RIS-assisted millimeter wave satellite communication system channel estimation method based on PARAFAC

Abstract

The invention discloses an RIS-assisted millimeter wave satellite communication system channel estimation method based on PARAFAC. The method comprises the following steps: constructing an RIS-assisted millimeter wave satellite communication system cascade channel model; the method comprises the following steps: modeling received signals of an RIS-assisted satellite communication system into a third-order parallel factor (PARAFAC) model through data reconstruction based on a multi-dimensional structure of an RIS-assisted millimeter wave satellite communication system channel; and performing parallel factorization on received signals of the RIS-assisted satellite communication system by using an alternating optimization method to obtain an estimated value of a model factor matrix, and finally reconstructing an RIS-assisted satellite communication channel by using the estimated value of the factor matrix to obtain a channel estimated value. The RIS-assisted millimeter wave satellite communication system channel estimation method can accurately achieve RIS-assisted millimeter wave satellite communication system channel estimation, and the performance of the RIS-assisted millimeter wave satellite communication system channel estimation method is superior to that of a traditional least square method (LS)-based channel estimation method.

Description

Technical Field

[0001] This invention relates to the field of wireless communication technology, and in particular to a channel estimation method for a RIS-assisted millimeter-wave satellite communication system based on PARAFAC. Background Technology

[0002] The integrated air-space-ground network is one of my country's important strategies. Future 6G networks will achieve seamless air-space-ground coverage through terrestrial cellular networks, as well as various non-terrestrial communication methods such as satellites, drones, and aerial platforms. For remote areas such as deserts, mountains, and oceans, deploying ground base stations (BS) is difficult and costly, and existing terrestrial network coverage remains largely unavailable. Given this limitation, satellite communication technology has become a competitive solution to supplement terrestrial communications, aiming to achieve global coverage. Millimeter-wave bands, due to their abundant spectrum resources, are gradually becoming a core development direction for modern communication systems. In satellite communication, millimeter waves have gained widespread application due to their excellent frequency band adaptability, making them an ideal communication solution. Millimeter-wave satellite communication systems, with their core advantages such as ultra-high bandwidth, high speed, miniaturization, and strong anti-interference, have become a key technology for solving the current bandwidth bottleneck in satellite communication, promoting terminal portability and ubiquitous application, and are one of the core supporting technologies for 6G integrated air-space-ground communication. However, traditional millimeter-wave satellite communication systems suffer from problems such as signal obstruction, excessive loss, insufficient coverage, and low spectrum efficiency, leading to a significant decline in system performance. To address this issue, researchers recently introduced Reconfigurable Intelligent Surface (RIS) technology into satellite communications to improve its performance. Studies show that RIS can effectively improve the energy efficiency, achievable data rate, and other performance aspects of satellite communication systems, while also enabling better beamforming and tracking. RIS consists of numerous low-cost passive electromagnetic units that can reflect incident signals by controlling amplitude and phase, intelligently controlling the wireless environment without the need for coding or complex processing. The main characteristics of RIS are low cost, thin size, light weight, and low power consumption.

[0003] However, to better achieve RIS beamforming and tracking and fully improve the energy efficiency and data rate of communication systems, RIS-assisted systems typically need to acquire high-quality Channel State Information (CSI). Therefore, since the emergence of RIS technology, channel estimation has been a research hotspot and a significant challenge in the design of RIS-assisted communication systems. Current research on channel estimation in RIS-assisted wireless systems mainly focuses on terrestrial wireless communication systems, with relatively little research on channel estimation in RIS-assisted satellite communication systems. Due to the large orbital radius and high altitude of satellites, channel path loss is significant. Therefore, using RIS in such systems typically requires configuring large-scale electromagnetic units to form high-resolution beams to compensate for path loss. However, the use of a large number of electromagnetic units leads to a sharp increase in pilot overhead during channel estimation, severely reducing the data transmission efficiency of the satellite system. Summary of the Invention

