CN104796239A - MIMO wireless communication system, MIMO signal detecting device and signal detecting method - Google Patents

Abstract

The invention provides an MIMO wireless communication system, an MIMO signal detecting device and a signal detecting method, wherein the MIMO signal detecting device comprises a search tree conversion unit, a search unit, a node selection unit, a node calculation unit and a three shearing/updating unit. Based on an optimal colored channel noise model, the complexity of the MIMO signal detecting device of the invention is relatively low while the performance thereof is almost equal to the performance of the ergodic search. The signal detecting method of the invention reduces search complexity under the condition of considering channel estimation error and ensures performance of communication simultaneously.

Description

A kind of mimo wireless communication system and signal supervisory instrument and method

Technical field

The present invention relates to communication technical field, particularly relate to a kind of mimo wireless communication system and signal supervisory instrument and method.

Background technology

Forth generation mobile communication (4G) and the 5th Generation Mobile Communication System (5G) afterwards, such as 3GPP LTE (Long term evaluation)/LTE-Advanced.Multiple-input, multiple-output (MIMO is used at UE (user equipment) receiver place, multiple-input multiple-output) and OFDM (OFDM, orthogonal frequency-division multiplexing) access scheme high data rate in down link is provided.In LTE, such as, UE type (UE category) 6 (supporting 4x4MIMO), down link can support the data rate up to 300Mbps; Such as, and in LTE-A, UE type 8, down link can be supported up to 3Gbps (gigabits/second), namely up to the data rate of 8 layers.

5G communication system target improves frequency usage rate, provides higher data rate with this.Such as, carrier aggregation (CA, carrier aggregation) can be adopted, or mixed networking mode (HetNets, heterogeneousnetworks).The general principle of above-mentioned technology is to improve frequency usage rate, but can cause strong jamming and affect performance in actual applications.In a wireless communication system, Multiuser Detection is effective Anti-Jamming Technique.In addition, nonopiate access (NOMA, non-orthogonal multiple access) etc. is widely used in overcoming the performance degradation disturbed and bring.MIMO signal detector is also widely used in above-mentioned technology.

In wireless communication receiver, MIMO signal detector is responsible for the detection of signal vector and the demodulation of constellation pattern.High-performance but the MMO signal detector of low complex degree are the keys that the reliable high data rate met in 4G and 5G communication system under above-mentioned typical scene requires.On the other hand, MIMO signal detects needs to obtain enough high-precision channel condition information (CSI, channel state information).For this reason, channel estimating is required.Typical case 4G communication system is by receiving some known reference signals for estimating CSI.Because the reference signal of limited quantity is by actual noise transmission, receiver only may obtain nonideal channel estimating, this causes MIMO signal detector to have to carry out complicated Digital Signal Processing to obtain reliable detection perform, and its complexity becomes the extensive practical bottleneck of MIMO technology.

MIMO signal detection method in current consideration channel estimation errors situation mainly contains following three kinds: first method is in signal detection process, suppose that channel estimating is perfect.The method have ignored channel estimation errors completely, is therefore also referred to as detection of mismatch.Detection of mismatch computation complexity is lower, but ignoring channel estimation errors causes MIMO signal detector can not provide gratifying detection perform, particularly when channel estimation errors is larger.

Second method is hypothesis channel estimation errors is white Gaussian noise (WEN, white estimationnoise), then according to the Gaussian distribution model of effective observation noise, adopt tree search algorithm (comprising spherical detection algorithm) calculate often transmit this spy log-likelihood this to reduce the impact of channel estimation errors.Tree search algorithm significantly can reduce algorithm complex while the best possibility predication performance of guarantee.But because channel estimation errors depends on symbol constellations, its detection model does not also meet white Gaussian noise distribution, and unsuitable distributed model is selected also will affect actual signal Detection results.

The third method is traversal search algorithm under the detection model of coloured noise based on channel estimation errors.Power spectral density uneven distribution on whole frequency domain of coloured noise, white noise is then uniformly distributed.In systems in practice, coloured noise is more common.The known ML based on coloured interchannel noise estimation (CEN, coloredestimation noise) estimates it is Optimum signal detection model.MIMO signal detector based on this model can provide optimum performance.But traversal search algorithm complex is along with the increase exponential increase of antenna amount and constellation order, so be not suitable for practical application.Such as, LTE/LTE-A supports 4x464QAMMIMO, and extends to 8x8256QAM MIMO, and this makes the computation complexity that this spy is often transmitted in its demodulation be about 1.6 × 10 separately ⁷with 1.8 × 10 ¹⁹mAC (multiply-accumulate).The possible digital of this numeral super prior art far away.

