CN101958852A - Method and device for estimating CINR of MLD receiver in MIMO system - Google Patents

Abstract

The invention discloses a method and a device for estimating carrier to interference noise ratio (CINR) of a maximum likelihood detector (MLD) receiver in a multiple input multiple output (MIMO) system. The method comprises the following steps of: for each transmitting signal, acquiring wireless channel response of the transmitting signal to a plurality of receiving antennas and covariance of noise and interference, wherein the interference covariance is the sum of wireless channel united response of other transmitting signals; and for each transmitting signal, calculating the CINR of the transmitting signal according to the wireless channel response and the covariance of noise and interference. The device comprises a channel response acquisition module, a covariance acquisition module and a CINR calculation module for calculating the CINR of the transmitting signal according to the wireless channel response and the covariance of noise and interference for each transmitting signal. The method and the device implement CINR estimation of the MLD receiver, and also can estimate multiple users.

Description

The CINR method of estimation and the device of MLD receiver in a kind of mimo system

Technical field

The present invention relates to the digital communication field, specifically, relate to a kind of multiple-input, multiple-output (Multiple Input Multiple Output, MIMO) Maximum Likelihood Detection (Maximum Likelihood Detector in the system, MLD) the carrier-in-interference noise ratio of receiver (Carrier to Interference Noise Ratio, method of estimation CINR) and device.

Background technology

(Carrier to Interference Noise Ratio CINR) is the ratio of the power of signal power and interference plus noise to the carrier-in-interference noise ratio, and it is the important parameter of reflection channel quality.The estimation of CINR has crucial meaning, and system can adjust coded system and transmitting power etc. according to CINR.

As a kind of multi-antenna technology, (Multiple Input Multiple Output, MIMO) system principal character is exactly thinking that on traditional sense harmful signal multipath transmisstion changes favorable factor in multiple-input, multiple-output.It made full use of channel in time random fading and multidiameter expand and improve transmission speed exponentially, do not need to increase simultaneously the bandwidth (just increasing the complexity of software and hardware) of system.Because mimo system remains the signal on the many antennas of Combinatorial Optimization, so maintain the advantage of smart antenna, also has bigger spatial degrees of freedom simultaneously.Owing to use array antenna to have the array gain at transmitting terminal or receiving terminal, the MIMO technology is owing to using many antennas to have associating send-receive diversity gain simultaneously at transmitting terminal and receiving terminal as smart antenna.

In mimo system, data are launched with matrix form, and this matrix emission form can be brought other advantage.Under certain condition, (M, N) bar independent symbols (data) stream can transmission (the matrix channel here is forming with M root reception antenna by the N transmit antennas) in matrix channel simultaneously for min.By linear transformation, matrix channel can be transformed into the form (being the matrix channel form of decorrelation) of several intrinsic mode (eigenmodes).(Spatial Multiplexing SM) just is to use the mimo system of this advantage to space multiplexing technique.

Because these advantages of mimo system, at 3G, in the Wimax technology such as (Worldwide Interoperability for Microwave Access, micro-wave access global inter communications), MIMO is widely used.But for the SM receiving terminal, the merging data after need be to solution space multiplexing carries out CINR and estimates that according to this CINR, MAC (Medium Access Control Layer, media access control layer) will adjust power control and modulation coding mode.

The comprehensive present multiplexing detection algorithm of various solution spaces, Maximum Likelihood Detection (Maximum Likelihood Detector, MLD) preferable performance is arranged, but because MLD is a kind of nonlinear algorithm, that it obtains after MIMO-decoder is the LLR (log-likelihood ratio) of bit stream, and FEC-decoder uses the LLR of bit stream to decipher the bit information that obtains transmitting terminal.Because the LLR of bit stream is the log-likelihood ratio that is used for channel decoding, does not have the power features of signal, thereby can't calculate CINR.

Therefore, in conjunction with the characteristics of MLD solution space multiplex technique, need obtain the method for the CINR of the signal of a kind of MLD solution space after multiplexing.

