CN109861934A - Method for accurately estimating space channel system function based on sparse theory - Google Patents
Method for accurately estimating space channel system function based on sparse theory Download PDFInfo
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- CN109861934A CN109861934A CN201910073243.0A CN201910073243A CN109861934A CN 109861934 A CN109861934 A CN 109861934A CN 201910073243 A CN201910073243 A CN 201910073243A CN 109861934 A CN109861934 A CN 109861934A
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Abstract
The invention discloses a method for accurately estimating a spatial channel system function based on a sparse theory, which comprises the following steps: considering that the number of main channels in a scenario is limited, a hybrid-based l is established when estimating the channel using the received data0A sparse canonical least squares model of norm; considering the non-convexity of the problem, convex relaxation is carried out on the problem by utilizing a convex optimization theory, and a mixture l is given1A sparse canonical least squares model of norm; and then reconstructing the received data according to the obtained result, and adjusting a weight factor between a fitting error and the channel sparsity in the optimization model according to the error between the received data and the original data until the weight factor meets a convergence condition. The invention can fully utilize the prior information of the space channel sparsity, thereby optimizing the fitting error of the received data and the sparsity of the channel coefficient vector, being more in line with the practical situation, and effectively avoiding the deviation of channel coefficient estimation caused by only considering the fitting error when the space channel is estimated by the traditional method.
Description
Technical field
The present invention relates to a kind of communications fields, more particularly, to a kind of accurate estimation space channel system based on sparse theory
The method of system function.
Background technique
As internet gradually deeply changes human lives, mobile communication rapid development, it has also become drive global economy hair
One of the main high-tech industry of exhibition.In mobile communications, signal is transmitted by electromagnetic wave between transmitting terminal and receiving end, I
The channel of electromagnetic transmission is called wireless channel.Wireless channel and the environment of surrounding are closely related, the nothing under varying environment
Line channel has the feature of some differentiation.How to find and extract these features and be applied to optimization wireless network, is
A current research hotspot.Since electromagnetic wave is different along the propagation distance of each paths, identical transmitting signal is via each
The time that paths reach receiving end is different, i.e., variant between the time delay of multipath.In addition, each paths are to identical transmitting
Signal in communication process caused by influence it is different, i.e., it is variant between the coefficient of multipath, as shown in Figure 1.Therefore, optimize
The key problem of network is exactly accurately to be estimated the wireless channel in space first.Currently, common method is to pass through minimum
Least square method obtains approximate solution: h=(GHG)-1GHR, the solution have only been done a preferable fitting to data, have not been fully considered
The important feature of channel sparsity in actual environment, so least square solution is for the estimation problem of wireless signal and improper,
It needs further to study the solving model of problem.
Summary of the invention
The method of the object of the present invention is to provide a kind of accurate estimation space channel system function based on sparse theory is led to
The weight factor number changed between error of fitting and channel degree of rarefication is crossed, it is sufficiently sharp while guaranteeing to receive data error of fitting
With this sparse prior information of space channel, so that accurate estimation space channel system function, of the existing technology to overcome
Defect.
The present invention is achieved by the following technical solutions:
The method of accurate estimation space channel system function based on sparse theory, which comprises the following steps:
(1) it uses the linear FM signal of certain bandwidth to spatial emission detectable signal in base station, is detectd pre-set
Receiving end receives the coupled signal comprising spatial channel information, samples respectively to echo data；
(2) space channel is estimated according to following trace flows:
Firstly, being recognized using the jammer transmitting existing FM signal in broadband to space channel, it is contemplated that a field
The several numbers of prevailing channel in scape are limited, and when using data are received to channel identifying, are established based on mixing l0Norm
Sparse canonical least square model, minimize | | Gh-r | |2+γ||h||0, wherein | | Gh-r | |2The fitting for representing data misses
Difference, | | h | |0The measurement of channel degree of rarefication is represented, γ > 0 is weighted factor；Convex relaxation is carried out to it using convex optimum theory, is mixed
Close l1The sparse canonical least square model minimize of norm | | Gh-r | |2+γ||h||1, must demonstrate,prove the model is a second order
Planning problem is bored, can effectively be solved using convex optimum theory, specifically: call the tool box CVX comprising adytum algorithm
Optimization problem after relaxation is solved；
(3) basis acquires channel model reconstructed reception data, and according to the error of fitting of itself and initial data, adjustment relaxation
Weight factor in Optimized model between error of fitting and channel degree of rarefication afterwards is effectively being fitted until it meets the condition of convergence
Ensure the sparsity of channel model on the basis of reception data.