Existing MIMO signal detector generally adopts tree search signal detector (comprising ball-type detector).Existing tree search signal detector is all based on white noise parameter model, and namely noise parameter is constant.

Therefore, for the problems referred to above, be necessary to propose further solution.

Summary of the invention

The object of the present invention is to provide a kind of mimo wireless communication system and signal supervisory instrument and method, to overcome the deficiencies in the prior art.

For achieving the above object, a kind of MIMO signal checkout gear provided by the invention, it comprises: search tree converting unit, search unit, sensor selection problem unit, node calculate unit, hedge clipper cut/updating block;

Described search tree converting unit, it is for by N _r× N _tmimo system and respective channel are estimated to be converted to N with channel estimation error variance _tthe search tree of+1 layer;

Described search unit, it is for judging whether current detection node layer exists sublayer node and be not detected, in this way, advance to corresponding sublayer node to detect, otherwise, retreat the father's node layer to current detection node layer, when not having node be not detected or do not need to be detected, search unit stops;

Described sensor selection problem unit, it for determining nodal test order in the node of sublayer;

Described node calculate unit, it, for according to described nodal test order, calculates the coloured noise parameter of respective nodes and corresponding Testing index value successively; This coloured noise calculation of parameter depends on corresponding the transmitting of father's node layer of described node;

Described hedge clipper cuts/updating block, its for the Testing index value of this respective nodes with prune variable γ, variable γ is pruned when nodal test desired value is greater than, respective nodes and all child nodes thereof are cut off by from tree structure, otherwise, prune the Testing index value that namely variable γ is updated to respective nodes.

As the improvement of MIMO signal checkout gear of the present invention, in described node calculate unit, the coloured noise calculation of parameter of described node does not rely on corresponding the transmitting of sublayer node of described node.

As the improvement of MIMO signal checkout gear of the present invention, in described node calculate unit, calculate the floor value of the Testing index of described node.

For achieving the above object, a kind of mimo wireless communication system that the present invention also provides, it comprises: transmitter and receiver;

Described transmitter comprises: information source produces end, encoder, modulator, serioparallel exchange unit;

Described receiver comprises: MIMO signal checkout gear, parallel serial conversion unit, decoder as claimed in claim 1.

As the improvement of mimo wireless communication system of the present invention, the Mathematical Modeling of described mimo wireless communication system is: r=Hx+n, wherein, and r=[r ₁, r ₂... r _nr] ^tn _r× 1 dimension complex received signal vector, x=[x ₁, x ₂... x _nt] ^tn _t× 1 dimension transmission signal vector, wherein x _ifor independently choosing from a limited constellation of complex pattern, described H is N _r× N _tthe plural wireless channel matrix of dimension.

As the improvement of mimo wireless communication system of the present invention, described constellation pattern is any one in QPSK, 16QAM, 64QAM and 256QAM.

For achieving the above object, a kind of signal detecting method that the present invention also provides, it is according to constellation modulation system, channel estimating and channel estimation error variance v ², complete the detection to MIMO signal, and export the log-likelihood ratio of the every transmitted bit sending signal.

Particularly, described method comprises the steps:

S1. by N _r× N _tmimo system and respective channel are estimated with channel estimation error variance v ²be converted to N _tthe search tree of+1 layer;

S2. judge whether current detection node layer exists sublayer node and be not detected, in this way, advance to corresponding sublayer node and detect, otherwise, retreat the father's node layer to current detection node layer, when not having node be not detected or do not need to be detected, search unit stops;

S3. in the node of sublayer, determine nodal test order;

S4. according to described nodal test order, the coloured noise parameter of respective nodes and corresponding Testing index value is calculated successively; This coloured noise calculation of parameter depends on corresponding the transmitting of father's node layer of described node;

S5. contrast the Testing index value of respective nodes and pruning variable γ, prune variable γ when nodal test desired value is greater than, respective nodes and all child nodes thereof are cut off by from tree structure, otherwise, prune the Testing index value that namely variable γ is updated to respective nodes.