Summary of the invention

Because above-mentioned background, the invention provides a kind of method of estimation and device of carrier-in-interference noise ratio, the signal after can be to the MLD solution space multiplexing carries out CINR and estimates.

In order to solve the problems of the technologies described above, the present invention has adopted following technical scheme:

The carrier-in-interference noise ratio method of estimation of Maximum Likelihood Detection receiver transmits for each in a kind of mimo systems, comprises following steps:

A, obtain this and transmit signals to the radio channel response of many reception antennas and the covariance of noise-plus-interference; Wherein, disturb covariance to be the autocorrelative summation of other radio channel response that transmit;

B, the radio channel response that obtains according to steps A and the covariance of noise-plus-interference are calculated the carrier-in-interference noise ratio that this transmits, i.e. CINR.

In a kind of embodiment of said method, described each carrier-in-interference noise ratio that transmits adopts following formula to calculate:

Wherein, CINR _nBe n carrier-in-interference noise ratio that transmits, h _nBe n radio channel response that transmits signals to many reception antennas,

Be n transposed matrix that transmits signals to the radio channel response of many reception antennas, σ ²I is a noise covariance,

Be the autocorrelative summation of other radio channel response that transmit.

In a kind of embodiment of said method, described formula

Merge by high specific

Obtain, each described high specific that transmits merges

Covariance and reception merging data according to this radio channel response that transmits, noise-plus-interference calculate, wherein, the reception merging data of described many signals is the summation of the receiver noise of each received signal that transmits and many reception antennas.

In a kind of embodiment of said method, described high specific merges

Adopt following formula to calculate:

Be n transposed matrix that transmits signals to the radio channel response of many reception antennas, σ ²I is a noise covariance,

Be the autocorrelative summation of other radio channel response that transmit, r is the reception merging data,

Be each received signal sum that transmits, n is the receiver noise of many reception antennas.

The invention also discloses the carrier-in-interference noise ratio estimation unit of Maximum Likelihood Detection receiver in a kind of mimo systems, comprise:

The channel response acquisition module is used for each is transmitted, and obtains the radio channel response that this transmits signals to many reception antennas;

The covariance acquisition module is used for each is transmitted, and obtains the covariance of this noise-plus-interference that transmits; Wherein, disturb covariance to be the autocorrelative summation of other radio channel response that transmit;

Carrier-in-interference noise ratio computing module is used for each is transmitted, and according to the covariance of its radio channel response and noise-plus-interference, calculates the carrier-in-interference noise ratio that this transmits.

The present invention is with least mean-square error (Minimum Mean Squared Error, MMSE) CINR of receiver estimates to simulate the CINR estimation that approaches the MLD receiver, and in approaching calculating, for a plurality of users in the mimo systems, at transmitting of targeted customer, transmitting of other users is considered as this targeted customer's interference, and contribute in this targeted customer's the interference covariance, radio channel response by the targeted customer, the covariance of noise-plus-interference, calculate targeted customer's CINR, thereby, can estimate the CINR of different user for the MLD receiver.

Description of drawings

The description that Fig. 1 is exemplary a kind of typical mimo system framework;

The description that Fig. 2 is exemplary CINR of the present invention estimate flow process;

The description that Fig. 3 is exemplary the structure of CINR estimation unit of the present invention.

Embodiment

Below in conjunction with accompanying drawing the specific embodiment of the present invention is elaborated.

The present invention relates generally to the CINR method of estimation based on the signal of the SM technology reception of MIMO, and this CINR method can realize that the CINR of MLD receiver estimates, can estimate a plurality of different users simultaneously.

In the SM of MIMO system, can equivalence a plurality of user's data streams are regarded as mutual interference, the process equivalence of separating SM is the multi-user data detection.Use H-BLAST[BLAST with SM, Bell Labs Layered Space-Time, demixing time space, comprising H-BLAST (horizontal Space Time Coding), V-BLAST (vertical Space Time Coding), D-BLAST (diagonal angle Space Time Coding)] a plurality of data flow of coding are example, need estimate the CINR of each comfortable solution space of each data flow after multiplexing.

