CN109150364B - Mobile terminal, interference noise estimation method thereof, and computer-readable storage medium - Google Patents

Mobile terminal, interference noise estimation method thereof, and computer-readable storage medium Download PDF

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CN109150364B
CN109150364B CN201710507740.8A CN201710507740A CN109150364B CN 109150364 B CN109150364 B CN 109150364B CN 201710507740 A CN201710507740 A CN 201710507740A CN 109150364 B CN109150364 B CN 109150364B
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interference
covariance matrix
noise covariance
matrix
noise
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CN109150364A (en
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余辉
霍成海
李卫国
严伟
李俊强
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Spreadtrum Communications Shanghai Co Ltd
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    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04J—MULTIPLEX COMMUNICATION
    • H04J11/00—Orthogonal multiplex systems, e.g. using WALSH codes
    • H04J11/0023—Interference mitigation or co-ordination
    • H04J11/005—Interference mitigation or co-ordination of intercell interference

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Abstract

A mobile terminal, an interference noise estimation method and a computer readable storage medium thereof, wherein the interference noise estimation method comprises the steps of calculating an autocorrelation matrix corresponding to a received signal according to the received signal, calculating an autocorrelation matrix corresponding to a service signal sent by a service cell, subtracting the autocorrelation matrix corresponding to the received signal from the autocorrelation matrix corresponding to the service signal sent by the service cell to obtain a difference value as a interference and noise covariance matrix of the mobile terminal.

Description

Mobile terminal, interference noise estimation method thereof, and computer-readable storage medium
Technical Field
The present invention relates to the field of mobile communications, and in particular, to mobile terminals, interference noise estimation methods thereof, and computer-readable storage media.
Background
The Interference Rejection Combining (IRC) method can eliminate inter-cell Interference by fully utilizing the receive diversity at the receiving end, and can effectively improve the throughput of the wireless communication system. The key to suppressing interference using the IRC method is to obtain an interference and noise covariance matrix.
Currently, in the third generation partnership project (3)rdGeneration Partnership Project, 3GPP) in Long Term Evolution (LTE), an interference and noise covariance matrix is estimated using received signals.
When the covariance matrix of the interference and the noise is estimated by adopting the method, the calculation complexity is low, but the error is large, so that the performance loss of the system is increased.
Disclosure of Invention
The technical problem solved by the embodiment of the invention is how to improve the precision of the interference and noise covariance matrix obtained by estimation.
In order to solve the above technical problem, an embodiment of the present invention provides an interference noise estimation method for mobile terminals, including calculating an autocorrelation matrix corresponding to a received signal according to the received signal, calculating an autocorrelation matrix corresponding to a service signal sent by a serving cell, and subtracting the autocorrelation matrix corresponding to the received signal from the autocorrelation matrix corresponding to the service signal sent by the serving cell, where the obtained difference is used as a interference and noise covariance matrix of the mobile terminal.
Optionally, the autocorrelation matrix corresponding to the received signal is calculated by using the following formula:
Figure BDA0001335054230000011
wherein R1 is an autocorrelation matrix corresponding to the received signal, K is the number of traffic REs needed to calculate the th interference and noise covariance matrix, RkFor the received signal, rk *Is rkThe conjugate of (a) to (b),
Figure BDA0001335054230000012
ρSis the ratio of the traffic signal transmit power to the pilot signal transmit power, ρ, of the serving cellIIs the ratio of the traffic signal transmit power to the pilot signal transmit power of the interfering cell,
Figure BDA0001335054230000021
a precoding matrix for a serving cell corresponding to the kth service RE,
Figure BDA0001335054230000022
a precoding matrix for an interfering cell corresponding to the kth service RE,
Figure BDA0001335054230000023
corresponding to the estimated k-th service REThe channel matrix of the serving cell of (a),
Figure BDA0001335054230000024
for the estimated interfering cell channel matrix corresponding to the kth service RE,
Figure BDA0001335054230000025
for the service signal of the serving cell corresponding to the kth service RE,for the traffic signal of the interfering cell corresponding to the kth traffic RE, nkK is more than or equal to 1 and less than or equal to K, and is noise corresponding to the kth service RE.
Optionally, the autocorrelation matrix corresponding to the service signal sent by the serving cell is calculated by using the following formula:
Figure BDA0001335054230000027
wherein, R2 is an autocorrelation matrix corresponding to the service signal sent by the serving cell.
Optionally, after obtaining the th interference and noise covariance matrix of the mobile terminal, the method further includes compensating the th interference and noise covariance matrix.
Optionally, the compensating the th interference and noise covariance matrix includes obtaining a second interference and noise covariance matrix of the mobile terminal according to the received pilot signal, obtaining a third interference and noise covariance matrix according to the traffic signal and the noise signal of the interference cell in the received signal, obtaining a third interference and noise covariance matrix of the mobile terminal according to the estimation, calculating a th reliability metric value corresponding to the th interference and noise covariance matrix, a second reliability metric value corresponding to the second interference and noise covariance matrix, and a third reliability metric value corresponding to the third interference and noise covariance matrix, respectively, allocating a weighting coefficient to the th reliability metric value, allocating a second weighting coefficient to the second reliability metric value, and allocating a third weighting coefficient to the third reliability metric value, wherein the sum of the weighting coefficient, the second weighting coefficient, and the third weighting coefficient is 1, multiplying the weighting coefficient with the th interference and noise covariance matrix to obtain a third interference and noise covariance matrix, multiplying the second weighting coefficient with the and the third weighting coefficient by the third weighting coefficient to obtain a product, and calculating a product of the second interference and noise covariance matrix, and multiplying the third weighting coefficient by the third weighting matrix to obtain a product, and calculating a product of the third interference and the product of the 3623 to obtain a product, and the product of the third interference and the third noise covariance matrix, and the product of the interference and the product of the noise covariance matrix, wherein the interference and the product is calculated by the product of the interference and the.
Optionally, the second interference and noise covariance matrix of the mobile terminal is estimated by using the following formula:wherein R isnormal,1For the second interference and noise covariance matrix, K is the number of pilot REs needed to calculate the second interference and noise covariance matrix, rkIs the received signal and
Figure BDA0001335054230000029
Figure BDA00013350542300000210
for the estimated serving cell channel matrix corresponding to the kth pilot RE,
Figure BDA0001335054230000031
for the estimated interfering cell channel matrix corresponding to the kth pilot RE,
Figure BDA0001335054230000032
for the pilot signal of the serving cell corresponding to the kth pilot RE,
Figure BDA0001335054230000033
for the pilot signal of the interfering cell corresponding to the kth pilot RE, nkFor the noise corresponding to the kth pilot RE,
Figure BDA0001335054230000034
is composed of
Figure BDA0001335054230000035
K is more than or equal to 1 and less than or equal to K.
