CN114629754A - Interference noise equalization method, system and storage medium - Google Patents
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Abstract
The invention discloses an interference noise equalization method, a system and a storage medium, which are used for solving the problem of co-channel interference between adjacent cells, and the method comprises the following steps: the following operations are performed for each interference suppression area in the form of a resource block: calculating an interference noise correlation matrix corresponding to the interference suppression area; determining a multi-channel equalization merging coefficient matrix based on the interference noise correlation matrix; estimating a sending signal according to the multi-channel equalization merging coefficient matrix and a frequency domain signal corresponding to the interference suppression area in the received signal; wherein the interference noise correlation matrix is composed of a weighted sum of a first interference covariance matrix calculated using the MRC method and a second interference covariance matrix calculated using the IRC method. Therefore, the weight value of the equalization combination can be adaptively adjusted according to real-time multi-channel interference and noise measurement values, the receiving performance of the multi-channel receiver in each signal-to-interference-and-noise ratio interval can be improved, and the system throughput and the system capacity are improved to a greater extent.
Description
Technical Field
The present invention relates to the field of communications technologies, and in particular, to a method, a system, and a storage medium for interference noise equalization.
Background
As shown in fig. 1, the co-channel interference between adjacent cells is one of the important reasons for the degradation of communication quality, because the interference source is a data signal transmitted by the user of the adjacent cell on the same co-channel resource, the receiving end must estimate the channel coefficient, the interference channel coefficient, or the interference characteristic of the expected data more accurately to perform data detection more accurately.
In order to solve the problem of co-channel interference between adjacent cells, LTE and NR systems mainly employ interference coordination techniques to avoid interference in the scheduling aspect or employ interference cancellation techniques to suppress interference in the physical layer of the base station receiving end. The Interference cancellation techniques used by the physical layer commonly include two Combining and equalizing algorithms, MRC (Maximum Ratio Combining) and IRC (Interference Rejection Combining) based on MMSE (Minimum Mean Square Error) criterion.
If the receiver combines the multi-path signals and the interference and noise of each receiving channel are independent and uncorrelated, the MRC can maximize the signal-to-noise ratio of the combined output; if there is correlation between interference and noise of each receiving channel, MRC is not optimal, and IRC using correlation between different receiving channels can obtain better interference and noise suppression effect.
Because the interference and noise of each channel of the receiver are constantly changed in time domain and frequency domain, the optimal performance working intervals of MRC algorithm and IRC algorithm have intersection, and at present, there is no merging and balancing scheme which can synthesize the optimal performance of the MRC algorithm and the IRC algorithm. How to adaptively use different interference suppression algorithms in a same-frequency interference environment has no optimal solution.
Disclosure of Invention
The invention aims to provide an interference noise equalization method, an interference noise equalization system and a storage medium, so as to solve the problem of co-channel interference between adjacent cells.
To achieve the above object, the present invention provides an interference noise equalization method for a receiving end of an Orthogonal Frequency Division Multiplexing (OFDM) or Orthogonal Frequency Division Multiple Access (OFDMA) communication system, the method comprising: the following operations are performed for each interference suppression area in the form of a resource block: calculating an interference noise correlation matrix corresponding to the interference suppression area; determining a multi-channel equalization merging coefficient matrix based on the interference noise correlation matrix; estimating a sending signal according to the multi-channel equalization merging coefficient matrix and a frequency domain signal corresponding to the interference suppression area in the received signal; wherein the interference noise correlation matrix is composed of a weighted sum of a first interference covariance matrix calculated using the MRC method and a second interference covariance matrix calculated using the IRC method.
The present invention also provides an interference noise equalization system for a receiving end of an Orthogonal Frequency Division Multiplexing (OFDM) or Orthogonal Frequency Division Multiple Access (OFDMA) communication system, the system comprising: the device comprises a first device and a second device, wherein the first device is used for calculating an interference noise correlation matrix corresponding to an interference suppression area in each resource block form aiming at the interference suppression area; second means for determining a multi-channel equalization combining coefficient matrix based on the interference noise correlation matrix; a third device, configured to estimate a transmission signal according to the multi-channel equalization combining coefficient matrix and a frequency domain signal corresponding to the interference suppression area in the received signal; wherein the interference noise correlation matrix is composed of a weighted sum of a first interference covariance matrix calculated using the MRC method and a second interference covariance matrix calculated using the IRC method.
In another aspect, the present invention further provides a computer-readable storage medium, in which a computer program is stored, and the computer program, when executed by a processor, implements any of the interference noise equalization methods described above.
The interference noise equalization method, the system and the storage medium provided by the invention aim to adaptively adjust the coefficients of the combining equalization in different interference suppression areas according to the real-time interference noise intensity and the interference noise covariance matrix, so that the multichannel receiver can obtain the optimal combining equalization performance in each signal-to-interference-and-noise ratio interval of each interference suppression area, and the system throughput and the system capacity are improved to a greater extent.
Drawings
The technical solution and other advantages of the present invention will become apparent from the following detailed description of specific embodiments of the present invention, which is to be read in connection with the accompanying drawings.
Fig. 1 shows a schematic diagram of a neighboring multi-cell in the prior art.
Fig. 2 is a flowchart illustrating an interference noise estimation method according to an embodiment of the present invention.
