CN107517169A - A kind of half-blind channel estimating method of cloud Radio Access Network integration and cooperation sub-clustering - Google Patents

A kind of half-blind channel estimating method of cloud Radio Access Network integration and cooperation sub-clustering Download PDF

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CN107517169A
CN107517169A CN201710615766.4A CN201710615766A CN107517169A CN 107517169 A CN107517169 A CN 107517169A CN 201710615766 A CN201710615766 A CN 201710615766A CN 107517169 A CN107517169 A CN 107517169A
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mrow
cluster
msub
remote radio
cooperative cluster
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CN107517169B (en
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赵中原
李瑛�
王珂
杨大全
王文博
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Beijing University of Posts and Telecommunications
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Beijing University of Posts and Telecommunications
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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
    • H04L25/024—Channel estimation channel estimation algorithms
    • H04L25/0256—Channel estimation using minimum mean square error criteria
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/022—Site diversity; Macro-diversity
    • H04B7/026—Co-operative diversity, e.g. using fixed or mobile stations as relays
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/08—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station
    • H04B7/0837—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station using pre-detection combining
    • H04B7/0842—Weighted combining
    • H04B7/0848—Joint weighting
    • H04B7/0854—Joint weighting using error minimizing algorithms, e.g. minimum mean squared error [MMSE], "cross-correlation" or matrix inversion
    • 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
    • H04L25/0222—Estimation of channel variability, e.g. coherence bandwidth, coherence time, fading frequency
    • 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
    • H04L25/0238—Channel estimation using blind estimation
    • 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
    • H04L25/024—Channel estimation channel estimation algorithms
    • H04L25/0242—Channel estimation channel estimation algorithms using matrix methods
    • 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

Abstract

The invention discloses a kind of half-blind channel estimating method of cloud Radio Access Network integration and cooperation sub-clustering, belong to cloud Radio Access Network field, be specially：Users all first sends pilot tone and data message to Remote Radio Unit, the pilot frequency information of oneself is superimposed after Remote Radio Unit amplifies and is transmitted to centralized baseband processing unit pond, then channel condition information is obtained after centralized baseband processing unit pond processing, cooperative cluster is divided to Remote Radio Unit, and merge fractured operation, the different corresponding benefit functions of sub-clustering mode are assessed, obtain optimal sub-clustering mode, finally to the information of each cluster received, first with half-blind channel estimating method, by being handled accordingly in centralized baseband processing unit pond, obtain the independent channel status information of access link and forward link, re-demodulation goes out data message.The present invention significantly reduces the pilot-frequency expense needed for channel estimation, considerably improves the data transmission efficiency of cloud Radio Access Network.

Description

A kind of half-blind channel estimating method of cloud Radio Access Network integration and cooperation sub-clustering
Technical field
The present invention relates to cloud Radio Access Network field, the half of specifically a kind of cloud Radio Access Network integration and cooperation sub-clustering Blind channel estimation method.
Background technology
For the pressure for solving the data transfer of system and processing is brought, cloud Radio Access Network becomes 5G radio communications The critical network framework used in system.But pilot-frequency expense will take extra Radio Resource in channel estimation, from And cause system data transmission rate reduction.Meanwhile rationally control the cooperation scale of cloud Radio Access Network to improve and be System data transmission performance.
Channel estimation methods pilot-frequency expense of the prior art is big, and does not account for and utilize suitable sub-clustering lifting system System performance, causes the data transmission efficiency of network relatively low.
The content of the invention
The present invention improves the data transmission efficiency in network to reduce the pilot-frequency expense of channel estimation, it is proposed that a kind of The half-blind channel estimating method of cloud Radio Access Network integration and cooperation sub-clustering, is comprised the following steps that：
Step 1: under cloud Radio Access Network transmitting scene, user is established, at Remote Radio Unit and centralized base band Manage the traffic model between unit cells；
Described transmitting scene includes：K user is transmitted information at centralized base band by M Remote Radio Unit Unit cells are managed, pass through wireless forward pass link connection, each user between Remote Radio Unit and centralized baseband processing unit pond A Remote Radio Unit is connected by antenna respectively, each Remote Radio Unit is at least connected with a user.
Step 2: each user the first orthogonal guide frequency information sum sent to Remote Radio Unit by access link it is believed that Breath；
Step 3: each Remote Radio Unit the first orthogonal guide frequency information and data message superposition the to receiving respectively After two orthogonal guide frequency information, centralized baseband processing unit pond is sent to；
Specially：Each Remote Radio Unit receive the first orthogonal guide frequency information sum for each user being attached thereto it is believed that Breath, and the second orthogonal guide frequency information is superimposed using the mode of piecemeal splicing pilot tone in all information of each user, use afterwards The mode of amplification forwarding, the first orthogonal guide frequency information and data message that will be received, and the second orthogonal guide frequency information pass through Wireless forward pass link is sent to centralized baseband processing unit pond；
Step 4: centralized baseband processing unit pond divides cooperative cluster to Remote Radio Unit, and merge-split behaviour Make, the result for the sub-clustering that cooperates is optimized；
Specially：
M Remote Radio Unit random division is N number of disjoint association by step 401, centralized baseband processing unit pond Make cluster and initialized；
N number of disjoint Random Cooperation cluster is：C1,...,Cn,...,CN, N≤M.