[0004] To address the aforementioned problems, this invention provides a RIS-assisted channel estimation method (PRSCE) for millimeter-wave satellite communication systems based on PARAFAC, comprising the following steps: Step S1: Construct a RIS-assisted cascaded channel model for millimeter-wave satellite communication systems; Step S2: Based on the multidimensional structure of the channel of the RIS-assisted millimeter-wave satellite communication system, the received signal of the RIS-assisted satellite communication system is modeled as a third-order parallel factor model through data reconstruction; Step S3: Use the alternating optimization method to perform parallel factor decomposition on the received signal of the RIS-assisted satellite communication system to obtain the estimated value of the model factor matrix. Finally, use the estimated value of the factor matrix to reconstruct the RIS-assisted satellite communication channel to obtain the channel estimate.

[0005] Beneficial effects: Compared with the prior art, the present invention has the following advantages: The method proposed in this invention utilizes the multidimensional structure of the channel of the RIS-assisted millimeter-wave satellite communication system, makes full use of the correlation between data components of different dimensions, reduces the dimensionality requirement of some factor matrices during data estimation based on parallel factor decomposition, effectively reduces the pilot length used for channel estimation, thereby reducing the pilot overhead of channel estimation, and outperforms the traditional channel estimation method based on least squares (LS). Attached Figure Description

[0006] Figure 1 This is a flowchart illustrating a specific implementation of a RIS-assisted channel estimation method for millimeter-wave satellite communication systems based on PARAFAC, provided by the present invention. Figure 2 This is a schematic diagram of the process for reconstructing the equivalent channel matrix based on parallel factorization provided by the present invention. Figure 3 This is a performance comparison chart between the channel estimation method provided by this invention and the traditional channel estimation method NMSE based on least squares (LS). Detailed Implementation

[0007] The invention will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0008] like Figure 1 As shown, the present invention includes the following steps: Step S1: Construct a RIS-assisted cascaded channel model for millimeter-wave satellite communication systems.

[0009] A RIS-assisted millimeter-wave satellite channel model is constructed as follows: Consider a millimeter-wave geostationary orbit (GEO) satellite communication system, including a geostationary orbit satellite, a RIS, user equipment (UE), and a gateway. A feed link exists between the satellite and the gateway, enabling the gateway to transmit control signals to the satellite. The RIS is connected to the gateway via a wired link, allowing the gateway to modify the RIS parameters in real time. The RIS is equipped with multiple reflective elements, independently controlled by the gateway, which can passively reflect incident signals to enhance the received signal strength. Uplink transmission is considered, where the user equipment transmits signals to the satellite.

[0010] Assume that both the satellite and the user equipment (UE) use uniform linear arrays (ULAs) with half-wavelength spacing. The number of ULA antennas on the satellite side and the UE side are respectively represented by... and Indicated; RIS unit number is represented by Indicated. The uplink channel between the UE and RIS is used Indicated. The uplink channel between RIS and the satellite is used. Indicated. The uplink channel between the UE and the satellite is used. To represent. To simplify The estimation, with RIS turned off in this paper, is a standard millimeter-wave MIMO channel estimation problem, which can be solved by many methods. When the estimation is complete, activate RIS. When estimating the cascaded channel... and hour, It can be treated as a constant; therefore, we focus on the estimation of cascaded channels.

[0011] The transmitter sends P distinct pilot vectors to the receiver for channel estimation, where each pilot vector is in... R Repeated transmission occurs in consecutive time slots, assuming each pilot vector transmission and reception occupies one time slot. Further assuming the wireless channel is a block fading channel, then... and The phase shift matrix of RIS remains unchanged over K consecutive time slots. ,in For the first ( ( ) phase shift vectors of time slots. The base of the natural logarithm. Represents the imaginary unit. This represents the phase shift of the RIS unit; let K = PR; then the signal received by the satellite can be expressed as: (1) in as well as These represent the satellite-side merging matrix, the satellite-side radio frequency (RF) chain number, the user equipment-side transmitted signal, and the additive white Gaussian noise vector, respectively.