The solution space multiplex receiver can be divided into linear receiver and non-linear receiver.As described above, because MLD is non-linear receiver, the LLR of its bit stream is a mathematics statistic, does not have the power features of signal, thereby can't calculate the CINR of the multiplexing back of each road solution space data flow.Linear receiver then can calculate the CINR of each circuit-switched data stream of the multiplexing back of linear receiver solution space by the channel response of signal, in view of this, the present invention has conceived the account form of " changing directly for indirect ", by investigating relatively, determined least mean-square error (Minimum Mean Squared Error, MMSE) the solution space multiplexing performance of receiver and MLD receiver are the most approaching, thereby adopt the mode of MMSE receiver analog computation.

The MMSE receiver is a kind of linear receiver, and what obtain after its solution space is multiplexing is modulation symbol, carries the power features of signal, thereby can be used for calculating CINR.The CINR of MMSE receiver better calculates, and can approach the CINR of the signal of MLD solution space after multiplexing preferably.

As shown in Figure 1, among the figure exemplary description typical mimo system framework, this paper repeats no more Elementary Function and the working method thereof that wherein is well known to those skilled in the art, and only estimates that at CINR relevant portion describes.

As shown in Figure 2, the description of this illustrated example CINR of the present invention estimate flow process, mainly comprise:

S01, transmit, obtain this and transmit signals to the radio channel response of many reception antennas and the covariance of noise-plus-interference for each; Wherein, disturb covariance to be the autocorrelative summation of other radio channel response that transmit;

S02, transmit,, calculate the carrier-in-interference noise ratio that this transmits according to the covariance of its radio channel response and noise-plus-interference for each.

Usually mimo system comprises many transmit antennas, independent data stream of every transmit antennas emission, the data flow of each transmit antennas can adopt different modulation coding modes or belong to different users, for convenience of description, in this article, transmitted signal streams on one transmit antennas is equivalent to a user, and user hereinafter promptly refers to the transmitted signal streams on the transmit antennas; MIMO also comprises many reception antennas, and every reception antenna all receives the wireless signal of a plurality of data flow after spatial coherence merges on many transmit antennas, obtains transmitted signal streams on each road transmitting antenna by the solution space multiplexing algorithm at receiving terminal.

Being without loss of generality, at first is that example describes with two users.Two users' the data flow that transmits all adopts the H-BLAST coded system:

$\left[\begin{array}{c}{r}_1\\ r_2\\ .\\ .\\ .\\ r_{N_{\mathrm{RX}}}\end{array}\right]=\left[\begin{array}{cc}{h}_{11}& h_{12}\\ h_{21}& h_{22}\\ .& .\\ .& .\\ .& .\\ h_{N_{\mathrm{RX}}1}& h_{N_{\mathrm{RX}}2}\end{array}\right]\left[\begin{array}{c}{s}_1\\ s_2\end{array}\right]+\left[\begin{array}{c}{n}_1\\ n_2\\ .\\ .\\ .\\ n_{N_{\mathrm{RX}}}\end{array}\right]---\left(2.1\right)$

Simple for following discussion, might as well make:

$r=\left[\begin{array}{c}{r}_1\\ r_2\\ .\\ .\\ .\\ r_{N_{\mathrm{RX}}}\end{array}\right],$ $h_1=\begin{array}{c}\left[\begin{array}{c}{h}_{11}\\ h_{21}\\ .\\ .\\ .\\ h_{N_{\mathrm{RX}}1}\end{array}\right],\end{array}$ $h_2=\left[\begin{array}{c}{h}_{12}\\ h_{22}\\ .\\ .\\ .\\ h_{N_{\mathrm{RX}}2}\end{array}\right],$ $n=\left[\begin{array}{c}{n}_1\\ n_2\\ .\\ .\\ .\\ n_{N_{\mathrm{RX}}}\end{array}\right]---\left(2.2\right)$

