WO2008001421A1

WO2008001421A1 - Reception quality measuring method

Info

Publication number: WO2008001421A1
Application number: PCT/JP2006/312746
Authority: WO
Inventors: Kazunori Inogai
Original assignee: Panasonic Corporation
Priority date: 2006-06-26
Filing date: 2006-06-26
Publication date: 2008-01-03

Abstract

A reception quality measuring method in which received signal quality can be easily measured with high precision and stability even if the received signal contains many residual interference components. A non-Gaussian measuring apparatus (103) measures the non-Gaussian property of the distribution of the received signal and determines that as the non-Gaussian property increases, the quality of the received signal is improved. This enables correct measurement of the quality of the received signal without separating the signal from the residual interference components albeit the signal is at a low level.

Description

Specification

Reception quality measurement method

Technical field

[0001] The present invention relates to a reception quality measurement method in a wireless system such as a wireless LAN or a cellular system.

Background art

Conventionally, FDMA, TDMA, and CDMA have been put to practical use as channel multiplexing schemes for mobile communication systems. Currently, even if the number of users is increased, the transmission bandwidth does not increase, but the only method that can be used is the spatial multiplexing method (SDMA method) using MIMO transmission (for example, see Non-Patent Document 1).

[0003] Regardless of which of these methods is used, a function for measuring received signal quality, which is a criterion for selecting and executing appropriate processing in various ways, is very important.

[0004] Here, in FDMA and TDMA, each channel signal can be separated relatively easily by a filter or a time window. Therefore, the received signal quality can be measured by assuming that the receiver noise power is constant. I helped.

[0005] On the other hand, in CDMA, each user signal is separated based on the orthogonality of the code. Actually, the orthogonality of the code is not always maintained due to the influence of the multipath transmission path and the received signal is large. In some cases, interference components remain. For this reason, in CDMA, it is necessary to measure the residual interference power as well as simply measuring the reception level. The following two methods were used to separate and measure the signal in the received signal and the residual interference component including receiver noise.

[0006] 1. Method of receiving a known symbol and separating its distortion component as a residual interference component

2. Method of separating the deviation from the provisional decision value obtained by hard decision on the received symbol as the residual interference component

Next, received signal quality measurement in MIMO transmission will be described. Figure 1 shows the concept of a conventional MIMO transmission system. In FIG. 1, the MIMO transmitter 10 includes known symbols from M transmit antennas TxANT 0 to TxANT M-1 for each frame time. Transmit pattern and k-channel TDM multiplexed signal. These are mixed and received by the N receiving antennas RxANT-0 to RxANT-N-1 of the MIMO receiver 20. Here, when the service area is narrow or divided into subcarriers when combined with OFDM transmission, frequency selective fading due to multinos propagation path delay differences can be ignored, so the transmission line matrix Each element is a complex number, and the following equation holds between the transmitted symbol and the received symbol. The following equation is expressed as x = Hs in matrix representation.

[Number 1]

(ヽ

,

, Where = = 0,1,..., N -1 is the received symbol at the i th receiving antenna (1)

= 0,1, ..., Μ-1 is the transmitted symbol from the jth transmit antenna

^X J ^J

h .. is the transmission coefficient between the jth transmitting antenna and the transmitting antenna

1J

[0008] The signal separation unit 21 of the MIMO receiver 20 is a signal for obtaining M signals transmitted from M antennas TxANT-0 to TxANT-M-1 on the transmission side from N received symbols. Separation is performed (this is equivalent to despreading in CDMA transmission). Signal separation is performed in two stages: channel estimation and separation.

[0009] First, as shown in FIG. 1, because the transmitting antenna TxANT—0 transmits a known symbol! /, The other transmitting antennas TxANT—l to TxANT—M—1 do not transmit signals. At this time, the distortion of the known symbols received by each receiving antenna RxANT—0 to RxANT—N—1 is detected by complex division, and the quotient becomes h 1, h 2,. .

00 10 N- l 0

Similarly, when only the transmitting antenna TxANT 1 transmits a known symbol, h and h 1 01 1

,..., H t, all elements can be measured to obtain an N X M transmission line matrix H.

1 N-l 1

This is channel estimation. Using this channel estimation value, the original transmission symbol vector X can be extracted and separated from the reception symbol vector y. This process is performed by the signal separation unit 21. The following three are known as typical algorithms performed in the signal separation unit 21.