Step 402, N number of Random Cooperation cluster transmit data to centralized baseband processing unit pond simultaneously, record transmission every time For a frame, the benefit function of each Random Cooperation cluster in calculating respectively per frame；
Random Cooperation cluster C in i-th framenBenefit function be calculated as follows：
WhereinRepresent Random Cooperation cluster C during the i-th -1 framenIn all Remote Radio Unit overall transmission rate, Represent the i-th -1 frame to Random Cooperation cluster CnIn all Remote Radio Unit carry out the mean square errors of channel estimations.
Step 403, for the i-th frame, using the benefit function of each Random Cooperation cluster of the frame, all radio frequencies of the frame are drawn Remote unit reconsolidates cooperative cluster；
Comprise the following steps that：
For the Random Cooperation cluster C of the i-th frame1,...,Cn,...,CN, traversal selection s is as initial merging association successively Make cluster Pk, s=1,2 ... N；Calculate initial merging cooperative cluster PkBenefit functionAnd judge the benefit of s Random Cooperation cluster Whether function sum meetsIf it is, determine to merge cooperative cluster PkDivide successfully；Otherwise, retain s with Machine cooperative cluster nonjoinder, ergodic process is repeated, until the merging cooperative cluster of Remote Radio Unit no longer changes.
Step 404, for the i-th frame, using the benefit function of each Random Cooperation cluster in the frame, all in the frame are penetrated Frequency extension unit splits cooperative cluster again；
Comprise the following steps that：
For some Random Cooperation cluster C of the i-th framen, it is disjoint that Remote Radio Unit composition t therein is traveled through successively Random Cooperation cluster, as fractionation cooperative cluster S1,...,St；And each benefit function for splitting cooperative cluster is calculated respectively, judge random Cooperative cluster CnWhether meet with the benefit function sum of all fractionation cooperative clustersIf it is, determine random association Make cluster CnIt is split as t independent cooperative cluster S1,...,StSuccess；Otherwise, Random Cooperation cluster C is retainednDo not split, repeat to travel through Process, until the fractionation cooperative cluster of all Random Cooperation clusters all no longer changes.
Step 405, for the i-th frame, continuous repeat step 403 and step 404, until obtaining final all merging cooperative clusters Optimization cooperative cluster is used as with cooperative cluster is split.
Step 5: in units of optimizing cooperative cluster, semi-blind channel is carried out using the first orthogonal guide frequency information butt joint incoming link Estimation, semi-blind channel estimation is carried out to forward pass link using the second orthogonal guide frequency information；
Comprise the following steps that：
Step 501, in the i-th frame each optimization cooperative cluster, to access link channel condition information carry out semi-blind channel The result of estimation is initialized, while the semi-blind channel estimation result of forward pass downlink channel state information is initialized；
For n-th of optimization cooperative cluster in the i-th frame, to access link channel condition information G1,nCarry out semi-blind channel estimation Result be initialized as
G1,nChannel matrix of the user to Remote Radio Unit in n-th of optimization cooperative cluster of expression；Represent that size is Kn×MnFull 0 matrix；KnRepresent the number of users that Remote Radio Unit connects in n-th of optimization cooperative cluster, MnRepresent n-th Optimize the quantity of Remote Radio Unit in cooperative cluster；
Meanwhile to forward pass downlink channel state information G2,nSemi-blind channel estimation result be initialized as
G2,nWireless channel of the Remote Radio Unit to centralized baseband processing unit pond in n-th of optimization cooperative cluster of expression Matrix；Expression size is Mn× D full 0 matrix；D is represented between Remote Radio Unit and centralized baseband processing unit pond Wireless forward pass number of links.
Step 502, in the i-th frame n-th optimization cooperative cluster, two semi-blind channel estimation results are iterated, will The iteration result of the m-1 times preserve toWith
In i-th frame in n-th of optimization m-1 iteration of cooperative cluster, to access link channel condition information G1,nCarry out half fanaticism Road estimation result bePreserve extremelyTo forward pass downlink channel state information G in m-1 iteration2,nHalf The result of blind Channel Estimation isPreserve extremely
Step 503, in the i-th frame n-th optimization cooperative cluster, calculate the m time iteration in access link channel status letter Cease G1,nSemi-blind channel estimation result
Using KKT conditions (Karush-Kuhn-Tucker Conditions, Caro need-Kuhn-Tucker condition) solve with Lower optimization problem obtains result
Wherein,AqIt is Remote Radio Unit forwarding pilot frequency information Magnification factor, IDRepresent the unit matrix that size is D × D, q1,n(l) l-th of user's hair in n-th of optimization cooperative cluster is represented The length for giving Remote Radio Unit is L pilot frequency information.
