Electronic device and operating method thereof

Abstract

The invention provides an electronic device and an operating method thereof. The electronic device includes a communication circuit and a communication processor, where the communication circuit includes 2N receiving antennas, and the communication processor includes a covariance matrix generation circuit and a whitening filter matrix generation circuit, the covariance matrix generation circuit generates a covariance matrix for the 2N receive antennas based on a measurement of a receive signal, and the whitening filter matrix generation circuit calculates a whitening filter for N receive antennas based on a Cholesky decomposition. The covariance matrix includes a first sub-matrix, a second sub-matrix, a third sub-matrix, and a fourth sub-matrix, and the whitening filter matrix generation circuit calculates a whitening filter matrix for the 2N reception antennas based on a first whitening filter matrix for the first sub-matrix and characteristics of a Cholesky decomposition, the first sub-matrix corresponds to a diagonal sub-matrix of the covariance matrix.

Description

[0001] This application is based on and claims priority to Korean Patent Application No. 10-2024-0144348, filed on October 21, 2024, with the Korean Intellectual Property Office, the disclosure of which is incorporated herein by reference in its entirety. Technical Field

[0002] This disclosure relates to electronic devices, and more specifically, to an electronic device for calculating a whitening filter and a method of operating the same. Background Technology

[0003] To increase channel capacity or support multiple users, various techniques such as spatial diversity and spatial multiplexing based on various antennas have been introduced. Furthermore, the number of supported antennas is steadily increasing. For example, consider four existing receive antennas supporting eight receive antennas. Moreover, to support higher throughput in next-generation communication systems (such as 6G communication), it may be necessary to support even more antennas (e.g., 16 or more receive antennas). However, given that the computational complexity for interference control increases exponentially with the number of antennas, hardware and software implementations can be difficult due to this high complexity. Therefore, a method is needed that can control interference while reducing computational complexity as the number of antennas increases. Summary of the Invention

[0004] One aspect of the present invention is to provide a whitening filter-based electronic device and a method of operating thereof that reuses whitening filters corresponding to a small number of receiving antennas.

[0005] According to one or more embodiments, an electronic device is provided, comprising: a communication circuit including 2N receiving antennas; and a communication processor including a covariance matrix generation circuit and a whitening filter matrix generation circuit, wherein the covariance matrix generation circuit generates a covariance matrix for the 2N receiving antennas based on measurements of received signals, and the whitening filter matrix generation circuit calculates a whitening filter for the N receiving antennas based on Cholesky decomposition. The covariance matrix includes a first submatrix, a second submatrix, a third submatrix, and a fourth submatrix, and the whitening filter matrix generation circuit calculates a whitening filter matrix for the 2N receiving antennas based on the characteristics of a first whitening filter matrix for the first submatrix and Cholesky decomposition, wherein the first submatrix corresponds to a diagonal submatrix of the covariance matrix.

[0006] According to another aspect of one or more embodiments, a method of operating an electronic device including 2N receiving antennas is provided, the method comprising: generating a covariance matrix for the 2N receiving antennas based on measurements of received signals, wherein the covariance matrix includes a first submatrix, a second submatrix, a third submatrix, and a fourth submatrix, wherein the first submatrix corresponds to a diagonal submatrix of the covariance matrix; calculating a first whitening filter matrix for the first submatrix; calculating a second whitening filter matrix based on the third submatrix and the first whitening filter matrix of the covariance matrix; and calculating a third whitening filter matrix based on the second whitening filter matrix, wherein the third whitening filter matrix satisfies a Choreski decomposition of the fourth submatrix and the substitution matrix of the covariance matrix.

[0007] According to another aspect of one or more embodiments, a communication processor connected to 2N receiving antennas is provided. The communication processor includes: a covariance matrix generation circuit that generates a covariance matrix for the 2N receiving antennas based on measurements of received signals; and a whitening filter matrix generation circuit that calculates a whitening filter for the N receiving antennas based on Cholesky decomposition. The covariance matrix includes a first submatrix, a second submatrix, a third submatrix, and a fourth submatrix, wherein the first submatrix corresponds to a diagonal submatrix of the covariance matrix, and the whitening filter matrix generation circuit calculates the whitening filter matrix for the 2N receiving antennas based on the characteristics of a first whitening filter matrix for the first submatrix and Cholesky decomposition. Attached Figure Description

[0008] Various embodiments will become clearer from the following detailed description taken in conjunction with the accompanying drawings, in which: Figure 1 This is a diagram illustrating a wireless communication system according to an embodiment; Figure 2 This is a block diagram of a receiving device according to an embodiment; Figure 3 This is a detailed block diagram of the communication circuit according to an embodiment; Figure 4 This is a diagram illustrating a multiple-input multiple-output (MIMO) environment according to an embodiment; Figure 5 This is a block diagram of a communication processor according to an embodiment; Figure 6 This is a diagram illustrating an example of a whitening filter matrix generation circuit according to an embodiment; Figure 7 This is a block diagram of a communication processor according to an embodiment; Figure 8A This is a block diagram of a communication processor according to an embodiment; Figure 8BThis is a diagram illustrating an example of a block unit covariance matrix according to an embodiment; Figure 9 This is a flowchart illustrating an operation method of a communication processor according to an embodiment; Figure 10 This is a flowchart illustrating an operation method of a communication processor according to an embodiment; and Figure 11 This is a block diagram of a wireless communication device according to an embodiment. Detailed Implementation

[0009] In the following, various embodiments will be described in detail with reference to the accompanying drawings. As used in this specification, the phrases in the form of "at least one of A, B or C" include, within their scope, "A only", "B only", "C only", "A and B", "A and C", "B and C" and "A, B and C".

