CN104901910A - Detection method and device for multiple input multiple output (MIMO) system - Google Patents
Detection method and device for multiple input multiple output (MIMO) system Download PDFInfo
- Publication number
- CN104901910A CN104901910A CN201410083479.XA CN201410083479A CN104901910A CN 104901910 A CN104901910 A CN 104901910A CN 201410083479 A CN201410083479 A CN 201410083479A CN 104901910 A CN104901910 A CN 104901910A
- Authority
- CN
- China
- Prior art keywords
- survival
- node
- child node
- metric value
- layer
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L25/00—Baseband systems
- H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
- H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
- H04L25/03006—Arrangements for removing intersymbol interference
- H04L25/03178—Arrangements involving sequence estimation techniques
- H04L25/03203—Trellis search techniques
- H04L25/03229—Trellis search techniques with state-reduction using grouping of states
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L25/00—Baseband systems
- H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
- H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
- H04L25/03006—Arrangements for removing intersymbol interference
- H04L25/03178—Arrangements involving sequence estimation techniques
- H04L25/03184—Details concerning the metric
- H04L25/03197—Details concerning the metric methods of calculation involving metrics
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L25/00—Baseband systems
- H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
- H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
- H04L25/03006—Arrangements for removing intersymbol interference
- H04L25/03178—Arrangements involving sequence estimation techniques
- H04L25/03312—Arrangements specific to the provision of output signals
- H04L25/03318—Provision of soft decisions
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L25/00—Baseband systems
- H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
- H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
- H04L25/03006—Arrangements for removing intersymbol interference
- H04L25/03178—Arrangements involving sequence estimation techniques
- H04L25/03337—Arrangements involving per-survivor processing
Landscapes
- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Physics & Mathematics (AREA)
- Optics & Photonics (AREA)
- Radio Transmission System (AREA)
Abstract
The invention discloses a detection method and device for signals in a multiple input multiple output (MIMO) system. The method comprises the steps of searching a tree structure equivalent to a signal vector of the MIMO system layer by layer, wherein when child nodes are expanded for survival nodes of each layer of the tree structure, the survival nodes are divided into at least two groups according to the order of accumulation metric values, the survival nodes of the same group expand the same quantity of child nodes, and the quantity of the child nodes expanded from the survival node in the group with a large accumulation metric value is less than the quantity of the child nodes expanded from the survival node in the group with a small accumulation metric value; outputting K survival paths maintained after completion of layer by layer searching and the survival nodes corresponding to the K survival paths; and determining a soft bit result of detection according to the K survival paths and the survival nodes corresponding to the K survival paths. As the child nodes expanded at each layer are reduced, tree searching computation amount is lowered. The paths, in which the survival nodes with small accumulation metric values are located, are more possible to be the final survival path, so that the method does not affect the detection performance.
Description
Technical field
The present invention relates to wireless communication technology field, particularly relate to detection method and the device of a kind of multiple-input and multiple-output (MIMO) system.
Background technology
Increasing rapidly of high speed wireless data access service and number of users, needs the support of higher rate, more jumbo wireless link, and determines that the most basic factor of transmission of radio links usefulness is channel capacity.Spatial multiplexing MIMO technology effective improves channel capacity, is the core technology of Long Term Evolution (LTE) system.
For the detection of Spatial Multiplexing Scheme of MIMO System, existing detection algorithm mainly comprises linearity test, sequence Interference Cancellation (SIC) detects, Maximum Likelihood Detection (ML).
The hardware implementing complexity of linear detection algorithm and SIC algorithm is lower, but the two poor performance under the wireless channel that decline is serious, there is larger gap with the performance of ML algorithm.
ML algorithm calculate Received signal strength and the Euclidean distance likely between vector, and find a minimum distance.When possibilities such as all transmittings vectors, ML algorithm reaches the optimum performance that maximum a posteriori probability (MAP) detects.But its complexity with order of modulation and number of transmission antennas increase and rise.
The search of ML algorithm traversal formula is because its heavy computation complexity makes can not or to be difficult in systems in practice realize.The main complexity adopting globular decoding (SD) detection algorithm based on tree search to reduce ML algorithm at present.
The basic thought of globular decoding detection algorithm the full traversal search that ML detects is narrowed down to one determine in the multidimensional diameter of Spherical Volume of radius, to reach the object reducing ML detection complexity.The point search process of the similar ML of its rudimentary algorithm flow process, aspect of performance is close to ML.
The detection of MIMO signal can be equivalent to the search to tree structure by the SD detection algorithm based on tree search.In this tree structure, the required number of child nodes launched of each father node is that constellation point number determines in the planisphere that uses of layer thus.The corresponding one group of partial information vector of each node, the line segment weight between every two connected nodes is corresponding part Euclidean distance.MIMO signal test problems can be converted into the problem of searching for the minimum node of weight in a tree structure, and this is the one simplification of shortest route problem.