Fig. 3 shows a flow chart of a method — a combining and equalizing algorithm for each interference suppression zone.
Fig. 4 shows a flowchart of an algorithm for calculating an equivalent post-equalization SINR value for each interference suppression zone in the second method.
Fig. 5 shows a flowchart of an algorithm for calculating the equalized equivalent SINR value for each interference suppression zone according to method three.
Detailed Description
The technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. 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.
The terms "first," "second," "third," and the like in the description and in the claims, as well as in the drawings, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the objects so described are interchangeable under appropriate circumstances. In the description of the present invention, "a plurality" means two or more unless specifically defined otherwise. Furthermore, the terms "comprising" and "having," as well as any variations thereof, are intended to cover a non-exclusive inclusion. Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in the form of software, or in one or more hardware circuits or integrated circuits, or in different networks and/or processor means and/or micro-indicator means.
In the description of the present invention, it should be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; may be mechanically connected, may be electrically connected or may be in communication with each other; either directly or indirectly through intervening media, either internally or in any other relationship. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
The present invention will be described in further detail with reference to the accompanying drawings and detailed description, in order to make the objects, features and advantages thereof more comprehensible.
The sending end in the embodiment of the present invention may be a control device such as a base station and a relay station, and may also be a terminal device of an uplink in a wireless communication system, such as a mobile phone and a notebook computer. Similarly, the receiving end is used for receiving the data signal of the transmitting end, and the receiving end may be a terminal device in an uplink in the wireless communication system, such as a mobile phone, a notebook computer, and the like, or may be a control device in a downlink in the wireless communication system, such as a base station, a relay station, and the like.
The conventional combining and equalizing strategy of the multi-channel receiver in the common technology is to fixedly select a combining and equalizing algorithm from MRC and IRC. Based on the above, the related art proposes to calculate the optimal combining and equalizing algorithm at the current time by using certain received signal characteristics, and to select one of MRC and IRC. The problems of the above scheme are:
1. the accuracy of calculating which merging and equalizing algorithm is used by using the received signal characteristics is influenced by various factors, and various algorithm schemes cannot be unified;
2. interference noise varies rapidly in time and frequency, and using a single IRC or MRC cannot match the channel real-time conditions, requiring optimization of the interference and noise covariance matrices.
Therefore, in order to solve the above technical problem, an embodiment of the present invention provides a new interference noise equalization method, which aims to adaptively adjust combining and equalizing coefficients in different interference suppression areas according to a real-time interference noise strength and an interference noise covariance matrix, so that a multi-channel receiver can obtain an optimal combining and equalizing performance in each sir interval of each interference suppression area, and improve system throughput and system capacity to a greater extent.
The embodiment of the invention can be applied to the merging balance of a multi-channel receiver of wireless communication, can be used on indoor small stations, outdoor macro stations/micro stations/pico stations, UE terminals and other equipment, can be integrated in radio base stations or terminal equipment such as DU, RU, BBU and the like, can improve the merging receiving signal-to-noise ratio of the multi-channel receiver, and achieves the purposes of inhibiting interference and improving the system capacity.
The receiving end divides a received data bearing area into one or more interference suppression areas, each interference suppression area is a time-frequency two-dimensional resource block in a frame/half-frame structure, namely each interference suppression area comprises a plurality of continuous OFDM/OFDMA symbols in time and a plurality of continuous subcarriers in frequency domain. The received data carrying area may include one time-frequency two-dimensional resource block, or may include a plurality of separate time-frequency two-dimensional resource blocks, and in the embodiment of the present invention, each independent time-frequency two-dimensional resource block is used as an interference suppression area. Of course, in other embodiments, each relatively independent time-frequency two-dimensional resource block in the received data carrying region may also be further divided into a plurality of interference suppression regions.
In an OFDM/OFDMA communication system, the above-mentioned interference suppression region may carry one or more data streams, where each data stream corresponds to one or more data subcarriers and pilot subcarriers, and the pilot subcarriers corresponding to different data streams are different.
As shown in fig. 2, the following operations are performed for each interference suppression area in the form of a resource block:
step S10, calculating an interference noise correlation matrix corresponding to the interference suppression area;
step S20, determining a multichannel equalization combination coefficient matrix based on the interference noise correlation matrix;
step S30, estimating a sending signal according to the multi-channel equalization merging coefficient matrix and a frequency domain signal corresponding to the interference suppression area in the received signal; wherein the interference noise correlation matrix is composed of a weighted sum of a first interference covariance matrix calculated using the MRC method and a second interference covariance matrix calculated using the IRC method.
It should be noted that, in the embodiment of the present invention, "Resource block form" refers to a time-frequency two-dimensional Resource block, which is one or more symbols in the time domain and one or more REs (Resource elements) in the frequency domain. The embodiment of the invention does not limit the way of dividing the resource blocks. The scheduling resource can be divided into a plurality of time-frequency two-dimensional resource blocks in a certain mode, and the length of each resource block in the time domain and the frequency domain can be different.
Specifically, the interference noise correlation matrix is represented by:
wherein, the first and the second end of the pipe are connected with each other,
representing the interference noise correlation matrix in a time domain,
representing a first interference covariance matrix calculated using the MRC method,
representing a second interference covariance matrix calculated using the IRC approach,
and
weights representing the first interference covariance matrix and the second interference covariance matrix, respectively.