Optionally, the following formula is adopted to estimate a third interference and noise covariance matrix of the mobile terminal:
Figure BDA0001335054230000036
wherein R isnormal,2Is the third interference and noise covariance matrix, K is the number of traffic REs needed to calculate the third interference and noise covariance matrix,
Figure BDA0001335054230000037
for the estimated serving cell channel matrix corresponding to the kth service RE,
Figure BDA0001335054230000038
for the estimated interference cell channel matrix, rho, corresponding to the kth service REIIs the ratio of the traffic signal transmit power to the pilot signal transmit power of the interfering cell,precoding matrix, R, for interfering cell corresponding to kth service REnThe covariance matrix corresponding to the noise on the kth traffic RE.
Optionally, the calculating the th reliability metric includes calculating products of all elements on a th main diagonal of the interference and noise covariance matrix and obtaining real1, obtaining secondary diagonal elements of a 2 x 2 matrix on a th main diagonal of the interference and noise covariance matrix, calculating products of the obtained secondary diagonal elements and obtaining real2, and performing division operation on real1 and real2 to obtain a quotient serving as the th reliability metric.
Optionally, the calculating the second reliability metric value includes: calculating the product of all elements on the main diagonal of the second interference and noise covariance matrix and taking real 3; acquiring secondary diagonal elements of a 2 x 2 matrix on a primary diagonal of the second interference and noise covariance matrix, calculating products of the acquired secondary diagonal elements, and taking a real part real 4; and dividing real3 and real4 to obtain a quotient value as the second reliability metric value.
Optionally, the calculating the third reliability metric includes: calculating the product of all elements on the main diagonal of the third interference and noise covariance matrix and taking real 5; acquiring secondary diagonal elements of a 2 x 2 matrix on a primary diagonal of the third interference and noise covariance matrix, calculating products of the acquired secondary diagonal elements, and taking a real part real 6; and dividing real5 and real6 to obtain a quotient value as the third reliability metric value.
The embodiment of the invention also provides mobile terminals, which comprise a calculation unit used for calculating an autocorrelation matrix corresponding to the received signal according to the received signal, a second calculation unit used for calculating an autocorrelation matrix corresponding to a service signal sent by a serving cell, and an interference and noise covariance matrix determination unit used for subtracting the autocorrelation matrix corresponding to the received signal and the autocorrelation matrix corresponding to the service signal sent by the serving cell to obtain a difference value as a th interference and noise covariance matrix of the mobile terminal.
Optionally, the th calculating unit is configured to calculate an autocorrelation matrix corresponding to the received signal by using the following formula:
Figure BDA0001335054230000041
wherein R1 is an autocorrelation matrix corresponding to the received signal, K is the number of traffic REs needed to calculate the th interference and noise covariance matrix, RkFor the received signal, rk *Is rkThe conjugate of (a) to (b),
Figure BDA0001335054230000042
ρSis the ratio of the traffic signal transmit power to the pilot signal transmit power, ρ, of the serving cellIServing an interfering cellThe ratio of the signal transmit power to the pilot signal transmit power,
Figure BDA0001335054230000043
a precoding matrix for a serving cell corresponding to the kth service RE,a precoding matrix for an interfering cell corresponding to the kth service RE,
Figure BDA0001335054230000045
for the estimated serving cell channel matrix corresponding to the kth service RE,
Figure BDA0001335054230000046
for the estimated interfering cell channel matrix corresponding to the kth service RE,
Figure BDA0001335054230000047
for the service signal of the serving cell corresponding to the kth service RE,
Figure BDA0001335054230000048
for the traffic signal of the interfering cell corresponding to the kth traffic RE, nkK is more than or equal to 1 and less than or equal to K, and is noise corresponding to the kth service RE.
Optionally, the second calculating unit is configured to calculate an autocorrelation matrix corresponding to the service signal sent by the serving cell by using the following formula:
Figure BDA0001335054230000049
wherein, R2 is an autocorrelation matrix corresponding to the pilot signal transmitted by the serving cell.
Optionally, the mobile terminal further includes a compensation unit, configured to compensate the th interference and noise covariance matrix after obtaining the th interference and noise covariance matrix.
Optionally, the compensation unit is configured to obtain a second interference and noise covariance matrix of the mobile terminal according to a received pilot signal, obtain a third interference and noise covariance matrix of the mobile terminal according to a traffic signal and a noise signal of an interference cell in the received signal, respectively calculate a reliability metric corresponding to the -th interference and noise covariance matrix, a second reliability metric corresponding to the second interference and noise covariance matrix, and a third reliability metric corresponding to the third interference and noise covariance matrix, respectively allocate a weighting coefficient to the -th reliability metric, allocate a second weighting coefficient to the second reliability metric, and allocate a third weighting coefficient to the third reliability metric, where a sum of the weighting coefficient, the second weighting coefficient, and the third weighting coefficient is 1, multiply the weighting coefficient, the second weighting coefficient, the third weighting coefficient, and the noise covariance matrix to obtain a third weighting coefficient , multiply the second weighting coefficient, the third weighting coefficient, and the third weighting coefficient by a product of the second interference and noise covariance matrix, obtain a product, multiply the third weighting coefficient by a product of the 36 and calculate a third covariance matrix, and obtain a product by a product of the third covariance matrix, and calculate a product by a product of the third weighting coefficient by a product of the interference and a third covariance matrix, and calculate a third product of the interference and obtain a third covariance matrix, and a noise product by a product of the interference and a third product.
Optionally, the compensation unit is configured to estimate a second interference and noise covariance matrix of the mobile terminal by using the following formula:wherein R isnormal,1For the second interference and noise covariance matrix, K is the number of pilot REs needed to calculate the second interference and noise covariance matrix, rkIs the received signal and
Figure BDA0001335054230000052
for the estimated serving cell channel matrix corresponding to the kth pilot RE,
Figure BDA0001335054230000053
for the estimated interfering cell channel matrix corresponding to the kth pilot RE,
Figure BDA0001335054230000054
for the pilot signal of the serving cell corresponding to the kth pilot RE,
Figure BDA0001335054230000055
for the pilot signal of the interfering cell corresponding to the kth pilot RE, nkFor the noise corresponding to the kth pilot RE,is composed of
Figure BDA00013350542300000512
K is more than or equal to 1 and less than or equal to K.