Core concept based on the SD detection algorithm of tree search is to retrain the locating vector in ML detection, thus reduces the scope of search and the interstitial content of expansion.Theoretical according to rudimentary algorithm, the method for a traversal tree structure has depth-priority-searching method, width first traversal and metric priority algorithm.Wherein, breadth First SD detection algorithm is more suitable for hardware implementing.
Breadth First SD detection algorithm is from root node, and according to the principle traverse tree structure of breadth First, in the process of tree search, every one deck only retains the path (survivor path) that K bar has least part Euclidean distance sum.Key step is: suppose currently to have proceeded to k+1 layer, and first algorithm expands child node based on the father node of every layer of K survivor path retained, and each father node expands M child node, obtains the path that K*M bar is new.Then, the K*M paths after expansion is sorted according to accumulation Euclidean distance sum (i.e. cumulative metric value), retains the survivor path of minimum K bar as next layer, and by other route deletions.Repeat this operation until reach the leaf node of tree structure.
In the tree search procedure of breadth First SD detection algorithm, main operand is that two kinds of operations of every one deck bring:
(1) each father node expands M child node, calculates multiplication and add operation that each child node branched measurement value brings.In the process, the number of child nodes of the required expansion of each father node is that constellation point number determines in the planisphere that uses of layer thus.Such as, under Quadrature Phase Shift Keying (Quadrature Phase Shift Keying, QPSK) debud mode, a father node expands 4 child nodes; And in 64 quadrature amplitude modulation (Quadrature Amplitude Modulation, QAM) modulation system, a father node expands 64 child nodes.After each child node expansion, all to calculate the Euclidean distance of new route, relate to certain multiplication and add operation.The number of child nodes of a father node expansion is more, and the multiplication brought and the amount of addition operations be proportional increase also.
(2) comparison operation that the laggard line ordering of K*M paths brings is expanded.In the process, every one deck needs ascending for K*M paths sequence, retains the survivor path of minimum K bar as next layer, and by other route deletions.When K*M is larger, a large amount of sort operation can be taken to, make hardware implementing very complicated.
For the problem that every one deck operand is large, existing innovatory algorithm reduces operand by the number of restriction expansion child node.Such as based on the width first traversal of Candidate Set: for different modulation systems setting child node Candidate Set, it is only a subset of all constellation point in planisphere.Therefore, the number of child nodes M expanded by Candidate Set is significantly less than constellation point total number in planisphere.Compare primal algorithm, reduce M value, reduce integral operation amount.But, due to M numerical value less time can bring appreciable impact to detection perform, the setting of M numerical value is subject to a definite limitation.
In fact, in the process of tree search, the metric of every bar survivor path is different, and the path that cumulative metric value is little has larger probability becomes final path, and the large path of cumulative metric value has less probability and becomes final path.Breadth First SD detection algorithm and innovatory algorithm are in tree search procedure, and every one deck father node all extends the child node of fixed number (M).Adopt larger M numerical value can ensure to retain more survivor path, but cause the problem that overall calculation amount is large; And adopt less M numerical value can reduce overall calculation amount, but less survivor path can be retained, the performance of detection algorithm may be lost.This is a double-barreled question of existing detection algorithm.
Summary of the invention
The object of this invention is to provide detection method and the device of signal in a kind of mimo system, the problem cannot taken into account with the performance and amount of calculation that solve detection algorithm.
The object of the invention is to be achieved through the following technical solutions:
A detection method for mimo system, comprising:
The tree structure of the signal vector equivalence with mimo system is successively searched for; Wherein, when the survival point spread child node to this tree structure every layer, the survival node of same layer is divided at least two groups according to the sequence of cumulative metric value, child node quantity with the survival point spread of group is identical, and the child node quantity of point spread of surviving in the group that cumulative metric value is large is less than in the little group of cumulative metric value the child node quantity of point spread of surviving;
Export the survival node that the K bar survivor path of successively search for rear reservation is corresponding with this K bar survivor path;
According to above-mentioned K bar survivor path and corresponding survival node, determine the soft bit result detected.
The son node number expanded due to every one deck is less than the son node number of prior art expansion, thus reduces the operand of tree search.Because path, survival node place that cumulative metric value is little is that the possibility of final survivor path is larger, the technical scheme that therefore embodiment of the present invention provides does not affect detection perform.
Wherein, from the initial ranging layer of tree structure, at the selected node of initially surviving of this layer, start to set search procedure.Every layer of search procedure can be sketched and be: to the survival point spread child node of this layer; Calculate the branched measurement value of path, each child node place at this layer of expansion, the branched measurement value of the path, each child node place of expansion at this layer is added up with the branched measurement value of complete layer respectively, the cumulative metric value in the path, each child node place be expanded; By the child node of expansion according to the sequence of cumulative metric value, retain the survival node of front K child node as lower one deck according to ascending order.
Before carrying out tree search, QR decomposition is carried out to channel matrix, obtains upper triangular matrix R and unitary matrice Q; And carry out preliminary treatment to received signal, obtain the equivalence vector Y of received signal vector.In tree search procedure, according to upper triangular matrix R and equivalence vector Y Branch Computed metric.