By adopting the technical scheme of the embodiment of the invention, the covariance matrixes of the IRC and the MRC can be jointly utilized, and various hard handover algorithms are unified; and the covariance matrix of interference and noise is optimized, so that the real-time condition of the channel is better matched, and the detection performance of a receiver system is favorably improved.
Further, in the OFDM/OFDMA communication system, the step of estimating the transmission signal according to the multi-channel equalization combining coefficient matrix and the frequency domain signal corresponding to the interference suppression area in the received signal includes:
constructing a channel model of a receiver system for multi-channel transmission, said channel model being represented by the following formula:
wherein, the first and the second end of the pipe are connected with each other,
the dimension of the estimated value representing the product of the frequency domain channel response experienced by the transmitted signal and the precoding matrix is the number of receiving channels multiplied by the number of transmitting channels;
representing a precoding matrix, wherein the dimensionality is the number of sending channels multiplied by the number of layers;
representing a transmission signal, and the dimensionality is the layer number multiplied by 1;
representing the sum of interference and noise superimposed on the received signal, with dimensions of the number of received channels x 1,
the received frequency domain signal is represented, and the dimension is the number of receiving channels multiplied by 1.
Since the frequency domain response and the precoding matrix are not distinguished in the actual channel estimation, the channel model can be further simplified as follows:
wherein, the first and the second end of the pipe are connected with each other,
the dimension of the estimated value representing the product of the frequency domain channel response experienced by the transmitted signal and the precoding matrix is the number of receiving channels multiplied by the number of layers;
representing a transmission signal, and the dimensionality is the layer number multiplied by 1;
representing the sum of interference and noise superimposed on the received signal, with dimensions of the number of received channels x 1,
representing the received frequency domain signal, and the dimension is the number of receiving channels multiplied by 1.
The step of determining a multi-channel equalization combining coefficient matrix based on the interference noise correlation matrix comprises the following steps:
and calculating the multichannel equalization merging coefficient matrix by adopting an MMSE (minimum mean square error) criterion and adopting the following formula:
wherein, among others,
is a matrix of units, and is,
an estimate representing the product of the frequency domain channel response experienced by the transmitted signal and the precoding matrix,
an inverse matrix representing the interference noise correlation matrix,
and representing the multi-channel equalization merging coefficient matrix.
The first interference covariance matrix is represented by:
wherein dimension is
Which indicates the number of the reception channels,
to represent
Book of changes
The columns of the image data are arranged in rows,
indicating the estimated noise interference strength of the ith receiving channel,
。
the second interference covariance matrix is represented by:
wherein dimension is
Which indicates the number of the reception channels,
to represent
Book of changes
The columns of the image data are,
representing the correlation of the interference noise between the receive channel i and the receive channel j,
，
indicating the estimated noise interference strength of the ith receiving channel,
。
generally, to estimate a transmission signal at a receiving end, equalization combining of multi-channel reception signals is required. The step of estimating the transmission signal according to the multi-channel equalization combining coefficient matrix and the frequency domain signal corresponding to the interference suppression area in the received signal comprises the following steps:
the transmitted signal is estimated using:
wherein the content of the first and second substances,
representing the estimated transmitted signal, the dimension is the number of layers x 1,
representing the frequency domain signal corresponding to the interference suppression zone in the received signal,
and representing the multi-channel equalization merging coefficient matrix.
The following exemplarily introduces three weights for determining the first interference covariance matrix and the second interference covariance matrix
And
and a corresponding embodiment.
The first method,
In this embodiment, the processed interference suppression area is a resource block with time-frequency two-dimensional granularity (a time-frequency resource granularity block at least includes one data subcarrier in a frequency domain and at least one symbol length in a time domain). The flow of the combining and equalizing algorithm in each interference suppression area is shown in fig. 3, and the following algorithm steps are respectively performed in each interference suppression area:
s11, measuring the environmental background noise to obtain the background noise intensity corresponding to the interference suppression area
；
S12, estimating the noise interference strength among a plurality of receiving channels, wherein,
indicating the estimated noise interference strength of the ith receiving channel,
(ii) a The technical solution of the present patent does not limit the estimation method of the noise interference strength, including but not limited to the methods of performing noise interference estimation by receiving signals at known pilot positions and performing noise interference estimation by idle subcarriers.
S13, calculating the average noise intensity estimated among the multiple receiving channels according to the following formula:
wherein the content of the first and second substances,
in order to receive the number of channels,
the average noise strength estimated between the multiple receive channels.
S14, calculating the ratio of the estimated average noise intensity to the background noise intensity:
s15, respectively calculating weights corresponding to the first interference covariance matrix and the second interference covariance matrix according to the following formula:
finally, S16, according to the weight corresponding to the first interference covariance matrix
Weights corresponding to the second interference covariance matrix
Calculating an interference noise correlation matrix in the interference suppression area, wherein the dimensionality is the receiving channel number multiplied by the receiving channel number:
repeating the steps S11-S15 for all the interference suppression areas can obtain the interference noise correlation matrix in all the interference suppression areas.