[0010] Figure 1 This is a diagram illustrating a wireless communication system according to an embodiment.

[0011] Reference Figure 1 The wireless communication system 10 may include a transmitting device 100 and a receiving device 200. The transmitting device 100 may refer to a means for encoding data and transmitting a signal to the receiving device 200 via a wireless channel. For example, when the signal is an uplink signal, the transmitting device 100 may correspond to a user equipment (UE), and the receiving device 200 may correspond to a base station. In another example, when the signal is a downlink signal, the transmitting device 100 may correspond to a base station, and the receiving device 200 may correspond to a user equipment.

[0012] According to an embodiment, the transmitting device 100 may include an encoder 110 and a deserializer 120. The encoder 110 may encode data according to various encoding techniques. For example, the encoder 110 may encode data based on at least one of turbo code, convolution code, or polar code. The deserializer 120 may deserialize a series of bit strings. The deserializer 120 may receive bit strings of codewords encoded from the encoder 110 and deserialize the series of bit strings through multiple inputs. For example, the deserializer 120 may deserialize the series of bit strings and map the bit strings to each of multiple layers. The multiple layers may correspond to each rank of a multiple-input multiple-output (MIMO) wireless communication system. For example, in the case where the wireless communication system 10 is a 4×4 MIMO wireless communication system, the series of bit strings may be deserialized into four bit strings.

[0013] According to an embodiment, the receiving device 200 may include a MIMO detector 210 and a decoder 220. The MIMO detector 210 can detect MIMO signals. The MIMO detector 210 can generate soft decision information during the detection of MIMO signals to perform error correction through the decoder 220. For example, the MIMO detector 210 may be based on a linear detection technique using minimum mean square error (MMSE), zero-forcing (ZF), and / or matched filter (MF), or a nonlinear detection technique using maximum likelihood (ML).

[0014] Figure 2 This is a block diagram of the receiving device 200 according to an embodiment.

[0015] Reference Figure 2 The receiving device 200 may include a processor 201, a communication circuit 203, and a memory 205.

[0016] Processor 201 can control the overall operation of receiving device 200. For example, processor 201 can send signals to and receive signals from transmitting device 100 via communication circuit 203. Furthermore, processor 201 can write data to memory 205 and read data from memory 205. A portion of communication circuit 203 and processor 201 may be referred to as a communication processor.

[0017] Communication circuit 203 performs functions for transmitting signals to and receiving signals from a transmitting device via a wireless channel. For example, communication circuit 203 performs conversion functions between baseband signals and bitstreams according to the system's physical layer specifications. For instance, when transmitting data to transmitting device 100, communication circuit 203 can generate complex symbols by encoding and modulating the transmitted bit string, and when receiving data from transmitting device 100, communication circuit 203 can recover the received bit string by demodulating and decoding the baseband signal. Communication circuit 203 can up-convert baseband signals to RF band signals and then transmit the RF band signals through an antenna, or down-convert RF band signals received through an antenna back to baseband signals. For example, communication circuit 203 may include transmit filters, receive filters, amplifiers, mixers, oscillators, digital-to-analog converters (DACs), analog-to-digital converters (ADCs), etc. Communication circuit 203 can perform beamforming. Communication circuit 203 can apply beamforming weights to signals to be transmitted to / received from transmitting device 100 in order to impart directionality to the transmitted / received signals. According to an embodiment, communication circuit 203 can receive spatially multiplexed MIMO signals via MIMO detector 210 and obtain error-corrected bit strings via decoder 220.

[0018] Memory 205 may store data such as basic programs, application programs, and / or setting information for operation of receiving device 200. Memory 205 may include volatile memory, non-volatile memory, or a combination of volatile and non-volatile memory. Memory 205 may provide stored data upon request from processor 201.

[0019] Figure 3 This is a detailed block diagram of the communication circuit 203 according to an embodiment.

[0020] Reference Figure 3 The communication circuit 203 may include a decoding and demodulation circuit 310, a digital beamforming circuit 320, a first receiving path 330-1 to the Nth receiving path 330-N, and an analog beamforming circuit 340.

[0021] According to an embodiment, the decoding and demodulation circuit 310 can perform channel decoding. For channel decoding, at least one of low-density parity-check (LDPC) codes, convolutional codes, polar codes, or turbine codes can be used. For example, the decoding and demodulation circuit 310 may be adapted to... Figure 1 The decoder 220 of the receiving device 200.

[0022] The digital beamforming circuit 320 multiplies the analog signals received through the first receiving path 330-1 to the Nth receiving path 330-N by beamforming weights. Here, the beamforming weights are used to change the amplitude and phase of the signal. In this case, multiplexed modulation symbols according to MIMO transmission technology can be received through the first receiving path 330-1 to the Nth receiving path 330-N.