[0012] The signals from PR time slots are superimposed on the matrix. In, it can be represented as (2) in This represents the transmit signal matrix on the user equipment side; Represents the total phase shift matrix of RIS within R time slots; M is additive white Gaussian noise. H is the equivalent channel matrix.

[0013] Assume that both the satellite and user equipment use uniform linear arrays (ULAs) with half-wavelength spacing. According to the SV channel model, The expression is as follows: (3) in L Indicates the number of paths. Indicates the first The channel gain of each path follows CN(0,1). and They represent the first The angle of arrival (AOA) and the angle of departure (AOD) of the path RIS. The array manifold vector is represented in the following form: (4) Where N represents the number of antennas. Indicates the departure angle of the user equipment or the arrival angle of the RIS. The base of the natural logarithm. It represents the imaginary unit.

[0014] Considering the signals from L paths together, for simplicity, we define... , and These are the array manifold matrix of the user end, the array manifold matrix of the RIS end, and the channel gain matrix under L paths, respectively, in the following specific forms: (5) The uplink channel between the user equipment and the RIS It is represented as follows: (6) Note that the loss in free space is expressed as follows: (7) in, and These represent the wavelength, the gain of each RIS unit, the gain of each satellite antenna, the distance between the satellite and the RIS, the Boltzmann constant, the atmospheric noise temperature, and the bandwidth, respectively. The statement is as follows: (8) in and Let represent the satellite's angle of arrival and the RIS's angle of departure, respectively; for simplicity, define . They respectively represent the formula (8) ,Right now (9) but It can be rewritten as follows: (10) Then H can be written as (11) in, This represents the Khatri-Rao product.

[0015] Step S2: Based on the multidimensional structure of the RIS-assisted millimeter-wave satellite communication system channel, the received signal of the RIS-assisted satellite communication system is modeled as a third-order parallel factor model through data reconstruction.

[0016] First, turn on all antennas of the user equipment, then turn off the last two antennas. The received signal will then be as follows: (12) in ; Let be the pilot matrix, satisfying For simplicity, additive white Gaussian noise M is ignored here, and the matrix... It is expressed as follows: (13) Secondly, if all antennas of the user equipment are turned on, and then the first and last antennas of the user equipment are turned off, the received signal will be as follows: (14) in Let be the pilot matrix, satisfying ;matrix With matrix It has rotational invariance, as shown below: (15) in , is the rotation transformation matrix; Next, turn on all antennas of the user equipment, and then turn off the first and second antennas of the user equipment. The received signal will then be as follows: (16) in Let be the pilot matrix, satisfying ;matrix With matrix It has rotational invariance, as shown below: (17) The three received signals are combined into a single matrix, modeled as a parallel factor model, as follows: (18) in , ;remember (19) Then matrix Let the three factor matrices of the parallel factor model be... Represents the first... n If so, X can be rewritten as follows: (20) The matrix above can be rearranged and rewritten as follows: (twenty one) (twenty two).

[0017] Step S3: Use the alternating optimization method to perform parallel factor decomposition on the received signal of the RIS-assisted satellite communication system to obtain the estimated value of the model factor matrix. Finally, use the estimated value of the factor matrix to reconstruct the RIS-assisted satellite communication channel to obtain the channel estimate.

[0018] Using equation (20), according to the least squares criterion, the estimated value of C is... (twenty three) Using equation (21), according to the least squares criterion, the estimated value of A is (twenty four) Using equation (22), according to the least squares criterion, the estimated value of B is... (25) The basic idea of ​​the algorithm is as follows: according to equations (23), (24), and (25), update one of matrices A, B, and C successively, and use the updated matrix as the parameter for the next matrix update. Repeat the above steps until the algorithm converges. The specific algorithm is as follows: Step 1): Initialize the factor matrix ; Step 2): ; Step 3): Using equation (23) and Calculate the first digit of C. k Next iteration value ; Step 4): Using equation (24) and Calculate the first digit of A. k Next iteration value ; Step 5): Using equation (25) and Calculate the first B k Next iteration value ; Step 6): Repeat steps 2-5, let: ;

[0019] when The iteration ends when the number is less than a very small number.