The first embodiment is as follows:
for example, the PUSCH uplink configuration will be described with NR system bandwidth =100M, subcarrier spacing =30kHz, terminal 2T, base station side 2R, number of layers =1, and port {0 }.
In this embodiment, the processing granularity of the equalization is an interference suppression area, and if slot-level interference suppression is performed on the full bandwidth, the interference suppression area is a time-frequency two-dimensional resource block that occupies 3276 subcarriers in the frequency domain and occupies 14 OFDM symbols in the time domain.
For each subcarrier of each OFDM symbol, the following algorithm steps are performed in the interference suppression zone, respectively:
s11, measuring the environmental background noise;
configuring idle time to measure background noise intensity in interference suppression area without signal transmission in actual environment and recording the background noise intensity
(linear value), the base station side can measure the background noise through the DMRS of the PUSCH or other reference signals.
S12, receiving channel interference and noise intensity estimation;
since the base station side 2R is, the number of reception channels = 2. The noise interference strength (linearity value) of 2 receiving channels is
And
. If the received signal at the pilot location is used for noise interference estimation, the noise interference estimation can be simplified as:
wherein the content of the first and second substances,
the dimension is the number of receiving channels × 1=2 × 1;
a received signal indicating a pilot position, the dimension being the number of reception channels × 1=2 × 1;
an estimated value representing the product of the precoding matrixes of the corresponding domains of the frequency domain channels of the transmission signal manager, wherein the dimensionality is the receiving channel number multiplied by the layer number =2 multiplied by 1;
the dimension representing the pilot data to be transmitted is the number of layers × 1=1 × 1.
S13, calculating the average noise intensity estimated among a plurality of receiving channels;
for example, in this embodiment, the average noise interference strength estimated between 2 receiving channels is calculated as:
s14, calculating the ratio of the estimated average noise intensity to the background noise intensity:
assumed to be estimated
，
Then, then
。
S15, calculating a weight;
bringing the following into
Calculating combining weights of a first interference covariance Matrix (MRC) and a second interference covariance matrix (IRC):
finally, S16, the weight value is calculated
And
substituting the following formula into an interference noise correlation matrix in an interference suppression area, and calculating the dimension receiving channel number multiplied by the receiving channel number:
repeating the above steps S11-S15 for each subcarrier (3276) and each symbol (14) within the interference rejection zone may result in an interference noise correlation matrix within the entire interference rejection zone.
The second method,
In this embodiment, the processed interference suppression area is a resource block with time-frequency two-dimensional granularity (a time-frequency resource granularity block at least includes one data subcarrier in a frequency domain and at least one symbol length in a time domain). The flow of the algorithm for calculating the equalized equivalent SINR for each interference suppression area by MRC and IRC under the MMSE criterion is shown in fig. 4, and the following algorithm steps are respectively performed in each interference suppression area:
s21, calculating the first interference covariance matrix
And the second interference covariance matrix
；
Wherein dimension is
Which indicates the number of the reception channels,
to represent
Book of changes
The columns of the image data are,
indicating the estimated noise interference strength of the ith receiving channel,
。
wherein, the first and the second end of the pipe are connected with each other,dimension (D)
Which indicates the number of the reception channels,
to represent
Book of changes
The columns of the image data are,
representing the correlation of the interference noise between the receive channel i and the receive channel j,
，
indicating the estimated noise interference strength of the ith receiving channel,
。
s22, respectively calculating the equalization weights corresponding to the first interference covariance matrix and the second interference covariance matrix according to the following formula:
wherein the content of the first and second substances,
an inverse matrix representing the first interference covariance matrix,
an inverse matrix representing the second interference covariance matrix,
representing the equalization weights corresponding to the first interference covariance matrix,
representing the equalization weight corresponding to the second interference covariance matrix,
an estimate representing the product of the frequency domain channel response experienced by the transmitted signal and the precoding matrix,
representing an identity matrix;
estimating the interference covariance matrix of MRC and IRC and the product of the frequency domain channel response experienced by the transmitted signal and the precoding matrix
The following formula is substituted to calculate the equalization weights.
S23, respectively calculating the equalized normalized signal amplitude values corresponding to the MRC mode and the IRC mode according to the following formulas:
wherein, the first and the second end of the pipe are connected with each other,
represents the normalized signal amplitude value after equalization corresponding to the MRC mode,
represents the equalized normalized signal amplitude value corresponding to the IRC mode,
representing the equalization weights corresponding to the first interference covariance matrix,
representing the equalization weight corresponding to the second interference covariance matrix,
an estimate representing the product of the frequency domain channel response experienced by the transmitted signal and the precoding matrix.
S24, respectively calculating the equalized normalized interference noise power values corresponding to the MRC mode and the IRC mode according to the following formula:
wherein the content of the first and second substances,
representing the equalized normalized signal amplitude value corresponding to the MRC mode,
represents the normalized signal amplitude value after equalization corresponding to the IRC mode,
indicating the equalized normalized interference noise power value corresponding to the MRC mode,
and expressing the equalized normalized interference noise power value corresponding to the IRC mode.