Optionally, the compensation unit is configured to estimate a third interference and noise covariance matrix of the mobile terminal by using the following formula:wherein R isnormal,2Is the third interference and noise covariance matrix, K is the number of traffic REs needed to calculate the third interference and noise covariance matrix,
Figure BDA0001335054230000058
for the estimated serving cell channel matrix corresponding to the kth service RE,
Figure BDA0001335054230000059
for the estimated interference cell channel matrix, rho, corresponding to the kth service REIIs the ratio of the traffic signal transmit power to the pilot signal transmit power of the interfering cell,
Figure BDA00013350542300000510
precoding matrix, R, for interfering cell corresponding to kth service REnThe covariance matrix corresponding to the noise on the kth traffic RE.
Optionally, the calculating the th reliability metric includes calculating products of all elements on a th main diagonal of the interference and noise covariance matrix and obtaining real1, obtaining secondary diagonal elements of a 2 x 2 matrix on a th main diagonal of the interference and noise covariance matrix, calculating products of the obtained secondary diagonal elements and obtaining real2, and performing division operation on real1 and real2 to obtain a quotient serving as the th reliability metric.
Optionally, the calculating the second reliability metric value includes: calculating the product of all elements on the main diagonal of the second interference and noise covariance matrix and taking real 3; acquiring secondary diagonal elements of a 2 x 2 matrix on a primary diagonal of the second interference and noise covariance matrix, calculating products of the acquired secondary diagonal elements, and taking a real part real 4; and dividing real3 and real4 to obtain a quotient value as the second reliability metric value.
Optionally, the calculating the third reliability metric includes: calculating the product of all elements on the main diagonal of the third interference and noise covariance matrix and taking real 5; acquiring secondary diagonal elements of a 2 x 2 matrix on a primary diagonal of the third interference and noise covariance matrix, calculating products of the acquired secondary diagonal elements, and taking a real part real 6; and dividing real5 and real6 to obtain a quotient value as the third reliability metric value.
The embodiment of the present invention further provides computer-readable storage media, and when the computer instructions are executed, the steps of the method for estimating interference noise of a mobile terminal described in any above are performed.
The embodiment of the present invention further provides kinds of mobile terminals, which include a memory and a processor, where the memory stores computer instructions executable on the processor, and the processor executes the computer instructions to perform the steps of any mentioned above method for estimating interference noise of a mobile terminal.
Compared with the prior art, the technical scheme of the embodiment of the invention has the following beneficial effects:
subtracting the autocorrelation matrix corresponding to the received signal from the autocorrelation matrix corresponding to the service signal of the serving cell, so that an th interference and noise covariance matrix corresponding to the interference and noise signals in the received signal can be obtained through calculation, and therefore, an accurate interference and noise covariance matrix can be obtained, and the accuracy of the interference and noise covariance matrix obtained through estimation can be effectively improved.
, after obtaining the th interference and noise covariance matrix, the second interference and noise covariance matrix and the third interference and noise covariance matrix are combined to compensate the th interference and noise covariance matrix, so that the accuracy of the interference and noise covariance matrix can be further improved .
Drawings
Fig. 1 is a flowchart of an interference noise estimation method for kinds of mobile terminals in an embodiment of the present invention;
fig. 2 is a schematic structural diagram of kinds of mobile terminals in the embodiment of the present invention.
Detailed Description
In the prior art, the received signal is usually estimated to obtain an interference and noise covariance matrix, as shown in the following formula (1):
in the formula (1), Rnormal,1For an interference and noise covariance matrix estimated using the received signal, K is the number of pilot REs needed to estimate the interference and noise covariance matrix, rkIs the received signal and
Figure BDA0001335054230000072
Figure BDA0001335054230000079
for the estimated serving cell channel matrix corresponding to the kth pilot RE,
Figure BDA0001335054230000073
for the estimated interfering cell channel matrix corresponding to the kth pilot RE,
Figure BDA0001335054230000074
for the pilot signal of the serving cell corresponding to the kth pilot RE,
Figure BDA0001335054230000075
for the pilot signal of the interfering cell corresponding to the kth pilot RE, nkFor the noise corresponding to the kth pilot RE,
Figure BDA0001335054230000076
is composed ofK is more than or equal to 1 and less than or equal to K.
As can be seen from equation (1), when the interference and noise covariance matrix is estimated, the influence of the precoding matrix of the interfering cell is not considered. When the precoding matrix of the interference cell is a non-unit matrix, the accuracy of the interference and noise covariance matrix obtained by estimation is poor, and the influence on the system performance is large.
In the embodiment of the invention, the autocorrelation matrix corresponding to the received signal is subtracted from the autocorrelation matrix corresponding to the service signal of the serving cell, so that the th interference and noise covariance matrix corresponding to the interference and noise signals in the received signal can be obtained through calculation, and therefore, the accurate interference and noise covariance matrix can be obtained, and the accuracy of the estimated interference and noise covariance matrix can be effectively improved.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in detail below.
The embodiment of the invention provides an interference noise estimation method for mobile terminals, which is described in detail by referring to fig. 1 through specific steps.
Step S101, according to the received signal, calculating the autocorrelation matrix corresponding to the received signal.
In practical applications, it is known that the signals received by the mobile terminal include signals transmitted by a serving cell, signals transmitted by an interfering cell, and noise signals.
In a specific implementation, the signal vector received by the mobile terminal on the kth RE is rk，rkCan be represented by the following formula (2):
Figure BDA0001335054230000078
in the formula (2), the reaction mixture is,
Figure BDA0001335054230000081
representing an effective channel matrix corresponding to a serving cell corresponding to the kth RE, wherein the effective channel matrix comprises an actual channel matrix and a precoding matrix;a signal of a serving cell corresponding to a kth RE;
Figure BDA0001335054230000083
representing the effective channel matrix corresponding to the interference cell corresponding to the kth RE;
Figure BDA0001335054230000084
a signal of an interference cell corresponding to a kth RE; n iskA noise signal corresponding to the kth RE; k is more than or equal to 1 and less than or equal to K, and K is the number of REs needed for executing the interference and noise covariance estimation.