Step 504, the access link channel condition information G to n-th of optimization the m times iteration of cooperative cluster in the i-th frame1,n's Channel estimation results are updated, order
Step 505, in the i-th frame n-th optimization cooperative cluster, calculate the m time iteration in forward pass downlink channel state letter Cease G2,nSemi-blind channel estimation result
Following optimization problem, which is solved, using Quasi-Newton algorithm obtains result
Wherein, B=G1,nq1,n(l),
Step 506, the forward pass downlink channel state information G to n-th of optimization the m times iteration of cooperative cluster in the i-th frame2,n's Channel estimation results are updated, order
Step 507, for n-th of optimization cooperative cluster in the i-th frame, calculate the m-1 time semi-blind channel estimation result and the m times The relative error ε of semi-blind channel estimation resultI(m)；
Step 508, judge relative error εI(m) value whether be less than given threshold value A or iterations reach it is default most Big iterations U, if it is, obtaining the semi-blind channel estimation result of twoWithOtherwise, return to step 502；
WhereinValue for last time iteration to access link channel condition information G1,nSemi-blind channel estimation As a result,Value for last time iteration to forward pass downlink channel state information G2,nSemi-blind channel estimation result.
Step 6: in units of optimizing cooperative cluster, centralized baseband processing unit pond is believed access link and forward pass link The result that channel state information carries out semi-blind channel estimation carries out joint-detection, solves what the user in each optimization cooperative cluster was transmitted Data message.
Data message is detected according to following criterion for n-th of optimization cooperative cluster in the i-th frame：
Wherein, y represents the data message from n-th of optimization cooperative cluster that centralized baseband processing unit pond receives, AsRepresent the power normalization factor of the Remote Radio Unit in n-th of optimization cooperative cluster, PRRepresent in n-th of optimization cooperative cluster Remote Radio Unit repeating power, PsRepresent that entering row information by the Remote Radio Unit in n-th of optimization cooperative cluster passes Defeated user sends the transmission power of information, and Ω represents to meet the numerical value set in all constellation points of given modulation system.
The advantage of the invention is that：
1), a kind of half-blind channel estimating method of cloud Radio Access Network integration and cooperation sub-clustering, by being racked wirelessly upper Access in the channel estimation of network and use semi-blind channel estimation and Remote Radio Unit cooperation sub-clustering combined optimization technology, effectively The pilot-frequency expense needed for channel estimation is reduced, considerably improves the data transmission efficiency of cloud Radio Access Network.
2) a kind of, half-blind channel estimating method of cloud Radio Access Network integration and cooperation sub-clustering, while utilize pilot tone sum It is believed that number carrying out channel estimation, the cooperation scale of Remote Radio Unit is controlled, so as to improve precision of channel estimation and system data Transmission rate.
Brief description of the drawings
Fig. 1 is the model and signal transmission form schematic diagram of cloud Radio Access Network of the present invention；
Fig. 2 is the flow chart of the half-blind channel estimating method of cloud Radio Access Network integration and cooperation sub-clustering of the present invention；
Fig. 3 divides cooperative cluster for the centralized baseband processing unit pond of the present invention and merges-split the flow chart of optimization；
Fig. 4 is the flow chart that the present invention carries out semi-blind channel estimation to the access link and forward pass link that optimize cooperative cluster；
Fig. 5 is the MSE contrast schematic diagrams of the invention with traditional MMSE and ZF channel estimation methods.
Embodiment
Below in conjunction with drawings and examples, the present invention is described in further detail.
Under cloud Radio Access Network transmitting scene, in traditional uplink channel estimation method, use all first Family sends respective pilot frequency information to Remote Radio Unit simultaneously, and the user profile received is amplified and folded by Remote Radio Unit The pilot signal of oneself is added to be transmitted to centralized baseband processing unit pond, what centralized baseband processing unit pond processing received leads Channel condition information is obtained after frequency signal.Due to being based entirely on pilot tone estimation channel condition information, therefore in order to improve estimation essence Degree reduces message transmission rate, it is necessary to increase pilot length.
The present invention, can be in centralized Base-Band Processing list in order to reduce the pilot-frequency expense of traditional uplink channel estimation method First pond is assessed the different corresponding benefit functions of sub-clustering mode, obtains optimal sub-clustering mode, to each cluster received Signal, first with half-blind channel estimating method, by being handled accordingly in centralized baseband processing unit pond, connect The independent channel status information of incoming link and forward link, re-demodulation go out data-signal.
As shown in Fig. 2 comprise the following steps that：
Step 1: under cloud Radio Access Network transmitting scene, user is established, at Remote Radio Unit and centralized base band Manage the traffic model between unit cells；
As shown in figure 1, in the communication system of reality, semi-blind channel estimation and sub-clustering joint that the embodiment of the present invention proposes Optimization is applicable to the cloud Radio Access Network of high transfer rate；Under cloud Radio Access Network transmitting scene, user is established, Traffic model between Remote Radio Unit and centralized baseband processing unit pond；Described transmitting scene includes：K user is led to Cross M Remote Radio Unit and transmit information to a centralized baseband processing unit pond, Remote Radio Unit and centralized base A remote radio list is connected by an antenna by wireless forward pass link connection, each user between tape handling unit pond Member, each Remote Radio Unit are at least connected with a user.Assuming that without straight between user and centralized baseband processing unit pond The connection connect, and user can only carry out information transfer by the Remote Radio Unit near it.
