CN110011775A - Joint realizes active user detection and its channel estimation methods and its system - Google Patents
Joint realizes active user detection and its channel estimation methods and its system Download PDFInfo
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- CN110011775A CN110011775A CN201910221801.3A CN201910221801A CN110011775A CN 110011775 A CN110011775 A CN 110011775A CN 201910221801 A CN201910221801 A CN 201910221801A CN 110011775 A CN110011775 A CN 110011775A
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- 238000001514 detection method Methods 0.000 title claims abstract description 50
- 238000000034 method Methods 0.000 title abstract description 34
- 238000004891 communication Methods 0.000 claims abstract description 38
- 230000004044 response Effects 0.000 claims description 15
- 230000007935 neutral effect Effects 0.000 claims description 6
- 230000008602 contraction Effects 0.000 claims description 5
- 239000011159 matrix material Substances 0.000 claims description 5
- 230000000694 effects Effects 0.000 claims description 4
- 230000005059 dormancy Effects 0.000 claims 2
- 238000013475 authorization Methods 0.000 description 10
- 230000005540 biological transmission Effects 0.000 description 3
- 230000000631 nonopiate Effects 0.000 description 3
- 238000010586 diagram Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000012546 transfer Methods 0.000 description 2
- 230000001413 cellular effect Effects 0.000 description 1
- 239000000284 extract Substances 0.000 description 1
- 238000003780 insertion Methods 0.000 description 1
- 230000037431 insertion Effects 0.000 description 1
- 238000010295 mobile communication Methods 0.000 description 1
- 238000010606 normalization Methods 0.000 description 1
- 230000002035 prolonged effect Effects 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
Classifications
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- 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
- H04L25/0202—Channel estimation
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- 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
- H04L25/0202—Channel estimation
- H04L25/0224—Channel estimation using sounding signals
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L5/00—Arrangements affording multiple use of the transmission path
- H04L5/003—Arrangements for allocating sub-channels of the transmission path
- H04L5/0048—Allocation of pilot signals, i.e. of signals known to the receiver
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/70—Services for machine-to-machine communication [M2M] or machine type communication [MTC]
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W74/00—Wireless channel access
- H04W74/08—Non-scheduled access, e.g. ALOHA
- H04W74/0833—Random access procedures, e.g. with 4-step access
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- Computer Networks & Wireless Communication (AREA)
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- Mobile Radio Communication Systems (AREA)
Abstract
The invention discloses a kind of joints to realize active user detection and its channel estimation methods and its system, active user detection method includes: the sparse signal reconfiguring for estimating to be modeled as in compressive sensing theory by active user detection and active user channels in the flood tide machine type communication, and goes out any active ues according to subscriber channel state estimation with SLO restructing algorithm.Method provided by the invention can reduce the length of pilot signal, and can obtain the channel estimating performance better than least square method.
Description
Technical field
The present invention relates to active users in machine type communication (machine type communication, MTC) scene to examine
Survey and its channel estimation methods.
Background technique
With the Internet of Things such as smart home, wisdom traffic and intelligent medical treatment application it is increasingly developed, currently there is an urgent need to build
It is vertical to provide the communication network of interconnection and interflow for machine type equipment.In order to realize the target, the 5th Generation Mobile Communication System (5G)
By flood tide machine type communication, enhance mobile broadband and the communication of super reliable low time delay is determined as the three kinds of business needed support.By
It is numerous in machine type number of devices, therefore, the great challenge that 5G faces be exactly need to provide for flood tide machine type equipment and
When network insertion and efficient data transmission.