S25, respectively calculating the equivalent after equalization corresponding to MRC mode and IRC mode according to the following formula
The value:
wherein the content of the first and second substances,
represents the equivalent after equalization corresponding to MRC mode
The value of the one or more of the one,
indicating the equalized equivalence corresponding to the IRC mode
The value of the one or more of the one,
representing the equalized normalized signal amplitude value corresponding to the MRC mode,
represents the equalized normalized signal amplitude value corresponding to the IRC mode,
indicating the normalized interference noise power value after equalization corresponding to the MRC mode,
indicating equalized normalized interference noise power corresponding to IRC modeThe value is obtained.
S26, respectively calculating the corresponding weights of the first interference covariance matrix and the second interference covariance matrix according to the following formula:
finally, S27, according to the weight corresponding to the first interference covariance matrix
Weights corresponding to the second interference covariance matrix
Calculating an interference noise correlation matrix in the interference suppression area, wherein the dimensionality is the receiving channel number multiplied by the receiving channel number:
repeating the steps S21-S25 for all the interference suppression areas can obtain the interference noise correlation matrix in all the interference suppression areas.
Example two:
illustratively, the PUSCH uplink configuration will be described with NR system bandwidth =100M, subcarrier spacing =30kHz, terminal 2T, base station side 2R, layer number =2, and port {0,2 }.
In this embodiment, the processing granularity of the equalization is an interference suppression area, and if slot-level interference suppression is performed on RBs 0-RB 49, the interference suppression area is a time-frequency two-dimensional resource block that occupies 600 subcarriers in the frequency domain and 14 OFDM symbols in the time domain.
For each subcarrier of each OFDM symbol, the following algorithm steps are performed in the interference suppression zone, respectively:
s21, calculating the first interference covariance matrix
And the second interference covariance matrix
；
Wherein dimension is
Which indicates the number of the reception channels,
to represent
Book of changes
The columns of the image data are,
indicating the estimated noise interference strength of the ith receiving channel,
。
wherein dimension is
Which indicates the number of the reception channels,
to represent
Book of changes
The columns of the image data are,
representing the correlation of the interference noise between the receive channel i and the receive channel j,
，
indicating the estimated noise interference strength of the ith receiving channel,
。
s22, respectively calculating the equalization weights corresponding to the first interference covariance matrix and the second interference covariance matrix according to the following formula:
wherein the content of the first and second substances,
an inverse matrix representing the first interference covariance matrix,
an inverse matrix representing the second interference covariance matrix,
representing the equalization weights corresponding to the first interference covariance matrix,
representing the balance weight corresponding to the second interference covariance matrix，
An estimate representing the product of the frequency domain channel response experienced by the transmitted signal and the precoding matrix,
representing an identity matrix;
wherein, the weight value is balanced
The number of layers × the number of receiving antennas =2 × 2.
S23, calculating normalized signal amplitude values after equalization of MRC and IRC respectively
；
Wherein the content of the first and second substances,
representing the equalized normalized signal amplitude value corresponding to the MRC mode,
represents the equalized normalized signal amplitude value corresponding to the IRC mode,
representing the equalization weights corresponding to the first interference covariance matrix,
representing the equalization weights corresponding to the second interference covariance matrix,
an estimated value representing a product of a frequency domain channel response experienced by a transmitted signal and a precoding matrix;
wherein the content of the first and second substances,
has dimensions of number of layers x number of layers =2 x 2, and
taking only diagonal elements as a result of each layer, i.e.
The dimensions of (a) are layer number × 1=2 × 1:
s24, respectively calculating the equalized normalized interference noise power values corresponding to the MRC mode and the IRC mode
：
Wherein the content of the first and second substances,
representing the equalized normalized signal amplitude value corresponding to the MRC mode,
represents the equalized normalized signal amplitude value corresponding to the IRC mode,
indicating the equalized normalized interference noise power value corresponding to the MRC mode,
expressing the equalized normalized interference noise power value corresponding to the IRC mode;
wherein the content of the first and second substances,
the dimension of (d) is the number of layers × 1=2 × 1.
S25 equality after equalization
Calculating a value;
calculating equalized equivalence of MRC and IRC respectively
The value:
wherein the content of the first and second substances,
represents the equivalent after equalization corresponding to MRC mode
The value of the one or more of the one,
indicating the equalized equivalence corresponding to the IRC mode
The value of the one or more of the one,
representing the equalized normalized signal amplitude value corresponding to the MRC mode,
represents the equalized normalized signal amplitude value corresponding to the IRC mode,
indicating the normalized interference noise power value after equalization corresponding to the MRC mode,
expressing the normalized interference noise power value after equalization corresponding to the IRC mode;
wherein the content of the first and second substances,
the dimension of (d) is the number of layers × 1=2 × 1.
For multiple layers
Requiring synthesis at the codeword level
Take linear average as an example:
s26, calculating combining weight
Respectively calculating weights corresponding to the first interference covariance matrix and the second interference covariance matrix according to the following formula:
finally, S27, according to the weight corresponding to the first interference covariance matrix
Weights corresponding to the second interference covariance matrix
Calculating an interference noise correlation matrix in the interference suppression area, wherein the dimensionality is the receiving channel number multiplied by the receiving channel number:
repeating the above steps S21-S25 for each subcarrier (600) and each symbol (14) within the interference suppression zone can obtain interference noise correlation matrices within all the interference suppression zones.
The third method,
In this embodiment, the processed interference suppression area is a resource block with time-frequency two-dimensional granularity (a time-frequency resource granularity block at least includes one data subcarrier in a frequency domain and at least one symbol length in a time domain).