Step 2: each user the first orthogonal guide frequency information sum sent to Remote Radio Unit by access link it is believed that Breath；
Step 3: each Remote Radio Unit is respectively at the first orthogonal guide frequency information and data message that receive After reason, after being superimposed the second orthogonal guide frequency information, centralized baseband processing unit pond is sent to；
Specially：Each Remote Radio Unit receive the first orthogonal guide frequency information sum for each user being attached thereto it is believed that Breath, and the second orthogonal guide frequency information is superimposed using the mode of piecemeal splicing pilot tone in all information of each user, use afterwards The mode of amplification forwarding, the first orthogonal guide frequency information and data message that will be received, and the second orthogonal guide frequency information pass through Wireless forward pass link is sent to centralized baseband processing unit pond；
Step 4: centralized baseband processing unit pond divides cooperative cluster to Remote Radio Unit, and merge-split behaviour Make, the result for the sub-clustering that cooperates is optimized；
By taking the i-th frame as an example, centralized baseband processing unit pond is according to the transmission rate and channel of each channel in the i-th -1 frame Estimate mean square error, by merging-fractured operation using maximum utility function as target, cooperation point is carried out to Remote Radio Unit Cluster.
As shown in figure 3, it is specially：
M Remote Radio Unit random division is N number of disjoint association by step 401, centralized baseband processing unit pond Make cluster and initialized；
N number of disjoint Random Cooperation cluster is：C1,...,Cn,...,CN, N≤M.
Step 402, N number of Random Cooperation cluster transmit data to centralized baseband processing unit pond simultaneously, record transmission every time For a frame, the benefit function of each Random Cooperation cluster in calculating respectively per frame；
Random Cooperation cluster C in i-th framenBenefit function be calculated as follows：
WhereinRepresent Random Cooperation cluster C during the i-th -1 framenIn all Remote Radio Unit overall transmission rate, Represent the i-th -1 frame to Random Cooperation cluster CnIn all Remote Radio Unit carry out the mean square errors of channel estimations.
Step 403, for the i-th frame, using the benefit function of each Random Cooperation cluster of the frame, all radio frequencies of the frame are drawn Remote unit reconsolidates cooperative cluster；
Comprise the following steps that：
For the Random Cooperation cluster C of the i-th frame1,...,Cn,...,CN, traversal selection s is as initial merging association successively Make cluster Pk, s=1,2 ... N；Calculate initial merging cooperative cluster PkBenefit functionAnd judge the benefit of s Random Cooperation cluster Whether function sum meetsIf it is, determine to merge cooperative cluster PkDivide successfully；Otherwise, retain s with Machine cooperative cluster nonjoinder, ergodic process is repeated, until the merging cooperative cluster of Remote Radio Unit no longer changes.
Step 404, for the i-th frame, using the benefit function of each Random Cooperation cluster in the frame, all in the frame are penetrated Frequency extension unit splits cooperative cluster again；
Comprise the following steps that：
For some Random Cooperation cluster C of the i-th framen, it is disjoint that Remote Radio Unit composition t therein is traveled through successively Random Cooperation cluster, as fractionation cooperative cluster S1,...,St；And each benefit function for splitting cooperative cluster is calculated respectively, judge random Cooperative cluster CnWhether meet with the benefit function sum of all fractionation cooperative clustersIf it is, determine random association Make cluster CnIt is split as t independent cooperative cluster S1,...,StSuccess；Otherwise, Random Cooperation cluster C is retainednDo not split, repeat to travel through Process, until the fractionation cooperative cluster of all Random Cooperation clusters all no longer changes.
Step 405, for the i-th frame, continuous repeatedly merging-splitting step, until obtain final all merging cooperative clusters and Cooperative cluster is split as optimization cooperative cluster.
Step 5: in units of optimizing cooperative cluster, semi-blind channel is carried out using the first orthogonal guide frequency information butt joint incoming link Estimation, semi-blind channel estimation is carried out to forward pass link using the second orthogonal guide frequency information；
As shown in figure 4, comprise the following steps that：
Step 501, in the i-th frame each optimization cooperative cluster, to access link channel condition information carry out semi-blind channel The result of estimation is initialized, while the semi-blind channel estimation result of forward pass downlink channel state information is initialized；
For n-th of optimization cooperative cluster in the i-th frame, to access link channel condition information G1,nCarry out semi-blind channel estimation Result be initialized as
G1,nChannel matrix of the user to Remote Radio Unit in n-th of optimization cooperative cluster of expression；Represent that size is Kn×MnFull 0 matrix；KnRepresent the number of users that Remote Radio Unit connects in n-th of optimization cooperative cluster, MnRepresent n-th Optimize the quantity of Remote Radio Unit in cooperative cluster；
Meanwhile to forward pass downlink channel state information G2,nSemi-blind channel estimation result be initialized as
G2,nWireless channel of the Remote Radio Unit to centralized baseband processing unit pond in n-th of optimization cooperative cluster of expression Matrix；Expression size is Mn× D full 0 matrix；D represent Remote Radio Unit and centralized baseband processing unit pond it Between wireless forward pass number of links；D≥M.