[0023] The analog beamforming circuit 340 performs beamforming on analog signals. The analog beamforming circuit 340 can perform beamforming on analog receiving beams to receive MIMO signals.

[0024] Each of the first receiving paths 330-1 to the Nth receiving path 330-N may include a Fast Fourier Transform (FFT) operation circuit, an analog-to-digital converter, a CP (cyclic prefix) removal circuit, a serial-to-parallel conversion circuit, and a downconverter. Each of the first receiving paths 330-1 to the Nth receiving path 330-N may downconvert the received signal to the baseband frequency, remove the CP to generate a serial time-domain baseband signal, convert the serial time-domain baseband signal into a parallel time-domain signal, perform an FFT algorithm to generate N parallel frequency-domain signals, and convert the parallel frequency-domain signals into a sequence of modulated data symbols. That is, the first receiving paths 330-1 to the Nth receiving path 330-N can provide independent signal processing for multiple streams generated by digital beamforming. However, depending on the implementation method, some components of the first receiving paths 330-1 to the Nth receiving path 330-N may be used together.

[0025] Figure 4 This is a diagram illustrating a MIMO environment according to an embodiment.

[0026] Reference Figure 4 Base station 410 and user equipment 420 can communicate with each other using a MIMO method. For this purpose, base station 410 may include multiple antennas Ant1, and user equipment 420 may include multiple antennas Ant2. Although Figure 4 The illustration shows that base station 410 includes two antennas Ant1 and user equipment 420 includes two antennas Ant2, but the embodiments are not limited thereto. It should be understood that the description herein also applies to embodiments in which base station 410 and user equipment 420 may each include more than two antennas.

[0027] Base station 410 may include a first transceiver 411, a second transceiver 412, a first antenna Ant1_1, and a second antenna Ant1_2. Each of the first transceiver 411 and the second transceiver 412 may be connected to an antenna. For example, the first transceiver 411 may be connected to the first antenna Ant1_1, and the second transceiver 412 may be connected to the second antenna Ant1_2. When base station 410 operates as a transmitting device, each of the first transceiver 411 and the second transceiver 412 may operate as a transmitter, and when base station 410 operates as a receiving device, each of the first transceiver 411 and the second transceiver 412 may operate as a receiver.

[0028] In transmit mode, the first transceiver 411 can generate a first signal Sig by combining a first component carrier signal C1 and a second component carrier signal C2, and output the generated first signal Sig to the user equipment 420. The first transceiver 411 can extract not only the first component carrier C1 from the first signal Sig, but also the second component carrier C2. Each of the first transceiver 411 and the second transceiver 412 can combine and transmit multiple component carrier signals instead of transmitting only one component carrier signal, and can extract multiple component carrier signals from the first signal Sig instead of extracting only one component carrier signal. The user equipment 420 may include a third transceiver 421, a fourth transceiver 422, a third antenna Ant2_1, and a fourth antenna Ant2_2. Since the user equipment 420 may be substantially the same as or similar to the base station 410, its description is omitted for brevity.

[0029] Figure 5 This is a block diagram of the communication processor 500 according to an embodiment.

[0030] Reference Figure 5The communication processor 500 may include a covariance matrix generation circuit 501, a whitening filter matrix generation circuit 503, and a symbol detection circuit 505. The communication processor 500 may also be referred to as a modem. According to an embodiment, Figure 5 The communication processor 500 may include Figure 2 It is part of the communication circuit 203 and / or processor 201.

[0031] According to an embodiment, the received signal in a wireless environment with interference is as follows.

[0032] [Equation 1]

[0033] here, Indicates size is The received signal vector, Indicates size is The channel matrix, Indicates size is The transmitted signal vector, and Indicates size is The received interference and noise vectors. Assume that... There is strong interference when there are multiple antennas. It can be represented as follows.

[0034] [Equation 2]

[0035] here, Indicates size is The interference channel matrix, This indicates that the size of the unit variance is The interference signal vector, and Indicates zero mean and The variance of the additive white Gaussian noise (AWGN) vector. Because It includes not only noise, but also interference components, therefore However, due to interference, it may not possess the white noise characteristic of ordinary noise. In this case, the covariance matrix... It can be represented as follows.

[0036] [Equation 3]

[0037] The terminal does not know the covariance matrix. The value can be estimated for a resource element (RE) that is allocated a demodulation reference signal (DMRS) or a cell-specific reference signal (CRS) in a resource block (RB).

[0038] [Equation 4]

[0039] here, This represents the set of RE indices for RS within RB, and Indicates having a subcarrier index and symbol index The RE index. Additionally... This represents the estimated channel matrix. Since the receiving terminal also generates the RS sequence based on the RE positions assigned to the DMRS or CRS, and knows the accurate... Therefore, the estimated noise covariance matrix can be obtained. .

[0040] In this case, due to Let represent a Hermitian positive definite matrix, so the Cholesky decomposition can be applied as follows, and the result of the application can be expressed as follows.

[0041] [Equation 5]

[0042] here, This represents a lower triangular matrix with real diagonal elements. It can be seen that using... inverse matrix It can be used as a filter to whiten noise containing interference, as follows.

[0043] [Equation 6]

[0044] The covariance matrix generation circuit 501 measures the covariance between signals received through each antenna and outputs the measured covariance as a matrix. For example, when the number of receiving antennas is 4, the covariance matrix can be as follows.

