CN101754343B - Channel transmission quality feedback method, system and device - Google Patents
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Abstract
The invention discloses a channel transmission quality feedback method, a system and a device. The channel transmission quality feedback method comprises the following steps: signal-to-noise ratio of a sub-channel is selected according to a threshold to form a signal-to-noise ratio sub-vector, and the formed signal-to-noise ratio sub-vector is undertaken the non-linear conversion; the signal-to-noise ratio sub-sector after the non-linear conversion is polynomially fitted to obtain a feedback parameter, and the feedback parameter is transmitted and is used for ensuring that a transmitting end obtains the signal-to-noise ratio sub-vector so as to determine the channel transmission quality. Through the above method, the transmitting end utilizes the signal-to-noise ratio sub-vector to predict the variation of the signal-to-noise ratio sub-vector when different powers are adopted to improve factors and to predict the effective signal-to-noise ratio corresponding to different coding modulation ways as well as the block error rate corresponding to the signal-to-noise ratio sub-vector, so the quantity of the feedback parameters can be reduced, and the prediction precision of the channel transmission quality can be improved.
Description
Technical Field
The embodiment of the invention relates to the technical field of communication, in particular to a method, a system and equipment for feeding back channel transmission quality.
Background
The prior art respectively provides methods such as an EESM (explicit Effective Signal to Noise Ratio mapping), an MI-ESM (Mutual Information-Effective Signal to Noise Ratio mapping), and a Mean Information-Effective Signal to Noise Ratio mapping) and an MMIB (Mean Information mapping) for the purpose of easily obtaining BLER (Block Error rate) of a multi-parallel subchannel system under different coding modulation when a system channel changes slowly or is substantially unchanged during transmission of one data packet. These effective snr mapping methods map the snr vector of the parallel sub-channels to an effective snr value, and then use this effective snr value to find the estimated BLER value from a basic AWGN (Additive White Gaussian Noise) link level performance curve.
The introduction of the effective signal-to-noise ratio mapping method greatly simplifies the parameters for representing the multi-parallel sub-channel system, and the addition and average operation in the effective signal-to-noise ratio mapping enables one value of the effective signal-to-noise ratio to correspond to the quality states of multiple parallel sub-channels, namely one effective signal-to-noise ratio cannot accurately represent the quality states of the multiple parallel sub-channels, but the effective signal-to-noise ratios of different parameters of the same channel can represent the quality states of the parallel sub-channels. And in the EESM, MI-ESM and MMIB methods, the calculation of the effective signal-to-noise ratio needs to know the signal-to-noise ratio state of the current sub-channel. In the effective signal-to-noise ratio calculation, the value of the effective signal-to-noise ratio is independent of the sequence of the signal-to-noise ratios in the vector, the contributions of components with different values in the signal-to-noise ratio vector to the effective signal-to-noise ratio are different, namely the contribution of a subchannel with lower signal-to-noise ratio is large, while the contribution of a subchannel with higher signal-to-noise ratio is small, and when the value of the signal-to-noise ratio in a certain subchannel is very large, the contribution can even be. Therefore, the sub-channel with a smaller snr value is mainly used to determine the effective snr, and the snr of this portion can also accurately characterize the quality status of the parallel sub-channels.
In order to effectively transmit the quality state of multiple parallel sub-channels and overcome the problems of linear fitting, the prior art proposes a low feedback scheme of link quality report based on the EESM technology. In the prior art, a relationship between an effective signal-to-noise ratio and beta is utilized, and a fitted parameter is used as feedback information by a curve fitting method. The beta can be changed in a larger range, and the linear approximate range is limited, so that a linear fitting method can bring larger prediction error, the nonlinear fitting improves the fitting precision of effective signal-to-noise ratio to the beta to a certain extent by adding a parameter, but the precision is still not high enough, and the prediction error is different when the beta and the power promoting factor are different, so that the prediction error can cause the block error rate with a steep curve to have larger deviation. .
In order to adopt a power bit allocation algorithm with better performance at a transmitting end, a method for feeding back a signal-to-noise ratio of each subcarrier is proposed in the second prior art. In the second prior art, channel quality is transmitted by fitting the shape of the change of the signal-to-noise ratio of the parallel sub-channels according to the shape of the change of the signal-to-noise ratio along with the sequence number. However, the second prior art does not fully consider that the signal-to-noise ratio of each parallel sub-channel has different effects on the total transmission quality of the system, and therefore, the signal-to-noise ratio sequence recovered by the second prior art has a large error in representing the transmission quality of the channel. Compared with the first prior art, the second prior art transmits the original serial numbers of the sequenced sub-channels besides the fitting coefficients, and the feedback information quantity is large. In MIMO-OFDM and other systems with a large number of parallel sub-channels, the complexity of the operation in the prior art is high, the feedback data volume is large, and the error of the recovered signal-to-noise ratio vector in the aspect of representing the transmission quality of the system is also large.