Cellular network is currently to pass through dedicated random access control channel and using allowing user's competitor by way of authorization
Layer transfer resource is managed, four-stage is generally included, firstly, each active user randomly extracts one in orthogonal pilot signals pond
A pilot signal is simultaneously sent to base station, and notice base station user has data to need to send；Then, base station is leading of each receiving
Frequency signal sends a response signal, and authorization can continue to transmit information；Then, the user for receiving authorization signal continues to base
It stands and sends connection request；Finally, base station is to the resource for distributing transmission data there is no the user of pilot collision and authorizes the use
Network is accessed at family, and does not do response to the user that pilot collision occurs, after the user of access failure needs to wait a time
Again contention access network.The access scheme of this classical authorization is not suitable for flood tide machine type communication, because are as follows: first, channel
Coherence time and coherence bandwidth it is limited, this just determines the limited length of pilot signal, to lead in orthogonal pilot signals pond
Frequency number of signals is limited, accesses in face of flood tide, and pilot collision rate is high, extends the time-consuming of equipment access network.Second, machine type
The characteristics of communication is the communication of burst type short packages, it is sometimes desirable to which the data information of transmission only several bits are awarded according to tradition
Power formula access scheme causes system whole efficiency low considerably beyond the time of data transfer phase when access phase accounts for.Cause
This, flood tide machine type communication cannot use traditional authentication type access scheme, need to develop nonopiate and without the random of authorization
Access scheme.Nonopiate and without authorizing each machine type equipment in access scheme to arrange a fixed pilot signal,
If at a time machine type equipment has data to need to send, which directly transmits pilot signal and data information at once, this
Sample can be to avoid pilot collision and prolonged authorization access application, but the core support technology of the access scheme is needed from huge
Active user is detected in the machine type equipment of amount and estimates its channel state information.
Summary of the invention
The object of the present invention is to provide joints in a kind of flood tide machine type communication to realize that active user detection and its channel are estimated
The method of meter, the method overcome the problems that turn-on time in existing authorization access technology is long.
To achieve the goals above, the present invention provides active user detection method in a kind of flood tide machine type communication,
It is characterized in that, active user detection method includes: in the flood tide machine type communication
The sparse signal reconfiguring being modeled as in compressive sensing theory is estimated into active user detection and active user channels, and
Any active ues are gone out according to subscriber channel state estimation with SLO (smooth L0 norm algorithm) restructing algorithm.
Preferably, the sparse letter being modeled as in compressive sensing theory is being estimated into active user detection and active user channels
Number reconstruct before, comprising:
Flood tide machine type equipment is authorized into non-orthogonal mode random access base station by exempting from.
Preferably, flood tide machine type equipment is authorized into non-orthogonal mode random access base station by exempting from, comprising:
The pilot signal of flood tide machine type equipment and data information are sent directly to the base station；And by multiple flood tide machines
Each flood tide machine type equipment distributes the pilot frequency sequence of a preset length, and nothing between multiple sequences in device class equipment
Orthogonality relation need to be met.
Preferably, active user detection and its channel estimation are modeled as the sparse signal reconfiguring in compressive sensing theory,
Include:
A certain time slot, if having K in K machine type equipmentaA flood tide machine type equipment is in active state, then base station receives
The K arrivedaThe pilot signal that a active user is sent may be expressed as:
Wherein, p (k) indicates number of k-th of active user in system in all flood tide machine type equipment；Base station and huge
What amount machine type equipment was respectively mounted is single antenna；hp(k)It is channel response of a flood tide machine type equipment of P (k) to base station；xp(k)
=[xp(k),1,xp(k),2..., xp(k),N]TIt is the pilot frequency sequence that a flood tide machine type equipment of pth (k) is sent, w is that mean value is 0, side
Difference is σ2Gaussian noise；
Work as KaA flood tide machine type equipment is in active state, then K-KaA flood tide machine type equipment is in a dormant state；Place
In the flood tide machine type equipment of dormant state, its communication link is not activated, so that its channel response is zero；If considering all
Flood tide machine type equipment, the then pilot signal received can be expressed equivalently as by following formula
Wherein, h is a sparse vector, includes K-KaA neutral element, KaA nonzero element, and nonzero element is in h
Position is corresponding with the number p (k) of active user.