[0045] [Equation 7]

[0046] here, Let represent the covariance matrix, and each row and column of the covariance matrix corresponds to a receiving antenna. For example, It can indicate the correlation (e.g., autocorrelation) between the first receiving antennas. It can indicate the correlation between the first receiving antenna and the second receiving antenna. It can indicate the correlation between the first receiving antenna and the third receiving antenna. It can indicate the correlation between the first and fourth receiving antennas. Additionally, It can indicate the correlation between the second receiving antenna and the first receiving antenna. It can indicate the correlation between the third receiving antenna and the first receiving antenna, and It can indicate the correlation between the fourth receiving antenna and the first receiving antenna. According to an embodiment, when the number of receiving antennas is 8, the size of the covariance matrix can be 8×8, and when the number of receiving antennas is 16, the size of the covariance matrix can be 16×16.

[0047] According to an embodiment, the whitening filter matrix generation circuit 503 can calculate a higher-level whitening filter matrix based on a lower-level whitening filter matrix. The lower-level whitening filter matrix can be a whitening filter matrix corresponding to N receiving antennas, and the higher-level whitening filter matrix can be a whitening filter matrix corresponding to 2N receiving antennas. For example, the lower-level whitening filter matrix can be a 2×2 matrix corresponding to two receiving antennas, and the higher-level whitening filter matrix can be a 4×4 matrix corresponding to four receiving antennas.

[0048] According to an embodiment, the whitening filter matrix generation circuit 503 can be based on a block identity inverse matrix. This block identity inverse matrix is ​​equivalent to replacing a 2N×2N matrix with four N×N submatrices. For example, if... yes In the 2N×2N matrix, then It can be expressed as .here, to Each of these can correspond to a matrix of size N×N. The whitening filter matrix is ​​based on the block identity inverse matrix. It is represented as follows.

[0049] [Equation 8]

[0050] here, to Each of these can correspond to a lower-level matrix. For example, if we assume... If it is a high-level whitening filter matrix, then to Each of these can be a matrix of the same size as the low-level whitening filter matrix. For example, if the high-level whitening filter is 4×4, then... to Each of them can be a 2×2 matrix.

[0051] Based on the Cholesky decomposition described above. It is a lower triangular matrix, therefore, it can be replaced by zero. Components. In this case, the high-level whitening filter matrix can be represented as follows.

[0052] [Equation 9]

[0053] According to an embodiment, when the size of the high-level whitening filter matrix is ​​4×4, it can be represented as follows.

[0054] [Equation 10]

[0055] According to the embodiment, based on Equation 5 above, since This represents the calculation of the N×N whitening filter matrix (which is related to the calculation in Equation 5). (The form is the same), the whitening filter matrix generation circuit 503 can be based on The N×N whitening filter matrix is ​​calculated to obtain Subsequently, the whitening filter matrix generation circuit 503 can also be based on the previously obtained... as well as Calculate as follows .

[0056] [Equation 11]

[0057] Subsequently, the whitening filter matrix generation circuit 503 can be based on the previously obtained... as well as Calculate as follows .

[0058] [Equation 12]

[0059] Specifically, this can be achieved by using the right side as... Substitute to calculate Because, based on Equation 5 and substitution, The calculation is for a whitening filter matrix of size N×N (which has the same properties as in Equation 5). (In the same form), the whitening filter matrix generation circuit 503 can obtain a high-level whitening filter matrix according to Equation 9. ,as follows.

[0060] [Equation 13]

[0061] According to an embodiment, the symbol detection circuit 505 can detect symbols based on a signal to which a whitening filter has been applied. For example, the whitening filter matrix generation circuit 503 can perform whitening on the received signal using a high-level whitening filter matrix obtained based on a low-level whitening filter matrix. Thereafter, the symbol detection circuit 505 can calculate the ML (Meaning of Matrix) of the whitened signal and detect symbols based on the ML calculation result.

[0062] In the above embodiments, it has been described that the whitening filter matrix generation circuit 503 is arranged inside the communication processor 500, but the embodiments are not limited thereto. According to various embodiments, the whitening filter matrix generation circuit 503 may be implemented as a separate block outside the communication processor 500.

[0063] Figure 6 This is a diagram illustrating an example of a whitening filter matrix generation circuit 600 according to various embodiments.

[0064] Reference Figure 6 , Figure 6 The whitening filter matrix generation circuit 600 can be corresponding to Figure 5 The whitening filter matrix generation circuit 500. In an embodiment, Figure 6 The whitening filter matrix generation circuit 600 can be adapted to cases involving 2N receiving antennas.

[0065] According to an embodiment, the whitening filter matrix generation circuit 600 can receive the covariance matrix. For example, the whitening filter matrix generation circuit 600 can be derived from the covariance matrix generation circuit (e.g., Figure 5 501) Received covariance matrix Covariance matrix This represents the covariance matrix for signals received by 2N receiving antennas. For example, the covariance matrix... It can be a matrix of size 2N×2N.

[0066] According to an embodiment, the whitening filter matrix generation circuit 600 can receive a low-level whitening filter matrix. The whitening filter matrix generation circuit 600 can be based on a low-level whitening filter matrix. Output the high-level whitening filter matrix according to the following equation. ,in, and Corresponding to a low-level whitening filter matrix .