[0020] After the algorithm finishes, the estimated matrix is ​​obtained. As mentioned earlier, Then through achievable The estimated value can be obtained according to equation (19). The estimated value. Because ,pass achievable The estimated value is obtained. Finally, the estimated value of the equivalent channel matrix H is reconstructed using equation (11).

[0021] This invention uses the NMSE performance metric to verify the performance of the PRSCE algorithm through simulation experiments. The NMSE expression is as follows: In the simulation experiment, the antennas of the RIS-assisted millimeter-wave MIMO satellite communication system all adopted a uniform array with 16 satellite antennas, 16 UE antennas, 8 RIS antennas, and 64 pilot signals. Figure 3 It can be seen that the channel estimation performance of the PRSCE algorithm proposed in this invention is better than that of the traditional LS algorithm.

Claims

1. A method for channel estimation in a RIS-assisted millimeter-wave satellite communication system based on PARAFAC, characterized in that, The method comprises the following steps: Step S1: constructing a RIS-aided millimeter wave satellite communication system cascade channel model; Step S2: based on the multi-dimensional structure of the RIS-aided millimeter wave satellite communication system channel, the RIS-aided satellite communication system received signal is modeled as a third-order parallel factor model through data reconstruction; Step S3: using an alternating optimization method to perform parallel factor decomposition on the RIS-aided satellite communication system received signal, to obtain an estimated value of a model factor matrix, and finally using the estimated value of the factor matrix to reconstruct the RIS-aided satellite communication channel to obtain a channel estimated value.

2. The PARAFAC-based RIS-assisted millimeter-wave satellite communication system channel estimation method of claim 1, wherein, The specific process of the step S1 is: Consider a millimeter wave geosynchronous orbit satellite uplink transmission communication system, comprising a geosynchronous orbit satellite, an RIS, a user equipment and a gateway; there is a feeder link between the satellite and the gateway, so that the gateway can transmit control signals to the satellite; the RIS is connected with the gateway through a wired link, so that the gateway can change the parameters of the RIS in real time; The RIS is equipped with a plurality of reflecting elements, which are independently controlled by the gateway, and is used for passively reflecting incident signals to enhance the received signal strength; The number of antennas of the satellite-side and user equipment-side ULAs are denoted by and respectively; the number of RIS elements is denoted by ; the uplink channel between the user equipment and the RIS is denoted by ; the uplink channel between the RIS and the satellite is denoted by ; the uplink channel between the user equipment and the satellite is denoted by ; to simplify the estimation of , the RIS is turned off, which is a standard mmWave MIMO channel estimation problem; when is estimated, the RIS is turned on. When estimating the concatenated channel and , is treated as a constant; thus concentrating the processing of the estimation of the concatenated channel; The sending end sends P different pilot vectors to the receiving end for channel estimation, wherein each pilot vector is repeatedly transmitted in R K consecutive time slots, assuming that the transceiving of each pilot vector occupies one time slot, and assuming that the wireless channel is a block fading channel, then and In K consecutive time slots, the phase shift matrix of the RIS is wherein is the phase shift vector of the Kth time slot, , denotes the base of the natural logarithm, denotes the imaginary unit, denotes the phase offset of the RIS unit; let K=PR; then the signal received by the satellite is represented as: （1） wherein and respectively represent a combining matrix on the satellite side, the number of radio frequency chains on the satellite side, a transmit signal on the user equipment side, and an additive white Gaussian noise vector. The signals of PR time slots are superimposed in the matrix is represented as （2） wherein denotes the transmit signal matrix at the user equipment side; denotes the overall phase shift matrix of the RIS over R time slots; M is an additive white Gaussian noise, H is an equivalent channel matrix; Assume that both the satellite and the user equipment employ uniform linear arrays with half-wavelength spacing; according to the SV channel model, is expressed as follows: (3) wherein L denotes the number of paths, denotes the channel gain of the th path and is subject to CN(0,1); and denote the angle of arrival and the angle of departure of the th path RIS, respectively, for the user equipment; denotes the array manifold vector, in particular as follows: (4) where N denotes the number of antennas, denotes the angle of departure of the user equipment or the angle of arrival of the RIS, denotes the base of the natural logarithm, denotes the imaginary unit; Considering the signals of L paths jointly, for simplicity, define , and as the array manifold matrix of the user end, the array manifold matrix of the RIS end and the channel gain matrix under L paths, respectively, and the specific forms are as follows: (5) then the uplink channel between the user equipment and the RIS is represented as follows: (6) Note that the loss of free space is represented as follows: (7) wherein, and respectively represent wavelength, gain of each RIS unit, gain of each satellite antenna, distance between satellite and RIS, Boltzmann constant, noise temperature of sky and bandwidth. Then the uplink channel between the RIS and the satellite The expression is as follows: (8) where and denote the angle of arrival of the satellite and the angle of departure of the RIS, respectively; for simplicity of representation, define denote the angles in equation (8) i.e. （9） then Rewritten as follows: (10) H is rewritten as: (11) wherein, denotes the Khatri-Rao product.