As the improvement of signal detecting method of the present invention, this expression formula of described log-likelihood is:

$L=\left(C_{\mathrm{ij}}\right|r)=\underset{{x\∈x}_{\mathrm{ij}}^{-1}}{\min }\mathrm{\Λ}\left(x\right)-\underset{{x\∈x}_{\mathrm{ij}}^{+1}}{\min }\mathrm{\Λ}\left(x\right),$

Wherein, Λ (x) is Testing index, and the expression formula of described Λ (x) is as follows:

$\begin{array}{c}\mathrm{\Λ}\left(x\right)=\frac{{\left|\right|r-\hat{H}\mathrm{\Ξx}\left|\right|}^2}{{\mathrm{\σ}}_n^2+{\mathrm{\Σ}}_{k=1}^{N_t}(1-{\mathrm{\ξ}}_k){\left|\right|x_k\left|\right|}^2}\\ +N_r\log \mathrm{\π}({\mathrm{\σ}}_n^2+{\mathrm{\Σ}}_{k=1}^{N_t}(1-{\mathrm{\ξ}}_k){\left|\right|x_k\left|\right|}^2)\end{array}.$

As the improvement of signal detecting method of the present invention, in described step S3, according to the principle of depth-first or the principle of breadth-first, in the node of sublayer, determine nodal test order.

As the improvement of signal detecting method of the present invention, in described step S4, the coloured noise calculation of parameter of described node does not rely on corresponding the transmitting of sublayer node of described node.

As the improvement of signal detecting method of the present invention, the expression formula of the Testing index of the respective nodes in described step S4 is as follows:

$\begin{array}{c}\mathrm{\Λ}\left(x_m\right)=\frac{1}{{{\mathrm{\σ}}_n^2+\mathrm{\Σ}}_{k=m}^{N_t}(1-{\mathrm{\ξ}}_k){\left|\right|x_k\left|\right|}^2+{\mathrm{\θ}}_m}{\mathrm{\Σ}}_{k=m}^{N_t-1}{\mathrm{\λ}}_m\\ +N_r\log \mathrm{\π}({\mathrm{\σ}}_n^2+{\mathrm{\Σ}}_{k=m}^{N_t}(1-{\mathrm{\ξ}}_k){\left|\right|x_k\left|\right|}^2+{\mathrm{\θ}}_m)\end{array}.$

As the improvement of signal detecting method of the present invention, described step S4 calculates the floor value of the Testing index of respective nodes.

As the improvement of signal detecting method of the present invention, in described step S4, when calculating the floor value of the Testing index of respective nodes, determined by detection critical point and two boundary points at the most.

With prior art mutually this, the invention has the beneficial effects as follows: MIMO signal checkout gear of the present invention is based on the coloured interchannel noise model of optimum, and its complexity is lower, and performance is no better than traversal search.Signal detecting method of the present invention, in consideration channel estimation errors situation, reduces search complexity.Ensure that the performance of communication simultaneously.

Accompanying drawing explanation

In order to be illustrated more clearly in the embodiment of the present invention or technical scheme of the prior art, be briefly described to the accompanying drawing used required in embodiment or description of the prior art below, apparently, the accompanying drawing that the following describes is only some embodiments recorded in the present invention, for those of ordinary skill in the art, under the prerequisite not paying creative work, other accompanying drawing can also be obtained according to these accompanying drawings.

Fig. 1 is the module diagram of MIMO signal checkout gear of the present invention;

Fig. 2 is the module diagram of search tree modular converter in MIMO signal checkout gear of the present invention;

Fig. 3 is the module diagram of transmitter in MIMO signal checkout gear of the present invention;

Fig. 4 is the module diagram of receiver in MIMO signal checkout gear of the present invention;

Fig. 5 is tree structure schematic diagram in MIMO signal checkout gear of the present invention;

Fig. 6 is this curve chart of noise under QPSK modulation;

Fig. 7 is this curve chart of noise under 16QAM modulation;

Fig. 8 is this curve chart of noise under 64QAM modulation.

Embodiment

Technical scheme in the present invention is understood better in order to make those skilled in the art person, below in conjunction with the accompanying drawing in the embodiment of the present invention, technical scheme in the embodiment of the present invention is clearly and completely described, obviously, described embodiment is only the present invention's part embodiment, instead of whole embodiments.Based on the embodiment in the present invention, those of ordinary skill in the art, not making the every other embodiment obtained under creative work prerequisite, should belong to the scope of protection of the invention.

As shown in Figure 1, MIMO signal checkout gear of the present invention comprises: search tree converting unit 11, search unit 12, sensor selection problem unit 13, node calculate unit 14, hedge clipper cut/updating block 15.

Described MIMO signal verifying attachment adopts tree search algorithm, and it is for according to constellation modulation system and channel estimating with channel estimating variance v ², complete the detection to MIMO signal, and export the log-likelihood ratio often transmitting this spy sending signal.Specifically comprise: search tree converting unit 11, search unit 12, sensor selection problem unit 13, node calculate unit 14, hedge clipper cut/updating block 15.