[0067] [Equation 14]

[0068] Figure 7This is a block diagram of a communication processor 700 according to an embodiment.

[0069] Reference Figure 7 The communication processor 700 can be corresponding to Figure 5 The communication processor 500.

[0070] According to an embodiment, the whitening filter matrix generation circuit 720 may have a recursive structure. For example, the whitening filter matrix generation circuit 720 may receive a covariance matrix from the covariance matrix generation circuit 710. Subsequently, the whitening filter matrix generation circuit 720 can first calculate and feed back the low-level whitening filter matrix. For example, the whitening filter matrix generation circuit 720 can calculate and output the whitening filter matrix corresponding to the lower-level whitening filter matrix. and The whitening filter matrix generation circuit 720 is based on Equation 10. The calculation is used to generate the low-level whitening filter matrix. And the low-level whitening filter matrix The whitening filter matrix generation circuit 720 can be fed back based on the recursive structure. The whitening filter matrix generation circuit 720 can be based on Equation 11. To obtain the matrix through calculation And based on Equations 10 and 12 Cholesky decomposition to generate It can be based on a recursive structure. Feedback is sent to the whitening filter matrix generation circuit 720.

[0071] According to an embodiment, the whitening filter matrix generation circuit 720 can subsequently output a high-level whitening filter matrix. For example, the whitening filter matrix generation circuit 720 can generate the whitening filter matrix by first calculating... , and Substitute into Equation 14 to obtain the high-level whitening filter matrix.

[0072] As described above, since a whitening filter matrix 720 with a recursive structure is provided, a whitening filter matrix of size 2N×2N can be computed using only hardware capable of computed to an N×N whitening filter matrix, thereby improving computational and area complexity.

[0073] Figure 8A This is a block diagram of a communication processor 800 according to an embodiment.

[0074] Reference Figure 8A The communication processor 800 can be corresponding to Figure 5 The communication processor 500.

[0075] According to an embodiment, the communication processor 800 may include a covariance matrix generation circuit 810 and a plurality of whitening filter matrix generation circuits, the plurality of whitening filter matrix generation circuits including, for example, a first whitening filter matrix generation circuit 820, a second whitening filter matrix generation circuit 830, and a third whitening filter matrix generation circuit 840. The plurality of whitening filter matrix generation circuits 820, 830, and 840 may be connected in a daisy-chain cascaded manner.

[0076] The first whitening filter matrix generation circuit 820 can receive the covariance matrix from the covariance matrix generation circuit 810. The first whitening filter matrix generation circuit 820 can generate the whitening filter matrix based on the received covariance matrix. To calculate and output the whitening filter matrix In this case, the first whitening filter matrix generation circuit 820 can generate the calculated whitening filter matrix. The output is sent to the second whitening filter matrix generation circuit 830.

[0077] The second whitening filter matrix generation circuit 830 can receive the covariance matrix from the covariance matrix generation circuit 810. Additionally, the second whitening filter matrix generation circuit 830 can receive the whitening filter matrix from the first whitening filter matrix generation circuit 820. The second whitening filter matrix generation circuit 830 can be based on the received covariance matrix. and whitening filter matrix To calculate and output the whitening filter matrix For example, the second whitening filter matrix generation circuit 830 can utilize the data received from the first whitening filter matrix generation circuit 820. and And use Equation 11 to calculate and will Substitute into Equation 14 to obtain the whitening filter matrix. The second whitening filter matrix generation circuit 830 can generate the calculated whitening filter matrix. The output is sent to the third whitening filter matrix generation circuit 840.

[0078] The third whitening filter matrix generation circuit 840 can receive the covariance matrix from the covariance matrix generation circuit 810. Additionally, the third whitening filter matrix generation circuit 840 can receive the whitening filter matrix from the second whitening filter matrix generation circuit 830. The third whitening filter matrix generation circuit 840 can be based on the received covariance matrix. and whitening filter matrix To calculate and output the whitening filter matrix For example, the third whitening filter matrix generation circuit 840 can utilize the data received from the second whitening filter matrix generation circuit 830. and And use Equation 11 to calculate and will Substitute into Equation 14 to obtain the whitening filter matrix. .

[0079] As described above, since multiple whitening filter matrix generation circuits 820, 830 and 840 with daisy-chain structure are provided, the whitening filter matrix corresponding to many receiving antennas can be calculated by adding circuits that can compute N×N whitening filters one by one whenever the number of receiving antennas doubles, thus greatly improving computational and area complexity.

[0080] Figure 8B This is a diagram illustrating an example of a block unit covariance matrix according to an embodiment.

[0081] Reference Figure 8B It can convert a covariance matrix of size 4N×4N into a covariance matrix. It is divided into four unit sub-blocks ("sub-blocks" can also be called "sub-matrices"). The covariance matrix is ​​of size 4N×4N. It can be Figure 8A covariance matrix For example, a covariance matrix of size 4N×4N can be used. Grouped into the first sub-block Second sub-block Third sub-block and the fourth sub-block . sub-block to Each of them can be a matrix of size 2N×2N, and can be Figure 8A In .