According to a preset step length
Sequentially assigning weights
Go through from 0 to 1 (
) And for each traversal
Respectively calculating the equalized equivalence under the MMSE criterion
A value; for all of
Determining the maximum equivalence after equalization
The weight value corresponding to the value
Then will the
As weights for the first interference covariance matrix. The flow of the algorithm for calculating the equalized equivalent SINR for each interference suppression zone is shown in fig. 5.
Wherein for each traversal
The following operations are performed:
s31, calculating an interference noise correlation matrix according to the following formula:
s32, calculating the balanced combining weight according to the following formula:
wherein the content of the first and second substances,
an inverse matrix representing the interference noise correlation matrix,
an estimate representing the product of the frequency domain channel response experienced by the transmitted signal and the precoding matrix,
representing an identity matrix.
S33, calculating the equalized normalized signal amplitude value according to the following formula:
wherein the content of the first and second substances,
represents the normalized signal amplitude value after equalization,
the weight of the balanced combining is shown,
an estimate representing the product of the frequency domain channel response experienced by the transmitted signal and the precoding matrix.
S34, calculating the normalized interference noise power value after equalization according to the following formula:
wherein the content of the first and second substances,
representing the normalized interference noise power value after equalization,
representing the equalized normalized signal amplitude value.
S35, calculating the equivalent value after equalization according to the following formula
The value:
wherein the content of the first and second substances,
representing equalized equivalence
The value of the one or more of the one,
represents the normalized signal amplitude value after equalization,
representing the normalized interference noise power value after equalization.
S36, repeating the above steps S31-S35, and traversing
To find equivalence
Of greatest value
Is marked as
Maximum refresh
Value and corresponding
。
Finally, an interference covariance matrix with optimal performance in the current interference suppression area can be calculated as:
repeating the steps S31-S35 for all the interference suppression areas can obtain the interference noise correlation matrix in all the interference suppression areas.
Example three:
for example, the PUSCH uplink configuration will be described with NR system bandwidth =100M, subcarrier spacing =30kHz, terminal 2T, base station side 2R, layer number =2, and ports {0,2 }.
In this embodiment, the processing granularity of the equalization is an interference suppression area, and if slot-level interference suppression is performed on RBs 0-RB 49, the interference suppression area is a time-frequency two-dimensional resource block that occupies 600 subcarriers in the frequency domain and 14 OFDM symbols in the time domain. For each subcarrier of each OFDM symbol, the following algorithm steps are performed in the interference suppression zone, respectively:
by setting in each interference suppression area
In a certain step length
Go through from 0 to 1, e.g. for
，
The values of (A) are the following 11 types:
。
for each traversal
Calculating post-equalization equivalence under MMSE criterion
The steps of the values are as follows:
s31, calculating an interference noise correlation matrix according to the following formula:
s32, calculating a balanced combining weight:
interference covariance matrix
And an estimate of the product of the frequency domain channel response experienced by the transmitted signal and the precoding matrix
Substituting the following formula to calculate the balance weight;
wherein the content of the first and second substances,
an inverse matrix representing the interference noise correlation matrix,
is an identity matrix.
S33, calculating the normalized signal amplitude value after equalization
：
Wherein the content of the first and second substances,
represents the normalized signal amplitude value after equalization,
the weight of the balanced combining is shown,
an estimate representing the product of the frequency domain channel response experienced by the transmitted signal and the precoding matrix.
S34, calculating the normalized interference noise power value after equalization according to the following formula:
wherein the content of the first and second substances,
representing the equalized normalized interference noise power value,
representing the equalized normalized signal amplitude value;
wherein the content of the first and second substances,
the dimension of (d) is the number of layers × 1=2 × 1.
S35, calculating the equivalent value after equalization according to the following formula
The value:
wherein the content of the first and second substances,
representing equalized equivalence
The value of the sum of the values,
represents the normalized signal amplitude value after equalization,
representing the equalized normalized interference noise power value;
wherein the content of the first and second substances,
the dimension of (d) is the number of layers × 1=2 × 1.
For multiple layers
Requiring synthesis at the codeword level
Take linear average as an example:
s36, refresh maximum
And corresponding
If not present
Then, then
，
。
If present
And is
Then, then
，
。
If present
And is
Then not update
And
。
for all
And repeating the steps S31-S35, and then calculating to obtain an optimal interference covariance matrix as follows:
repeating the above steps S31-S35 for each subcarrier (600) and each symbol (14) in the interference suppression area can calculate the interference noise correlation matrix in the entire interference suppression area.
By adopting the technical scheme of the embodiment of the invention, the combining and balancing coefficients in different interference suppression areas can be adaptively adjusted according to the real-time interference noise intensity and the interference noise covariance matrix, so that the multichannel receiver can obtain the optimal combining and balancing performance in each signal-to-interference-and-noise ratio interval of each interference suppression area, the throughput and the system capacity are improved to a greater extent, and the interference suppression performance and the data detection accuracy are improved.