Wherein, r is N _Rx* 1 reception column vector, N _RxBe the reception antenna number, s ₁, s ₂Represent two data flow of H-BLAST to transmit h respectively ₁The expression s emission signal s ₁To N _RxThe radio channel response of root reception antenna, h ₂The expression s emission signal s ₂To N _RxThe radio channel response of root reception antenna, n represents N _RxReceiver noise on the root reception antenna, under above-mentioned mark, formula (2.1) becomes:

r＝h ₁s ₁+h ₂s ₂+n (2.3)

Can see that r is a s emission signal s ₁Received signal h ₁s ₁, s emission signal s ₂Received signal h ₂s ₂, and the summation of receiver noise n, at this, r is defined as the reception merging data.

For user MS1:

r＝h ₁s ₁+n′

n′＝h ₂s ₂+n (A1)

Also promptly, in the present invention, for a certain user, other users' received signal is considered as this user's interference.Thus, the covariance matrix of noise+interference of calculating user MS1 is:

${\mathrm{\Σ}}_1=D+h_2{h}_2^H---\left(A2\right)$

Also promptly, the covariance of noise+interference of user MS1 comprises noise covariance D and disturbs covariance

At this, will

Be defined as s emission signal s ₂The radio channel response auto-correlation.

Under above-mentioned mark, use to disturb suppress the back high specific merge (Interference Restrain Combine, IRC) receiver, the high specific that obtains MS1 merge (Maximal Ratio Combine MRC) is:

${\tilde{s}}_1=h_1^H{\mathrm{\Σ}}_1^{-1}r=h_1^H{({\mathrm{\σ}}^{2}I+h_2{h}_2^H)}^{-1}r---\left(A3\right)$

Here,

Be equivalent to n '=h ₂s ₂+ n albefaction is a white noise, just can do the high specific merging to each antenna afterwards and obtain Also promptly, the high specific of MS1 merges

S emission signal s for MS1 ₁To N _RxThe transposed matrix of the radio channel response of root reception antenna

The inverse matrix of the covariance matrix of noise+interference of MS1

And the product that receives merging data r.

In like manner, obtain the high specific merging of user MS2:

${\mathrm{\Σ}}_2={\mathrm{\σ}}^{2}I+h_1{h}_1^H---\left(A4\right)$

${\tilde{s}}_2=h_2^H{\mathrm{\Σ}}_2^{-1}r=h_2^H{({\mathrm{\σ}}^{2}I+h_1{h}_1^H)}^{-1}r---\left(A5\right)$

In view of the above, by CINR=P _s/ N _s, wherein, P _sAnd N _sBe respectively high specific combined signal power and the ratio of noise power, the CINR that can obtain two MS same sub-carrier is as follows:

${\mathrm{CINR}}_1=h_1^H{({\mathrm{\σ}}^{2}I+h_2{h}_2^H)}^{-1}{h}_1---\left(A6\right)$

${\mathrm{CINR}}_2=h_2^H{({\mathrm{\σ}}^{2}I+h_1{h}_1^H)}^{-1}{h}_2---\left(A7\right)$

Formula (A2) and (A4) in the matrix ∑ ₁And ∑ ₂All be N _RX* N _RXMatrix, all be 4 * 4 matrix such as these two matrixes under the situation of four antennas, the inversion operation more complicated of this matrix, but utilize formula (A2) and structure (A4) can simplify the computing of matrix inversion.According to matrix inversion lemma (Matrix Inverse Lemma)

${(A+{\mathrm{uv}}^H)}^{-1}=A^{-1}-\frac{A^{-1}{\mathrm{uv}}^H{A}^{-1}}{1+v^H{A}^{-1}u}---\left(A8\right)$

Can obtain:

${({\mathrm{\σ}}^{2}I+h_k{h}_k^H)}^{-1}={\left({\mathrm{\σ}}^{2}I\right)}^{-1}-\frac{{\left({\mathrm{\σ}}^{2}I\right)}^{-1}{h}_k{h}_k^H{\left({\mathrm{\σ}}^{2}I\right)}^{-1}}{1+h_k^H{\left({\mathrm{\σ}}^{2}I\right)}^{-1}{h}_k};k=\mathrm{1,2}$