[0082] The first sub-block of size 2N×2N Up to the fourth sub-block Each sub-block can be divided into four block units. For example, the first sub-block is 2N×2N. It can be grouped into block 1-1 Blocks 1-2 Blocks 1-3 and blocks 1-4 Second sub-block It can be grouped into block 2-1 Block 2-2 Blocks 2-3 and blocks 2-4 Third sub-block It can be grouped into block 3-1 Block 3-2 Block 3-3 and the 3rd and 4th pieces Fourth sub-block It can be grouped into block 4-1 Block 4-2 Block 4-3 and the 4th-4th block .piece To block Each of them can be an N×N matrix, and can be Figure 8A In .

[0083] According to the embodiment, when compared with a covariance matrix of size 4N×4N... The corresponding whitening filter matrix is When, the following equation can be satisfied.

[0084] [Equation 15]

[0085] Here, it can be seen that when referring to Equation 10... (It is the same as in Equation 5) When they have the same form, Represents a sub-block of size 2N×2N The corresponding whitening filter matrix In other words, refer to them together. Figure 8A When the whitening filter matrix generation circuit 840 obtains a 4N×4N covariance matrix ( Figure 8B In or Figure 8A In And obtain At that time, the whitening filter matrix generation circuit 840 can calculate the covariance matrix of 4N×4N. The corresponding whitening filter matrix ,in, It is with 2N×2N sub-blocks (or when the covariance matrix is ​​4N×4N) Figure 8B In Or Figure 8A In The whitening filter matrix corresponding to the top left sub-block when divided into four sub-blocks. For example, the whitening filter matrix generation circuit 840 can obtain... Substitute into equation 11 to calculate And by calculating Substitute into equation 12 to calculate for The whitening filter matrix is ​​then calculated. .

[0086] When compared with a covariance matrix of size 2N×2N The corresponding whitening filter matrix is When, the following equation can be satisfied.

[0087] [Equation 16]

[0088] Here, it can be seen that Represents N×N sub-blocks The corresponding whitening filter matrix In other words, refer to them together. Figure 8A When the whitening filter matrix generation circuit 830 obtains a 2N×2N covariance matrix ( Figure 8B In or Figure 8A In And obtain At that time, the whitening filter matrix generation circuit 830 can calculate the covariance matrix of 2N×2N. The corresponding whitening filter matrix ,in, It is with N×N blocks (Or when the covariance matrix is ​​2N×2N) Figure 8B In or Figure 8A In The whitening filter matrix corresponding to the top left block when the block is divided into four blocks. For example, the whitening filter matrix generation circuit 830 can obtain... Substitute into equation 11 to calculate And by calculating Substitute into equation 12 to calculate for The whitening filter matrix is ​​then calculated. Therefore, the whitening filter generation circuit 820 can receive an N×N covariance matrix. And output the corresponding whitening filter matrix. With Provided to the whitening filter generation circuit 830.

[0089] Figure 9 This is a flowchart illustrating an operation method of a communication processor according to an embodiment.

[0090] Reference Figure 9When operating the S910, the communication processor (e.g., Figure 5 The initial level of the whitening filter matrix can be determined using 500. For example, the initial level could be... .grade The whitening filter matrix can be In this case, it can be considered that... For example, the initial level can be determined such that the number of existing antennas is proportional to the size of the whitening filter matrix. N The values ​​are the same. For example, when there are two receiving antennas, =1.

[0091] When operating the S920, the communication processor 500 can generate levels. The covariance matrix. (Rank) The covariance matrix can be of size N×N According to an embodiment, the covariance matrix generation circuit (e.g., Figure 5 (501) can measure the received signal to generate a covariance matrix indicating the correlation between antennas. According to some embodiments, the communication processor 500 can generate a hierarchy during operation S920. covariance matrix And identify a covariance matrix of size N×N. Among them, the covariance matrix It is with having a hierarchy covariance matrix The covariance matrix of the corresponding sub-blocks in the matrix.

[0092] When operating the S930, the communication processor 500 can generate information with hierarchical levels. The whitening filter matrix. (Level) The whitening filter matrix can be of size N×N. Whitening filter matrix generation circuit (e.g., Figure 5 The 503 in the equation can be used to calculate the grade based on Cholesky decomposition and Equation 5. Whitening filter matrix .

[0093] When operating the S940, the communication processor 500 can generate levels. The covariance matrix. (Rank) The covariance matrix can be of size 2N×2N. In an embodiment, the covariance matrix generation circuit (e.g., Figure 5 (501) can measure the received signal to generate a covariance matrix indicating the correlation between antennas. According to some embodiments, when the grade is initially measured in operation S920... covariance matrix In this case, operation S940 can be omitted.

[0094] When operating the S950, the communication processor 500 can generate information with hierarchical levels. The whitening filter matrix. It has a hierarchy. The whitening filter matrix can be of size 2N×2N. The whitening filter matrix generation circuit 503 can generate the whitening filter matrix by combining the matrix calculated in operation S930. Whitening filter matrix Correspondingly Substitute into equation 11 to calculate And by calculating Substitute into equation 12 to calculate , and After that, the calculated , and Substitute into Equation 14 to obtain the whitening filter matrix .

[0095] Figure 10 This is a flowchart illustrating an operation method of a communication processor according to an embodiment.