Preferably, any active ues are gone out according to subscriber channel state estimation with SLO (smooth L0 norm algorithm) restructing algorithm,
Include:
Step 121, observation signal y, observing matrix X, threshold value σ are inputtedmin, contraction factor ρ, step size mu and the number of iterations L；
Step 122, it enablesWherein, superscript notationIndicate pseudo-inverse operation operation；
Step 123, if σ > σmin, then sequence executes (I) and (II)；Otherwise, step 124 is executed,
(I) on set of feasible solution { h | y=Xh }, from initial solutionL times following iteration steepest descent algorithm is begun through,
Maximize objective function
(a) element value of setting vector δ is
(b) it enablesThen pass throughIt willIt projects on its set of feasible solution；
(II) σ ← ρ σ, and return step 123 are enabled；
Step 124, it calculatesAnd find out KaThe position number of a greatest member value, by the KaA position number deposit set
I exports the active user I detected and active user channels status information
It is living in the flood tide machine type communication the present invention also provides active user detection system in a kind of flood tide machine type communication
Employing family detection system includes:
The sparse signal reconfiguring being modeled as in compressive sensing theory is estimated into active user detection and active user channels, and
Go out the equipment of any active ues according to subscriber channel state estimation with SLO (smooth L0 norm algorithm) restructing algorithm.
Preferably, comprising:
Equipment by flood tide machine type equipment by exempting to authorize non-orthogonal mode random access base station.
Preferably, the equipment by flood tide machine type equipment by exempting to authorize non-orthogonal mode random access base station, comprising:
The equipment that the pilot signal of flood tide machine type equipment and data information are sent directly to the base station；And it will be multiple
Each flood tide machine type equipment distributes the pilot frequency sequence of a preset length, and multiple sequences in flood tide machine type equipment
Between without meeting the equipment of orthogonality relation.
Preferably, active user detection and its channel estimation are modeled as the sparse signal reconfiguring in compressive sensing theory
Equipment, comprising:
A certain time slot, if having K in K machine type equipmentaA flood tide machine type equipment is in active state, then base station receives
The K arrivedaThe pilot signal that a active user is sent may be expressed as:
Wherein, p (k) indicates number of k-th of active user in system in all flood tide machine type equipment；Base station and huge
What amount machine type equipment was respectively mounted is single antenna；hp(k)It is channel response of a flood tide machine type equipment of P (k) to base station；xp(k)
=[xp(k),1,xp(k),2,…,xp(k),N]TIt is the pilot frequency sequence that a flood tide machine type equipment of pth (k) is sent, w is that mean value is 0, side
Difference is σ2Gaussian noise；
Work as KaA flood tide machine type equipment is in active state, then K-KaA flood tide machine type equipment is in a dormant state；Place
In the flood tide machine type equipment of dormant state, its communication link is not activated, so that its channel response is zero；If considering all
Flood tide machine type equipment, the then pilot signal received can be expressed equivalently as by following formula
Wherein, h is a sparse vector, includes K-KaA neutral element, KaA nonzero element, and nonzero element is in h
Position is corresponding with the number p (k) of active user.
Preferably, any active ues are gone out according to subscriber channel state estimation with SLO (smooth L0 norm algorithm) restructing algorithm
Equipment, comprising:
Input equipment inputs observation signal y, observing matrix X, threshold value σmin, contraction factor ρ, step size mu and the number of iterations L；
It enablesWherein, superscript notationIndicate pseudo-inverse operation operation；
Equipment is judged, if σ > σmin, then sequence executes (I) and (II)；Otherwise, output equipment work is executed,
(I) on set of feasible solution { h | y=Xh }, from initial solutionL times following iteration steepest descent algorithm is begun through,
Maximize objective function
(a) element value of setting vector δ is
(b) it enablesThen pass throughIt willIt projects on its set of feasible solution；
(II) σ ← ρ σ is enabled, and returns to judgement equipment；
Output equipment calculatesAnd find out KaThe position number of a greatest member value, by the KaA position number deposit collection
I is closed, the active user I detected and active user channels status information are exported
Compared with prior art, active user detection provided by the invention and its channel estimation methods use compressed sensing weight
Structure algorithm SL0 can significantly reduce pilot signal length required for channel estimation.This method computation complexity is low, easily
In realization.