Preferably, to the specific implementation of the survival point spread child node of the same layer of tree structure can be: the survival node of same layer is divided into two groups according to the sequence of cumulative metric value; According to the quantity of constellation point in the planisphere that survival node place layer uses, it is one group of survival point spread child node that cumulative metric value is little; For one group of survival point spread child node that cumulative metric value is larger.
In the various embodiments described above, the survival nodes that often group comprises is determined according to wireless channel conditions.
Based on the inventive concept same with method, the embodiment of the present invention also provides the checkout gear of signal in a kind of mimo system, comprising:
Tree search unit, for successively searching for the tree structure of the signal vector equivalence with mimo system; Wherein, when the survival point spread child node to this tree structure every layer, the survival node of same layer is divided at least two groups according to the sequence of cumulative metric value, child node quantity with the survival point spread of group is identical, and the child node quantity of point spread of surviving in the group that cumulative metric value is large is less than in the little group of cumulative metric value the child node quantity of point spread of surviving;
Output unit, for exporting the K bar survivor path of successively having searched for rear reservation and survival node corresponding to described K bar survivor path;
Testing result determining unit, for according to above-mentioned K bar survivor path and corresponding survival node, determines the soft bit result detected.
The son node number expanded due to every one deck is less than the son node number of prior art expansion, thus reduces the operand of tree search.Because path, survival node place that cumulative metric value is little is that the possibility of final survivor path is larger, the technical scheme that therefore embodiment of the present invention provides does not affect detection perform.
Preferably, tree search unit comprises each layer layer process one to one subelement with above-mentioned tree structure, each layer of process subelement is searched for one deck of tree structure respectively, wherein, the layer process subelement that later layer is corresponding carries out searching for the node that used survival node is the survival point spread of front one deck.
Preferably, each layer of process subelement specifically for: the survival node of one deck is divided at least two groups according to the sequence of cumulative metric value, is respectively and often organizes survival point spread child node; Calculate the branched measurement value of path, each child node place at current layer of expansion; Calculate the cumulative metric value in the path, each child node place of expansion; The cumulative metric value that described cumulative metric value computing module calculates is sorted, according to ascending order, the survival node of a front K child node as lower one deck is exported.
Accordingly, layer process subelement can comprise with lower module:
Child node expansion module, for the survival node of one deck is divided at least two groups according to the sequence of cumulative metric value, is respectively and often organizes survival point spread child node;
Branched measurement value computing module, for calculating the branched measurement value of each child node of expansion;
Cumulative metric value computing module, for calculating the cumulative metric value in the path, each child node place of expansion;
Order module, sorts for the cumulative metric value calculated by cumulative metric value computing module, is exported by the survival node of a front K child node as lower one deck according to ascending order.
Concrete, the order module of the layer process subelement that current layer is corresponding exports K child node according to the sequence of cumulative metric value, so that the child node expansion module of layer process subelement corresponding to lower one deck is expanded this K child node (the survival node of lower one deck) according to the sequence of cumulative metric value.
Preferably, child node expansion module is used for: the survival node of one deck is divided into two groups according to the sequence of cumulative metric value; According to the quantity of constellation point in the planisphere that search layer uses, it is one group of survival point spread child node that cumulative metric value is little; For one group of survival point spread child node that cumulative metric value is larger.
Based on above-mentioned any device embodiment, preferably, the survival nodes that often group comprises is determined according to wireless channel conditions.
Based on above-mentioned any device embodiment, this device also comprises: QR resolving cell, carries out QR decomposition for channel matrix to received signal, obtains upper triangular matrix and unitary matrice; Pretreatment unit, for carrying out preliminary treatment to received signal, successively searches for described tree structure according to pre-processed results and described upper triangular matrix to set search unit.
Based on the inventive concept same with method, the embodiment of the present invention also provides the checkout gear of signal in a kind of mimo system, comprises processor.
This processor is configured to, and successively searches for the tree structure of the signal vector equivalence with mimo system; Wherein, when the survival point spread child node to this tree structure every layer, the survival node of same layer is divided at least two groups according to the sequence of cumulative metric value, child node quantity with the survival point spread of group is identical, and the child node quantity of point spread of surviving in the group that cumulative metric value is large is less than in the little group of cumulative metric value the child node quantity of point spread of surviving; Export and successively searched for the K bar survivor path of rear reservation and survival node corresponding to described K bar survivor path; According to this K bar survivor path and corresponding survival node, determine the soft bit result detected.
The son node number expanded due to every one deck is less than the son node number of prior art expansion, thus reduces the operand of tree search.Because path, survival node place that cumulative metric value is little is that the possibility of final survivor path is larger, the technical scheme that therefore embodiment of the present invention provides does not affect detection perform.