${({\mathrm{\σ}}^{2}I+h_k{h}_k^H)}^{-1}=D^{-1}-\frac{D^{-1}{h}_k{h}_k^H{D}^{-1}}{1+\underset{n=1}{\overset{N_{\mathrm{RX}}}{\mathrm{\Σ}}}\frac{h_{\mathrm{nk}}^{*}{h}_{\mathrm{nk}}}{{\mathrm{\σ}}_n^2}}=D^{-1}-\frac{\left(D^{-1}{h}_k\right)\left(h_k^H{D}^{-1}\right)}{1+\underset{n=1}{\overset{N_{\mathrm{RX}}}{\mathrm{\Σ}}}\frac{h_{\mathrm{nk}}^{*}{h}_{\mathrm{nk}}}{{\mathrm{\σ}}_n^2}};k=\mathrm{1,2}---\left(A10\right)$

Here

Use D ^-1Be the particularity of diagonal matrix and vector operation, can be reduced to:

$D^{-1}{h}_k{h}_k^H{D}^{-1}=\left(D^{-1}{h}_k\right)\left(h_k^H{D}^{-1}\right)$

Wherein $D^{-1}{h}_k=\left[\begin{array}{c}\frac{1}{{\mathrm{\σ}}_1^2}{h}_{1k}\\ \frac{1}{{\mathrm{\σ}}_2^2}{h}_{2k}\\ .\\ .\\ .\\ \frac{1}{{\mathrm{\σ}}_{N_{\mathrm{RX}}}^2}{h}_{N_{\mathrm{RX}}k}\end{array}\right],$ $h_k^H{D}^{-1}=\left[\begin{array}{cccc}\frac{1}{{\mathrm{\σ}}_1^2}{h}_{1k}^{*}& \frac{1}{{\mathrm{\σ}}_2^2}{h}_{2k}^{*}& \·\·\·& \frac{1}{{\mathrm{\σ}}_{N_{\mathrm{RX}}}^2}{h}_{N_{\mathrm{RX}}k}^{*}\end{array}\right]$

Can obtain:

${\mathrm{CINR}}_1=h_1^H(D^{-1}-\frac{\left(D^{-1}{h}_2\right)\left(h_2^H{D}^{-1}\right)}{1+\underset{n=1}{\overset{N_{\mathrm{RX}}}{\mathrm{\Σ}}}\frac{h_{n2}^{*}{h}_{n2}}{{\mathrm{\σ}}_n^2}})h_1$

${\mathrm{CINR}}_2=h_2^H(D^{-1}-\frac{\left(D^{-1}{h}_1\right)\left(h_1^H{D}^{-1}\right)}{1+\underset{n=1}{\overset{N_{\mathrm{RX}}}{\mathrm{\Σ}}}\frac{h_{n1}^{*}{h}_{n1}}{{\mathrm{\σ}}_n^2}})h_2---\left(A11\right)$

Here

Be the power of making an uproar the end of n root reception antenna.

Above-mentioned stream with two user's data estimated to be illustrated to CINR of the present invention, below it is generalized to n signal flow:

Order:

$r=\left[\begin{array}{c}{r}_1\\ r_2\\ .\\ .\\ .\\ r_{N_{\mathrm{RX}}}\end{array}\right],$ $h_1=\begin{array}{c}\left[\begin{array}{c}{h}_{11}\\ h_{21}\\ .\\ .\\ .\\ h_{N_{\mathrm{RX}}1}\end{array}\right],\end{array}$ $h_2=\begin{array}{c}\left[\begin{array}{c}{h}_{12}\\ h_{22}\\ .\\ .\\ .\\ h_{N_{\mathrm{RX}}2}\end{array}\right],\end{array}\·\·\·,$ $h_n=\begin{array}{c}\left[\begin{array}{c}{h}_{1n}\\ h_{2n}\\ .\\ .\\ .\\ h_{N_{\mathrm{RX}}n}\end{array}\right],\end{array}\·\·\·,$ $h_{N_{\mathrm{TX}}}=\left[\begin{array}{c}{h}_{1N_{\mathrm{TX}}}\\ h_{2N_{\mathrm{TX}}}\\ .\\ .\\ .\\ h_{N_{\mathrm{RX}}{N}_{\mathrm{TX}}}\end{array}\right],$ $n=\left[\begin{array}{c}{n}_1\\ n_2\\ .\\ .\\ .\\ n_{N_{\mathrm{RX}}}\end{array}\right]$