Wherein, described search tree converting unit 11 is for estimating Nr × Nt mimo system and respective channel with channel estimation error variance v ²be converted to N _tthe search tree of+1 layer.Described search unit 12, for judging whether current detection node layer exists sublayer node and be not detected, in this way, advances to corresponding sublayer node and detects, otherwise, retreat the father's node layer to current detection node layer, when not having node be not detected or do not need to be detected, search unit stops.Described sensor selection problem unit 13 for determining nodal test order in the node of sublayer.Described node calculate unit 14, for according to described nodal test order, calculates the Testing index value of respective nodes successively.Described hedge clipper cuts/updating block 15 for the Testing index value of this respective nodes with prune variable γ, variable γ is pruned when nodal test desired value is greater than, respective nodes and all child nodes thereof are cut off by from tree structure, otherwise, prune the Testing index value that namely variable γ is updated to respective nodes.

Further, described search tree converting unit 11 is also estimated for receive channel and corresponding channel estimation error variance v ², and preliminary treatment is carried out to it.

As shown in Figure 2, particularly, described search tree converting unit 11 comprises: matrix construction unit 21, matrix decomposition unit 22, vectorial generation unit 23, output unit 24.

Wherein, described matrix construction unit 21 is for by channel estimation error variance v ²be configured to matrix Ξ.Described matrix decomposition unit 22 is for by channel estimating with the product of Ξ carry out matrix decomposition (such as QR decomposes or Cholesky decomposes) and be converted to tree structure matrix.QR is adopted to decompose in the present invention.After being decomposed by QR, matrix be decomposed into upper triangular matrix R and orthogonal matrix Q.Described vector generates list 23 yuan is multiplied by orthogonal matrix Q associate matrix Q for the signal vector r received by MIMO signal checkout gear ^h, obtain vectorial y.Described output unit 24 is for exporting described upper triangular matrix R, matrix Ξ, vectorial y to described search unit.

As shown in Figure 3,4, based on above-mentioned MIMO signal checkout gear, the present invention also provides a kind of mimo wireless communication system, and it comprises: transmitter 30 and receiver 40.Wherein, described transmitter 30 is for sending signal to receiver, and described receiver 40 receives this signal, and detects the channel estimation errors joined with this signal correction.Meanwhile, the channel estimation errors that all Received signal strength are associated is saved as a data vector, and be applied to following MIMO signal checkout gear.

The Mathematical Modeling of described mimo wireless communication system is: r=Hx+n, wherein, and r=[r ₁, r ₂... rN _r] ^tn _r× 1 dimension complex received signal vector, x=[x ₁, x ₂... x _nt] ^tn _t× 1 dimension transmission signal vector, x _ifor independently choosing from a limited constellation of complex pattern.Described constellation pattern can be any one in QPSK, 16QAM, 64QAM and 256QAM, also can be other existing constellation pattern, such as ASK, PSK and TCM etc.Described H is N _r× N _tthe plural wireless channel matrix of dimension.

Described transmitter 30 comprises: information source produces end, encoder, modulator, serioparallel exchange unit.Described information source produces end for generation of information code current, information code current after encoder encodes, by forming specific constellation pattern after modulators modulate.Then, serioparallel exchange unit changes the stream compression after modulation into Nt channel parallel data stream, and the antenna finally by transmitter sends.

Described receiver 40 comprises: MIMO signal checkout gear 41, parallel serial conversion unit 42, decoder 43 as above.MIMO signal checkout gear utilizes channel-estimation information to detect to received signal, then carries out parallel-serial conversion by parallel serial conversion unit, finally by reverting to raw information code stream after decoders decode.

Correspondingly, the present invention also provides a kind of signal detecting method based on above-mentioned MIMO signal checkout gear, and described method is according to constellation modulation system, channel estimating and channel estimation errors Ξ, complete the detection to MIMO signal, and export the log-likelihood ratio of the every transmitted bit sending signal.