Accompanying drawing explanation
The detection method flow chart that Fig. 1 provides for one embodiment of the invention;
The detection method flow chart that Fig. 2 provides for another embodiment of the present invention;
The tree search procedure schematic diagram that Fig. 3 provides for the embodiment of the present invention;
The device schematic diagram that Fig. 4 provides for one embodiment of the invention;
The device schematic diagram that Fig. 5 provides for another embodiment of the present invention;
The layer process subelement schematic diagram that Fig. 6 provides for the embodiment of the present invention;
The device schematic diagram that Fig. 7 provides for another embodiment of the present invention.
Embodiment
The present invention proposes the input scheme in a kind of low-complexity MIMO system, and its core concept improves the tree search procedure of breadth First SD algorithm.When to every layer of survival point spread child node, be at least two groups by the survival node division of same layer, be respectively and often organize survival point spread child node, make the child node quantity of the survival point spread with group identical, the child node quantity of point spread of surviving in the group that cumulative metric value is large is less than in the little group of cumulative metric value the child node quantity of point spread of surviving.
The son node number expanded due to every one deck is less than the son node number of prior art expansion, thus reduces the operand of tree search, reduces hardware implementing complexity.Because path, survival node place that cumulative metric value is little is that the possibility of final survivor path is larger, the technical scheme that therefore embodiment of the present invention provides does not affect detection perform.
Before the embodiment of the present invention is described in detail, first the layer of the tree structure that the embodiment of the present invention relates to, the concept of node are described.
Tree structure has Nr layer, and Nr is the quantity of reception antenna in mimo system.In order to obtain better Detection results, from Nr layer, tree structure is successively searched for.Certainly, other layers also can be selected as the initiation layer of search.
The node of every layer is also called father node.Due in the process of tree search, every layer of front K father node only retaining cumulative metric value ascending order, therefore, is called survival node by K father node of every layer of reservation.
The child node obtained the survival point spread of every layer is as the father node of lower one deck.In the embodiment of the present invention, lower one deck is relative search order.Such as, Nr-1 layer is lower one deck of low Nr layer.
Below in conjunction with accompanying drawing, the technical scheme that the embodiment of the present invention provides is described in detail.
A detection method for signal in mimo system, as shown in Figure 1, specifically comprises following operation:
Step 100, the tree structure of the signal vector equivalence with mimo system successively to be searched for; Wherein, when the survival point spread child node to this tree structure every layer, the survival node of same layer is divided at least two groups according to the sequence of cumulative metric value, child node quantity with the survival point spread of group is identical, and the child node quantity of point spread of surviving in the group that cumulative metric value is large is less than in the little group of cumulative metric value the child node quantity of point spread of surviving.
Step 110, export and successively searched for the K bar survivor path of rear reservation and survival node corresponding to this K bar survivor path.
Step 120, survival node according to above-mentioned K bar survivor path and correspondence, determine the soft bit result detected.
Wherein, from the initial ranging layer of tree structure, at the selected node of initially surviving of this layer, start to set search procedure.Every layer of search procedure can be sketched and be: to the survival point spread child node of this layer; Calculate the branched measurement value of path, each child node place at this layer of expansion, the branched measurement value of the path, each child node place of expansion at this layer is added up with the branched measurement value of complete layer respectively, the cumulative metric value in the path, each child node place be expanded; By the child node of expansion according to the sequence of cumulative metric value, retain the survival node of front K child node as lower one deck according to ascending order.
Before carrying out tree search, QR decomposition is carried out to channel matrix, obtains upper triangular matrix R and unitary matrice Q; And carry out preliminary treatment to received signal, obtain the equivalence vector Y of received signal vector.In tree search procedure, according to upper triangular matrix R and equivalence vector Y Branch Computed metric.
Preferably, to the specific implementation of the survival point spread child node of the same layer of tree structure can be: the survival node of same layer is divided into two groups according to the sequence of cumulative metric value; According to the quantity of constellation point in the planisphere that survival node place layer uses, it is one group of survival point spread child node that cumulative metric value is little; For one group of survival point spread child node that cumulative metric value is larger.
Take number of transmission antennas as Nt, reception antenna quantity is Nr, emission signal vector S=[s
1, s
2s
nt] mimo system be example, definition Received signal strength X=HS+n.
Wherein, X=[x
1, x
2..., x
nr] be received signal vector, n=[n
1, n
2... n
nr] be noise vector from each reception antenna place, H is N
t× N
rchannel matrix.
Adopt method that the embodiment of the present invention detects the signal in this mimo system as shown in Figure 2, specifically comprise following operation:
Step 200, QR decomposition is carried out to channel matrix H, obtain upper triangular matrix R and unitary matrice Q.That is:
H=QR
Step 210, to received signal vector carry out preliminary treatment.That is:
Received signal vector X is multiplied by the conjugate transpose of unitary matrice Q, obtains its equivalent vectorial Y:
Y=Q
HX=RS+w
Wherein, w=Q
hn
Step 220, according to upper triangular matrix R and equivalence vector Y, the tree structure of the signal vector equivalence with mimo system is successively searched for.
Concrete, from the Nr layer of tree structure, selected initial father node, successively search for according to flow process as shown in Figure 3:
The K of current layer survival node division is two groups by step 21, sequence according to cumulative metric value, performs step 22.