In LTE systems, a mobile terminal typically estimates the channel of a serving Cell using a pilot signal, which may be a Cell-specific Reference signal (CRS). The estimated channel matrix of the serving cell is
Figure BDA0001335054230000085
The estimated channel matrix of the interfering cell isThe signal vector r received in the kth traffic REkCan be converted from the above formula (2) to the following formula (3):
Figure BDA0001335054230000087
where ρ isSIs the ratio of the traffic signal transmit power to the pilot signal transmit power, ρ, of the serving cellIIs the ratio of the traffic signal transmit power to the pilot signal transmit power of the interfering cell,
Figure BDA0001335054230000088
a precoding matrix for a serving cell corresponding to the kth service RE,
Figure BDA0001335054230000089
and the precoding matrix is the precoding matrix of the interference cell corresponding to the kth service RE.
According to equation (3), the received signal vector r in the k-th pilot REkCan be simplified to the following formula (4):
Figure BDA00013350542300000810
in the formula (4), the reaction mixture is,
Figure BDA00013350542300000811
pilot signals of a serving cell corresponding to the kth pilot RE;
Figure BDA00013350542300000812
is the pilot signal of the interfering cell corresponding to the kth pilot RE.
In the formula (3), r iskFor the signal vector received on the kth traffic RE,
Figure BDA00013350542300000813
for the service signal of the serving cell corresponding to the kth service RE,
Figure BDA00013350542300000814
is the service signal of the interfering cell corresponding to the kth service RE. And in formula (4), rkFor the signal vector received on the kth pilot RE,
Figure BDA00013350542300000815
for the pilot signal of the serving cell corresponding to the kth pilot RE,
Figure BDA00013350542300000816
is the pilot signal of the interfering cell corresponding to the kth pilot RE.
In a specific implementation, calculating the autocorrelation matrix corresponding to the received signal refers to calculating the autocorrelation matrix corresponding to the received signal of the kth traffic RE, rather than calculating the autocorrelation matrix corresponding to the received signal of the kth pilot RE.
Therefore, in the embodiment of the present invention, when calculating the autocorrelation matrix corresponding to the received signal, r in the calculation formula (3) is rkA corresponding autocorrelation matrix.
In a specific implementation, the autocorrelation matrix corresponding to the received signal of the kth service RE is calculated by using the following formula (5):
Figure BDA0001335054230000091
in equation (5), R1 is the autocorrelation matrix corresponding to the calculated signal of the kth traffic RE, and R in equation (5)kIs r in formula (3)k。
Step S102, calculating an autocorrelation matrix corresponding to the service signal sent by the service cell.
In practical applications, it is known that the signal of the kth service RE includes a service signal transmitted by a serving cell, a service signal transmitted by an interfering cell, and a noise signal. The mobile terminal can know the service signal sent by the serving cell in advance, so that the mobile terminal calculates and obtains an autocorrelation matrix corresponding to the service signal sent by the serving cell.
In a specific implementation, with reference to equation (4), the autocorrelation matrix corresponding to the service signal sent by the serving cell may be calculated by using equation (6) as follows:
Figure BDA0001335054230000092
wherein, R2 is an autocorrelation matrix corresponding to a traffic signal sent by the serving cell.
Step S103, subtracting the autocorrelation matrix corresponding to the received signal from the autocorrelation matrix corresponding to the service signal sent by the serving cell, and taking the obtained difference as an th interference and noise covariance matrix of the mobile terminal.
Therefore, the part of the autocorrelation matrix corresponding to the received signal except the autocorrelation matrix corresponding to the traffic signal transmitted by the serving cell can be used as th interference and noise covariance matrix of the mobile terminal.
Thus, in an implementation, the th interference and noise covariance matrix for the mobile terminal is shown in equation (7) below:
in the formula (7), Rproposed th interference and noise covariance matrix.
In the prior art, in LTE of 3GPP, two methods for calculating an interference and noise covariance matrix are proposed, i.e., a method estimates the interference and noise covariance matrix by directly using a received pilot signal, and a method ii estimates the interference and noise covariance matrix according to a service signal and a noise signal of an interference cell in a received signal.
In practical applications, the calculated interference and noise covariance matrix can be referred to as equation (1) for method . for method two, the calculated interference and noise covariance matrix can be referred to as equation (8):
Figure BDA0001335054230000101
in the formula (8), Rnormal,2A noise interference covariance matrix estimated from a traffic signal of an interfering cell and a noise signal in a received signal,
Figure BDA0001335054230000102
and the precoding matrix is the precoding matrix of the interference cell corresponding to the kth service RE.
Due to estimating rho of interfering cellsIAnd
Figure BDA0001335054230000103
in practical implementation, the operation complexity is high, so that equation (8) can be simplified to obtain equation (9):
Figure BDA0001335054230000104
in the formula (9), the reaction mixture is,is composed of
Figure BDA0001335054230000106
By conjugate transpose of RnThe covariance matrix corresponding to the noise on the kth traffic RE.
Although the interference and noise covariance matrix can be calculated by using the above expression (1) or expression (9), neither expression (1) or expression (9) takes into account the precoding matrix of the interfering cell
Figure BDA0001335054230000107
The influence of (c). In practical application, it can be known that the precoding matrix of the cell is interfered
Figure BDA0001335054230000108
When the covariance matrix is a non-unit matrix, the obtained interference and noise covariance matrix has a large error and a large influence on the system performance.
In the embodiment of the present invention, when the th interference and noise covariance matrix of the mobile terminal is calculated, the autocorrelation matrix corresponding to the received signal is subtracted from the autocorrelation matrix corresponding to the service signal of the serving cell, and the interference and noise covariance matrix is calculated on the basis of not knowing the precoding matrix of the interference cell, because for the mobile terminal, the precoding matrix of the interference cell belongs to parts of interference and noise, when the autocorrelation matrix corresponding to the received signal is subtracted from the autocorrelation matrix corresponding to the service signal of the serving cell, the th interference and noise covariance matrix obtained has parameters corresponding to the precoding matrix of the interference cell, therefore, compared with the prior art, the interference and noise covariance estimation method of the mobile terminal provided in the embodiment of the present invention can effectively improve the accuracy of the interference and noise covariance matrix.
In a specific implementation, when the th interference and noise covariance matrix is estimated, all or part of the service REs in a Resource Block (RB) are used, because the number of the service REs in a single RB is limited, the th interference and noise covariance matrix calculated by the formula (7) has a -determined error although the accuracy is high, and the obtained th interference and noise covariance matrix can be compensated for further increasing the accuracy of the estimated th interference and noise covariance matrix by .