Correspondingly, an embodiment of the present invention further provides an interference noise equalization system, for a receiving end of an Orthogonal Frequency Division Multiplexing (OFDM) or Orthogonal Frequency Division Multiple Access (OFDMA) communication system, where the system includes:
the device comprises a first device and a second device, wherein the first device is used for calculating an interference noise correlation matrix corresponding to an interference suppression area in each resource block form aiming at the interference suppression area;
second means for determining a multi-channel equalization combining coefficient matrix based on the interference noise correlation matrix;
a third device, configured to estimate a transmission signal according to the multi-channel equalization combining coefficient matrix and a frequency domain signal corresponding to the interference suppression area in the received signal;
wherein the interference noise correlation matrix is composed of a weighted sum of a first interference covariance matrix calculated using an MRC method and a second interference covariance matrix calculated using an IRC method.
The second device is used for determining a multi-channel equalization merging coefficient matrix based on the interference noise correlation matrix, and the adopted calculation formula is as follows:
it should be understood that other aspects and effects of the interference noise equalization system can be found in the foregoing interference noise estimation method, and are not described herein again.
It should be noted that, in the embodiment of the present invention, "Resource block form" refers to a time-frequency two-dimensional Resource block, which is one or more symbols in the time domain and one or more REs (Resource elements) in the frequency domain. The embodiment of the invention does not limit the way of dividing the resource blocks. The scheduling resource can be divided into a plurality of time-frequency two-dimensional resource blocks in a certain mode, and the length of each resource block in the time domain and the frequency domain can be different.
In another embodiment, a computer-readable storage medium is provided, on which a computer program is stored, which computer program, when being executed by a processor, is adapted to carry out any of the interference noise equalization methods as described above.
For specific limitations and implementation of the above steps, reference may be made to an embodiment of a physical random access signal processing method for a distributed base station system, which is not described herein again.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The interference noise equalization method, system and storage medium provided by the embodiment of the present invention are described in detail above, and a specific example is applied in the description to explain the principle and the implementation of the present invention, and the description of the above embodiment is only used to help understanding the technical scheme and the core idea of the present invention; those of ordinary skill in the art will understand that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (12)
1. An interference noise equalization method for a receiving end of an Orthogonal Frequency Division Multiplexing (OFDM) or Orthogonal Frequency Division Multiple Access (OFDMA) communication system, the method comprising:
the following operations are performed for each interference suppression area in the form of a resource block:
calculating an interference noise correlation matrix corresponding to the interference suppression area;
determining a multi-channel equalization merging coefficient matrix based on the interference noise correlation matrix;
estimating a sending signal according to the multi-channel equalization merging coefficient matrix and a frequency domain signal corresponding to the interference suppression area in the received signal;
wherein the interference noise correlation matrix is composed of a weighted sum of a first interference covariance matrix calculated using the MRC method and a second interference covariance matrix calculated using the IRC method.
2. The interference noise equalization method of claim 1,
the interference noise correlation matrix is represented by:
wherein the content of the first and second substances,
a correlation matrix representing the interference noise is generated,
representing a first interference covariance matrix calculated using the MRC approach,
representing a second interference covariance matrix calculated using the IRC approach,
and
weights representing the first interference covariance matrix and the second interference covariance matrix, respectively.
3. The interference noise equalization method of claim 2,
the first interference covariance matrix is represented by:
wherein dimension is
Which indicates the number of the reception channels,
to represent
Book of changes
The columns of the image data are,
indicating the estimated noise interference strength of the ith receiving channel,
。
4. the interference noise equalization method of claim 3,
the second interference covariance matrix is represented by:
wherein dimension is
Which indicates the number of the reception channels,
to represent
Book of changes
The columns of the image data are,
representing the correlation of the interference noise between the receive channel i and the receive channel j,
，
indicating the estimated noise interference strength of the ith receiving channel,
。
5. the interference noise equalization method of claim 4 wherein said first interferer is calculated based onWeights corresponding to the difference matrix and the second interference covariance matrix
And
：
s11, measuring the environmental background noise to obtain the background noise intensity corresponding to the interference suppression area
；
S12, estimating the noise interference strength among a plurality of receiving channels, wherein,
indicating the estimated noise interference strength of the ith receiving channel,
；
s13, calculating the average noise intensity estimated among the multiple receiving channels according to the following formula:
wherein the content of the first and second substances,
in order to receive the number of channels,
an average noise strength estimated among a plurality of receiving channels;
s14, calculating the ratio of the estimated average noise intensity to the background noise intensity:
s15, respectively calculating weights corresponding to the first interference covariance matrix and the second interference covariance matrix according to the following formula:
6. the interference noise equalization method of claim 4, wherein weights corresponding to the first interference covariance matrix and the second interference covariance matrix are calculated according to the following method
And
：
s21, calculating the first interference covariance matrix
And the second interference covariance matrix
；
S22, respectively calculating the equalization weights corresponding to the first interference covariance matrix and the second interference covariance matrix according to the following formula:
wherein the content of the first and second substances,
an inverse matrix representing the first interference covariance matrix,
an inverse matrix representing the second interference covariance matrix,
representing the equalization weights corresponding to the first interference covariance matrix,
representing the equalization weight corresponding to the second interference covariance matrix,
is a matrix of units, and is,