Step 502, in the i-th frame n-th optimization cooperative cluster, two semi-blind channel estimation results are iterated, will The iteration result of the m-1 times preserve toWith
In i-th frame in n-th of optimization m-1 iteration of cooperative cluster, to access link channel condition information G1,nCarry out half fanaticism Road estimation result bePreserve extremelyTo forward pass downlink channel state information G in m-1 iteration2,nHalf The result of blind Channel Estimation isPreserve extremely
Step 503, in the i-th frame n-th optimization cooperative cluster, calculate the m time iteration in access link channel status letter Cease G1,nSemi-blind channel estimation result
Following optimization problem, which is solved, using KKT conditions obtains result
Wherein,AqIt is Remote Radio Unit forwarding pilot frequency information Magnification factor, IDRepresent the unit matrix that size is D × D, q1,n(l) l-th of user's hair in n-th of optimization cooperative cluster is represented The length for giving Remote Radio Unit is L pilot frequency information, and in order to reduce channel estimation expense, L is less than normal length, and L1≥ K。
Step 504, the access link channel condition information G to n-th of optimization the m times iteration of cooperative cluster in the i-th frame1,n's Channel estimation results are updated, order
Step 505, in the i-th frame n-th optimization cooperative cluster, calculate the m time iteration in forward pass downlink channel state letter Cease G2,nSemi-blind channel estimation result
Following optimization problem, which is solved, using Quasi-Newton algorithm obtains result
Wherein, B=G1,nq1,n(l),
Step 506, the forward pass downlink channel state information G to n-th of optimization the m times iteration of cooperative cluster in the i-th frame2,n's Channel estimation results are updated, order
Step 507, for n-th of optimization cooperative cluster in the i-th frame, calculate the m-1 time semi-blind channel estimation result and the m times The relative error ε of semi-blind channel estimation resultI(m)；
Step 508, judge relative error εI(m) value whether be less than given threshold value A or iterations reach it is default most Big iterations U, if it is, obtaining the semi-blind channel estimation result of twoWithOtherwise, return to step 502；
WhereinValue for last time iteration to access link channel condition information G1,nSemi-blind channel estimation As a result,Value for last time iteration to forward pass downlink channel state information G2,nSemi-blind channel estimation result.
Step 6: in units of optimizing cooperative cluster, centralized baseband processing unit pond is believed access link and forward pass link The result that channel state information carries out semi-blind channel estimation carries out joint-detection, solves what the user in each optimization cooperative cluster was transmitted Data message.
The present invention is by taking maximum-likelihood detec-tion as an example, for n-th of optimization cooperative cluster in the i-th frame according to following criterion to data Information is detected：
Wherein, y represents the data message from n-th of optimization cooperative cluster that centralized baseband processing unit pond receives, AsRepresent the power normalization factor of the Remote Radio Unit in n-th of optimization cooperative cluster, PRRepresent in n-th of optimization cooperative cluster Remote Radio Unit repeating power, PsRepresent that entering row information by the Remote Radio Unit in n-th of optimization cooperative cluster passes Defeated user sends the transmission power of information, and Ω represents to meet the numerical value set in all constellation points of given modulation system.
The present invention is estimated by semi-blind channel estimation and the combined optimization of Remote Radio Unit cooperation cluster-dividing method, semi-blind channel Meter utilizes pilot tone and data signal extraction channel condition information, reduces pilot-frequency expense.Centralized baseband processing unit pond is based on effect Beneficial function, the relation of balance system message transmission rate and precision of channel estimation in sub-clustering, optimal cooperation scheme is obtained, then Joint pilot signal obtains the independent channel status information of access link and forward pass link, and demodulated data signal, reduces pilot tone Expense, improve system data rates.
In order to assess the performance gain of the present invention, by the performance gain of the present invention and MMSE of the tradition based on pilot tone The performance gain of channel estimation scheme is compared；As shown in figure 5, be number of users be 10, far end radio frequency extension unit quantity For 5 and centralized baseband processing unit pond antenna amount be 5 cloud Radio Access Network under rayleigh fading channel situation time Go through the MSE (mean square error) of the above two method of estimation of 10000 times and the curve map of pilot sequence length, the song of asterisk mark Line is the estimation performance of access link, and the curve of square marks is the estimation performance of forward pass link.
Experiment shows, 6 × 10 are increased to from 0 in the length ratio of pilot tone in the transmitted signals-3During, present invention institute is right The MSE estimations performance for two channels answered will be better than traditional MMSE channel estimation methods and ZF channel estimation methods all the time, And if assume that MSE is fixed, the pilot tone that the present invention uses is shorter, and the advantage for improving message transmission rate is more obvious.
The present invention can be significantly reduced in channel estimation by Remote Radio Unit cooperation sub-clustering and semi-blind channel estimation Pilot-frequency expense, precision of channel estimation is improved, further improve the data transmission performance of system, simple to operate, it is convenient to realize.When So, any product for implementing embodiments of the invention it is not absolutely required to reach all the above advantage simultaneously.