[0010] (1) Spatial filter bank method: based on ZF algorithm or MMSE algorithm A method that separates signals one by one with a filter that has a coefficient calculated from the transmission path matrix H.

(2) Interference canceller method: A method in which a signal separated by a spatial filter is re-encoded and multiplied by a transmission line matrix H to generate a replica, and this is separated while increasing SIR by subtracting the received signal power. .

(3) Maximum likelihood determination method: From the reception symbol vector candidates obtained by multiplying a huge number of transmission symbol vector candidates by the transmission path matrix H, select the actual reception symbol vector with the smallest Euclidean distance. Method.

[0011] The quality measurement of the received signal in MIMO transmission is obtained by measuring the known symbol distortion in the separated signal by the known symbol distortion measurement units 22-0 to 22-M-1.

FIG. 2 shows known symbols in the separated signal. As shown in the figure, even if a known symbol with the same amplitude is transmitted, its received amplitude fluctuates, so that it is separated as a result of residual interference components and receiver noise, and the power is calculated by dividing it. The quality of the separated signal can be obtained.

[0013] FIG. 3 is an explanatory diagram of received signal quality measurement based on provisional determination, and shows constellation during 16QAM symbol reception. When the actual symbol is received at the position indicated by X, the nearest 16QAM reception point is selected as the temporary decision value, and the difference between the actual received symbol and the temporary decision value is received as the residual interference component. By separating the signal due to machine noise and calculating its power, the quality of the separated signal can be obtained using all received symbols including known symbols.

Non-Patent Document 1: Daibell: “Promotion and Elemental Technology of MIMO System”, IEICE, Antenna 'Design for Propagation' Analysis Workshop (29Z30), 2004/11

Disclosure of the invention

Problems to be solved by the invention

[0014] By the way, in CDMA and MIMO, when measuring the quality of a received signal, it is common to use the method of 1. and the method of 2. These methods include the following: There was a problem.

[0015] In the method of 1. above, the number of known symbols that can be used is usually limited in order to avoid an extreme decrease in the transmission rate, so that it is difficult to obtain sufficient accuracy. For example, the central limit According to the theorem, it is difficult to achieve high accuracy with the conventional measurement method that uses only known symbols with limited power that improves 3 dB accuracy each time the number of measurement symbols is doubled. In order to measure the force, frame synchronization is necessary to identify the reception time of known symbols, so it takes time to start reception start force measurement, and measurement is not possible in a low SINR environment where synchronization is likely to be lost. There was a problem of becoming possible.

[0016] The method of 2. above has a problem that if the provisional judgment value has an error, a large error occurs in the measured value, and numerical stability cannot be obtained.

[0017] In particular, in the SDMA system represented by MIMO transmission, user signals are separated based on differences in transmission path paths without using "code orthogonality", so that there is more residual interference and reception. Signal quality measurement will be more difficult than CDMA.

[0018] An object of the present invention is to provide a reception quality measurement method that can easily perform highly accurate and stable reception signal quality measurement even when the reception signal includes a large amount of residual interference components.

Means for solving the problem

[0019] The reception quality measurement method of the present invention measures the non-Gaussianity of the signal distribution of the reception signal, and determines that the quality of the reception signal is better as the non-Gaussianity is larger.

The invention's effect

[0020] According to the present invention, the quality of the received signal can be measured based on non-Gaussianity, which can be measured without separating the signal and the residual interference component, and can be correctly judged even with a low-level signal. Therefore, even when the received signal contains a lot of residual interference components, it becomes possible to easily perform highly accurate and stable received signal quality measurement.

Brief Description of Drawings

[0021] [Fig. 1] Diagram showing the concept of a conventional MIMO transmission system

[Fig.2] Diagram for explaining quality measurement using conventional known symbols

[Figure 3] Diagram for explaining quality measurement by conventional provisional judgment

FIG. 4 is a diagram for explaining the first embodiment which is an application example of the reception quality measurement method according to the present invention.

FIG. 5 shows an embodiment in which the reception quality measurement method according to the present invention is used for reception diversity control. Figure for explanation of 2

FIG. 6 is a diagram for explaining the third embodiment in which the reception quality measurement method according to the present invention is used for transmission diversity control.

FIG. 7 is a diagram for explaining Embodiment 4 in which the reception quality measurement method according to the present invention is used for link adaptation of a MIMO transmission system.