Concrete, according to the ascending order of cumulative metric value, being one group (being called first group) by front W survival node division, is another group (being called second group) by remaining K-W survival node division.Wherein, according to the value of W in characteristics of radio channels determination detection algorithm.Can the W of selection of small when wireless channel conditions is better, on the contrary larger W can be selected.Prerequisite to affect final detection perform.
In step 22, the planisphere that uses according to current layer, the quantity of constellation point, is that each survival node in first group expands M child node respectively; Be that each survival node in second group expands Mq child node respectively; Perform step 23.
Wherein, existing algorithm can be adopted to be each survival point spread child node in first group.
In second group, the value of the child node quantity Mq of each survival point spread is less than the value of M.Mq value is less more effective for reduction computation complexity, but prerequisite to affect final detection perform.
Step 23, to expansion each child node, calculate the branched measurement value of its path, place at this layer respectively, perform step 24.
Suppose the ascending order of survival node according to cumulative metric value of current layer, numbering is respectively 1,2 ..., K.Whole child nodes of each survival point spread are according to predetermined order or Random assignment numbering, and for the survival node of first group, corresponding child node numbering is respectively 1,2,, M, for the survival node of second group, corresponding child node numbering is respectively 1,2 ..., M
q.
Based on above-mentioned hypothesis, be numbered the child node being numbered a that the survival node of q is corresponding
path, place calculates branched measurement value corresponding to every paths at the branched measurement value of current layer
Wherein, q=1,2 ..., K; For the survival node of first group, a=1,2 ..., M, for the survival node of second group, a=1,2 ..., Mq; y
pp the element of Y, r
picapable i-th element of p of upper triangular matrix R, r
ppcapable p the element of p of upper triangular matrix R,
be
upper layer node.
Step 24, path, each child node place for expansion, add up the branched measurement value of the branched measurement value of current layer with complete layer, obtain the cumulative metric value of each path at current layer, perform step 25.
Step 25, according to the cumulative metric value of each path at current layer, sort to all child nodes of current layer expansion, before retaining according to ascending order, K child node is as the survival node of lower one deck, execution step 26.
Step 26, judge whether current layer is the 1st layer, if so, tree search procedure terminates, otherwise, return step 21.
As can be seen from above-mentioned algorithm, adopt packet expansion method, every one deck obtains W*M+ (K-W) * M
qindividual child node, corresponding W*M+ (K-W) * M
qpaths.In addition, every one deck is by W*M+ (K-W) * M
qindividual child node sorts, and retains K minimum child node of cumulative metric value and path, place.
Compared with existing algorithm, due to W*M+ (K-W) * M
qbe significantly less than K*M.Therefore the algorithm that the embodiment of the present invention provides effectively can reduce the addition of every one deck in existing tree search algorithm process, multiplication and sort operation amount.
Step 230, K child node finally retaining and path, place to be exported.
K child node of the final reservation of step 240, basis and path, place, determine the soft bit result detected.
In the various embodiments described above, the survival nodes that often group comprises is determined according to the impact of detection perform.
Based on the inventive concept same with method, the embodiment of the present invention also provides the checkout gear of signal in a kind of mimo system, as shown in Figure 4, comprising:
Tree search unit 41, for successively searching for the tree structure of the signal vector equivalence with mimo system; Wherein, when the survival point spread child node to this tree structure every layer, the survival node of same layer is divided at least two groups according to the sequence of cumulative metric value, child node quantity with the survival point spread of group is identical, and the child node quantity of point spread of surviving in the group that cumulative metric value is large is less than in the little group of cumulative metric value the child node quantity of point spread of surviving;
Output unit 42, for exporting the K bar survivor path of successively having searched for rear reservation and survival node corresponding to described K bar survivor path.
Testing result determining unit 43, for according to described K bar survivor path and corresponding survival node, determines the soft bit result detected.
The son node number expanded due to every one deck is less than the son node number of prior art expansion, thus reduces the operand of tree search.Because path, survival node place that cumulative metric value is little is that the possibility of final survivor path is larger, the technical scheme that therefore embodiment of the present invention provides does not affect detection perform.
Preferably, as shown in Figure 5, tree search unit 41 comprises each layer layer process one to one subelement 410 with above-mentioned tree structure, each layer of process subelement 410 is searched for one deck of tree structure respectively, wherein, the layer process subelement that later layer is corresponding carries out searching for the node that used survival node is the survival point spread of front one deck.
Preferably, each layer of process subelement specifically for: the survival node of one deck is divided at least two groups according to the sequence of cumulative metric value, is respectively and often organizes survival point spread child node; Calculate the branched measurement value of path, each child node place at current layer of expansion; Calculate the cumulative metric value in the path, each child node place of expansion; The cumulative metric value that described cumulative metric value computing module calculates is sorted, according to ascending order, the survival node of a front K child node as lower one deck is exported.