Disclosure of Invention
The embodiment of the invention provides a method, a system and equipment for feeding back channel transmission quality, which are used for reducing the number of feedback parameters and improving the prediction precision of the channel transmission quality.
An embodiment of the present invention provides a method for feeding back channel transmission quality, including:
selecting a sub-channel signal-to-noise ratio according to a threshold to form a signal-to-noise ratio sub-vector, and carrying out nonlinear transformation on the formed signal-to-noise ratio sub-vector;
and performing polynomial fitting on the signal-to-noise ratio sub-vector after the nonlinear transformation to obtain a feedback parameter, and sending the feedback parameter, wherein the feedback parameter is used for enabling a sending end to obtain the signal-to-noise ratio sub-vector and determining the channel transmission quality.
In another aspect, an embodiment of the present invention provides a method for determining channel transmission quality, including:
obtaining feedback parameters sent by a receiving end;
according to the feedback parameters, a vector corresponding to the sending end is constructed according to a fitting polynomial;
carrying out inverse transformation of nonlinear transformation on the constructed vector to obtain a signal-to-noise ratio sub-vector formed by signal-to-noise ratios of a plurality of parallel sub-channels;
and determining the channel transmission quality according to the signal-to-noise ratio sub-vector.
In another aspect, an embodiment of the present invention provides a system for determining channel transmission quality, including:
the receiving end equipment is used for selecting the signal-to-noise ratio of the sub-channel according to the threshold, forming a signal-to-noise ratio sub-vector and carrying out nonlinear transformation on the formed signal-to-noise ratio sub-vector; performing polynomial fitting on the signal-to-noise ratio sub-vector after nonlinear transformation to obtain a feedback parameter, and sending the feedback parameter;
the sending end equipment is used for obtaining the feedback parameters sent by the receiving end equipment and constructing vectors corresponding to the sending end equipment according to the feedback parameters and fitting polynomials; and carrying out inverse transformation of nonlinear transformation on the constructed vector to obtain a signal-to-noise ratio sub-vector formed by signal-to-noise ratios of a plurality of parallel sub-channels, and determining the channel transmission quality according to the signal-to-noise ratio sub-vector.
In another aspect, an embodiment of the present invention provides a receiving end device, including:
the selection module is used for selecting the signal-to-noise ratio of the sub-channel according to the threshold to form a signal-to-noise ratio sub-vector;
the transformation module is used for carrying out nonlinear transformation on the signal-to-noise ratio sub-vector formed by the selection module;
the fitting module is used for carrying out polynomial fitting on the signal-to-noise ratio sub-vector converted by the conversion module to obtain a feedback parameter;
and the sending module is used for sending the feedback parameters obtained by the fitting module to sending end equipment.
In another aspect, an embodiment of the present invention provides a sending-end device, including:
the receiving module is used for obtaining feedback parameters sent by receiving end equipment;
the construction module is used for constructing a vector corresponding to the sending end equipment according to the feedback parameters obtained by the receiving module and a fitting polynomial;
the inverse transformation module is used for carrying out inverse transformation of nonlinear transformation on the vector constructed by the construction module to obtain a signal-to-noise ratio sub-vector formed by signal-to-noise ratios of a plurality of parallel sub-channels;
and the transmission quality determining module is used for determining the channel transmission quality according to the signal-to-noise ratio sub-vector obtained by the inverse transformation module.
Compared with the prior art, the embodiment of the invention has the following advantages: according to the embodiment of the invention, the receiving end selects the sub-channel signal-to-noise ratio from the sub-channel signal-to-noise ratios according to the threshold to form the signal-to-noise ratio sub-vector, and the feedback parameters are obtained according to the signal-to-noise ratio sub-vector, so that the number of the feedback parameters is reduced. The sending end can recover the signal-to-noise ratio sub-vector representing the transmission quality of each parallel sub-channel according to the feedback parameter, the signal-to-noise ratio sub-vector can be used for predicting the change of the signal-to-noise ratio sub-vector under the condition of adopting different power boosting factors, the effective signal-to-noise ratios corresponding to different coding modulation modes and the block error rate corresponding to the signal-to-noise ratio sub-vector are predicted, and the prediction precision of the channel transmission quality is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a flowchart of a method for feeding back channel transmission quality according to an embodiment of the present invention;
FIG. 2 is a flow chart of transmitting feedback parameters according to an embodiment of the present invention;
FIG. 3 is a flow chart of recovering signal-to-noise ratio sub-vectors according to an embodiment of the present invention;
fig. 4 is a block diagram of a system for determining channel transmission quality according to an embodiment of the present invention;
fig. 5 is a structural diagram of a receiving end device according to an embodiment of the present invention;
fig. 6 is a structural diagram of another receiving end device according to another embodiment of the present invention;
fig. 7 is a structural diagram of a sending-end device according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The embodiment of the invention provides a feedback method of channel transmission quality, which is oriented to systems such as OFDM, MIMO-OFDM and the like, the signal-to-noise ratios in each parallel sub-channel are sequenced at a receiving end to form a signal-to-noise ratio sub-vector with monotonicity, the signal-to-noise ratio sub-vector which is closely related to the channel transmission quality is selected from the signal-to-noise ratio sub-vector, parameters which represent the instantaneous channel transmission quality are formed by carrying out companding and fitting processing on the selected signal-to-noise ratio sub-vector, the parameters are fed back to the transmitting end, then the signal-to-noise ratio sub-vector which represents the transmission quality of each parallel sub-channel is recovered by monotonicity detection and processing according to the transformation which is inverse to that of the receiving end, the signal-to-noise ratio sub-vector is utilized to accurately predict the change of the signal-to-noise ratio sub-vector under the adoption of different power, and a block error rate (BLER) corresponding to the signal-to-noise ratio sub-vector. The feedback parameters formed by the embodiment of the invention are simple, the operation complexity is low, the information recovered by the feedback parameters is general, the effective signal-to-noise ratios of different types can be predicted, the prediction precision is high, the state of the transmission quality of the instantaneous parallel sub-channel can be accurately given, and conditions are provided for improving the throughput and the transmission reliability of OFDM, MIMO-OFDM and other systems by further utilizing the self-adaptive transmission technology.