3. The PARAFAC-based RIS-assisted millimeter-wave satellite communication system channel estimation method of claim 2, wherein, The specific process of the step S2 is: First, turn on all the antennas of the user equipment, and then turn off the last two antennas of the user equipment, then the received signal is represented as follows: （12） where ; is the pilot matrix, satisfying ; for simplicity, additive white Gaussian noise M, matrix is represented as follows: （13） Second, turn on all the antennas of the user equipment, and then turn off the first and last antennas of the user equipment, then the received signal is represented as follows: （14） wherein is a pilot matrix, satisfying ; matrix with matrix with rotational invariance, represented as follows: （15） wherein is a rotation transformation matrix; Third, turn on all the antennas of the user equipment, and then turn off the first and second antennas of the user equipment, then the received signal is represented as follows: （16） wherein is a pilot matrix satisfying ; matrix and matrix has the rotation invariance, which is expressed as follows: （17） Combine the three received signals into a matrix, model it as a parallel factor (PARAFAC) model, and define it as follows: （18） wherein , ; Let （19） Then matrix Let the three factor matrices of the parallel factor model be... Represents the first... n If so, X can be rewritten as follows: （20） According to the structural characteristics of the PARAFAC model, rearrange the elements of the X matrix in formula (12) to obtain matrices Y and Z, and the specific form is as follows: （21） （22）。 4. The PARAFAC-based RIS-assisted millimeter-wave satellite communication system channel estimation method of claim 1, wherein, The specific process of the step S3 is: Using formula (20), according to the least square criterion, the estimated value of C is （23） Using formula (21), according to the least square criterion, the estimated value of A is （24） Using formula (22), according to the least square criterion, the estimated value of B is （25） Record The matrix representing the k iteration, the algorithm is as follows: Step 1): Initialization of factor matrix ; Step 2): ; Step 3): Compute the Cth iteration value of C using formula (23) and k ;​​ Step 4): Compute the first iteration value of A using formula (24) and , and formula (25) k ; and ; Step 5): Using equation (25) and Calculate the first B k Next iteration value ; Step 6): repeat steps 2-5, and let ； When The iteration ends when the difference is less than a small number. After the algorithm, the estimated matrix ; is obtained by The estimated value of is obtained according to equation (19); since , the estimated value of is obtained by Finally, the estimated value of the equivalent channel matrix H is reconstructed by equation (11).​

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