In a specific implementation, the second interference and noise covariance matrix of the mobile terminal may be estimated according to the received pilot signal, and then the third interference and noise covariance matrix of the mobile terminal may be estimated according to the service signal and the noise signal of the interfering cell in the received signal.
The second interference and noise covariance matrix of the mobile terminal estimated from the received signal is Rnormal,1The specific calculation formula refers to formula (1); according to the service signal and the noise signal of the interference cell in the received signals, the estimated covariance matrix of the third interference and the noise is Rnormal,2The specific calculation formula may be expressed by equation (8) or equation (9).
According to the values, a weighting coefficient is distributed to the th reliability metric value, a second weighting coefficient is distributed to the second reliability metric value, a third weighting coefficient is distributed to the third reliability metric value, and the sum of the weighting coefficient, the second weighting coefficient and the third weighting coefficient is 1.
For example, the th reliability metric value is the largest, the second reliability metric value is the next lowest, and the third reliability metric value is the smallest, the th reliability metric value is assigned a th weighting factor of 0.7, the second reliability metric value is assigned a second weighting factor of 0.2, and the third reliability metric value is assigned a third weighting factor of 0.1.
It is understood that in practical applications, weighting coefficients may be respectively assigned to the three reliability metric values according to practical application scenarios.
The method comprises the steps of multiplying a th weighting coefficient by a th interference and noise covariance matrix to obtain a th product, multiplying a second weighting coefficient by a second interference and noise covariance matrix to obtain a second product, multiplying a third weighting coefficient by a third interference and noise covariance matrix to obtain a third product, and adding the th product, the second product and the third product to obtain a sum which can be used as a compensated th interference and noise covariance matrix.
In the specific implementation, when the th reliability metric is calculated, the product of all elements on the main diagonal of the th interference and noise covariance matrix is calculated, the real part of the obtained product is taken as real1, then the sub diagonal elements of the 2 x 2 matrix on the main diagonal of the th interference and noise covariance matrix are obtained, the product of the obtained sub diagonal elements is calculated, the real part of the obtained product is taken as real2, the real1 and real2 are divided, and the obtained quotient is taken as the th reliability metric.
Taking two receiving antennas as an example, the th interference and noise covariance matrix is calculated as the following formula (10):
wherein R isproposedThe calculated th interference and noise covariance matrix.
the element on the main diagonal of the interference and noise covariance matrix is rp11And rp22Calculating rp11And rp22Taking the real part of the resulting product as real 1. interference and noise covariance matrix, and R is the 2 x 2 matrix on the main diagonal of the matrixproposedItself, RproposedThe minor diagonal element of (a) is rp12And rp21Calculating rp12And rp21The real part of the obtained product is taken as real 2. then the th reliability metric value is calculated as true 1-true 1/true 2.
Taking four receiving antennas as an example, the th interference and noise covariance matrix is calculated as the following formula (11):
Figure BDA0001335054230000122
in equation (11), the element on the main diagonal of the th interference and noise covariance matrix is rp11、rp22、rp33And rp44Calculating rp11*rp22*rp33*rp44And take the real part of the resulting product as real1, i.e.: real1 ═ real (r)p11*rp22*rp33*rp44)，real(rp11*rp22*rp33*rp44) To find rp11*rp22*rp33*rp44The real part of (a).
the 2 x 2 matrix on the main diagonal of the interference and noise covariance matrix includes:
Figure BDA0001335054230000131
andwherein, the matrix
Figure BDA0001335054230000133
The element on the minor diagonal of (1) is rp12And rp21Matrix of
Figure BDA0001335054230000134
The element on the minor diagonal of (1) is rp34And rp43. Calculating rp12*rp21*rp34*rp43And take the real part of the resulting product as real2, i.e.: real2 ═ real (r)p12*rp21*rp34*rp43)。
At this time, the th reliability metric is:
metric1＝real1/real2＝real(rp11*rp22*rp33*rp44)/real(rp12*rp21*rp34*rp43)。
in a specific implementation, when calculating the second reliability metric, the product of all elements on the main diagonal of the second interference and noise covariance matrix is calculated, and the real part of the obtained product is taken as real 3. Then, the secondary diagonal elements of the 2 x 2 matrix on the primary diagonal of the second interference and noise covariance matrix are obtained, the product of the obtained secondary diagonal elements is calculated, and the real part of the obtained product is taken as real 4. And dividing real3 and real4 to obtain a quotient value as a second reliability metric value.
When calculating the third reliability metric, the product of all elements on the main diagonal of the third interference and noise covariance matrix is calculated, and the real part of the obtained product is taken as real 5. Then, the secondary diagonal elements of the 2 x 2 matrix on the primary diagonal of the third interference and noise covariance matrix are obtained, the product of the obtained secondary diagonal elements is calculated, and the real part of the obtained product is taken as real 6. And dividing real5 and real6 to obtain a quotient value as a third reliability metric value.
Specifically, the calculation of the second reliability metric value and the calculation of the third reliability metric value may refer to the calculation of the th reliability metric value provided in the foregoing embodiment of the present invention, which is not described herein again.
Referring to fig. 2, there are shown kinds of mobile terminals 20 in the embodiment of the present invention, which include a th calculating unit 201, a second calculating unit 202, and an interference and noise covariance matrix determining unit 203, wherein:
an th calculating unit 201, configured to calculate, according to a received signal, an autocorrelation matrix corresponding to the received signal;
a second calculating unit 202, configured to calculate an autocorrelation matrix corresponding to a service signal sent by the serving cell;
an interference and noise covariance matrix determining unit 203, configured to subtract the autocorrelation matrix corresponding to the received signal from the autocorrelation matrix corresponding to the service signal sent by the serving cell, and obtain a difference value as an th interference and noise covariance matrix of the mobile terminal.
In a specific implementation, the th calculating unit 201 may be configured to calculate an autocorrelation matrix corresponding to the received signal by using the following formula:
Figure BDA0001335054230000141
wherein R1 is an autocorrelation matrix corresponding to the received signal, K is the number of traffic REs needed to calculate the th interference and noise covariance matrix, RkFor the received signal, rk *Is rkThe conjugate of (a) to (b),
Figure BDA0001335054230000142
ρSis the ratio of the traffic signal transmit power to the pilot signal transmit power, ρ, of the serving cellIIs the ratio of the traffic signal transmit power to the pilot signal transmit power of the interfering cell,
Figure BDA0001335054230000143
a precoding matrix for a serving cell corresponding to the kth service RE,a precoding matrix for an interfering cell corresponding to the kth service RE,
Figure BDA0001335054230000145
for the estimated serving cell channel matrix corresponding to the kth service RE,
Figure BDA0001335054230000146
for the estimated interfering cell channel matrix corresponding to the kth service RE,
Figure BDA0001335054230000147
for the service signal of the serving cell corresponding to the kth service RE,
Figure BDA0001335054230000148
for the traffic signal of the interfering cell corresponding to the kth traffic RE, nkK is more than or equal to 1 and less than or equal to K, and is noise corresponding to the kth service RE.