Other features and advantages of the present invention will the following detailed description will be given in the detailed implementation section.
Detailed description of the invention
The drawings are intended to provide a further understanding of the invention, and constitutes part of specification, with following tool
Body embodiment is used to explain the present invention together, but is not construed as limiting the invention.In the accompanying drawings:
Fig. 1 is to illustrate that joint realizes active user detection and its channel estimation in a kind of flood tide machine type communication of the invention
The flow chart of method implementation steps；
Fig. 2 is to combine to realize active user detection and its channel estimation methods (labeled as the present invention with SL0 compressed sensing
The method of offer) and least square method detection active user accuracy comparison diagram；
Fig. 3 is the normalization with method provided by the invention and Least Square Method active user channels status information
Mean square error curve graph.
Specific embodiment
Below in conjunction with attached drawing, detailed description of the preferred embodiments.It should be understood that this place is retouched
The specific embodiment stated is merely to illustrate and explain the present invention, and is not intended to restrict the invention.
The present invention provides active user detection method in a kind of flood tide machine type communication, activity in the flood tide machine type communication
User's detection method includes:
The sparse signal reconfiguring being modeled as in compressive sensing theory is estimated into active user detection and active user channels, and
Any active ues are gone out according to subscriber channel state estimation with SLO (smooth L0 norm algorithm) restructing algorithm.
Compared with prior art, active user detection provided by the invention and its channel estimation methods use compressed sensing weight
Structure algorithm SL0 can significantly reduce pilot signal length required for channel estimation.This method computation complexity is low, easily
In realization.
The system model of the embodiment of the present invention is discussed in detail in the content of embodiment in order to better understand the present invention first.
Consider that a machine type equipment communication scenes, including a base station and K machine type equipment, base station and machine type equipment are respectively mounted
Be single antenna, using it is nonopiate and exempt from authorization multiple access agreement.Assuming that having K in a certain coherence timeaA machine type
To base station pilot signal transmitted, then the pilot signal that base station receives is represented by equipment
Wherein p (k) indicates number of k-th of active user in system in all machine type equipment；hp(k)It is serial number P
(k) channel response of the machine type equipment to base station；xp(k)=[xp(k),1,xp(k),2,…,xp(k),N]TIt is a machine type of pth (k)
The pilot frequency sequence that equipment is sent, w are that mean value is 0, variance σ2Gaussian noise.
Joint realizes that active user detection and its channel are estimated in a kind of flood tide machine type communication disclosed by the embodiments of the present invention
Meter method, mainly includes the following steps:
Step 1: flood tide machine type equipment authorizes non-orthogonal mode random access system by exempting from.Any machine type is set
Standby access base station exempts from authorization, i.e., any active user (having data that the equipment sent is needed to be known as active user) can directly to
Base station pilot signal transmitted and data information do not need first to send access application to base station, and can only agree to access receiving
Instruction after just can be with pilot signal transmitted and data information.In addition, it is leading for N that each equipment, which is assigned a length,
Frequency sequence is not required to meet orthogonality relation between sequence.
Step 2: any active ues detection and its channel estimation are modeled as the sparse signal reconfiguring in compressive sensing theory.
K machine type equipment, the K in certain time period are shared in systemaA machinery equipment is in active state, then remaining K-KaIt is a
Machine type equipment is in a dormant state.Machine type equipment its communication link in a dormant state does not activate, thus its channel
Response is zero.If all machine type equipment in consideration system, formula (1) can be expressed equivalently as
Wherein h is a sparse vector, includes K-KaA neutral element, KaA nonzero element, and nonzero element is in h
Position is corresponding with p (k) in formula (1).