an estimated value representing a product of a frequency domain channel response experienced by a transmitted signal and a precoding matrix;
s23, respectively calculating the equalized normalized signal amplitude values corresponding to the MRC mode and the IRC mode according to the following formulas:
wherein the content of the first and second substances,
representing post-equalization normalized signal amplitude corresponding to MRC modeThe value of the one or more of the one,
represents the equalized normalized signal amplitude value corresponding to the IRC mode,
representing the equalization weights corresponding to the first interference covariance matrix,
representing the equalization weight corresponding to the second interference covariance matrix,
an estimated value representing a product of a frequency domain channel response experienced by a transmitted signal and a precoding matrix;
s24, respectively calculating the equalized normalized interference noise power values corresponding to the MRC mode and the IRC mode according to the following formula:
wherein the content of the first and second substances,
representing the equalized normalized signal amplitude value corresponding to the MRC mode,
represents the equalized normalized signal amplitude value corresponding to the IRC mode,
representing equalized normalized interference noise corresponding to MRC modeThe value of the sound power is,
expressing the equalized normalized interference noise power value corresponding to the IRC mode;
s25, respectively calculating the equivalent after equalization corresponding to MRC mode and IRC mode according to the following formula
The value:
wherein, the first and the second end of the pipe are connected with each other,
represents the equivalent after equalization corresponding to MRC mode
The value of the one or more of the one,
indicating the equalized equivalence corresponding to the IRC mode
The value of the one or more of the one,
represents the normalized signal amplitude value after equalization corresponding to the MRC mode,
represents the equalized normalized signal amplitude value corresponding to the IRC mode,
indicating the normalized interference noise power value after equalization corresponding to the MRC mode,
expressing the normalized interference noise power value after equalization corresponding to the IRC mode;
s26, respectively calculating weights corresponding to the first interference covariance matrix and the second interference covariance matrix according to the following formula:
7. the interference noise equalization method of claim 4, wherein weights corresponding to the first interference covariance matrix and the second interference covariance matrix are calculated according to the following method
And
：
according to a preset step length
Sequentially assigning weights
Go through from 0 to 1 (
) And for each traversal
Under the criterion of separately calculating MMSEEqualized equivalence of
A value;
for all
Determining the maximum equivalence after equalization
The weight value corresponding to the value
Then will the
As weights for the first interference covariance matrix,
as weights of the second interference covariance matrix.
8. The interference noise equalization method of claim 7 wherein said computing an equalized equivalent
The values include:
for each traversal
The following operations are performed:
s31, calculating an interference noise correlation matrix according to the following formula:
s32, calculating the balance combining weight according to the following formula:
wherein the content of the first and second substances,
an inverse matrix representing the interference noise correlation matrix,
an estimate representing the product of the frequency domain channel response experienced by the transmitted signal and the precoding matrix,
is an identity matrix;
s33, calculating the equalized normalized signal amplitude value according to the following formula:
wherein, the first and the second end of the pipe are connected with each other,
represents the normalized signal amplitude value after equalization,
the weight of the balanced combining is shown,
an estimated value representing a product of a frequency domain channel response experienced by a transmitted signal and a precoding matrix;
s34, calculating the normalized interference noise power value after equalization according to the following formula:
wherein the content of the first and second substances,
representing the normalized interference noise power value after equalization,
representing the equalized normalized signal amplitude value;
s35, calculating the equivalent value after equalization according to the following formula
The value:
wherein, the first and the second end of the pipe are connected with each other,
representing equalized equivalence
The value of the one or more of the one,
represents the normalized signal amplitude value after equalization,
representing the normalized interference noise power value after equalization.
9. The interference noise equalization method of claim 2 wherein said step of determining a multi-channel equalization combining coefficient matrix based on said interference noise correlation matrix comprises:
and calculating the multichannel equalization merging coefficient matrix by adopting an MMSE (minimum mean square error) criterion and adopting the following formula:
wherein the content of the first and second substances,
is a matrix of units, and is,
an estimate representing the product of the frequency domain channel response experienced by the transmitted signal and the precoding matrix,
an inverse matrix representing the interference noise correlation matrix,
and representing the multi-channel equalization merging coefficient matrix.
10. The interference noise equalizing method of claim 9, wherein the step of estimating the transmission signal according to the multi-channel equalization combining coefficient matrix and the frequency domain signal corresponding to the interference suppression zone in the received signal comprises:
the transmitted signal is estimated using:
wherein the content of the first and second substances,
which is indicative of the estimated transmitted signal,
representing the frequency domain signal corresponding to the interference suppression zone in the received signal,
and representing the multi-channel equalization merging coefficient matrix.
11. An interference noise equalization system for a receiving end of an Orthogonal Frequency Division Multiplexing (OFDM) or Orthogonal Frequency Division Multiple Access (OFDMA) communication system, the system comprising:
a first device, configured to calculate, for each interference suppression area in the form of resource block, an interference noise correlation matrix corresponding to the interference suppression area;
second means for determining a multi-channel equalization combining coefficient matrix based on the interference noise correlation matrix;
a third device, configured to estimate a transmission signal according to the multi-channel equalization combining coefficient matrix and a frequency domain signal corresponding to the interference suppression area in the received signal;
wherein the interference noise correlation matrix is composed of a weighted sum of a first interference covariance matrix calculated using the MRC method and a second interference covariance matrix calculated using the IRC method.
12. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the interference noise equalization method according to any one of claims 1 to 10.
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