[FIG. 8] The reception quality measurement method according to the present invention is used for transmission power control of MIMO transmission systems.

V, diagram for explaining Embodiment 5

[Fig.9] Diagram for explaining Kurtosis

[Fig.10] Diagram for explaining Negentropy

BEST MODE FOR CARRYING OUT THE INVENTION

Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.

[0023] (Principle)

The feature of the present invention is that when the transmission signals that are independent of each other according to the non-Gaussian distribution are mixed, the central limit theorem approximates the Gaussian distribution. Is to measure. Incidentally, the transmission signal has a non-Gaussian distribution as is clear from the constellation. Non-Gaussianity can be quantified with statistics such as higher-order cumulant negentropy.

[0024] Since non-Gaussianity is a concept unrelated to the signal level, quality judgment can be performed correctly even with a low-level signal. For example, if there is a low-level signal that does not contain residual interference components, it will be low quality if judged by the reception level, but it will become high quality if judged by non-Gaussianity.

. Conversely, the same applies to a high-level signal containing a lot of residual interference components. Therefore, non-gaussiness is an effective quality standard even for received signals containing residual interference components.

Furthermore, non-Gaussianity is a statistic that can be measured without separating the signal and the residual interference component. Therefore, no known symbols are required for measurement, and high-accuracy measurement using all received symbols can be performed. In addition, since frame synchronization is not required for measurement, measurement is easy, and measurement can be started at the same time as reception starts, so the pull-in time can be shortened.

[0026] In addition, in the non-Gaussian measurement, there is no numerical instability of the measured value due to the provisional determination. [0027] As described above, by measuring the received signal quality with a statistic such as higher-order cumulant Negentropy that represents non-Gaussianity, the conventional problem is solved, and the received signal contains a large amount of residual interference components. Even in this case, it becomes possible to easily perform highly accurate and stable evaluation.

[0028] Incidentally, the inventor of the present invention has been rapidly attracting attention in recent years with Fast-ICA (Independent

The present invention has been achieved with reference to independent component analysis represented by a component analysis) algorithm, which is based on non-Gaussian principle. In Fast-ICA, when multiple source signals follow non-Gaussian distributions independent of each other, these mixed signals approach the Gaussian distribution by the central limit theorem, and conversely maximize the non-Gaussianity of the separated signal. To work. In other words, it uses the absolute value of Kurtosis (kurtosis) or negentropy as a quantity representing non-Gaussianity and a quantity representing separation performance, and operates to maximize these.

[0029] Transmission data of mobile communication is obviously non-Gaussian distribution (because it is a discrete distribution) and is considered to be independent from each other, and the same method can be applied. In other words, if there are many residual interference components and receiver noise in the separated signal, the non-Gaussianity will decrease, and if these are small, the non-Gaussianity will increase.

[0030] Therefore, based on non-Gaussianity, a highly accurate and practical measurement method of reception quality using all symbols other than known symbols can be realized.

[Embodiment 1]

This embodiment presents that the present invention is used for measuring line quality. In FIG. 4, the test mobile device 100 is provided with a non-Gaussian measuring device 103 that measures (evaluates) the quality of the received signal based on the non-Gaussian property of the received signal. The non-Gaussian measuring device 103 receives a reception signal that is received by the antenna 101 and subjected to predetermined radio reception processing such as down-conversion and analog digital conversion by the receiver 102.

[0032] The non-Gaussianity measuring device 103 is configured to obtain a quality measurement result that the higher the non-Gaussianness is, the better the reception quality is.

[0033] When selecting the installation location of the base station of the cellular system, the radio wave from the test base station 200 is received by the test mobile device 100, and the quality measurement result of the received signal is accumulated, so that the propagation state of the traveling course And estimate the transmission characteristics at each point and formulate a placement plan . In such cases, conventionally, reception quality has been evaluated by measuring the reception level.

[0034] However, in the vicinity of an area boundary in an experiment using a plurality of base stations, or in a traveling course in which interference waves from other systems exist, there are large interference waves, so from a simple reception level (including interference waves) Cannot correctly predict the transmission characteristics, and it is necessary to measure the received signal and the interference wave separately. For this reason, conventionally, a method using the above-described provisional determination method and a known symbol is used. However, the former method should not use numerical instability force. The latter method using known symbols greatly affects the frame synchronization performance that is essential for the measurement, so the device is complicated to maintain reliability. In addition, it is necessary to prepare a measuring device for each wireless transmission format.