Accordingly, as shown in Figure 6, each layer of process subelement 410 can comprise:
Child node expansion module 61, for the survival node of one deck is divided at least two groups according to the sequence of cumulative metric value, is respectively and often organizes survival point spread child node;
Branched measurement value computing module 62, for calculating the branched measurement value of each child node of expansion;
Cumulative metric value computing module 63, for calculating the cumulative metric value in the path, each child node place of expansion;
Order module 64, sorts for the cumulative metric value calculated by cumulative metric value computing module 63, is exported by the survival node of a front K child node as lower one deck according to ascending order.
Concrete, the order module 64 of the layer process subelement 410 that current layer is corresponding exports K child node according to the sequence of cumulative metric value, so that the child node expansion module 61 of layer process subelement 410 corresponding to lower one deck is expanded this K child node (the survival node of lower one deck) according to the sequence of cumulative metric value.
Preferably, child node expansion module 61 for: the survival node of one deck is divided into two groups according to the sequence of cumulative metric value; According to the quantity of constellation point in the planisphere that search layer uses, it is one group of survival point spread child node that cumulative metric value is little; For one group of survival point spread child node that cumulative metric value is larger.
Based on above-mentioned any device embodiment, preferably, the survival nodes that often group comprises is determined according to wireless channel conditions.
Based on above-mentioned any device embodiment, as shown in Figure 7, this device also comprises: QR resolving cell 43, carries out QR decomposition for channel matrix to received signal, obtains upper triangular matrix and unitary matrice; Pretreatment unit 44, for carrying out preliminary treatment to received signal, successively searches for described tree structure according to pre-processed results and described upper triangular matrix to set search unit.
Based on the inventive concept same with method, the embodiment of the present invention also provides the checkout gear of signal in a kind of mimo system, comprises processor.
This processor is configured to, and successively searches for the tree structure of the signal vector equivalence with mimo system; Wherein, when the survival point spread child node to this tree structure every layer, the survival node of same layer is divided at least two groups according to the sequence of cumulative metric value, child node quantity with the survival point spread of group is identical, and the child node quantity of point spread of surviving in the group that cumulative metric value is large is less than in the little group of cumulative metric value the child node quantity of point spread of surviving; Export and successively searched for the K bar survivor path of rear reservation and survival node corresponding to described K bar survivor path; According to described K bar survivor path and corresponding survival node, determine the soft bit result detected.
The son node number expanded due to every one deck is less than the son node number of prior art expansion, thus reduces the operand of tree search.Because path, survival node place that cumulative metric value is little is that the possibility of final survivor path is larger, the technical scheme that therefore embodiment of the present invention provides does not affect detection perform.
Those skilled in the art should understand, embodiments of the invention can be provided as method, system or computer program.Therefore, the present invention can adopt the form of complete hardware embodiment, completely software implementation or the embodiment in conjunction with software and hardware aspect.And the present invention can adopt in one or more form wherein including the upper computer program implemented of computer-usable storage medium (including but not limited to magnetic disc store, CD-ROM, optical memory etc.) of computer usable program code.
The present invention describes with reference to according to the flow chart of the method for the embodiment of the present invention, equipment (system) and computer program and/or block diagram.Should understand can by the combination of the flow process in each flow process in computer program instructions realization flow figure and/or block diagram and/or square frame and flow chart and/or block diagram and/or square frame.These computer program instructions can being provided to the processor of all-purpose computer, special-purpose computer, Embedded Processor or other programmable data processing device to produce a machine, making the instruction performed by the processor of computer or other programmable data processing device produce device for realizing the function of specifying in flow chart flow process or multiple flow process and/or block diagram square frame or multiple square frame.
These computer program instructions also can be stored in can in the computer-readable memory that works in a specific way of vectoring computer or other programmable data processing device, the instruction making to be stored in this computer-readable memory produces the manufacture comprising command device, and this command device realizes the function of specifying in flow chart flow process or multiple flow process and/or block diagram square frame or multiple square frame.
These computer program instructions also can be loaded in computer or other programmable data processing device, make on computer or other programmable devices, to perform sequence of operations step to produce computer implemented process, thus the instruction performed on computer or other programmable devices is provided for the step realizing the function of specifying in flow chart flow process or multiple flow process and/or block diagram square frame or multiple square frame.
Although describe the preferred embodiments of the present invention, those skilled in the art once obtain the basic creative concept of cicada, then can make other change and amendment to these embodiments.So claims are intended to be interpreted as comprising preferred embodiment and falling into all changes and the amendment of the scope of the invention.
Obviously, those skilled in the art can carry out various change and modification to the present invention and not depart from the spirit and scope of the present invention.Like this, if these amendments of the present invention and modification belong within the scope of the claims in the present invention and equivalent technologies thereof, then the present invention is also intended to comprise these change and modification.