In a specific implementation, the second calculating unit 202 may be configured to calculate an autocorrelation matrix corresponding to a service signal sent by the serving cell by using the following formula:
wherein, R2 is an autocorrelation matrix array corresponding to the service signal sent by the serving cell.
In a specific implementation, the mobile terminal 20 may further include a compensation unit 204, configured to compensate the th interference and noise covariance matrix after obtaining the th interference and noise covariance matrix.
In a specific implementation, the compensation unit 204 may be configured to obtain a second interference and noise covariance matrix of the mobile terminal according to a received pilot signal, obtain a third interference and noise covariance matrix of the mobile terminal according to a traffic signal and a noise signal of an interference cell in the received signal, calculate a reliability metric corresponding to the th interference and noise covariance matrix, a second reliability metric corresponding to the second interference and noise covariance matrix, and a third reliability metric corresponding to the third interference and noise covariance matrix, respectively, allocate a weighting coefficient to the th reliability metric, allocate a second weighting coefficient to the second reliability metric, and allocate a third weighting coefficient to the third reliability metric, where a sum of the weighting coefficient, the second weighting coefficient, and the third weighting coefficient is 1, multiply the 365639 weighting coefficient with the third interference and noise covariance matrix to obtain a , multiply the second interference and noise covariance matrix by the second weighting coefficient, multiply the second interference and noise covariance matrix by the third weighting coefficient, and calculate a product by the third covariance matrix, and calculate a product by the third weighting coefficient, and calculate a product by the third covariance matrix, where the product is a product of the interference and the third covariance matrix are calculated as a product by the third covariance matrix, and the product of the interference and the sum of the interference and the noise covariance matrix are calculated by the third product of the 365635.
In a specific implementation, the compensation unit 204 may be configured to estimate a second interference and noise covariance matrix of the mobile terminal by using the following formula:
Figure BDA0001335054230000151
wherein R isnormal,1For the second interference and noise covariance matrix, K is the number of pilot REs needed to calculate the second interference and noise covariance matrix, rkIs the received signal and
Figure BDA0001335054230000152
Figure BDA00013350542300001512
serving cell corresponding to estimated k pilot REThe matrix of the channels is then used,
Figure BDA0001335054230000153
for the estimated interfering cell channel matrix corresponding to the kth pilot RE,
Figure BDA0001335054230000154
for the pilot signal of the serving cell corresponding to the kth pilot RE,
Figure BDA0001335054230000155
for the pilot signal of the interfering cell corresponding to the kth pilot RE, nkFor the noise corresponding to the kth pilot RE,is composed ofK is more than or equal to 1 and less than or equal to K.
In a specific implementation, the compensation unit 204 may be configured to estimate a third interference and noise covariance matrix of the mobile terminal by using the following formula:
Figure BDA0001335054230000158
wherein R isnormal,2Is the third interference and noise covariance matrix, K is the number of traffic REs needed to calculate the third interference and noise covariance matrix,
Figure BDA0001335054230000159
for the estimated serving cell channel matrix corresponding to the kth service RE,
Figure BDA00013350542300001510
for the estimated interference cell channel matrix, rho, corresponding to the kth service REIIs the ratio of the traffic signal transmit power to the pilot signal transmit power of the interfering cell,
Figure BDA00013350542300001511
precoding matrix, R, for interfering cell corresponding to kth service REnThe covariance matrix corresponding to the noise on the kth traffic RE.
In a specific implementation, the calculating the th reliability metric includes calculating products of all elements on a th main diagonal of the interference and noise covariance matrix and obtaining a real part real1, obtaining a th sub diagonal element of a 2 x 2 matrix on the th main diagonal of the interference and noise covariance matrix, calculating products of the obtained sub diagonal elements and obtaining a real part real2, and dividing real1 and real2 to obtain a quotient serving as the reliability metric.
In a specific implementation, the calculating the second reliability metric includes: calculating the product of all elements on the main diagonal of the second interference and noise covariance matrix and taking real 3; acquiring secondary diagonal elements of a 2 x 2 matrix on a primary diagonal of the second interference and noise covariance matrix, calculating products of the acquired secondary diagonal elements, and taking a real part real 4; and dividing real3 and real4 to obtain a quotient value as the second reliability metric value.
In a specific implementation, the calculating the third reliability metric includes: calculating the product of all elements on the main diagonal of the third interference and noise covariance matrix and taking real 5; acquiring secondary diagonal elements of a 2 x 2 matrix on a primary diagonal of the third interference and noise covariance matrix, calculating products of the acquired secondary diagonal elements, and taking a real part real 6; and dividing real5 and real6 to obtain a quotient value as the third reliability metric value.
The embodiment of the present invention further provides computer-readable storage media, on which computer instructions are stored, and when the computer instructions are executed, the steps of the interference noise estimation method for a mobile terminal provided in the above embodiment of the present invention may be executed.
The embodiment of the present invention further provides mobile terminals, which include a memory and a processor, where the memory stores computer instructions executable on the processor, and the processor, when executing the computer instructions, may execute the steps of the interference noise estimation method for a mobile terminal provided in the foregoing embodiment of the present invention.
Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by associated hardware instructed by a program, which may be stored in a computer readable storage medium, which may include ROM, RAM, magnetic or optical disk, etc.
Although the present invention is disclosed above, the present invention is not limited thereto. Various changes and modifications may be effected therein by one skilled in the art without departing from the spirit and scope of the invention as defined in the appended claims.