Meaning the same, then

$r=h_1{s}_1+h_2{s}_2+\·\·\·+h_n{s}_n+\·\·\·+h_{N_{\mathrm{TX}}}{s}_{N_{\mathrm{TX}}}+n---\left(2.5\right)$

Transmit for n:

r＝h _ns _n+n′

$n^{\′}=\underset{i\≠n}{\overset{N_{\mathrm{TX}}}{\underset{i=1}{\mathrm{\Σ}}}}{h}_i{s}_i+n$

The covariance matrix of interference plus noise is:

${\mathrm{\Σ}}_n=D+\underset{i\≠n}{\overset{N_{\mathrm{TX}}}{\underset{i=1}{\mathrm{\Σ}}}}{h}_i{h}_i^H$

Adopt the derivation identical with aforementioned two users, the CINR value that can obtain the nth user is:

${\mathrm{CINR}}_n=h_n^H{({\mathrm{\σ}}^{2}I+\underset{i\≠n}{\overset{N_{\mathrm{TX}}}{\underset{i=1}{\mathrm{\Σ}}}}{h}_i{h}_i^H)}^{-1}{h}_n.$

The description CINR estimation unit of the present invention that Fig. 3 is exemplary, it mainly comprises:

The channel response acquisition module is used for each is transmitted, and obtains the radio channel response that this transmits signals to many reception antennas;

The covariance acquisition module is used for each is transmitted, and obtains the covariance of this noise-plus-interference that transmits; Wherein, disturb covariance to be the autocorrelative summation of other radio channel response that transmit;

Carrier-in-interference noise ratio computing module is used for each is transmitted, and according to the covariance of its radio channel response and noise-plus-interference, calculates the carrier-in-interference noise ratio that this transmits.

Similar aforementioned, carrier-in-interference noise ratio computing module is to adopt following formula to calculate each carrier-in-interference noise ratio that transmits:

Wherein, CINR _nBe n carrier-in-interference noise ratio that transmits, h _nBe n radio channel response that transmits signals to many reception antennas,

Be n transposed matrix that transmits signals to the radio channel response of many reception antennas, σ ²I is a noise covariance,

Be the autocorrelative summation of other radio channel response that transmit.

Carrier-in-interference noise ratio computing module comprises the high specific joint account unit that is used to calculate the high specific merging, formula The high specific that calculates according to high specific joint account unit merges acquisition, and the high specific merge cells adopts following formula to calculate the high specific merging:

Wherein,

Be that n high specific that transmits run jointly,

Be n transposed matrix that transmits signals to the radio channel response of many reception antennas, σ ²I is a noise covariance,

Be the autocorrelative summation of other radio channel response that transmit, r is the reception merging data,

Be each received signal sum that transmits, n is the receiver noise of many reception antennas.

The present invention adopts the mode of MMSE receiver analog computation, thereby the CINR that can carry out the MLD receiver estimates, only need the channel estimating unit in Fig. 1 carry out just can finishing the CINR estimation after the channel estimating, and do not need MLD receiver flow process is changed or carry out some special processings by the CINR unit.And the present invention can carry out CINR to a plurality of different users and estimate.In CINR estimates, adopting high specific to merge calculates, nominal more accurately goes out the influence of other data flow to current data stream, better approach the CINR estimated value of the multiplexing back of MLD receiver solution space data, have higher CINR estimated accuracy, thereby help utilizing the CINR estimated value to carry out relevant treatment such as power control.