The embodiment of the invention provides a feedback method of channel transmission quality, wherein a receiving end sequences signal-to-noise ratios in each parallel sub-channel, selects signal-to-noise ratios which are closely related to the representation and the channel transmission quality to form signal-to-noise ratio sub-vectors, forms feedback parameters which represent instantaneous channel transmission quality after carrying out companding and fitting processing on the formed signal-to-noise ratio sub-vectors, feeds the feedback parameters back to the sending end, recovers the signal-to-noise ratios which represent the transmission quality of each parallel sub-channel according to the inverse processing of the signal-to-noise ratio sub-vectors in the receiving end, can accurately predict the change of the signal-to-noise ratio sub-vectors under different power boosting factors by using the signal-to-noise ratio sub-vectors, predicts the parameters of effective signal-to-noise ratios EESM, MI-ESM, MMIB and the like corresponding to different coding.
As shown in fig. 1, a flowchart of a method for feeding back channel transmission quality according to an embodiment of the present invention specifically includes:
and step S101, selecting a sub-channel signal-to-noise ratio according to a threshold to form a signal-to-noise ratio sub-vector.
In the embodiment of the invention, the receiving end can sequence the signal-to-noise ratios of a plurality of parallel sub-channels. The method specifically comprises the following steps:
SNR due to effective SNReffIs calculated with the individual subchannel signal-to-noise ratio γ ═ γ1，γ2，...，γN]TThe arrangement order of the sub-channels is irrelevant, and for convenience of subsequent processing, the signal-to-noise ratios of the multiple parallel sub-channels can be sorted and transformed according to the numerical value of each component, which can be expressed as:
γ′＝S(γ) (1)
wherein γ' ═ γ1′，γ2′，...，γN′]T，γ1′≤γ2′≤...≤γN', S (-) denotes a change of ordering from small to large. However, the embodiments of the present invention are not limited to this, and the snr sub-vectors may be sorted from large to small according to the values of the components.
Then, the receiving end selects the sub-channel signal-to-noise ratio closely related to the channel transmission quality from the ordered signal-to-noise ratios to form a signal-to-noise ratio sub-vector.