The invention has the advantages that
The present invention can make full use of this prior information of space channel sparsity, so that taking into account optimization receives data fitting
The degree of rarefication of error and channel coefficient vector, also more meets reality, effectively prevents conventional method and estimates to space channel
Timing only considers the deviation that error of fitting causes channel coefficients to estimate.
Detailed description of the invention
Fig. 1 is the channel schematic diagram that signal space is propagated.
Specific embodiment
As shown in Figure 1, the method for the accurate estimation space channel system function based on sparse theory, which is characterized in that packet
Include following steps:
(1) it uses the linear FM signal of certain bandwidth to spatial emission detectable signal in base station, is detectd pre-set
Receiving end receives the coupled signal comprising spatial channel information, samples respectively to echo data；
(2) space channel is estimated according to following trace flows: firstly, emitting the existing frequency modulation in broadband using jammer
Signal recognizes space channel, it is contemplated that the several numbers of prevailing channel in one scenario are limited, and are utilizing reception
When data are to channel identifying, establish based on mixing l0The sparse canonical least square model of norm, minimize | | Gh-r | |2+
γ||h||0, wherein | | Gh-r | |2The error of fitting of data is represented, | | h | |0The measurement of channel degree of rarefication is represented, γ > 0 is weighting
The factor, it is realized to the fit quality of data and the balance and compromise of channel coefficient vector degree of rarefication, to take into account the property of the two
Energy；In view of the nonconvex property of this problem, existing method is difficult to provide an effective method for solving, and the present invention is managed using convex optimization
By convex relaxation is carried out to it, l is mixed1The sparse canonical least square model minimize of norm | | Gh-r | |2+γ||h||1, can
It is a Second-order cone programming problem so that the model must be demonstrate,proved, can be effectively solved using convex optimum theory, can specifically be adjusted
The optimization problem after relaxation is solved with the tool box CVX comprising adytum algorithm；
(3) basis acquires channel model reconstructed reception data, and according to the error of fitting of itself and initial data, adjustment relaxation
Weight factor in Optimized model between error of fitting and channel degree of rarefication afterwards is effectively being fitted until it meets the condition of convergence
To ensure the sparsity of channel model on the basis of reception data, to more meet actual conditions.
Claims (1)
1. the method for the accurate estimation space channel system function based on sparse theory, which comprises the following steps:
(1) it uses the linear FM signal of certain bandwidth to spatial emission detectable signal in base station, detects receiving end pre-set
Coupled signal comprising spatial channel information is received, echo data is sampled respectively；
(2) space channel is estimated according to following trace flows:
Firstly, being recognized using the jammer transmitting existing FM signal in broadband to space channel, it is contemplated that in one scenario
The several numbers of prevailing channel be limited, using receive data to channel identifying when, establish based on mixing l0Norm it is sparse
Canonical least square model, minimize | | Gh-r | |2+γ||h||0, wherein | | Gh-r | |2The error of fitting of data is represented, | |
h||0The measurement of channel degree of rarefication is represented, γ > 0 is weighted factor；Convex relaxation is carried out to it using convex optimum theory, mixes l1Model
Several sparse canonical least square model minimize | | Gh-r | |2+γ||h||1, must demonstrate,prove the model is a Second-order cone programming
Problem can effectively be solved using convex optimum theory, specifically: call the tool box CVX comprising adytum algorithm to relaxation
Optimization problem afterwards is solved；
(3) basis acquires channel model reconstructed reception data, and according to the error of fitting of itself and initial data, excellent after adjustment relaxation
Change the weight factor in model between error of fitting and channel degree of rarefication, until it meets the condition of convergence, is received in effective fitting
Ensure the sparsity of channel model on the basis of data.
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| US20180138978A1 (en) * | 2013-05-01 | 2018-05-17 | U.S. Army Research Laboratory Attn: Rdrl-Loc-I | Opto-electronic oscillator with stimulated brillouin scattering feedbac, |
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