Claims (4)

1. a kind of half-blind channel estimating method of cloud Radio Access Network integration and cooperation sub-clustering, it is characterised in that specific steps are such as Under：
Step 1: under cloud Radio Access Network transmitting scene, user, Remote Radio Unit and centralized Base-Band Processing list are established Traffic model between first pond；
Step 2: each user sends the first orthogonal guide frequency information and data message by access link to Remote Radio Unit；
Step 3: each Remote Radio Unit is being superimposed second just to the first orthogonal guide frequency information and data message received respectively After handing over pilot frequency information, centralized baseband processing unit pond is sent to；
Step 4: centralized baseband processing unit pond divides cooperative cluster to Remote Radio Unit, and-fractured operation is merged, The result for the sub-clustering that cooperates is optimized；
Step 5: in units of optimizing cooperative cluster, semi-blind channel estimation is carried out using the first orthogonal guide frequency information butt joint incoming link, Semi-blind channel estimation is carried out to forward pass link using the second orthogonal guide frequency information；
Comprise the following steps that：
Step 501, in the i-th frame each optimization cooperative cluster, to access link channel condition information carry out semi-blind channel estimation Result initialized, while the semi-blind channel estimation result of forward pass downlink channel state information is initialized；
For n-th of optimization cooperative cluster in the i-th frame, to access link channel condition information G1,nCarry out the knot of semi-blind channel estimation Fruit is initialized as
G1, nChannel matrix of the user to Remote Radio Unit in n-th of optimization cooperative cluster of expression；Expression size is Kn×Mn Full 0 matrix；KnRepresent the number of users that Remote Radio Unit connects in n-th of optimization cooperative cluster, MnRepresent n-th of optimization association Make the quantity of Remote Radio Unit in cluster；
Meanwhile to forward pass downlink channel state information G2, nSemi-blind channel estimation result be initialized as
G2,nWireless channel matrix of the Remote Radio Unit to centralized baseband processing unit pond in n-th of optimization cooperative cluster of expression；Expression size is Mn× D full 0 matrix；D represents the nothing between Remote Radio Unit and centralized baseband processing unit pond Line forward pass number of links；
Step 502, in the i-th frame n-th optimization cooperative cluster, two semi-blind channel estimation results are iterated, by m-1 Secondary iteration result preserve toWith
In i-th frame in n-th of optimization m-1 iteration of cooperative cluster, to access link channel condition information G1, nSemi-blind channel is carried out to estimate The result of meter isPreserve extremelyTo forward pass downlink channel state information G in m-1 iteration2,nHalf fanaticism Road estimation result bePreserve extremely
Step 503, in the i-th frame n-th optimization cooperative cluster, calculate the m times iteration in access link channel condition information G1,n Semi-blind channel estimation result
Solved using KKT conditions (Karush-Kuhn-Tucker Conditions, Caro need-Kuhn-Tucker condition) following excellent Change problem obtains result
<mrow> <munder> <mi>min</mi> <msub> <mi>G</mi> <mrow> <mn>1</mn> <mo>,</mo> <mi>n</mi> </mrow> </msub> </munder> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>l</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>K</mi> </munderover> <msubsup> <mi>G</mi> <mrow> <mn>1</mn> <mo>,</mo> <mi>n</mi> </mrow> <mi>H</mi> </msubsup> <msub> <mi>AG</mi> <mrow> <mn>1</mn> <mo>,</mo> <mi>n</mi> </mrow> </msub> <mrow> <mo>(</mo> <msub> <mi>q</mi> <mrow> <mn>1</mn> <mo>,</mo> <mi>n</mi> </mrow> </msub> <mo>(</mo> <mi>l</mi> <mo>)</mo> <msubsup> <mi>q</mi> <mrow> <mn>1</mn> <mo>,</mo> <mi>n</mi> </mrow> <mi>H</mi> </msubsup> <mo>(</mo> <mi>l</mi> <mo>)</mo> <mo>)</mo> </mrow> </mrow>
Wherein,AqIt is putting for Remote Radio Unit forwarding pilot frequency information Big factor, IDRepresent the unit matrix that size is D × D, q1,n(l) represent that l-th of user is sent in n-th of optimization cooperative cluster The length of Remote Radio Unit is L pilot frequency information；
Step 504, the access link channel condition information G to n-th of optimization the m times iteration of cooperative cluster in the i-th frame1,nChannel Estimated result is updated, order
Step 505, in the i-th frame n-th optimization cooperative cluster, calculate the m times iteration in forward pass downlink channel state information G2,n Semi-blind channel estimation result
Following optimization problem, which is solved, using Quasi-Newton algorithm obtains result