In the frequency selective channel, the variation range of the signal-to-noise ratio of each sub-channel is large, the influence of the large signal-to-noise ratio on the channel transmission quality is small and can be even ignored sometimes, and the signal-to-noise ratio of the sub-channel with the small value directly influences the size of the effective signal-to-noise ratio and also directly influences the transmission quality of the system. The embodiment of the invention only processes the signal-to-noise ratio of partial sub-channels closely related to the channel transmission quality, not only can accurately reflect the current channel transmission quality, but also can greatly reduce the complexity of a processing algorithm. When selecting the sub-channel signal-to-noise ratio closely related to the channel transmission quality, the selection is carried out according to the signal-to-noise ratio threshold and the dimension threshold of the sub-vector. Firstly, a signal-to-noise ratio threshold gamma is adoptedthMake a selection of
Then G is mixed1And dimension threshold G2And comparing, and determining the dimension of the finally selected signal-to-noise ratio sub-vector as follows:
Gth＝max{G1，G2} (3)
thus, the constructed new snr subvector can be expressed as <math>
<mrow>
<mi>θ</mi>
<mo>=</mo>
<msup>
<mrow>
<mo>[</mo>
<msubsup>
<mi>γ</mi>
<mn>1</mn>
<mo>′</mo>
</msubsup>
<mo>,</mo>
<msubsup>
<mi>γ</mi>
<mn>2</mn>
<mo>′</mo>
</msubsup>
<mo>,</mo>
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<mi>γ</mi>
<msub>
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</msub>
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</msubsup>
<mo>]</mo>
</mrow>
<mi>T</mi>
</msup>
<mo>.</mo>
</mrow>
</math>
When less than the threshold gamma of the signal-to-noise ratiothThe dimension of the signal-to-noise ratio sub-vector formed by the signal-to-noise ratio of the sub-channel is smaller than the dimension threshold G2Then, the receiving end selects a corresponding number of gamma larger than the threshold of the signal-to-noise ratio according to the dimension threshold in the sequenced signal-to-noise ratiothForming a signal-to-noise ratio sub-vector such that the dimension of the formed signal-to-noise ratio sub-vector is equal to the dimension threshold G2；
When the dimension of the signal-to-noise ratio sub-vector formed by the signal-to-noise ratio of the sub-channel smaller than the signal-to-noise ratio threshold is larger than the dimension threshold G2Then, the receiving end selects the gamma less than the threshold of the signal-to-noise ratiothForming a signal-to-noise ratio sub-vector, where the dimension of the signal-to-noise ratio sub-vector is equal to G1。
In selecting signal-to-noise ratio sub-vectorTime-of-measure, signal-to-noise ratio threshold gammathTo satisfy less than gammathAll signal-to-noise ratios of (a) contribute significantly more than the effective signal-to-noise ratio of (b) than the ratio gammathA large signal-to-noise ratio. Dimension threshold G2The same number as the order of the fit is generally chosen to ensure that the accuracy of the signal-to-noise ratio is restored.
The embodiment of the invention determines the threshold GthIn the process, the SNR subvector representing the channel transmission quality can be determined only by using the SNR threshold, and the threshold G is determined by the contribution of each component of the sequenced SNR to the effective SNRthAnd using the threshold GthA signal-to-noise ratio sub-vector is selected.
In the embodiment of the invention, the threshold GthIt may also be a dimension threshold G2According to dimension threshold G2And selecting the sub-channel signal-to-noise ratios from the sorted signal-to-noise ratios to form signal-to-noise ratio sub-vectors.
And step S102, carrying out nonlinear transformation on the formed signal-to-noise ratio sub-vectors.
For signal-to-noise ratio sub-vector <math>
<mrow>
<mi>θ</mi>
<mo>=</mo>
<msup>
<mrow>
<mo>[</mo>
<msubsup>
<mi>γ</mi>
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</math> The nonlinear transformation is carried out, so as to reduce the error of the signal-to-noise ratio component with smaller value in the subsequent processing and improve the precision of the information representing the channel transmission quality. The nonlinear transformation can be expressed as:
ξ＝f(θ) (4)
wherein, the nonlinear transformation f (-) usually adopts companding transformation to convert the ordered SNR subvectors <math>
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</math> And performing companding, namely amplifying a smaller signal-to-noise ratio and compressing a larger signal-to-noise ratio, thereby improving the performance of the small signal in transmission. The nonlinear transformation of the embodiment of the invention adopts mu-law companding, and the companding function can be expressed as:
in the formula (5), x is a normalization input, y is a normalization output, and μ is a companding parameter, which indicates the companding degree.
Before the nonlinear transformation, the threshold γ in step S102 is usedthFor signal-to-noise ratio sub-vector <math>
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</math> And (6) carrying out normalization processing.
For the above nonlinear transformation, in addition to μ law companding, a law companding, logarithmic transformation, companding based on an error function erf (·), nonlinear companding by polygonal line approximation, or other nonlinear companding may be used.
And step S103, performing polynomial fitting on the signal-to-noise ratio sub-vector after the nonlinear transformation to obtain a feedback parameter, and sending the feedback parameter, wherein the feedback parameter is used for enabling a sending end to obtain the signal-to-noise ratio sub-vector and determining the transmission quality of a channel.
Let the signal-to-noise ratio sub-vector after nonlinear transformation be <math>
<mrow>
<mi>ξ</mi>
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</math> Fitting it with a polynomial whose coefficients are <math>
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</math> Then
α＝(XTX)-1XTξ (6)
Wherein, <math>
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</math>
by polynomial fitting, feedback parameters can be obtained <math>
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<mi>α</mi>
<mn>0</mn>
</msub>
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<msub>
<mi>α</mi>
<mn>1</mn>
</msub>
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<msub>
<mi>α</mi>
<mn>2</mn>
</msub>
<mo>,</mo>
<mo>.</mo>
<mo>.</mo>
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<msub>
<mi>α</mi>
<msub>
<mi>G</mi>
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</math>
In the polynomial fitting, a linear least square criterion may be adopted, and a weighted least square criterion, a minimum variance criterion, or the like may also be adopted. In the polynomial fitting, linear fitting or higher-order polynomial fitting may also be employed.