Claims (18)

1, A method for estimating interference noise of mobile terminal, comprising:
calculating an autocorrelation matrix corresponding to the received signal according to the received signal;
calculating an autocorrelation matrix corresponding to a service signal sent by a service cell;
subtracting the autocorrelation matrix corresponding to the received signal from the autocorrelation matrix corresponding to the service signal sent by the serving cell, and taking the obtained difference as an th interference and noise covariance matrix of the mobile terminal;
the method for compensating the interference and noise covariance matrix of the th mobile terminal includes the steps of obtaining a second interference and noise covariance matrix of the mobile terminal according to received pilot signals, obtaining a third interference and noise covariance matrix according to service signals and noise signals of an interference cell in the received signals, respectively calculating a th reliability metric value corresponding to the th interference and noise covariance matrix, a second reliability metric value corresponding to the second interference and noise covariance matrix and a third reliability metric value corresponding to the third interference and noise covariance matrix, respectively allocating a weighting coefficient to the th reliability metric value, allocating a second weighting coefficient to the second reliability metric value and allocating a third weighting coefficient to the third reliability metric value, setting the sum of the third weighting coefficient, the second weighting coefficient and the third weighting coefficient to be 1, multiplying the weighting coefficient and the third interference and noise covariance matrix to obtain a 2 th interference and noise covariance matrix, multiplying the second weighting coefficient and the third weighting coefficient by the third weighting coefficient to obtain a product of the 3526 and the third covariance matrix, and calculating the sum of the second weighting coefficient and the third weighting coefficient to be a product of the interference and the noise covariance matrix to obtain a product of the , and calculating a sum of the third interference and the sum of the product of the interference and the noise covariance matrix to obtain a product of the interference and the noise covariance matrix to be a product of the interference and the noise covariance.
2. The method of claim 1, wherein the autocorrelation matrix corresponding to the received signal is calculated using the following formula:
Figure FDA0002301201470000011
wherein R1 is an autocorrelation matrix corresponding to the received signal, K is the number of traffic REs needed to calculate the th interference and noise covariance matrix, RkFor the received signal, rk *Is rkThe conjugate of (a) to (b),
Figure FDA0002301201470000012
ρSis the ratio of the traffic signal transmit power to the pilot signal transmit power, ρ, of the serving cellIIs the ratio of the traffic signal transmit power to the pilot signal transmit power of the interfering cell,
Figure FDA0002301201470000013
a precoding matrix for a serving cell corresponding to the kth service RE,
Figure FDA0002301201470000014
for the k-th jobThe precoding matrix of the interfering cell corresponding to the traffic RE,
Figure FDA0002301201470000021
for the estimated serving cell channel matrix corresponding to the kth service RE,
Figure FDA0002301201470000022
for the estimated interfering cell channel matrix corresponding to the kth service RE,
Figure FDA0002301201470000023
for the service signal of the serving cell corresponding to the kth service RE,
Figure FDA0002301201470000024
for the traffic signal of the interfering cell corresponding to the kth traffic RE, nkK is more than or equal to 1 and less than or equal to K, and is noise corresponding to the kth service RE.
3. The method of claim 2, wherein the autocorrelation matrix corresponding to the traffic signal sent by the serving cell is calculated by using the following formula:
Figure FDA0002301201470000025
wherein, R2 is an autocorrelation matrix corresponding to the service signal sent by the serving cell.
4. The method of claim 1, wherein the second interference and noise covariance matrix of the mobile terminal is estimated by using the following formula:
Figure FDA0002301201470000026
wherein R isnormal,1Is the second interference and noise covariance matrix, K is the meterCalculating the number of pilot REs, r, required for the second interference and noise covariance matrixkIs the received signal and
Figure FDA0002301201470000027
Figure FDA0002301201470000028
for the estimated serving cell channel matrix corresponding to the kth pilot RE,
Figure FDA0002301201470000029
for the estimated interfering cell channel matrix corresponding to the kth pilot RE,
Figure FDA00023012014700000210
for the pilot signal of the serving cell corresponding to the kth pilot RE,
Figure FDA00023012014700000211
for the pilot signal of the interfering cell corresponding to the kth pilot RE, nkFor the noise corresponding to the kth pilot RE,
Figure FDA00023012014700000212
is composed of
Figure FDA00023012014700000213
K is more than or equal to 1 and less than or equal to K.
5. The method of claim 1, wherein the third interference and noise covariance matrix of the mobile terminal is estimated by using the following formula:
Figure FDA00023012014700000217
wherein R isnormal,2For the third interference and noise covariance matrix, K is the third interference and noise covariance matrix calculatedThe number of traffic REs required for the acoustic covariance matrix,
Figure FDA00023012014700000214
for the estimated serving cell channel matrix corresponding to the kth service RE,
Figure FDA00023012014700000215
for the estimated interference cell channel matrix, rho, corresponding to the kth service REIIs the ratio of the traffic signal transmit power to the pilot signal transmit power of the interfering cell,
Figure FDA00023012014700000216
precoding matrix, R, for interfering cell corresponding to kth service REnThe covariance matrix corresponding to the noise on the kth traffic RE.
6. The method of interference noise estimation for a mobile terminal of claim 1 wherein said calculating said reliability metric value comprises:
calculating products of all elements on a main diagonal of the th interference and noise covariance matrix and taking a real part real 1;
obtaining secondary diagonal elements of a 2 x 2 matrix on a primary diagonal of the interference and noise covariance matrix, calculating products of the obtained secondary diagonal elements and taking a real part real 2;
and dividing real1 and real2 to obtain a quotient value as the reliability metric value.
7. The method of interference noise estimation for a mobile terminal of claim 1 wherein said calculating said second reliability metric value comprises:
calculating the product of all elements on the main diagonal of the second interference and noise covariance matrix and taking real 3;
acquiring secondary diagonal elements of a 2 x 2 matrix on a primary diagonal of the second interference and noise covariance matrix, calculating products of the acquired secondary diagonal elements, and taking a real part real 4;
and dividing real3 and real4 to obtain a quotient value as the second reliability metric value.
8. The method of interference noise estimation for a mobile terminal of claim 1 wherein said calculating said third reliability metric value comprises:
calculating the product of all elements on the main diagonal of the third interference and noise covariance matrix and taking real 5;
acquiring secondary diagonal elements of a 2 x 2 matrix on a primary diagonal of the third interference and noise covariance matrix, calculating products of the acquired secondary diagonal elements, and taking a real part real 6;
and dividing real5 and real6 to obtain a quotient value as the third reliability metric value.
