific Integrated Circuit (ASIC), or one or more integrated circuits for controlling the execution of programs in accordance with the inventive arrangements. The communication bus may include a path that transfers information between the aforementioned components. A communications interface, using any transceiver or the like, for communicating with other devices or communications networks. The memory may be, but is not limited to, a read-only memory (ROM) or other type of static storage device that may store static information and instructions, a random-access memory (RAM) or other type of dynamic storage device that may store information and instructions, an electrically erasable programmable read-only memory (EEPRO), a compact disc read-only memory (CD-ROM) or other optical disk storage, disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer. The memory may be self-contained and coupled to the processor via a bus. The memory may also be integral to the processor.

Wherein, the memory is used for storing application program codes for executing the scheme of the invention and is controlled by the processor to execute. The processor is used for executing the application program codes stored in the memory, thereby realizing the communication method provided by the embodiment. The processor may include one or more CPUs, or may include a plurality of processors, and each of the processors may be a single-core processor or a multi-core processor. A processor herein may refer to one or more devices, circuits, and/or processing cores for processing data (e.g., computer program instructions).

Based on the same inventive concept, as shown in fig. 5, a large-scale MIM O satellite mobile communication channel estimation user terminal device disclosed in the embodiment of the present invention includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the computer program is loaded on the processor, the large-scale MIMO satellite mobile communication channel estimation method applied to the user terminal is implemented. In particular implementations, the user terminal device includes a processor, a communication bus, a memory, and a communication interface, which may take the form of various handheld devices, vehicle-mounted devices, wearable devices, computing devices, or other processing devices connected to a wireless modem with wireless communication capability.

As shown in fig. 6, the massive MIMO OFDM satellite mobile communication channel estimation system disclosed in the embodiment of the present invention includes a satellite and a user terminal, wherein the satellite is configured with an antenna array to communicate with the user terminal configured with multiple antennas or a single antenna in its coverage area; the satellite or a gateway station associated therewith is adapted to:

taking a sequence of the basic pilot modulated by different phase modulation factors as a pilot set; the satellite or the gateway station uses the statistical channel information including the space angle information and the average channel energy to implement pilot frequency distribution, determines the pilot frequency sequence of each user and sends the serial number to each user; a user sends a pilot signal, a satellite or a gateway station carries out channel estimation according to the received pilot signal, and a space-frequency two-stage channel estimation method is adopted to obtain an estimation value of a channel parameter;

the satellite or gateway station uses a graph-based pilot allocation algorithm for pilot allocation. The graph-based pilot allocation algorithm divides a set of users into S groups, where S represents the number of available pilots, such that users in the same group use the same pilots and users in different groups use different pilots. In the pilot frequency distribution algorithm based on the graph, the vertex set of the graph represents the user set, and the weight between the vertexes of the graph represents the interference between the users. The weight between the vertexes is obtained by calculating space angle information and average channel energy;

the user terminal is configured to: the user terminal periodically sends a detection signal to the satellite, or feeds back the geographical position information, the spatial angle information and the average channel energy of the user to the satellite, and the user terminal is used for the satellite or the gateway station to implement pilot frequency allocation and channel estimation;

The embodiment of the large-scale MIMO satellite mobile communication channel estimation system and the embodiment of the large-scale MIMO satellite mobile communication channel estimation method belong to the same inventive concept, and specific technical means implementation details can refer to the method embodiment, which is not described herein again. The invention does not relate to the prior art.

The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.

Claims

1. A large-scale MIMO OFDM satellite mobile communication channel estimation method is applied to a satellite mobile communication system and is characterized in that: the satellite configuration antenna array is communicated with a user terminal which is provided with a plurality of antennas or a single antenna in the coverage area; taking a sequence of the basic pilot modulated by different phase modulation factors as a pilot set; the satellite or the gateway station uses the statistical channel information including the space angle information and the average channel energy to implement pilot frequency distribution, determines the pilot frequency sequence of each user and sends the serial number to each user; the user sends pilot signal, the satellite or the gateway station carries out channel estimation according to the received pilot signal, and the estimated value of the channel parameter is obtained by adopting a space-frequency two-stage channel estimation method.