Step 3: with SL0 compressed sensing restructing algorithm joint-detection active user and estimating its channel state information.According to
According to the linear equation y=Xh+w of (2), use SL0 algorithm provided by the invention detects active user and estimates that its channel response has
Body step can be summarized as follows:
The present invention also provides a kind of most preferably embodiments, this method comprises:
Step 11, flood tide machine type equipment authorizes non-orthogonal mode random access system by exempting from；
Step 12, any active ues detection and its channel estimation are modeled as the sparse signal reconfiguring in compressive sensing theory,
And use SL0 (smoothed l0- norm algorithm) restructing algorithm joint-detection and estimate any active ues and its channel
Status information.
It is further preferred that in a step 11,
Any machine type equipment access base station exempts from authorization, i.e., any active user (equipment for having data to need to send
Referred to as active user) it can not need first to send access application to base station directly to base station pilot signal transmitted and data information, and
And can only receive agree to access instruction after just can be with pilot signal transmitted and data information.In addition, each equipment
It is assigned the pilot frequency sequence that a length is N, is not required to meet orthogonality relation between sequence.
It is further preferred that in step 12, active user detection and its channel estimation are modeled as compressive sensing theory
In sparse signal reconfiguring method include:
A certain time slot, if sharing K in systemaA machinery equipment is in active state, then the K that base station receivesaA activity
The pilot signal that user sends may be expressed as:
Wherein p (k) indicates number of k-th of active user in system in all machine type equipment；Base station and machine type
That equipment is respectively mounted is single antenna, hp(k)It is channel response of a machine type equipment of P (k) to base station；xp(k)=[xp(k),1,
xp(k),2,…,xp(k),N]TIt is the pilot frequency sequence that a machine type equipment of pth (k) is sent, w is that mean value is 0, variance σ2Gauss make an uproar
Sound.
K machine type equipment, the K in certain time period are shared in systemaA machinery equipment is in active state, then remaining
K-KaA machine type equipment is in a dormant state.Machine type equipment its communication link in a dormant state does not activate, from
And its channel response is zero.If all machine type equipment, the pilot signal received can be expressed equivalently as in consideration system
Wherein h is a sparse vector, includes K-KaA neutral element, KaA nonzero element, and nonzero element is in h
Position is corresponding with the number p (k) of active user in systems.
It is further preferred that in step 12, detecting active user with SL0 restructing algorithm and estimating its channel shape
The method of state information includes:
Step 121, observation signal y, observing matrix X, threshold value σ are inputtedmin, contraction factor ρ, step size mu and the number of iterations L；
Step 122, it enablesWherein superscript notationIndicate pseudo-inverse operation operation；
Step 123, if σ > σmin, then sequence executes (I) and (II)；Otherwise, step 124 is executed.
(I) on set of feasible solution { h | y=Xh }, from initial solutionL times following iteration steepest descent algorithm is begun through,
Maximize objective function
(a) element value of setting vector δ is
(b) it enablesThen pass throughIt willIt projects on its set of feasible solution；
(II) σ ← ρ σ, and return step 123 are enabled；
Step 124, it calculatesAnd find out KaThe position number of a greatest member value, by the KaA position number deposit set
I exports the active user I and its channel state information detected
Compared with prior art, active user detection provided by the invention and its channel estimation methods use compressed sensing weight
Structure algorithm SL0 can significantly reduce pilot signal length required for channel estimation.This method computation complexity is low, easily
In realization.
In order to verify the method for the present invention validity existing method compared with advantage, done the test of following simulation comparison.
The scenario parameters considered are: machine type number of devices K=200, active user number Ka=40；SL0 algorithmic variable parameter value
For σmin=0.001, ρ=0.5, μ=2, L=3.Fig. 2 is to combine to realize active user detection and its letter with SL0 compressed sensing
Channel estimation method (being labeled as method provided by the invention) uses the work of different length pilot signal with traditional least square method
Family detection correct probability comparison diagram is employed, as can be seen from the figure the detection correct probability of the method provided by the present invention is substantially better than most
Small square law.Fig. 3 is returned with least square method using the channel estimation of different length pilot signal with the method provided by the present invention
One changes mean square error curve graph, and as can be seen from the figure channel estimation methods provided by the invention can be reduced 50% pilot length,
And estimated accuracy is high.