The expression formula of described log-likelihood ratio is:

$L=\left(C_{\mathrm{ij}}\right|r)=\underset{{x\∈x}_{\mathrm{ij}}^{-1}}{\min }\mathrm{\Λ}\left(x\right)-\underset{{x\∈x}_{\mathrm{ij}}^{+1}}{\min }\mathrm{\Λ}\left(x\right),$

Wherein, Λ (x) is Testing index, and the expression formula of described Λ (x) is as follows:

$\begin{array}{c}\mathrm{\Λ}\left(x\right)=\frac{{\left|\right|r-\hat{H}\mathrm{\Ξx}\left|\right|}^2}{{\mathrm{\σ}}_n^2+{\mathrm{\Σ}}_{k=1}^{N_t}(1-{\mathrm{\ξ}}_k){\left|\right|x_k\left|\right|}^2}\\ +N_r\log \mathrm{\π}({\mathrm{\σ}}_n^2+{\mathrm{\Σ}}_{k=1}^{N_t}(1-{\mathrm{\ξ}}_k){\left|\right|x_k\left|\right|}^2)\end{array}.$

Due to thus Λ (x) can equivalents be:

$\begin{array}{c}\mathrm{\Λ}\left(x\right)=\frac{{\left|\right|y-\mathrm{Rx}\left|\right|}^2}{{\mathrm{\σ}}_n^2+{\mathrm{\Σ}}_{k=1}^{N_t}(1-{\mathrm{\ξ}}_k){\left|\right|x_k\left|\right|}^2}\\ +N_r\log \mathrm{\π}({\mathrm{\σ}}_n^2+{\mathrm{\Σ}}_{k=1}^{N_t}(1-{\mathrm{\ξ}}_k){\left|\right|x_k\left|\right|}^2)\\ =\frac{1}{{\mathrm{\σ}}_n^2+{\mathrm{\Σ}}_{k=1}^{N_t}(1-{\mathrm{\ξ}}_k){\left|\right|x_k\left|\right|}^2}{\mathrm{\Σ}}_{k=1}^{N_t+1}{\mathrm{\λ}}_k\\ +N_r\log \mathrm{\π}({\mathrm{\σ}}_n^2+{\mathrm{\Σ}}_{k=1}^{N_t}(1-{\mathrm{\ξ}}_k){\left|\right|x_k\left|\right|}^2)\end{array}---\left(1\right)$

In the equivalent expression of Λ (x), y=Q ^hr, for kth layer receives component y _kpart Euclidean distance.Y in formula _kthe kth component receiving vectorial y, r _mkit is the capable kth column element of m of upper triangular matrix R.X _kfor launching a kth component of vector x.

As described in Figure 5, particularly, described method comprises the steps:

S1. by N _r× N _tmimo system and respective channel are estimated with channel estimation error variance v ²be converted to N _tthe search tree of+1 layer;

Wherein, in this expression formula, Δ H is N _r× N _tthe complex channel evaluated error matrix of dimension; The expression formula of Δ H is as follows:

In described expression formula, described Δ h _ijbe the channel estimation errors from a jth transmitting antenna to i-th reception antenna, and average is zero, variance is v ² _ijcomplex-valued Gaussian variable.In addition, in present embodiment, suppose that all channel estimation error variance are identical: v _ij ²=v ².Thus, the situation of different channels estimation error variance can be supported completely, without any the loss in performance, wherein, digital v _ij ²obtain by measure channel quality.

Further, described step S1 comprises:

S10. by channel estimation error variance v ²be configured to matrix Ξ.Wherein, the expression formula of described Ξ is as follows:

Ξ＝diag(ξ ₁，...，ξ _Nt)，

Wherein, ξ _k=1/ (1+v ²).Diag () is diagonal matrix, ξ ₁..., ξ _ntfor the elements in a main diagonal, in matrix, itself and element are 0.

S11. by channel estimating with the product of Ξ decomposed by QR, be decomposed into upper triangular matrix R and orthogonal matrix Q.

S12. the signal vector r of reception is multiplied by the associate matrix Q of orthogonal matrix Q ^h, obtain vectorial y.

S13. described upper triangular matrix R, matrix Ξ, vectorial y is exported.

S2. judge whether current detection node layer exists sublayer node and be not detected, in this way, advance to corresponding sublayer node and detect, otherwise, retreat the father's node layer to current detection node layer, when not having node be not detected or do not need to be detected, search unit stops.

S3. in the node of sublayer, determine nodal test order.Wherein, according to the principle of depth-first or the principle of breadth-first, in the node of sublayer, determine nodal test order.

S4. according to described nodal test order, the coloured noise parameter of respective nodes and the floor value of corresponding Testing index value is calculated successively.Wherein, this coloured noise calculation of parameter depends on corresponding the transmitting of father's node layer of described node.In addition, when calculating the floor value of the Testing index of respective nodes, determined by detection critical point and two boundary points at the most.

Wherein, described lower bound may be the tightest lower bound.Similarly, in present embodiment, other more loose lower bound can be used and do not rely on the Testing index that the unknown transmits and carry out restituted signal.In addition, in present embodiment, also can use between Λ (x _m) the upper bound and lower bound and do not rely on the Testing index that the unknown transmits and carry out restituted signal.