[0035] In contrast, in this embodiment, since measurement is performed using non-Gaussianity, frame synchronization performance is not affected regardless of the presence or absence of interference waves. Highly accurate and stable results can be obtained. Also, a versatile measuring instrument that does not depend on the frame format can be realized.

[0036] If the non-Gaussian measuring device 103 is mounted on a portable terminal, a display corresponding to the actual reception quality can be performed rather than the reception electrolysis strength display.

[0037] (Embodiment 2)

This embodiment presents that the present invention is applied to reception diversity control.

[0038] Reception diversity according to the present embodiment will be described with reference to FIG. A signal transmitted from the transmitting station 300 is received by a plurality of antennas RxANT-0 to RxANT-N1 of the receiving station 400. The reception quality of the signals received by the respective antennas RxANT-0 to RxANT-N-1 is measured by the respective non-Gaussian measuring units 401-0 to 401-N-1. In other words, each of the non-Gaussian measurement units 401-0 to 401-N-1 obtains a quality measurement result that the higher the non-Gaussian property, the better the reception quality, based on the non-Gaussian property of the received signal. . Each non-Gaussian measurement unit 401-0 to 401-N-1 sends the measurement result obtained in this way to diversity combining unit 402. Diversity combining section 402 diversity combines the received signals obtained by antennas RxANT-0 to RxANT-N-1 based on the measurement results. [0039] In conventional reception diversity, a single stream signal is transmitted even with one antenna, and this is received by multiple antennas, and diversity combining is performed according to the reception level at the reception antenna, thereby reducing the SNR. Improvements have been made to obtain good reception characteristics. Furthermore, in a propagation environment where there are large interference waves where radio waves from multiple transmitters arrive, simple reception levels (including interference waves) do not accurately represent the reception quality. In consideration of the fact that the diversity effect cannot be obtained if the control is performed, it is common to use the method based on the above-described provisional determination and a method using a known symbol. However, the former method should not be used for the measurement of numerical instability. The latter method using known symbols is greatly affected by the frame synchronization performance that is essential for the measurement, so the device is complicated to maintain reliability. In addition, it is necessary to prepare a receive diversity circuit for each wireless transmission format.

In contrast, in the present embodiment, the quality of the signal obtained by each of the receiving antennas RxANT—0 to RxANT —N—l is measured using non-Gaussianity, and this is used for diversity combining. Since the index is used, it is possible to realize highly accurate and stable reception diversity control regardless of the presence or absence of interference waves and without being affected by the frame synchronization performance. In addition, versatile reception diversity independent of the frame format can be realized.

[Embodiment 3]

This embodiment presents that the present invention is applied to transmission diversity control. Specifically, the quality of the received signal is measured with high accuracy on the receiving side based on non-Gaussianity, and the coefficient of transmission diversity is set with high accuracy based on this measurement result.

[0042] The transmission diversity control according to the present embodiment will be described with reference to FIG. The transmitting station 500 copies a single stream signal by the number of transmission antennas by the weighting copy branching unit 501 and increases the number of transmission antennas, and multiplies them by a weighting coefficient, so that a plurality of transmission antennas TxAN T—0 to TxANT—M—1 minute The transmission signal is formed.

[0043] The receiving station 600 receives these mixed signals with one antenna. The channel estimation unit 601 performs channel estimation based on known symbol distortion. This channel estimation value is wirelessly transmitted to the transmission station 500 via the transmission device 602. In addition to this, the receiving station 600 has a non-Gaussian measuring unit 603, and the non-Gaussian measuring unit 603 receives a non-Gaussian signal. Measure the resistance. The non-Gaussianity measuring unit 603 transmits a transmission instruction signal instructing the transmission apparatus 602 to transmit a channel estimation value only when the non-Gaussianity of the received signal becomes lower than a predetermined threshold.

[0044] When the channel estimation value is fed back from receiving station 600, transmission station 500 changes the transmission diversity weighting factor based on the channel estimation value in transmission diversity control section 502 and sends the result to weighting copy branching section 501. To do. The weighting factor of this transmission diversity is calculated based on the channel estimation value obtained at the receiving station 600 so that it can be satisfactorily received by the receiving antenna RxANT.