The above flow is only one implementation manner of the embodiment of the present invention, but the embodiment of the present invention is not limited thereto, and the sequence of the step S101 and the step S102 may be arbitrarily arranged without affecting the implementation of the embodiment of the present invention.
In the following description of the embodiments of the invention, which are illustrated by way of example as quadratic polynomial fits, 3 feedback parameters are formed, each in α0、α1And alpha2And (4) showing. Wherein alpha is0、α1And alpha2Respectively Y-axis intercept, linear parameters and quadratic parameters.
To understand the characteristics of the feedback parameters, under the conditions of 5dB effective snr and 1.69 β, the embodiment of the present invention operates on α under different channel realizations and different types of channel conditions0、α1And alpha2Has been subjected to computer simulationAnd (6) testing. By simulation, the mean and variance of the three parameters in the ped a and ped B channels are shown in table 1.
TABLE 1 statistical characterization of feedback parameters
As can be seen from Table 1, the parameter α0、α1And alpha2Is not the same, where a0Is relatively fast, and alpha1And alpha2Is relatively slow, alpha1And alpha2The mean value of (a) is greater in the ped B than in the ped a, which indicates that the two parameters are mainly determined by the channel type and can characterize the frequency selectivity of the channel. It is not necessary in a particular feedback system to feed back the parameter α each time, depending on the nature of the change in the feedback parameter1And alpha2. That is, it is not necessary to feed back the parameter α when the channel type does not change significantly1And alpha2In (1). In the embodiment of the invention, alpha is firstly1And alpha2Is initialized to alpha'1And alpha'2And both the receiving end and the transmitting end know the initial value. If the measured alpha at the receiving end in each channel realization1And alpha2Within an allowable deviation range from the initial value, only the parameter alpha needs to be transmitted0(ii) a If the receiving end measures alpha1And alpha1If the deviation tolerance range of the initial value is exceeded, the receiving end transmits the signal with new alpha'1And alpha'2To the sender. Fig. 2 shows a flow chart of transmitting feedback parameters according to an embodiment of the present invention, and the method according to the embodiment of the present invention can greatly reduce the number of feedback parameters. The method specifically comprises the following steps:
step S201, obtaining a feedback parameter alpha through quadratic curve fitting0、α1And alpha2。
Step S202, judging the feedback parameter alpha0、α1And alpha2The rate of change of each feedback parameter is determined, with or without significant change from the previously stored value. If α is1And alpha2There is a significant change from the previously stored value, which indicates alpha1And alpha2If the channel changes rapidly, go to step S203; if α is0There is no significant change from the previously stored value, indicating a0If the channel changes slowly, step S204 is executed.
Step S203, sending designated information to update the feedback parameter alpha which changes rapidly along with the channel change1And alpha2。
Step S204, sending the feedback parameter alpha slowly changing along with the channel change in the conventional channel quality information0。
Step S205, feeding back the parameter (alpha)0，α′1，α′2) And transmitting to the transmitting end.
In the embodiment of the invention, when the feedback parameters are transmitted, the polynomial fitting parameters alpha0，α′1And alpha'2In addition to the above transmission scheme, the transmission of (A) can be performed first0，α′1And alpha'2And (3) coding, such as Huffman coding, Shannon coding, Vorino coding, arithmetic coding and Lempel-Ziv coding, transmitting the coded data, and decoding to obtain a fitting coefficient after transmission. Fitting parameter alpha to a polynomial that varies with time0，α′1And alpha'2The coded data may also be transmitted by DPCM (Differential Pulse Code Modulation), ADPCM (Adaptive Differential Pulse Code Modulation), or DM (Delta Modulation), so as to reduce the amount of feedback data.
The process of transmitting feedback parameters through a feedback channel, receiving the parameters fed back by a receiving end by a transmitting end, and recovering a signal-to-noise ratio sub-vector representing channel transmission quality by using the feedback parameters is shown in fig. 3, and specifically includes:
step S301, obtaining a feedback parameter sent by the receiving end.
Step S302, according to the feedback parameter α' ═ α0，α′1，α′2]TAnd constructing a vector corresponding to the transmitting end according to the fitting polynomial. The method specifically comprises the following steps:
with feedback parameter α' ═ α0，α′1，α′2]TThe sequence number of the channel is an independent variable, and a channel signal-to-noise ratio sub-vector xi 'corresponding to a sending end is constructed according to a fitting polynomial'1，ξ′2，...，ξ′N]The components of the constructed vector may be expressed as:
ξ′i＝α0+α′1·i+α′2·i2，i＝1，2，...，N (7)
step S303, inverse transformation of nonlinear transformation is carried out on the constructed vector to obtain a signal-to-noise ratio sub-vector formed by signal-to-noise ratios of a plurality of parallel sub-channels.