Above content be in conjunction with concrete preferred implementation to further describing that the present invention did, but this example of just lifting for ease of understanding should not think that concrete enforcement of the present invention is confined to these explanations.For the general technical staff of the technical field of the invention, without departing from the inventive concept of the premise, can make various possible being equal to and change or replacement, these changes or replacement all should belong to protection scope of the present invention.

Claims (8)

1. the carrier-in-interference noise ratio method of estimation of Maximum Likelihood Detection receiver in the mimo systems is characterized in that, transmits for each, comprises following steps:

A, obtain this and transmit signals to the radio channel response of many reception antennas and the covariance of noise-plus-interference; Wherein, disturb covariance to be the autocorrelative summation of other radio channel response that transmit;

B, the radio channel response that obtains according to steps A and the covariance of noise-plus-interference are calculated the carrier-in-interference noise ratio that this transmits, i.e. CINR.

2. the method for claim 1 is characterized in that, described each carrier-in-interference noise ratio that transmits adopts following formula to calculate:

Wherein, CINR _nBe n carrier-in-interference noise ratio that transmits, h _nBe n radio channel response that transmits signals to many reception antennas,

Be n transposed matrix that transmits signals to the radio channel response of many reception antennas, σ ²I is a noise covariance, Be the autocorrelative summation of other radio channel response that transmit.

3. method as claimed in claim 2 is characterized in that, described formula

Merge by high specific

Obtain, each described high specific that transmits merges Covariance and reception merging data according to this radio channel response that transmits, noise-plus-interference calculate, wherein, the reception merging data of described many signals is the summation of the receiver noise of each received signal that transmits and many reception antennas.

4. method as claimed in claim 3 is characterized in that, described high specific merges Adopt following formula to calculate:

Be n transposed matrix that transmits signals to the radio channel response of many reception antennas, σ ²I is a noise covariance,

Be the autocorrelative summation of other radio channel response that transmit, r is the reception merging data,

Be each received signal sum that transmits, n is the receiver noise of many reception antennas.

5. the carrier-in-interference noise ratio estimation unit of Maximum Likelihood Detection receiver in the mimo systems is characterized in that, comprises:

The channel response acquisition module is used for each is transmitted, and obtains the radio channel response that this transmits signals to many reception antennas;

The covariance acquisition module is used for each is transmitted, and obtains the covariance of this noise-plus-interference that transmits; Wherein, disturb covariance to be the autocorrelative summation of other radio channel response that transmit;

Carrier-in-interference noise ratio computing module is used for each is transmitted, and according to the covariance of its radio channel response and noise-plus-interference, calculates the carrier-in-interference noise ratio that this transmits.

6. device as claimed in claim 5 is characterized in that, described carrier-in-interference noise ratio computing module is to adopt following formula to calculate each carrier-in-interference noise ratio that transmits:

Wherein, CINR _nBe n carrier-in-interference noise ratio that transmits, h _nBe n radio channel response that transmits signals to many reception antennas,

Be n transposed matrix that transmits signals to the radio channel response of many reception antennas, σ ²I is a noise covariance, Be the autocorrelative summation of other radio channel response that transmit.

7. device as claimed in claim 6, it is characterized in that, described carrier-in-interference noise ratio computing module comprises high specific joint account unit, be used for calculating the high specific merging, merge the described formula of acquisition according to described high specific according to the covariance and the reception merging data of this radio channel response that transmits, noise-plus-interference Wherein, described reception merging data is the summation of the receiver noise of each received signal that transmits and many reception antennas.

8. device as claimed in claim 7 is characterized in that, described high specific joint account unit is to adopt following formula to calculate high specific to merge:

Wherein,

Be that n high specific that transmits merges,

Be n transposed matrix that transmits signals to the radio channel response of many reception antennas, σ ²I is a noise covariance,

Be the autocorrelative summation of other radio channel response that transmit, r is the reception merging data,

Be each received signal sum that transmits, n is the receiver noise of many reception antennas.

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