By the way, in transmission diversity transmission, channel estimation accuracy greatly affects transmission characteristics. However, since the channel estimation value obtained by the channel estimation unit 601 is performed using known symbols with a limited number, the value fluctuates, and it is not always good to update every time a known symbol is received.

In consideration of this, in this embodiment, the quality of the channel estimation value is determined using the non-gaussiness of the received signal, and the channel estimation value is fed back to transmitting station 500 only when the quality is degraded. I tried to do it. The transmitting station 500 holds the current value while the value is not updated by feedback.

[0047] As a result, the feedback information is transmitted only when it is necessary to substantially change the coefficient of transmission diversity, so that radio resources required for feedback can be saved and transmission errors in the feedback path can be reduced and stable. Transmit diversity can be realized. In addition, since non-Gaussianity is used, highly accurate and stable transmission diversity control can be realized regardless of the presence or absence of interference waves and without being affected by the frame synchronization performance.

[Embodiment 4]

This embodiment proposes that the present invention is applied to link adaptation of a MIMO transmission system.

[0049] The link adaptation of the present embodiment will be described with reference to FIG. Transmitting station 700 transmits M-channel transmission data from a plurality of antennas TxANT 0 to TxANT M−1 via MIMO error control encoding section 701 and MIMO modulation section 702. [0050] Receiving station 800 inputs signals received by a plurality of antennas RxANT-0 to RxANT-N-1 to MIMO signal demultiplexing section 801. MIMO signal demultiplexing section 801 performs channel estimation, and further uses this channel estimation value to generate M transmission signals X to X using separation algorithms such as a spatial filter bank method, an interference canceller method, and a maximum likelihood determination method. corresponds to x

0 M- 1

Obtain M separated signals z-z. M separated signals z to z are used for MIMO error correction recovery.

0 M- 1 0 M- 1

Error correction decoding is performed by the signal key unit 802 to be received data for M channels. In addition to this, the receiving station 800 can measure non-Gaussianity of each separated signal z to z.

0 M- 1

It has measuring units 803-0 to 803-M-1. The quality measurement results of the separated signals z to z obtained by the non-Gaussian measuring units 803-0 to 803-M 1 are sent to the transmitting station 700.

0 M- 1

[0051] When the transmitting station 700 receives the quality measurement results of the separated signals z to z from the receiving station 800,

0 M- 1

The quality measurement result of each separated signal z to z is converted into MCS (Modulation and Co

0 M- 1

ding Scheme) Input to control unit 703. The per-stream MCS control unit 703 controls the error correction coding rate and the modulation multi-level number according to the quality of each stream (each separated signal), thereby reducing variations in transmission characteristics between streams. Specifically, the per-stream MCS control unit 703 sends error signals to streams corresponding to the separated signals z to z by sending control signals to the MIMO error control code unit 701 and the MIMO modulation unit 702.

0 M- 1

The coding rate and the modulation multi-level number are set for each separated signal z to z.

0 M-1 Control according to quality.

[0052] Conventionally, these controls are performed using known symbols or based on reception quality measurement by provisional determination. In this embodiment, the separated signals z to z

0 M- 1 Since it is done by measuring non-Gaussianity, many symbols can be used for quality measurement and it has excellent numerical stability, so the link adaptation is more accurate and stable than before. To be able to realize

[0053] Also, when special high-speed transmission is required, such as file transfer or stream distribution, based on the non-Gaussian measurement result sent from the receiving station 800 in the error control code section 701, It can also be rearranged into a high-quality stream for transmission.

[Embodiment 5]

In this embodiment, the present invention is applied to transmission power control of a MIMO transmission system. It is the person who presents.

[0055] Transmission power control according to the present embodiment will be described with reference to FIG. 8 in which parts corresponding to those in FIG. The quality of each separated signal z to z is measured by the non-Gaussian measuring unit 803—0 to 803—M—1 at the receiving station 800, and the measurement result is sent to the transmitting station 900.

0 M- 1

Is the same as in the fourth embodiment.

[0056] When the transmitting station 900 receives the quality measurement result of each separated signal z to z from the receiving station 800,

0 M- 1

The quality measurement results of the separated signals z to z are input to the transmission power control unit 902. Sending

0 M- 1

The transmission power control unit 902 controls the transmission power in each transmission radio circuit 901-0 to 901-M-1 according to the quality of each stream (each separated signal), so that the required transmission quality of each stream is To reduce the transmission of unnecessary radio waves. Specifically, the transmission power control unit 902 sends the transmission power control signals to the respective transmission radio circuits 901-0 to 901-M-1, so that the separated signals z to z are transmitted.