After obtaining xi ', the transmitting end uses an inverse transformation f' (-) to recover the sub-channel signal-to-noise ratio, which is the nonlinear transformation f (·) in equation (4), and can be expressed as:
ξ″＝f′(ξ′) (8)
in the embodiment of the present invention, because μ law companding is adopted when forming the feedback information, μ law companding conversion should be performed when recovering the feedback information, which can be expressed as:
because the receiving end carries out normalization processing on the sub-channel signal-to-noise ratio, the sub-channel signal-to-noise ratio after decompression and expansion is multiplied by the normalization coefficient gammathAnd restoring the specific numerical value.
And step S304, detecting and processing the sub-channel signal-to-noise ratio, and reducing the error of data recovery by adopting a polynomial fitting coefficient.
Due to the sequencing effect, the signal-to-noise ratio sub-vector of the receiving end participating in the fitting process has monotonicity. Due to the fact that fitting coefficients of the signal-to-noise ratio sub-vectors are adopted during construction, large errors can occur to the signal-to-noise ratios of some sub-channels after construction, particularly to the sub-channels with large values, the signal-to-noise ratio sub-vectors after construction may not have monotonicity, and therefore the signal-to-noise ratio sub-vectors need to be detected and processed. And detecting and determining a partial sequence with a variation trend not meeting the requirement of monotonicity, and generating a sequence according to linear or nonlinear variation to replace the sequence not meeting the monotonicity, so as to form a sequence with the length being the number of sub-channels contained in the system and having monotonous variation.
Step S305, determining the channel transmission quality according to the recovered signal-to-noise ratio sub-vector.
Substituting the signal-to-noise ratio sub-vector xi' restored by the formula (8) into the following formula, obtaining:
in the formula (10), B is a system power boost factor. By changing the values of beta and B, SNR under different code modulation modes and different power boosting factors can be predictedeffThrough the effective snr, the transmitter can select a modulation and coding scheme suitable for the current channel state and the transmission quality requirement according to a FER (Frame Error Ratio) curve under the AWGN condition. The recovered signal-to-noise ratio sub-vector xi' can also be substituted into other formulas of effective signal-to-noise ratio to obtain the corresponding effective signal-to-noise ratio and the corresponding block error rate (BLER).
When the feedback information is formed, after the signal-to-noise ratio sub-vector of the channel transmission quality is selected, the signal-to-noise ratio sub-vector can be extracted at equal intervals to form a signal-to-noise ratio sub-vector with the length of N/p, wherein p is 1, 2. When the feedback information is recovered, a sequence with the length of the number of the sub-channels included in the system is formed by an interpolation method.
The signal-to-noise ratio sub-vector recovered by the embodiment of the invention can be used for calculating MI-ESM, MMIB and other applications needing known sub-channel signal-to-noise ratio besides EESM.
The embodiment of the invention provides a feedback method of channel transmission quality, which selects a signal-to-noise ratio sub-vector representing the signal-to-noise ratio closely related to the channel transmission quality, forms three parameters representing the instantaneous channel transmission quality after carrying out companding and fitting processing on the selected signal-to-noise ratio sub-vector, feeds the three parameters back to a base station, recovers the signal-to-noise ratio sub-vector representing the transmission quality of each parallel sub-channel according to the inverse processing in a mobile station, can accurately predict the change of the signal-to-noise ratio sub-vector under the condition of adopting different power boosting factors by utilizing the signal-to-noise ratio sub-vector, predicts the parameters of effective signal-to-noise ratios EESM, ESM, MMIB and the like corresponding to different coding modulation modes and the block error rate (BLER) corresponding to the signal-.
The feedback information in the embodiment of the invention is a signal-to-noise ratio sub-vector for representing the instantaneous transmission quality state of the channel. The feedback information formed by the method of the embodiment of the invention has less quantity, the processing required by the mobile station is simple, and the complexity is low; the base station can recover the signal-to-noise ratio sub-vector representing the instantaneous transmission quality state of the channel by using the received feedback information, and can predict various effective signal-to-noise ratio forms under different coding modulation modes and power promotion by using the vector.
As shown in fig. 4, a block diagram of a system for determining channel transmission quality according to an embodiment of the present invention includes:
the receiving end device 41 is configured to select a sub-channel signal-to-noise ratio according to a threshold, form a signal-to-noise ratio sub-vector, and perform nonlinear transformation on the formed signal-to-noise ratio sub-vector; performing polynomial fitting on the signal-to-noise ratio sub-vector after nonlinear transformation to obtain a feedback parameter, and sending the feedback parameter;
the sending end device 42 is configured to obtain a feedback parameter sent by the receiving end device 41, and construct a vector corresponding to the sending end device 42 according to the feedback parameter and the fitting polynomial; and carrying out inverse transformation of nonlinear transformation on the constructed vector to obtain a signal-to-noise ratio sub-vector formed by signal-to-noise ratios of a plurality of parallel sub-channels, and determining the channel transmission quality according to the signal-to-noise ratio sub-vector.