[0096] Reference Figure 10 In operation of S1005, the communication processor (e.g., Figure 5 The 500 in the middle can generate the maximum order covariance matrix. The maximum level can be a level corresponding to the number of receiving antennas. For example, when there are 16 receiving antennas, the maximum level covariance matrix... The size can be 16×16. Covariance matrix generation circuit (e.g., Figure 5 The 501) can measure the received signal to generate a maximum-order covariance matrix indicating the correlation between antennas. .

[0097] In operating S1010, the communication processor (e.g., Figure 5 The value of 500 can determine whether the target level whitening filter matrix has been generated. For example, the target level can be 4 (N). target =16), and the current whitening filter matrix can be a level 2 whitening filter matrix. In this case, since the level of the current whitening filter matrix is ​​lower than the target level (S1010, yes), the communication processor 500 can perform operation S1020.

[0098] In operation S1020, the communication processor 500 can increase the level of the whitening filter matrix by 1. In operation S1030, because... , It can be 8. Subsequently, in operation S1040, the communication processor 500 can identify the covariance matrix of level 3. The size of the covariance matrix of level 3 can be 8×8. For example, refer to... Figure 8B Maximum-order covariance matrix It can be And the covariance matrix of level 3 can be .

[0099] In operation S1050, the communication processor 500 can generate a level 3 whitening filter matrix. The level 3 whitening filter matrix can be 8×8 in size. The whitening filter matrix generation circuit 503 can be based on the 8×8 covariance matrix identified in operation S1040. and the 4×4 whitening filter matrix generated in the previous iteration To generate a level 3 whitening filter matrix .

[0100] After operation S1050, the process can return to operation S1010, and it can be determined whether the target level has been reached. When the target level is reached (S1010, No), the communication processor 500 can terminate the process. According to an embodiment, when the target level is not reached (S1010, Yes), the communication processor 500 can repeat operation S1020 to operation S1050.

[0101] Figure 11 This is a block diagram of a wireless communication device according to an embodiment.

[0102] Reference Figure 11 The wireless communication device 1100 may include a modem 1105 and a radio frequency integrated circuit (RFIC) 1160, and the modem 1105 may include an application-specific integrated circuit (ASIC) 1110 and an application-specific instruction set processor (ASIP) 1130, a memory 1150, a main processor 1170 and a main memory 1190. Figure 11 The wireless communication device 1100 may be the receiving device 200 according to the embodiment.

[0103] The RFIC 1160 can be connected to an antenna Ant to receive or transmit signals to an external location using a wireless communication network. For example, the antenna Ant may include two or more antennas as described above, such as reference... Figure 4Example. ASIP 1130 is a custom integrated circuit for a specific purpose and can support and execute instructions included in the instruction set for a specific application. Memory 1150 can communicate with ASIP 1130 and can store multiple instructions executed by ASIP 1130 as a non-transitory storage device. For example, as a non-limiting example, memory 1150 may include any type of memory that can be accessed by ASIP 1130, such as random access memory (RAM), read-only memory (ROM), magnetic tape, magnetic disk, optical disk, volatile memory, non-volatile memory, and combinations thereof.

[0104] The main processor 1170 can control the wireless communication device 1100 by executing multiple instructions. For example, the main processor 1170 can control the ASIC 1110 and ASIP 1130 to process data received through the wireless communication network or to process user input to the wireless communication device 1100.

[0105] Main memory 1190 can communicate with main processor 1170 and can store multiple instructions executed by main processor 1170 as a non-transitory storage device. For example, as a non-limiting example, main memory 1190 may include any type of memory accessible by main processor 1170, such as RAM, ROM, magnetic tape, magnetic disk, optical disk, volatile memory, non-volatile memory, and combinations thereof.

[0106] For example, in use, the wireless communication device 1100 can receive communication signals through the antenna Ant, and calculate, as described above, a whitening filter matrix for reducing interference through the individual antennas in the antenna Ant, and apply the whitening filter matrix to the received signal to remove interference from the received signal or reduce interference in the received signal, thereby resulting in clearer voice signal data throughput, and / or increased voice and data throughput, etc.

[0107] While various embodiments have been specifically shown and described with reference to the accompanying drawings, it should be understood that various changes in form and detail may be made therein without departing from the spirit and scope of the claims.

Claims

1. An electronic device comprising: The communication circuit includes 2N receiving antennas; as well as The communication processor includes: A covariance matrix generation circuit generates a covariance matrix for the 2N receiving antennas based on measurements of the received signal. The whitening filter matrix generation circuit calculates the whitening filter matrix for N receiving antennas based on the Chollisky decomposition. in: The covariance matrix includes a first sub-matrix, a second sub-matrix, a third sub-matrix, and a fourth sub-matrix, and The whitening filter matrix generation circuit calculates the first whitening filter matrix for the first submatrix based on the Choleski decomposition of the first submatrix, and calculates the whitening filter matrix for the 2N receiving antennas based on the first whitening filter matrix, wherein the first submatrix corresponds to the diagonal submatrix of the covariance matrix.

2. The electronic device as claimed in claim 1, wherein, The lower triangular matrix satisfying the Cholleski decomposition of the covariance matrix satisfies the following equation: in, Let the covariance matrix be represented. Represents the lower triangular matrix, This represents the first whitening filter matrix. This represents the second whitening filter matrix. This represents the third whitening filter matrix. Denotes the first submatrix. Describes the second submatrix. Describe the third submatrix, and This represents the fourth submatrix.