The transmission power for the stream corresponding to 0 M-1 is controlled according to the quality of each separated signal z to z.

0 M- 1

[0057] Conventionally, in the CDMA system, transmission power control based on SINR measured using known symbols of each stream is performed. In this embodiment, the non-Gaussianity of the separated signals z to z is reduced. Since it is done by measuring, many symposiums are used for quality measurement.

0 M- 1

Can be used and has excellent numerical stability, so that it is possible to achieve highly accurate and stable transmission power control.

In the present embodiment, as an example, the case where the quality measurement method based on non-Gaussianity of the present invention is applied to transmission power control in MIMO transmission has been described.

The same effect can be obtained when the quality measurement method based on non-Gaussianity of the present invention is applied to the transmission power control in A.

[Embodiment 6]

This embodiment presents a preferred measurement method as a method for measuring non-Gaussianity. Specifically, we present that the absolute value of the higher-order cumulant of the received signal is used as a non-Gaussian index.

[0060] The non-Gaussianity measuring method of the present embodiment calculates a fourth-order cumulant called Kurtosi s (also referred to as Kurtosis) shown in the following equation with respect to the received signal, and the absolute value is large. Gauss The signal is strong, that is, the signal quality (SINR) is high.

[Equation 2]

[0061] Here, the expression (2) is Kurtosis that is normalized by power. Ε [·] represents the average of the set. This set average Ε [·] should be calculated by replacing it with the time average as is often done in practice. Unlike the conventional quality measurement method using known symbols, equation (2) is executed for all received symbols, so a more accurate quality measurement result can be obtained.

It should be noted that the third-order or higher-order cumulant is theoretically 0 for the Gaussian signal, so that not only Kurtosis but also the third-order or higher-order cumulant can be used to perform the same non-Gaussian measurement.

[0063] Here, supplementary explanation will be given for cumulants. The statistic of signal X, kth moment (moment of moment), is expressed by equation (3). For example, the average of the first moment is given by equation (4).

[0064] [Equation 3]

E ^ ^k | = f X ^k p (X) dX (3)

[0065] [Equation 4] μ = / X-p (X) dX (4) In addition, the k-th moment around the mean expressed by equation (5) is often used.

[Equation 5]

[0066] The second moment is the variance σ. Note the k-th moment mu, appears at the coefficient when deployed tiller (6) Sekiritsu mother function number M (t) as equation _c [Equation 6]

Μ _χ (Χ ^ζ +

(6)

[0067] On the other hand, the k-th order cumulant K is the coefficient when the cumulant generating function K (t) that is the logarithm of the product moment generating function M (t) is Tiller-expanded as shown in Eq. (7). With the statistics obtained as

X

is there. Here, the 4th order cumulant is Kurtosis.

[Equation 7]

[0068] It is known that the 3rd-order or higher cumulant is 0 in the Gaussian distribution.

[0069] Kurtosis, a fourth-order cumulant, is a statistic whose value changes according to the sharpness of the probability density distribution, as shown in FIG. In other words, it is 0 for the Gaussian distribution, positive values for Super Gaussian, and negative values for Sub-Gaussian. Therefore, the absolute value of Kurtosis is a measure for non-Gaussianity, but since it includes the fourth power of the signal, the value changes sensitively even if an abnormal value is mixed even in one sample due to noise mixing. Lacks robustness. However, Kurtosis is often used because of its convenient properties as shown in Equation (8).

[Equation 8]

Kurt (x + y) = Kurt (x) + Kurt (y

Kurt (i3 x) 2 ⁴ Kurtix) (8)

[0070] The method of determining non-Gaussianity based on the higher-order cumulant absolute value presented in the present embodiment can be widely applied to quality measurement of received signals. For example, when measuring the quality of a separated signal in a MIMO receiver, it is determined that the higher the cumulant absolute value, the stronger the non-Gaussianity, that is, the separated signal quality (SINR) is high. be able to. (Embodiment 7)

This embodiment presents a preferred measurement method as a method for measuring non-Gaussianity. Specifically, we propose that the negentropy of the received signal be a non-Gaussian index.

[0072] The non-Gaussianity measuring method of the present embodiment calculates an approximate statistic called approximate negentropy represented by the following equation for the received signal, and the larger this value, the stronger the non-Gaussianity, that is, the signal Judged as high quality (SINR).