As shown in fig. 5, a structure diagram of a receiving end device according to an embodiment of the present invention includes:
a selecting module 411, configured to select a sub-channel signal-to-noise ratio according to a threshold to form a signal-to-noise ratio sub-vector;
a transformation module 412, configured to perform a nonlinear transformation on the signal-to-noise ratio sub-vector formed by the selection module 411;
a fitting module 413, configured to perform polynomial fitting on the signal-to-noise ratio sub-vector transformed by the transformation module 412 to obtain a feedback parameter;
a sending module 414, configured to send the feedback parameters obtained by the fitting module 413 to the sending-end device 42.
As shown in fig. 6, the receiving end device may further include:
a sorting module 415 for sorting the snr of the parallel sub-channels.
The thresholds may specifically be a signal-to-noise ratio threshold and a dimension threshold, and the selecting module 411 may include:
a signal-to-noise ratio selection sub-module 4111, configured to select a sub-channel signal-to-noise ratio greater than the signal-to-noise ratio threshold from the sub-channel signal-to-noise ratios sorted by the sorting module 415;
a first selecting sub-module 4112, configured to, when the dimension of the snr sub-vector formed by the snr sub-vectors selected by the snr selecting sub-module 4111 and smaller than the snr threshold is smaller than the dimension threshold, select a corresponding number of snr sub-vectors from smaller to larger in the ordered snr sub-vectors according to the dimension threshold and the snr sub-vectors larger than the snr threshold to form the snr sub-vector, so that the dimension of the snr sub-vector is equal to the dimension threshold;
a second selecting sub-module 4113, configured to select a sub-channel signal-to-noise ratio smaller than the signal-to-noise ratio threshold to form a signal-to-noise ratio sub-vector when the dimension of the signal-to-noise ratio sub-vector formed by the sub-channel signal-to-noise ratio smaller than the signal-to-noise ratio threshold selected by the signal-to-noise ratio selecting sub-module 4111 is larger than the dimension threshold.
The threshold may be a signal-to-noise ratio threshold, and the selecting module 411 is specifically configured to select a sub-channel signal-to-noise ratio from the sub-channel signal-to-noise ratios sorted by the sorting module 415 according to the signal-to-noise ratio threshold, so as to form a signal-to-noise ratio sub-vector.
The threshold may be a dimension threshold, and the selecting module 411 is specifically configured to select a sub-channel signal-to-noise ratio from the signal-to-noise ratios sorted by the sorting module 415 according to the dimension threshold, so as to form a signal-to-noise ratio sub-vector.
The sending module 414 is specifically configured to carry the feedback parameter in the specified information or the conventional channel quality information, and send the feedback parameter to the sending-end device 42. Specifically, the sending module 414 determines whether the feedback parameters have changed significantly from the previously stored values, i.e., determines the change rate of each feedback parameter. If the feedback parameter changes significantly from the previously stored value, which means that the feedback parameter changes rapidly with channel change, the sending module 414 sends specified information to update the feedback parameter that changes rapidly with channel change; if the feedback parameter does not change significantly from the previously stored value, which indicates that the feedback parameter changes slowly with channel changes, the sending module 414 sends the feedback parameter that changes slowly with channel changes in the regular channel quality information.
As shown in fig. 7, a structure diagram of a sending end device according to an embodiment of the present invention includes:
a receiving module 421, configured to obtain a feedback parameter sent by the receiving end device 41;
a constructing module 422, configured to construct a vector corresponding to the sending-end device 42 according to the fitting polynomial according to the feedback parameter obtained by the receiving module 421;
an inverse transformation module 423, configured to perform inverse transformation of the nonlinear transformation on the vector constructed by the construction module 422, to obtain a signal-to-noise ratio sub-vector formed by signal-to-noise ratios of multiple parallel sub-channels;
and a transmission quality determining module 424, configured to determine channel transmission quality according to the snr sub-vector obtained by the inverse transforming module 423.
The sending-end device 42 may further include:
and the detection module 425 is configured to detect and process the sub-channel signal-to-noise ratios in the signal-to-noise ratio sub-vectors obtained by the inverse transformation module 423, determine the sub-channel signal-to-noise ratio whose variation trend does not satisfy the monotonicity requirement, generate the sub-channel signal-to-noise ratio according to a linear or non-linear variation rule instead of the sub-channel signal-to-noise ratio which does not satisfy the monotonicity requirement, and form a signal-to-noise ratio sub-vector which has a length equal to the number of sub-channels included.
The transmission quality determining module 424 is specifically configured to determine one or both of an effective snr and a block error rate under different modulation and coding schemes and different power boosting factors according to the snr subvector detected and processed by the detecting module 425.
The modules may be distributed in one device or may be distributed in a plurality of devices. The modules can be combined into one module, and can also be further split into a plurality of sub-modules.
Through the above description of the embodiments, those skilled in the art will clearly understand that the present invention may be implemented by hardware, or by software plus a necessary general hardware platform. Based on such understanding, the technical solution of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a usb disk, a removable hard disk, etc.), and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the method according to the embodiments of the present invention.