S5. to floor value and the pruning variable γ of the Testing index of this respective nodes, when the floor value of nodal test index is greater than pruning variable γ, respective nodes and all child nodes thereof are cut off by from tree structure, otherwise, prune the Testing index floor value that namely variable γ is updated to respective nodes.

In addition, above-mentioned calculating and prune strategy be based on do not rely on described node do not search for corresponding the transmitting of sublayer node, this place claims the floor value of Testing index and respective nodes.

In formula (1), the calculating of overall Euclidean distance is converted to the cumulative of each layer segment Euclidean distance by the molecular moiety of Section 1.As only having this, iterative calculation method can be adopted to solve formula (1), but the Section 2 of formula (1) and the denominator part of Section 1 make iterative computation use, and make a concrete analysis of as follows:

In m layer, part Testing index Λ (x _m) can be expressed as:

$\begin{array}{c}\mathrm{\Λ}\left(x_m\right)=\frac{1}{{{\mathrm{\σ}}_n^2+\mathrm{\Σ}}_{k=m}^{N_t}(1-{\mathrm{\ξ}}_k){\left|\right|x_k\left|\right|}^2+{\mathrm{\Σ}}_{k=1}^{m-1}(1-{\mathrm{\ξ}}_k){\left|\right|x_k\left|\right|}^2}{\mathrm{\Σ}}_{k=m}^{N_t+1}{\mathrm{\λ}}_m\\ +N_r\log \mathrm{\π}({\mathrm{\σ}}_n^2+{\mathrm{\Σ}}_{k=m}^{N_t}(1-{\mathrm{\ξ}}_k){\left|\right|x_k\left|\right|}^2+{\mathrm{\Σ}}_{k=1}^{m-1}(1-{\mathrm{\ξ}}_k){\left|\right|x_k\left|\right|}^2)\end{array}---\left(2\right)$

Wherein, x _m=[x _m..., x _nt] be fractional transmission vector.In current m layer, only there is fractional transmission vector x _mknown, all the other x that transmit ₁..., x _m-1for unknown-value, thus, current portions Testing index Λ (x cannot be used for _m) calculating.

In present embodiment, by asking the detection mode of first derivative, can predict that the unknown transmits rapidly, concrete derivation is as follows: formula (2) can be expressed as further:

$\begin{array}{c}\mathrm{\Λ}\left(x_m\right)=\frac{1}{{{\mathrm{\σ}}_n^2+\mathrm{\Σ}}_{k=m}^{N_t}(1-{\mathrm{\ξ}}_k){\left|\right|x_k\left|\right|}^2+{\mathrm{\θ}}_m}{\mathrm{\Σ}}_{k=m}^{N_t+1}{\mathrm{\λ}}_m\\ +N_r\log \mathrm{\π}({\mathrm{\σ}}_n^2+{\mathrm{\Σ}}_{k=m}^{N_t}(1-{\mathrm{\ξ}}_k){\left|\right|x_k\left|\right|}^2+{\mathrm{\θ}}_m)\end{array}---\left(3\right)$

Wherein, one to transmit based on the unknown and the variable of correlated channels evaluated error.Order with be respectively and can select the minimum of signal and emission maximum energy in constellation pattern.Therefore, θ _mfollowing interval range must be belonged to:

${\mathrm{\Θ}}_m=\{{\mathrm{\Σ}}_{k=1}^{m-1}(1-{\mathrm{\ξ}}_k){\mathrm{\α}}_k\≤{\mathrm{\θ}}_k\≤{\mathrm{\Σ}}_{k=1}^{m-1}(1-{\mathrm{\ξ}}_k){\mathrm{\β}}_k\}---\left(4\right)$

According to formula (3) and (4), part Testing index Λ (x _m) lower bound can be expressed as:

${\mathrm{\Λ}}_L=\underset{\mathrm{\θ}\∈{\mathrm{\Θ}}_m}{\min }\mathrm{\Λ}\left(x_m\right)$

Its lower bound critical point can be obtained by first derivative detection mode.Critical point meets first derivative and equals 0, i.e. Λ ' (x _m)=0, can obtain thus:

${\mathrm{\θ}}_m^{*}=\frac{{\mathrm{\Σ}}_{k=m}^{N_t+1}{\mathrm{\λ}}_k-N_r({\mathrm{\σ}}_n^2+{\mathrm{\Σ}}_{k=m}^{N_t}(1-{\mathrm{\ξ}}_k){\left|\right|x_k\left|\right|}^2)}{N_r}$

Visible, θ ^* _mand do not rely on the unknown and transmit, thus above-mentioned search can be drawn and prune strategy to be conclusion based on not relying on the Testing index that the unknown transmits.