[Equation 9] Even function.

K „, k, is a positive constant as follows.

(9)

[0073] Here, in equation (9), it is assumed that z is normalized to an average of 0 and a variance of 1 before execution of the calculation. Ε [·] represents the set average. This set average Ε [·] should be calculated by replacing it with the time average as is often done in practice.

[0074] Fig. 10 shows the negentropy when the shape of the distribution is changed by the parameter μ in the probability density distribution shown in equation (10) and the approximate negentropy according to equation (9) under two conditions. is there. For any, Eq. (9) is a good approximation of negentropy under either condition.

[ _Equation 10] p (y) = β · Φ (γ) + (1—} 2φ (2 ( _Ύ -1), (1 0)

[0075] Note that G (y) = y ³ can be used for G (y) in equation (9).

0 0

If the rate density distribution function is an even function (if this condition is almost always satisfied in mobile communications), G (y) in Eq. (9) can be omitted and the approximate negentropy is ( 11)

0

It can be calculated by the formula.

[Equation 11] j (z) oc (E {G (Z)}-E {G (V)}) ² 'G (z> i even function

1

Here, V is a Gaussian signal according to the normal distribution <^ _v ) = ^ e ² and ζ is also normalized to mean 0 and variance 1.

■ 42%

(1 1)

[0076] As such an even function G (z), it is said that the equation (12) is effective.

[Equation 12]

G | z I 21 log cosh az, 1 <a≤ 2

_ _

G (z =-e ² (1 2)

[0077] Here, supplementary explanation of negentropy will be given. The entropy (average amount of information) that a continuous signal has is defined as in Eq. (13), and it is theoretically proven that the maximum value is obtained when the signal is Gaussian.

[Equation 13]

H (z) =-/ p (z} logp (z) dz (1 3)

[0078] Therefore, using this, a quantity called negentropy that is 0 when the signal has a Gaussian distribution and a positive value otherwise is devised as shown in equation (14). A large negentropy means that the non-Gaussian property of z is large, so it can be used as a measure of non-Gaussian property, and it has low sensitivity and robustness to outliers.

[Equation 14] ¾au _SS is a Gaussian signal with mean and variance equal to ^2.

However, in order to calculate negentropy, it is necessary to estimate the probability density function p (y) of the signal, and calculating as it is requires an enormous approximation and impractical approximation. One of the Negentropy approximation methods is a method based on the following polynomial approximation.

[Equation 15]

[0080] However, this method includes a kurtosis in the second term on the right side, so that a large approximation error occurs depending on the shape of the distribution as shown by the broken line in FIG.

[0081] As another method, there is a method that applies the concept of the maximum entropy method (hereinafter referred to as MEM) that has been applied for a long time in spectrum estimation and the like. MEM observes a random signal z using several observation functions G (z), G (z), ..., satisfies the observations, and

0 1

The distribution that maximizes the entropy of the signal (in other words, a distribution that can be considered without using any information other than the observed value) is the estimated value of the Z distribution.

[0082] The formula derived by applying this assumes that the distribution of z is a distribution that maximizes H (z), probably a distribution close to a Gaussian distribution, and estimates the lower limit of negentropy. For this reason, in Fig. 10, the approximate value is always smaller than the true value.

[0083] The method of determining non-Gaussianity by negentropy presented in this embodiment can be widely applied to the quality measurement of received signals. For example, when measuring the quality of the separated signal in a MIMO receiver, it is determined that the non-Gaussianity is more strongly separated as the negentropy value is larger, that is, the separated signal quality (SINR) is higher. Can do. Industrial applicability

[0084] The present invention is advantageous in that it is possible to easily perform highly accurate and stable reception signal quality measurement even when the reception signal includes a large amount of residual interference components. Device, receive diversity device, transmit diversity control, MIMO transmission system link It is useful when applied to quadration, transmission power control, path quality measurement, and the like.

Claims

The scope of the claims

[1] Measure the non-Gaussianity of the signal distribution of the received signal, and determine that the quality of the received signal is better as the non-Gaussianity is larger!

Reception quality measurement method.

[2] The reception quality measurement method according to claim 1, wherein the non-Gaussian property is measured based on a high-order cumulant absolute value of the reception signal.

[3] Measure the non-Gaussianity based on negentropy

The reception quality measurement method according to claim 1.