<mrow> <munder> <mi>min</mi> <msub> <mi>G</mi> <mrow> <mn>2</mn> <mo>,</mo> <mi>n</mi> </mrow> </msub> </munder> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>l</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>K</mi> </munderover> <msup> <mrow> <mo>(</mo> <msub> <mi>G</mi> <mrow> <mn>2</mn> <mo>,</mo> <mi>n</mi> </mrow> </msub> <mi>B</mi> <mo>)</mo> </mrow> <mi>H</mi> </msup> <msubsup> <mi>&amp;Sigma;</mi> <msub> <mi>Z</mi> <mrow> <mn>2</mn> <mo>,</mo> <mi>n</mi> </mrow> </msub> <mrow> <mo>-</mo> <mn>1</mn> </mrow> </msubsup> <msub> <mi>G</mi> <mrow> <mn>2</mn> <mo>,</mo> <mi>n</mi> </mrow> </msub> <mi>B</mi> </mrow>
Wherein, B=G1,nq1,n(l),
Step 506, the forward pass downlink channel state information G to n-th of optimization the m times iteration of cooperative cluster in the i-th frame2,nChannel Estimated result is updated, order
Step 507, the cooperative cluster that optimizes for n-th in the i-th frame, the m-1 times semi-blind channel estimation result of calculating and the m times half-blindness The relative error ε of channel estimation resultsI(m)；
<mrow> <msub> <mi>&amp;epsiv;</mi> <mi>I</mi> </msub> <mrow> <mo>(</mo> <mi>m</mi> <mo>)</mo> </mrow> <mo>=</mo> <mo>|</mo> <msubsup> <mi>G</mi> <mrow> <mn>1</mn> <mo>,</mo> <mi>n</mi> </mrow> <mrow> <mo>&amp;prime;</mo> <mn>1</mn> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>m</mi> <mo>)</mo> </mrow> <mo>-</mo> <msubsup> <mi>G</mi> <mrow> <mn>1</mn> <mo>,</mo> <mi>n</mi> </mrow> <mrow> <mo>&amp;prime;</mo> <mn>2</mn> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>m</mi> <mo>)</mo> </mrow> <mo>|</mo> <mo>+</mo> <mo>|</mo> <msubsup> <mi>G</mi> <mrow> <mn>2</mn> <mo>,</mo> <mi>n</mi> </mrow> <mrow> <mo>&amp;prime;</mo> <mn>1</mn> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>m</mi> <mo>)</mo> </mrow> <mo>-</mo> <msubsup> <mi>G</mi> <mrow> <mn>2</mn> <mo>,</mo> <mi>n</mi> </mrow> <mrow> <mo>&amp;prime;</mo> <mn>2</mn> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>m</mi> <mo>)</mo> </mrow> <mo>|</mo> </mrow>
Step 508, judge relative error εI(m) value whether is less than given threshold value A or iterations reaches default greatest iteration Number U, if it is, obtaining the semi-blind channel estimation result of twoWithOtherwise, return to step 502；
<mfenced open = "" close = ""> <mtable> <mtr> <mtd> <mrow> <msub> <mover> <mi>G</mi> <mo>^</mo> </mover> <mrow> <mn>1</mn> <mo>,</mo> <mi>n</mi> </mrow> </msub> <mo>=</mo> <msubsup> <mi>G</mi> <mrow> <mn>1</mn> <mo>,</mo> <mi>n</mi> </mrow> <mrow> <mo>&amp;prime;</mo> <mn>1</mn> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>m</mi> <mo>)</mo> </mrow> <mo>,</mo> </mrow> </mtd> <mtd> <mrow> <msub> <mover> <mi>G</mi> <mo>^</mo> </mover> <mrow> <mn>2</mn> <mo>,</mo> <mi>n</mi> </mrow> </msub> <mo>=</mo> <msubsup> <mi>G</mi> <mrow> <mn>2</mn> <mo>,</mo> <mi>n</mi> </mrow> <mrow> <mo>&amp;prime;</mo> <mn>1</mn> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>m</mi> <mo>)</mo> </mrow> <mo>;</mo> </mrow> </mtd> </mtr> </mtable> </mfenced>
WhereinValue for last time iteration to access link channel condition information G1,nSemi-blind channel estimation result,Value for last time iteration to forward pass downlink channel state information G2nSemi-blind channel estimation result；
Step 6: in units of optimizing cooperative cluster, centralized baseband processing unit pond is to access link and forward pass link channel shape The result that state information carries out semi-blind channel estimation carries out joint-detection, solves the data of user's transmission in each optimization cooperative cluster Information；
Data message is detected according to following criterion for n-th of optimization cooperative cluster in the i-th frame：
<mrow> <mover> <mi>S</mi> <mo>^</mo> </mover> <mo>=</mo> <mi>arg</mi> <munder> <mi>min</mi> <mrow> <mi>S</mi> <mo>&amp;Element;</mo> <mi>&amp;Omega;</mi> </mrow> </munder> <mo>|</mo> <mi>y</mi> <mo>-</mo> <msub> <mi>A</mi> <mi>s</mi> </msub> <msqrt> <msub> <mi>P</mi> <mi>R</mi> </msub> </msqrt> <msqrt> <msub> <mi>P</mi> <mi>s</mi> </msub> </msqrt> <msub> <mover> <mi>G</mi> <mo>^</mo> </mover> <mrow> <mn>1</mn> <mo>,</mo> <mi>n</mi> </mrow> </msub> <msub> <mover> <mi>G</mi> <mo>^</mo> </mover> <mrow> <mn>2</mn> <mo>,</mo> <mi>n</mi> </mrow> </msub> <mi>S</mi> <mo>|</mo> </mrow>
Wherein, y represents the data message from n-th of optimization cooperative cluster that centralized baseband processing unit pond receives, AsRepresent The power normalization factor of Remote Radio Unit in n-th of optimization cooperative cluster, PRRepresent the radio frequency in n-th of optimization cooperative cluster The repeating power of extension unit, PsRepresent the use by the Remote Radio Unit progress information transfer in n-th of optimization cooperative cluster Family sends the transmission power of information, and Ω represents to meet the numerical value set in all constellation points of given modulation system.