Claims (9)
1. the detection method of signal in multi-input multi-output system, is characterized in that, comprising:
The tree structure of the signal vector equivalence with multi-input multi-output system is successively searched for; Wherein, when the survival point spread child node to described tree structure every layer, survival node is divided at least two groups according to the sequence of cumulative metric value, child node quantity with the survival point spread of group is identical, and the child node quantity of point spread of surviving in the group that cumulative metric value is large is less than in the little group of cumulative metric value the child node quantity of point spread of surviving;
Export and successively searched for the K bar survivor path of rear reservation and survival node corresponding to described K bar survivor path;
According to described K bar survivor path and corresponding survival node, determine the soft bit result detected.
2. method according to claim 1, is characterized in that, to the survival point spread child node of the same layer of described tree structure, comprising:
Survival node is divided into two groups according to the sequence of cumulative metric value;
According to the quantity of constellation point in the planisphere that survival node place layer uses, it is one group of survival point spread child node that cumulative metric value is little;
For one group of survival point spread child node that cumulative metric value is larger.
3. method according to claim 1 and 2, is characterized in that, the nodes that often group comprises is determined according to wireless channel conditions.
4. the checkout gear of signal in multi-input multi-output system, is characterized in that, comprising:
Tree search unit, for successively searching for the tree structure of the signal vector equivalence with multi-input multi-output system; Wherein, when the survival point spread child node to described tree structure every layer, survival node is divided at least two groups according to the sequence of cumulative metric value, child node quantity with the survival point spread of group is identical, and the child node quantity of point spread of surviving in the group that cumulative metric value is large is less than in the little group of cumulative metric value the child node quantity of point spread of surviving;
Output unit, for exporting the K bar survivor path of successively having searched for rear reservation and survival node corresponding to described K bar survivor path;
Testing result determining unit, for according to described K bar survivor path and corresponding survival node, determines the soft bit result detected.
5. device according to claim 4, it is characterized in that, described tree search unit comprises each layer layer process one to one subelement with described tree structure, each layer of process subelement is searched for one deck of described tree structure respectively, wherein, the layer process subelement that later layer is corresponding carries out searching for the node that used survival node is the survival point spread of front one deck.
6. device according to claim 5, is characterized in that, each layer process subelement specifically for:
The survival node of one deck is divided at least two groups according to the sequence of cumulative metric value, is respectively and often organizes survival point spread child node;
Calculate the branched measurement value of path, each child node place at current layer of expansion;
Calculate the cumulative metric value in the path, each child node place of expansion;
The cumulative metric value that described cumulative metric value computing module calculates is sorted, according to ascending order, the survival node of a front K child node as lower one deck is exported.
7. device according to claim 6, is characterized in that, the survival node of one deck is divided at least two groups according to the sequence of cumulative metric value, be respectively often organize survival point spread child node time, described layer process submodule is used for:
The survival node of one deck is divided into two groups according to the sequence of cumulative metric value;
According to the quantity of constellation point in the planisphere that search layer uses, it is one group of survival point spread child node that cumulative metric value is little;
For one group of survival point spread child node that cumulative metric value is larger.
8. the device according to any one of claim 4 ~ 7, is characterized in that, the nodes that often group comprises is determined according to wireless channel conditions.
9. the device according to any one of claim 4 ~ 7, is characterized in that, also comprises:
QR resolving cell, carries out QR decomposition for channel matrix to received signal, obtains upper triangular matrix and unitary matrice;
Pretreatment unit, for carrying out preliminary treatment to received signal, successively searches for described tree structure according to pre-processed results and described upper triangular matrix to set search unit.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410083479.XA CN104901910A (en) | 2014-03-07 | 2014-03-07 | Detection method and device for multiple input multiple output (MIMO) system |
| PCT/CN2015/073720 WO2015131840A1 (en) | 2014-03-07 | 2015-03-05 | Detection method and apparatus of mimo system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410083479.XA CN104901910A (en) | 2014-03-07 | 2014-03-07 | Detection method and device for multiple input multiple output (MIMO) system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN104901910A true CN104901910A (en) | 2015-09-09 |
Family
ID=54034309
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201410083479.XA Pending CN104901910A (en) | 2014-03-07 | 2014-03-07 | Detection method and device for multiple input multiple output (MIMO) system |
Country Status (2)
| Country | Link |