Research the present invention is below applied to the simulated effect in typical 3GPPLTE/LTE-A scene, by channel estimation error variance value v ²be defined as NMSE (normalized mean square error), draw signal to noise ratio curve chart.

As can be seen from figures 6 to 8, Fig. 6 is the signal to noise ratio curve chart under QPSK modulation; Fig. 7 is the signal to noise ratio curve chart under 16QAM modulation; Fig. 8 is the signal to noise ratio curve chart under 64QAM modulation.

Wherein, Perfect CSI curve table is shown in MIMO signal Detection results under perfect channel estimation; Input effect of the present invention under ProposedCEN SD curve table is shown in imperfect channel estimation; WEN SD curve table is shown under imperfect channel estimation based on WEN method input effect; Mismatched SD curve table is shown in detection of mismatch method input effect under imperfect channel estimation.Consider hardware constraints factor, the node of limited quantity only explored by all simulators, and when exploration nodes reaches limit value, input terminates.In figure, Y-axis is code character error rate, X-axis be Received signal strength noise this.

This is reached to SNR needed for target code character error rate 0.01.As shown in Figure 6, the present invention can provide about 5dB gain; Have Fig. 7,8 known, the present invention can provide more than 10dB gain.Thus signal detecting method of the present invention reduces search complexity.Ensure that the performance of communication simultaneously.

To sum up, MIMO signal checkout gear of the present invention is based on the coloured interchannel noise model of optimum, and its complexity is lower, and performance is no better than traversal search.Signal detecting method of the present invention, in consideration channel estimation errors situation, reduces search complexity.Ensure that the performance of communication simultaneously.

To those skilled in the art, obviously the invention is not restricted to the details of above-mentioned one exemplary embodiment, and when not deviating from spirit of the present invention or essential characteristic, the present invention can be realized in other specific forms.Therefore, no matter from which point, all should embodiment be regarded as exemplary, and be nonrestrictive, scope of the present invention is limited by claims instead of above-mentioned explanation, and all changes be therefore intended in the implication of the equivalency by dropping on claim and scope are included in the present invention.Any Reference numeral in claim should be considered as the claim involved by limiting.

In addition, be to be understood that, although this specification is described according to execution mode, but not each execution mode only comprises an independently technical scheme, this narrating mode of specification is only for clarity sake, those skilled in the art should by specification integrally, and the technical scheme in each embodiment also through appropriately combined, can form other execution modes that it will be appreciated by those skilled in the art that.

Claims (13)

1. a MIMO signal checkout gear, is characterized in that, described MIMO signal checkout gear comprises: search tree converting unit, search unit, sensor selection problem unit, node calculate unit, hedge clipper cut/updating block;

Described search tree converting unit, it is for by N _r× N _tmimo system and respective channel are estimated to be converted to N with channel estimation error variance _tthe search tree of+1 layer;

Described search unit, it is for judging whether current detection node layer exists sublayer node and be not detected, in this way, advance to corresponding sublayer node to detect, otherwise, retreat the father's node layer to current detection node layer, when not having node be not detected or do not need to be detected, search unit stops;

Described sensor selection problem unit, it for determining nodal test order in the node of sublayer;

Described node calculate unit, it, for according to described nodal test order, calculates the coloured noise parameter of respective nodes and corresponding Testing index value successively; This coloured noise calculation of parameter depends on corresponding the transmitting of father's node layer of described node;

Described hedge clipper cuts/updating block, it is for contrasting the Testing index value of respective nodes and pruning variable γ, variable γ is pruned when nodal test desired value is greater than, respective nodes and all child nodes thereof are cut off by from tree structure, otherwise, prune the Testing index value that namely variable γ is updated to respective nodes.

2. MIMO signal checkout gear according to claim 1, is characterized in that, in described node calculate unit, the coloured noise calculation of parameter of described node does not rely on corresponding the transmitting of sublayer node of described node.

3. MIMO signal checkout gear according to claim 1, is characterized in that, in described node calculate unit, calculates the floor value of the Testing index of described node.

4. a mimo wireless communication system, is characterized in that, described mimo wireless communication system comprises: transmitter and receiver;

Described transmitter comprises: information source produces end, encoder, modulator, serioparallel exchange unit;

Described receiver comprises: MIMO signal checkout gear, parallel serial conversion unit, decoder as claimed in claim 1.