3. The electronic device as claimed in claim 2, wherein, First whitening filter matrix It satisfies the following equation for the first submatrix The matrix of the Choreski decomposition: .

4. The electronic device as claimed in claim 3, wherein, Second whitening filter matrix The following equations must be satisfied: .

5. The electronic device as claimed in claim 4, wherein, Third whitening filter matrix The following equations satisfy the permutation matrix Choreski's decomposition: in, Let the permutation matrix satisfy the following condition: .

6. The electronic device as claimed in claim 5, wherein, The whitening filter matrix generation circuit calculates the whitening filter matrix for the 2N receiving antennas according to the following equation. : 。 7. The electronic device as claimed in claim 6, wherein, The communication processor further includes a symbol detection circuit, wherein the symbol detection circuit is based on the whitening filter matrix for the 2N receiving antennas. The whitened signal is used to detect the symbol.

8. A method of operating an electronic device comprising 2N receiving antennas, the method comprising: A covariance matrix for the 2N receiving antennas is generated based on the measurement of the received signal, wherein the covariance matrix includes a first submatrix, a second submatrix, a third submatrix, and a fourth submatrix, wherein the first submatrix corresponds to the diagonal submatrix of the covariance matrix; Calculate the first whitening filter matrix for the first submatrix; The second whitening filter matrix is ​​calculated based on the third submatrix of the covariance matrix and the first whitening filter matrix; and Calculate the third whitening filter matrix, wherein the third whitening filter matrix satisfies the Cholliski decomposition of the permutation matrix, wherein the permutation matrix is ​​based on the fourth submatrix of the covariance matrix and the second whitening filter matrix; and The whitening filter matrix for the 2N receiving antennas is calculated based on the first whitening filter matrix, the second whitening filter matrix, and the third whitening filter matrix.

9. The operating method as described in claim 8, wherein, The lower triangular matrix satisfying the Cholleski decomposition of the covariance matrix satisfies the following equation: in, Let the covariance matrix be represented. Represents the lower triangular matrix, This represents the first whitening filter matrix. This represents the second whitening filter matrix. This represents the third whitening filter matrix. Denotes the first submatrix. Describes the second submatrix. Describe the third submatrix, and This represents the fourth submatrix.

10. The operating method as described in claim 9, wherein, First whitening filter matrix It satisfies the following equation for the first submatrix The matrix of the Choreski decomposition: .

11. The operating method as described in claim 10, wherein, Second whitening filter matrix The following equations must be satisfied: .

12. The operating method as described in claim 11, wherein, Third whitening filter matrix The following equation applies to the permutation matrix. Choreski's decomposition: in, Let the permutation matrix satisfy the following condition: .

13. The operating method as described in claim 12, further comprising: The whitening filter matrix for the 2N receiving antennas is calculated according to the following equation: 。 14. A communication processor connected to 2N receiving antennas, the communication processor comprising: A covariance matrix generation circuit generates a covariance matrix for the 2N receiving antennas based on measurements of the received signal. as well as The whitening filter matrix generation circuit calculates the whitening filter matrix for N receiving antennas based on the Chollisky decomposition. in: The covariance matrix includes a first submatrix, a second submatrix, a third submatrix, and a fourth submatrix, wherein the first submatrix corresponds to the diagonal submatrix of the covariance matrix, and The whitening filter matrix generation circuit calculates the first whitening filter matrix for the first submatrix based on the Choleski decomposition for the first submatrix, and calculates the whitening filter matrix for the 2N receiving antennas based on the first whitening filter matrix.

15. The communication processor as claimed in claim 14, wherein, The lower triangular matrix satisfying the Cholleski decomposition of the covariance matrix satisfies the following equation: in, Let the covariance matrix be represented. Represents the lower triangular matrix, This represents the first whitening filter matrix. This represents the second whitening filter matrix. This represents the third whitening filter matrix. Denotes the first submatrix. Describes the second submatrix. Describe the third submatrix, and This represents the fourth submatrix.

16. The communication processor as claimed in claim 15, wherein, The first whitening filter matrix corresponds to a lower triangular matrix that satisfies the Choleski decomposition of the first submatrix.

17. The communication processor of claim 16, wherein, The second whitening filter matrix corresponds to the matrix obtained by multiplying the third submatrix by the conjugate transpose of the inverse matrix of the first whitening filter matrix.

18. The communication processor of claim 17, wherein: The third whitening filter matrix corresponds to a lower triangular matrix that satisfies the Cholliski decomposition of the permutation matrix, and The permutation matrix corresponds to the matrix obtained by subtracting the matrix based on the second whitening filter matrix from the fourth submatrix, wherein the matrix based on the second whitening filter matrix is ​​obtained by multiplying the second whitening filter matrix by the conjugate transpose of the second whitening filter matrix.

19. The communication processor as claimed in claim 18, wherein, The whitening filter matrix for the 2N receiving antennas corresponds to the inverse of a lower triangular matrix including a first whitening filter matrix, a second whitening filter matrix, and a third whitening filter matrix.

20. The communication processor of claim 19, further comprising: A symbol detection circuit that detects symbols based on signals whitened according to the whitening filter matrix for the 2N receiving antennas.

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