It is described the prefered embodiments of the present invention in detail above in conjunction with attached drawing, still, the present invention is not limited to above-mentioned realities
The detail in mode is applied, within the scope of the technical concept of the present invention, a variety of letters can be carried out to technical solution of the present invention
Monotropic type, these simple variants all belong to the scope of protection of the present invention.
It is further to note that specific technical features described in the above specific embodiments, in not lance
In the case where shield, can be combined in any appropriate way, in order to avoid unnecessary repetition, the present invention to it is various can
No further explanation will be given for the combination of energy.
In addition, various embodiments of the present invention can be combined randomly, as long as it is without prejudice to originally
The thought of invention, it should also be regarded as the disclosure of the present invention.
Claims (10)
1. active user detection method in a kind of flood tide machine type communication, which is characterized in that movable in the flood tide machine type communication
User's detection method includes:
The sparse signal reconfiguring being modeled as in compressive sensing theory is estimated into active user detection and active user channels, and used
SLO restructing algorithm goes out any active ues according to subscriber channel state estimation.
2. active user detection method in flood tide machine type communication according to claim 1, which is characterized in that will be movable
Before the sparse signal reconfiguring that user's detection and active user channels estimation are modeled as in compressive sensing theory, comprising:
Flood tide machine type equipment is authorized into non-orthogonal mode random access base station by exempting from.
3. active user detection method in flood tide machine type communication according to claim 1, which is characterized in that by flood tide machine
Device class equipment authorizes non-orthogonal mode random access base station by exempting from, comprising:
The pilot signal of flood tide machine type equipment and data information are sent directly to the base station；And by multiple flood tide machine types
Each flood tide machine type equipment distributes the pilot frequency sequence of a preset length in equipment, and without full between multiple sequences
Sufficient orthogonality relation.
4. active user detection method in flood tide machine type communication according to claim 1, which is characterized in that use activity
Family detection and its channel estimation are modeled as the sparse signal reconfiguring in compressive sensing theory, comprising:
A certain time slot, if having K in K machine type equipmentaA flood tide machine type equipment is in active state, then base station receives
The KaThe pilot signal that a active user is sent may be expressed as:
Wherein, p (k) indicates number of k-th of active user in system in all flood tide machine type equipment；Base station and flood tide machine
What device class equipment was respectively mounted is single antenna；hp(k)It is channel response of a flood tide machine type equipment of P (k) to base station；xp(k)=
[xP (k), 1, xP (k), 2..., xP (k), N]TIt is the pilot frequency sequence that a flood tide machine type equipment of pth (k) is sent, w is that mean value is 0, variance
For σ2Gaussian noise；
Work as KaA flood tide machine type equipment is in active state, then K-KaA flood tide machine type equipment is in a dormant state；In not
Its communication link of the flood tide machine type equipment of dormancy state does not activate, so that its channel response is zero；If considering all flood tides
Machine type equipment, the then pilot signal received can be expressed equivalently as by following formula
Wherein, h is a sparse vector, includes K-KaA neutral element, KaA nonzero element, and position of the nonzero element in h
It is corresponding with the number p (k) of active user.