2. a kind of half-blind channel estimating method of cloud Radio Access Network integration and cooperation sub-clustering as claimed in claim 1, it is special Sign is that the transmitting scene described in step 1 includes：K user transmits information to concentration by M Remote Radio Unit Formula baseband processing unit pond, by wireless forward pass link connection between Remote Radio Unit and centralized baseband processing unit pond, Each user connects a Remote Radio Unit by antenna respectively, and each Remote Radio Unit is at least connected with a user.
3. a kind of half-blind channel estimating method of cloud Radio Access Network integration and cooperation sub-clustering as claimed in claim 1, it is special Sign is that the step 3 is specially：Each Remote Radio Unit receives the first orthogonal guide frequency letter for each user being attached thereto Breath and data message, and be superimposed the second orthogonal guide frequency using the mode of piecemeal splicing pilot tone in all information of each user and believe Breath, afterwards by the way of amplification forwarding, the first orthogonal guide frequency information and data message that will receive, and second orthogonal lead Frequency information is sent to centralized baseband processing unit pond by wireless forward pass link.
4. a kind of half-blind channel estimating method of cloud Radio Access Network integration and cooperation sub-clustering as claimed in claim 1, it is special Sign is that the step 4 is specially：
M Remote Radio Unit random division is N number of disjoint cooperative cluster by step 401, centralized baseband processing unit pond And initialized；
N number of disjoint Random Cooperation cluster is：C1,...,Cn,...,CN, N≤M；
Step 402, N number of Random Cooperation cluster transmit data to centralized baseband processing unit pond simultaneously, and record is transmitted as one every time Frame, the benefit function of each Random Cooperation cluster in calculating respectively per frame；
Random Cooperation cluster C in i-th framenBenefit function be calculated as follows：
<mrow> <msubsup> <mi>u</mi> <msub> <mi>C</mi> <mi>n</mi> </msub> <mi>i</mi> </msubsup> <mo>=</mo> <msubsup> <mi>r</mi> <msub> <mi>C</mi> <mi>n</mi> </msub> <mrow> <mi>i</mi> <mo>-</mo> <mn>1</mn> </mrow> </msubsup> <mo>-</mo> <msubsup> <mi>MSE</mi> <msub> <mi>C</mi> <mi>n</mi> </msub> <mrow> <mi>i</mi> <mo>-</mo> <mn>1</mn> </mrow> </msubsup> </mrow>
WhereinRepresent Random Cooperation cluster C during the i-th -1 framenIn all Remote Radio Unit overall transmission rate,Represent I-th -1 frame is to Random Cooperation cluster CnIn all Remote Radio Unit carry out the mean square errors of channel estimations；
Step 403, for the i-th frame, using the benefit function of each Random Cooperation cluster of the frame, by all remote radio lists of the frame Member reconsolidates cooperative cluster；
Comprise the following steps that：
For the Random Cooperation cluster C of the i-th frame1,...,Cn,...,CN, traversal selection s is as initial merging cooperative cluster successively Pk, s=1,2 ... N；Calculate initial merging cooperative cluster PkBenefit functionAnd judge the benefit function of s Random Cooperation cluster Whether sum meetsIf it is, determine to merge cooperative cluster PkDivide successfully；Otherwise, s random associations are retained Make cluster nonjoinder, ergodic process is repeated, until the merging cooperative cluster of Remote Radio Unit no longer changes；
Step 404, for the i-th frame, using the benefit function of each Random Cooperation cluster in the frame, all radio frequencies in the frame are drawn Remote unit splits cooperative cluster again；
Comprise the following steps that：
For some Random Cooperation cluster C of the i-th framen, it is disjoint random that Remote Radio Unit composition t therein is traveled through successively Cooperative cluster, as fractionation cooperative cluster S1,...,St；And each benefit function for splitting cooperative cluster is calculated respectively, judge Random Cooperation Cluster CnWhether meet with the benefit function sum of all fractionation cooperative clustersIf it is, determine Random Cooperation cluster CnIt is split as t independent cooperative cluster S1,...,StSuccess；Otherwise, Random Cooperation cluster C is retainednDo not split, repeat ergodic process, Until the fractionation cooperative cluster of all Random Cooperation clusters all no longer changes；
Step 405, for the i-th frame, continuous repeat step 403 and step 404, until obtaining final all merging cooperative clusters and tearing open Divide cooperative cluster as optimization cooperative cluster.
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