|---|---|
| CN (1) | CN104901910A (en) |
| WO (1) | WO2015131840A1 (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109660473A (en) * | 2017-10-10 | 2019-04-19 | 深圳市中兴微电子技术有限公司 | A kind of globular decoding detection method and device, computer readable storage medium |
| WO2020125177A1 (en) * | 2018-12-20 | 2020-06-25 | 中兴通讯股份有限公司 | Decoding method, terminal and storage medium |
| CN111950216A (en) * | 2020-07-22 | 2020-11-17 | 中国科学院计算技术研究所 | Method for generating multi-fan-out signal for superconducting RSFQ circuit |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115051900B (en) * | 2022-05-10 | 2024-01-16 | 四川创智联恒科技有限公司 | Wireless MIMO receiver detection method |
| CN115396064B (en) * | 2022-08-16 | 2023-11-24 | 网络通信与安全紫金山实验室 | Detection decoding method, detection decoding device, computer equipment and readable storage medium |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090060079A1 (en) * | 2007-08-31 | 2009-03-05 | Mewtel Technology Inc. | Method for detecting a symbol using trellis structure on the multiple input multiple output mobile communication system |
| CN102006148A (en) * | 2010-12-07 | 2011-04-06 | 西安电子科技大学 | Multiple-input multiple-output (MIMO) signal detection method based on breadth-first tree search |
| CN102246452A (en) * | 2011-06-28 | 2011-11-16 | 华为技术有限公司 | Detection method and system for MIMO system |
| CN102723975A (en) * | 2012-06-11 | 2012-10-10 | 北京大学 | Signal detection method and device of MIMO (multiple input multiple output) system |
-
2014
- 2014-03-07 CN CN201410083479.XA patent/CN104901910A/en active Pending
-
2015
- 2015-03-05 WO PCT/CN2015/073720 patent/WO2015131840A1/en active Application Filing
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090060079A1 (en) * | 2007-08-31 | 2009-03-05 | Mewtel Technology Inc. | Method for detecting a symbol using trellis structure on the multiple input multiple output mobile communication system |
| CN102006148A (en) * | 2010-12-07 | 2011-04-06 | 西安电子科技大学 | Multiple-input multiple-output (MIMO) signal detection method based on breadth-first tree search |
| CN102246452A (en) * | 2011-06-28 | 2011-11-16 | 华为技术有限公司 | Detection method and system for MIMO system |
| CN102723975A (en) * | 2012-06-11 | 2012-10-10 | 北京大学 | Signal detection method and device of MIMO (multiple input multiple output) system |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109660473A (en) * | 2017-10-10 | 2019-04-19 | 深圳市中兴微电子技术有限公司 | A kind of globular decoding detection method and device, computer readable storage medium |
| CN109660473B (en) * | 2017-10-10 | 2021-05-28 | 深圳市中兴微电子技术有限公司 | Spherical decoding detection method and device and computer readable storage medium |
| WO2020125177A1 (en) * | 2018-12-20 | 2020-06-25 | 中兴通讯股份有限公司 | Decoding method, terminal and storage medium |
| CN111950216A (en) * | 2020-07-22 | 2020-11-17 | 中国科学院计算技术研究所 | Method for generating multi-fan-out signal for superconducting RSFQ circuit |
| CN111950216B (en) * | 2020-07-22 | 2023-07-21 | 中国科学院计算技术研究所 | Method for generating multiple fan-out signals, computer readable storage medium and electronic device |
Also Published As
| Publication number | Publication date |
|---|---|
| WO2015131840A1 (en) | 2015-09-11 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| JP4429945B2 (en) | MIMO multiplex communication apparatus and signal separation method | |
| CN104901910A (en) | Detection method and device for multiple input multiple output (MIMO) system | |
| CN102723975B (en) | Signal detection method and device of MIMO (multiple input multiple output) system | |
| KR20090097838A (en) | Method and appraratus for receiving in multiple input multiple output system | |
| KR20080059014A (en) | Apparatus and method for receiving signal in multiple input multiple output wireless communication system | |
| CN103414534B (en) | A kind of generalized spatial modulation system receiver detection method in conjunction with threshold judgement | |
| CN101888287B (en) | Signal detection method and device for multi-input multi-output receiver | |
| CN102307080B (en) | Method and device for detecting serial block signal in MIMO (multiple-input multiple-output) system | |
| CN103532609B (en) | MIMO signal detection method based on K Best algorithm and detector | |
| CN102025454B (en) | Method and device for generating precoding matrix codebook | |
| CN103973602B (en) | Signal detecting method and device | |
| CN102246452B (en) | Detection method and system for MIMO system | |
| KR101423965B1 (en) | Orthotope sphere decoding method and apparatus for signal reconstruction in the multi-input multi-output antenna system | |
| TWI650984B (en) | Modulation method detection method and device | |
| CN109660473B (en) | Spherical decoding detection method and device and computer readable storage medium | |
| CN102291215A (en) | Signal detection method and device for MIMO (Multiple Input Multiple Output) system | |
| CN101964667B (en) | High-efficiency multi-antenna detection method for long term evolution scheme | |
| KR101959039B1 (en) | Orthotope sphere decoding method and apparatus for signal reconstruction in the multi-input multi-output antenna system | |
| CN105119665A (en) | MIMO (multiple input and multiple output) detection method based on lattice reduction | |
| CN103384180B (en) | Performing space-time decoding method and apparatus for multi-input multi-output system | |
| KR101804809B1 (en) | Symbol detection method in generalized spatial modulation multiple input multiple output system and receiver using thereof | |
| KR101632882B1 (en) | Method for detecting signal in spatial modulation multiple input multiple output system | |
| CN103684565A (en) | Method and device for determining soft bit information | |
| CN104753645B (en) | Multiple antennas interpretation method and system based on channel coding | |
| KR20190094991A (en) | Low complexity sphere decoding receiver and method for generalized spatial modulation |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20150909 |