5. mimo wireless communication system according to claim 4, is characterized in that, the Mathematical Modeling of described mimo wireless communication system is: r=Hx+n, wherein, and r=[r ₁, r ₂... r _nr] ^tn _r× 1 dimension complex received signal vector, x=[x ₁, x ₂... x _nt] ^tn _t× 1 dimension transmission signal vector, wherein x _ifor independently choosing from a limited constellation of complex pattern, described H is N _r× N _tthe plural wireless channel matrix of dimension.

6. mimo wireless communication system according to claim 4, is characterized in that, described constellation pattern is any one in QPSK, 16QAM, 64QAM and 256QAM.

7. a signal detecting method, is characterized in that, described method is according to constellation modulation system, channel estimating and channel estimation error variance v ², complete the detection to MIMO signal, and export the log-likelihood ratio of the every transmitted bit sending signal.

Particularly, described method comprises the steps:

S1. by N _r× N _tmimo system and respective channel are estimated with channel estimation error variance v ²be converted to N _tthe search tree of+1 layer;

S2. judge whether current detection node layer exists sublayer node and be not detected, in this way, advance to corresponding sublayer node and detect, otherwise, retreat the father's node layer to current detection node layer, when not having node be not detected or do not need to be detected, search unit stops;

S3. in the node of sublayer, determine nodal test order;

S4. according to described nodal test order, the coloured noise parameter of respective nodes and corresponding Testing index value is calculated successively; This coloured noise calculation of parameter depends on corresponding the transmitting of father's node layer of described node;

S5. contrast the Testing index value of respective nodes and pruning variable γ, prune variable γ when nodal test desired value is greater than, respective nodes and all child nodes thereof are cut off by from tree structure, otherwise, prune the Testing index value that namely variable γ is updated to respective nodes.

8. signal detecting method according to claim 7, is characterized in that, this expression formula of described log-likelihood is:

$L\left(c_{\mathrm{ij}}\right|r)=\underset{x\∈x_{\mathrm{ij}}^{-1}}{\min }\mathrm{\Λ}\left(x\right)-\underset{x\∈x_{\mathrm{ij}}^{+1}}{\min }\mathrm{\Λ}\left(x\right),$

Wherein, ∧ (x) is Testing index, and the expression formula of described ∧ (x) is as follows:

$\begin{array}{c}\mathrm{\Λ}\left(x\right)=\frac{{\left|\right|r-\hat{H}\mathrm{\Ξx}\left|\right|}^2}{{\mathrm{\σ}}_n^2+{\mathrm{\Σ}}_{k=1}^{N_t}(1-{\mathrm{\ξ}}_k){\left|\right|x_k\left|\right|}^2}\\ +N_r\log \mathrm{\π}({\mathrm{\σ}}_n^2+{\mathrm{\Σ}}_{k=1}^{N_t}(1-{\mathrm{\ξ}}_k){\left|\right|x_k\left|\right|}^2)\end{array}.$

9. signal detecting method according to claim 7, is characterized in that, in described step S3, according to the principle of depth-first or the principle of breadth-first, determines nodal test order in the node of sublayer.

10. signal detecting method according to claim 7, is characterized in that, in described step S4, the coloured noise calculation of parameter of described node does not rely on corresponding the transmitting of sublayer node of described node.

11. signal detecting methods according to claim 7, is characterized in that, the expression formula of the Testing index of the respective nodes in described step S4 is as follows:

$\begin{array}{c}\mathrm{\Λ}\left(x_m\right)=\frac{1}{{\mathrm{\σ}}_n^2+{\mathrm{\Σ}}_{k=m}^{N_t}(1-{\mathrm{\ξ}}_k){\left|\right|x_k\left|\right|}^2+{\mathrm{\θ}}_m}{\mathrm{\Σ}}_{k=m}^{N_t+1}{\mathrm{\λ}}_m\\ +N_r\log \mathrm{\π}({\mathrm{\σ}}_n^2+{\mathrm{\Σ}}_{k=m}^{N_t}(1-{\mathrm{\ξ}}_k){\left|\right|x_k\left|\right|}^2+{\mathrm{\θ}}_m)\end{array}.$

12. signal detecting methods according to claim 11, is characterized in that, described step S4 calculates the floor value of the Testing index of respective nodes.

13. signal detecting methods according to claim 12, is characterized in that, in described step S4, when calculating the floor value of the Testing index of respective nodes, are determined at the most by detection critical point and two boundary points.