A mobile terminal of type, comprising:
an th calculation unit, configured to calculate, according to a received signal, an autocorrelation matrix corresponding to the received signal;
the second calculation unit is used for calculating an autocorrelation matrix corresponding to the service signal sent by the service cell;
an interference and noise covariance matrix determination unit, configured to subtract an autocorrelation matrix corresponding to the received signal from an autocorrelation matrix corresponding to a service signal sent by the serving cell, and obtain a difference value serving as an th interference and noise covariance matrix of the mobile terminal;
the compensation unit is used for compensating the th interference and noise covariance matrix and comprises a step of obtaining a second interference and noise covariance matrix of the mobile terminal according to the received pilot signal estimation, a step of obtaining a third interference and noise covariance matrix of the mobile terminal according to the traffic signal and the noise signal of the interference cell in the received signal, a step of calculating a th reliability metric value corresponding to the th interference and noise covariance matrix, a step of calculating a second reliability metric value corresponding to the second interference and noise covariance matrix and a third reliability metric value corresponding to the third interference and noise covariance matrix respectively, a step of allocating a weighting coefficient to the th reliability metric value, a step of allocating a second weighting coefficient to the second reliability metric value and a third weighting coefficient to the third reliability metric value, a step of adding the sum of the weighting coefficient, the second weighting coefficient and the third weighting coefficient to 1, a step of multiplying the weighting coefficient and the th interference and noise covariance matrix to obtain a third interference and a step of multiplying the second weighting coefficient and the third weighting coefficient by the to obtain a product, and the product of the second interference and noise covariance matrix is calculated as a product of the sum of the third interference and the third weighting coefficient to obtain a product of the interference and the product of the 3623, and the product of the third interference and the third noise covariance matrix to obtain a product of the interference and the product of the interference and the product of the noise covariance matrix, and the product of.
10. The mobile terminal of claim 9, wherein the th calculating unit is configured to calculate the autocorrelation matrix corresponding to the received signal by using the following formula:
Figure FDA0002301201470000041
wherein R1 is an autocorrelation matrix corresponding to the received signal, K is the number of traffic REs needed to calculate the th interference and noise covariance matrix, RkFor the received signal, rk *Is rkThe conjugate of (a) to (b),
Figure FDA0002301201470000042
ρSis the ratio of the traffic signal transmit power to the pilot signal transmit power, ρ, of the serving cellIIs the ratio of the traffic signal transmit power to the pilot signal transmit power of the interfering cell,
Figure FDA0002301201470000043
a precoding matrix for a serving cell corresponding to the kth service RE,
Figure FDA0002301201470000044
a precoding matrix for an interfering cell corresponding to the kth service RE,
Figure FDA0002301201470000045
for the estimated serving cell channel matrix corresponding to the kth service RE,
Figure FDA0002301201470000046
for the estimated interfering cell channel matrix corresponding to the kth service RE,
Figure FDA0002301201470000047
for the service signal of the serving cell corresponding to the kth service RE,for the traffic signal of the interfering cell corresponding to the kth traffic RE, nkK is more than or equal to 1 and less than or equal to K, and is noise corresponding to the kth service RE.
11. The mobile terminal of claim 10, wherein the second calculating unit is configured to calculate an autocorrelation matrix corresponding to the service signal sent by the serving cell by using the following formula:
wherein, R2 is an autocorrelation matrix corresponding to the service signal sent by the serving cell.
12. The mobile terminal of claim 9, wherein the compensation unit is configured to estimate the second interference and noise covariance matrix of the mobile terminal by using the following formula:
wherein R isnormal,1For the second interference and noise covariance matrix, K is the number of pilot REs needed to calculate the second interference and noise covariance matrix, rkIs the received signal and
Figure FDA0002301201470000053
for the estimated serving cell channel matrix corresponding to the kth pilot RE,
Figure FDA0002301201470000055
for the estimated interfering cell channel matrix corresponding to the kth pilot RE,
Figure FDA0002301201470000056
for the pilot signal of the serving cell corresponding to the kth pilot RE,
Figure FDA0002301201470000057
for the pilot signal of the interfering cell corresponding to the kth pilot RE, nkFor the noise corresponding to the kth pilot RE,is composed of
Figure FDA0002301201470000059
K is more than or equal to 1 and less than or equal to K.
13. The mobile terminal of claim 9, wherein the compensation unit is configured to estimate a third interference and noise covariance matrix of the mobile terminal by using the following formula:
wherein R isnormal,2Is the third interference and noise covariance matrix, K is the number of traffic REs needed to calculate the third interference and noise covariance matrix,
Figure FDA00023012014700000511
for the estimated serving cell channel matrix corresponding to the kth service RE,
Figure FDA00023012014700000512
for the estimated interference cell channel matrix, rho, corresponding to the kth service REIIs the ratio of the traffic signal transmit power to the pilot signal transmit power of the interfering cell,
Figure FDA00023012014700000513
precoding matrix, R, for interfering cell corresponding to kth service REnThe covariance matrix corresponding to the noise on the kth traffic RE.
14. The mobile terminal of claim 9 wherein said calculating said th reliability metric value comprises:
calculating products of all elements on a main diagonal of the th interference and noise covariance matrix and taking a real part real 1;
obtaining secondary diagonal elements of a 2 x 2 matrix on a primary diagonal of the interference and noise covariance matrix, calculating products of the obtained secondary diagonal elements and taking a real part real 2;
and dividing real1 and real2 to obtain a quotient value as the reliability metric value.
15. The mobile terminal of claim 9 wherein said calculating said second reliability metric value comprises:
calculating the product of all elements on the main diagonal of the second interference and noise covariance matrix and taking real 3;
acquiring secondary diagonal elements of a 2 x 2 matrix on a primary diagonal of the second interference and noise covariance matrix, calculating products of the acquired secondary diagonal elements, and taking a real part real 4;
and dividing real3 and real4 to obtain a quotient value as the second reliability metric value.
16. The mobile terminal of claim 9 wherein said calculating said third reliability metric value comprises:
calculating the product of all elements on the main diagonal of the third interference and noise covariance matrix and taking real 5;
acquiring secondary diagonal elements of a 2 x 2 matrix on a primary diagonal of the third interference and noise covariance matrix, calculating products of the acquired secondary diagonal elements, and taking a real part real 6;
and dividing real5 and real6 to obtain a quotient value as the third reliability metric value.
17, computer readable storage medium having stored thereon computer instructions, characterized in that said computer instructions when executed perform the steps of the method for interference noise estimation of a mobile terminal according to any of claims 1-8.
18, mobile terminal comprising a memory and a processor, the memory having stored thereon computer instructions being executable on the processor, characterized in that the processor, when executing the computer instructions, performs the steps of the interference noise estimation method of the mobile terminal according to any of claims 1-8.
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