2. The massive MIMO OFDM satellite mobile communication channel estimation method of claim 1, wherein: the statistical channel information is obtained by an uplink detection process or by feedback information of each user terminal; in the uplink detection process, each user periodically sends a detection signal, and the satellite estimates the spatial angle information and the average channel energy of each user according to the received detection signal; the feedback information of each user terminal is the geographical position information, the spatial angle information and the average channel energy of the user.

3. The massive MIMO OFDM satellite mobile communication channel estimation method of claim 1, wherein: the satellite or the gateway station adopts a pilot frequency distribution algorithm based on a graph to carry out pilot frequency distribution; the graph-based pilot allocation algorithm divides a set of users into S groups, wherein S represents the number of available pilots, so that users in the same group use the same pilot and users in different groups use different pilots; in the pilot frequency distribution algorithm based on the graph, a vertex set of the graph represents a user set, and weights among the vertices of the graph represent interference among users; the weight between the vertexes is obtained by calculating space angle information and average channel energy; the map-based pilot allocation algorithm comprises the following steps:

4. the massive MIMO OFDM satellite mobile communication channel estimation method of claim 1, wherein: in the space-frequency two-stage channel estimation method, a channel estimation value is obtained by firstly carrying out subcarrier-by-subcarrier space domain processing on a satellite side receiving signal and then carrying out user-by-user frequency domain processing; the spatial domain processing is the same for all subcarriers; the user-by-user frequency domain processing is quickly realized by using a Toeplitz system solver.

5. A large-scale MIMO OFDM satellite mobile communication channel estimation method is applied to a user terminal, and is characterized in that:

6. The massive MIMO OFDM satellite mobile communication channel estimation method of claim 5, wherein: the Doppler frequency shift caused by the satellite movement and the minimum propagation delay of long-distance propagation are estimated by the user terminal according to the received synchronous signals, or calculated by the position information of the user terminal and the satellite; the Doppler frequency shift and minimum propagation delay information are dynamically updated as the satellite or the user terminal moves, and the frequency and time compensation amount is adaptively changed.

7. Massive MIMO OFDM satellite mobile communication channel estimation satellite-side apparatus comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that: the computer program when loaded into a processor implements the massive mimo ofdm satellite mobile communications channel estimation method according to any of claims 1 to 4.

8. A massive MIMO OFDM satellite mobile communications channel estimation user terminal device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that: the computer program when loaded into a processor implements the large-scale MIM O OFDM satellite mobile communications channel estimation method according to claim 5 or 6.

9. The large-scale MIMO OFDM satellite mobile communication channel estimation system comprises a satellite and a user terminal, and is characterized in that: the satellite configuration antenna array is communicated with a user terminal which is provided with a plurality of antennas or a single antenna in the coverage area; the satellite or a gateway station associated therewith is adapted to:

the satellite or the gateway station adopts a pilot frequency distribution algorithm based on a graph to carry out pilot frequency distribution; the graph-based pilot allocation algorithm divides a set of users into S groups, wherein S represents the number of available pilots, so that users in the same group use the same pilot and users in different groups use different pilots; in the pilot frequency distribution algorithm based on the graph, a vertex set of the graph represents a user set, and weights among the vertices of the graph represent interference among users; the weight between the vertexes is obtained by calculating space angle information and average channel energy;

the satellite or the gateway station adopts a space-frequency two-stage channel estimation method to carry out channel estimation according to the received pilot signal; in the space-frequency two-stage channel estimation method, a channel estimation value is obtained by firstly carrying out subcarrier-by-subcarrier space domain processing on a satellite side receiving signal and then carrying out user-by-user frequency domain processing; the spatial domain processing is the same for all subcarriers; the user-by-user frequency domain processing is quickly realized by using a Toeplitz system solver;

the user terminal is configured to: periodically sending a detection signal to a satellite, or feeding back the geographical position information, the spatial angle information and the average channel energy of a user to the satellite, wherein the geographical position information, the spatial angle information and the average channel energy are used for the satellite or a gateway station to implement pilot frequency allocation and channel estimation; compensating the frequency and time of the uplink transmission signal by using Doppler shift caused by satellite movement and minimum propagation delay of long-distance propagation; the pilot signal is transmitted using a pilot sequence assigned by a satellite or a gateway station.