5. active user detection method in flood tide machine type communication according to claim 1, which is characterized in that use SLO
(smooth L0 norm algorithm) restructing algorithm goes out any active ues according to subscriber channel state estimation, comprising:
Step 121, observation signal y, observing matrix X, threshold value σ are inputtedmin, contraction factor ρ, step size mu and the number of iterations L；
Step 122, it enablesWherein, superscript notationIndicate pseudo-inverse operation operation；
Step 123, if σ > σmin, then sequence executes (I) and (II)；Otherwise, step 124 is executed,
(I) on set of feasible solution { h | y=Xh }, from initial solutionL times following iteration steepest descent algorithm is begun through, it is maximum
Change objective function
(a) element value of setting vector δ is
(b) it enablesThen pass throughIt willIt projects on its set of feasible solution；
(II) σ ← ρ σ, and return step 123 are enabled；
Step 124, it calculatesAnd find out KaThe position number of a greatest member value, by the KaA position number is stored in set I, defeated
The active user I and active user channels status information detected out
6. active user detection system in a kind of flood tide machine type communication, which is characterized in that movable in the flood tide machine type communication
User's detection system includes:
The sparse signal reconfiguring being modeled as in compressive sensing theory is estimated into active user detection and active user channels, and used
The equipment that SLO (smooth L0 norm algorithm) restructing algorithm goes out any active ues according to subscriber channel state estimation.
7. active user detection system in flood tide machine type communication according to claim 6 characterized by comprising
Equipment by flood tide machine type equipment by exempting to authorize non-orthogonal mode random access base station.
8. active user detection system in flood tide machine type communication according to claim 6, which is characterized in that by flood tide machine
Equipment of the device class equipment by exempting to authorize non-orthogonal mode random access base station, comprising:
The equipment that the pilot signal of flood tide machine type equipment and data information are sent directly to the base station；And by multiple flood tides
Each flood tide machine type equipment distributes the pilot frequency sequence of a preset length in machine type equipment, and between multiple sequences
Equipment without meeting orthogonality relation.
9. active user detection system in flood tide machine type communication according to claim 6, which is characterized in that use activity
The equipment that family detection and its channel estimation are modeled as the sparse signal reconfiguring in compressive sensing theory, comprising:
A certain time slot, if having K in K machine type equipmentaA flood tide machine type equipment is in active state, then base station receives
The KaThe pilot signal that a active user is sent may be expressed as:
Wherein, p (k) indicates number of k-th of active user in system in all flood tide machine type equipment；Base station and flood tide machine
What device class equipment was respectively mounted is single antenna；hp(k)It is channel response of a flood tide machine type equipment of P (k) to base station；xp(k)=
[xP (k), 1, xP (k), 2..., xP (k), N]TIt is the pilot frequency sequence that a flood tide machine type equipment of pth (k) is sent, w is that mean value is 0, variance
For σ2Gaussian noise；
Work as KaA flood tide machine type equipment is in active state, then K-KaA flood tide machine type equipment is in a dormant state；In not
Its communication link of the flood tide machine type equipment of dormancy state does not activate, so that its channel response is zero；If considering all flood tides
Machine type equipment, the then pilot signal received can be expressed equivalently as by following formula
Wherein, h is a sparse vector, includes K-KaA neutral element, KaA nonzero element, and position of the nonzero element in h
It is corresponding with the number p (k) of active user.
10. active user detection system in flood tide machine type communication according to claim 6, which is characterized in that use SLO
The equipment that (smooth L0 norm algorithm) restructing algorithm goes out any active ues according to subscriber channel state estimation, comprising:
Input equipment inputs observation signal y, observing matrix X, threshold value σmin, contraction factor ρ, step size mu and the number of iterations L；
It enablesWherein, superscript notationIndicate pseudo-inverse operation operation；
Equipment is judged, if σ > σmin, then sequence executes (I) and (II)；Otherwise, output equipment work is executed,
(I) on set of feasible solution { h | y=Xh }, from initial solutionL times following iteration steepest descent algorithm is begun through, it is maximum
Change objective function
(a) element value of setting vector δ is
(b) it enablesThen pass throughIt willIt projects on its set of feasible solution；
(II) σ ← ρ σ is enabled, and returns to judgement equipment；
Output equipment calculatesAnd find out KaThe position number of a greatest member value, by the KaA position number is stored in set I,
Export the active user I detected and active user channels status information
Priority Applications (1)
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