Those skilled in the art will appreciate that the drawings are merely schematic representations of one preferred embodiment and that the blocks or flow diagrams in the drawings are not necessarily required to practice the present invention.
Those skilled in the art will appreciate that the modules in the devices in the embodiments may be distributed in the devices in the embodiments according to the description of the embodiments, and may be correspondingly changed in one or more devices different from the embodiments. The modules of the above embodiments may be combined into one module, or further split into multiple sub-modules.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
The above disclosure is only for a few specific embodiments of the present invention, but the present invention is not limited thereto, and any variations that can be made by those skilled in the art are intended to fall within the scope of the present invention.
Claims (20)
1. A method for feeding back channel transmission quality, comprising:
selecting a sub-channel signal-to-noise ratio according to a threshold to form a signal-to-noise ratio sub-vector, and carrying out nonlinear transformation on the formed signal-to-noise ratio sub-vector;
and performing polynomial fitting on the signal-to-noise ratio sub-vector after the nonlinear transformation to obtain a feedback parameter, and sending the feedback parameter, wherein the feedback parameter is used for enabling a sending end to obtain the signal-to-noise ratio sub-vector and determining the channel transmission quality.
2. The method of claim 1, wherein said selecting a subchannel signal-to-noise ratio based on a threshold further comprises: the signal-to-noise ratios of the parallel subchannels are ordered.
3. The method of claim 2, wherein the thresholds comprise a signal-to-noise ratio threshold and a dimensionality threshold,
selecting a sub-channel signal-to-noise ratio from the ordered signal-to-noise ratios according to a threshold, and forming a signal-to-noise ratio sub-vector comprising:
selecting a subchannel signal-to-noise ratio smaller than the signal-to-noise ratio threshold from the sorted signal-to-noise ratios;
when the dimension of a signal-to-noise ratio sub-vector formed by sub-channel signal-to-noise ratios smaller than the signal-to-noise ratio threshold is smaller than the dimension threshold, selecting a corresponding number of sub-channel signal-to-noise ratios from small to large in the sorted signal-to-noise ratios according to the dimension threshold and in the sub-channel signal-to-noise ratios larger than the signal-to-noise ratio threshold to form a signal-to-noise ratio sub-vector, so that the dimension of the formed signal-to-noise ratio sub-vector is equal to the dimension;
and when the dimension of the signal-to-noise ratio sub-vector formed by the signal-to-noise ratios of the sub-channels smaller than the signal-to-noise ratio threshold is larger than the dimension threshold, selecting the signal-to-noise ratio of the sub-channel smaller than the signal-to-noise ratio threshold to form the signal-to-noise ratio sub-vector.
4. The method of claim 2, wherein the threshold is in particular a signal-to-noise ratio threshold,
selecting a sub-channel signal-to-noise ratio from the ordered signal-to-noise ratios according to a threshold, and forming a signal-to-noise ratio sub-vector specifically comprises the following steps:
and selecting a sub-channel signal-to-noise ratio from the sequenced signal-to-noise ratios according to the signal-to-noise ratio threshold to form a signal-to-noise ratio sub-vector.
5. The method according to claim 2, characterized in that the threshold is in particular a dimension threshold,
selecting a sub-channel signal-to-noise ratio from the ordered signal-to-noise ratios according to a threshold, and forming a signal-to-noise ratio sub-vector specifically comprises the following steps:
and selecting a sub-channel signal-to-noise ratio from the sequenced signal-to-noise ratios according to the dimension threshold to form a signal-to-noise ratio sub-vector.
6. The method of claim 1, 3, 4 or 5, wherein said constructing signal-to-noise ratio sub-vectors comprises:
and uniformly extracting the sub-channel signal-to-noise ratio from the selected sub-channel signal-to-noise ratios to form a signal-to-noise ratio sub-vector.
7. The method of claim 1, wherein the sending the feedback parameters comprises:
and carrying the feedback parameters in the specified information or the conventional channel quality information, and feeding back the feedback parameters to the sending end.
8. The method according to claim 1 or 7, wherein said sending said feedback parameters specifically comprises:
and coding the feedback parameters, and sending the coded feedback parameters to the sending end.
9. A method for determining channel transmission quality, comprising:
obtaining feedback parameters sent by a receiving end;
according to the feedback parameters, a vector corresponding to the sending end is constructed according to a fitting polynomial;
carrying out inverse transformation of nonlinear transformation on the constructed vector to obtain a signal-to-noise ratio sub-vector formed by signal-to-noise ratios of a plurality of parallel sub-channels;
and determining the channel transmission quality according to the signal-to-noise ratio sub-vector.
10. The method of claim 9, wherein obtaining the snr subvector comprising snrs for a plurality of parallel subchannels further comprises:
and detecting and processing the sub-channel signal-to-noise ratios in the signal-to-noise ratio sub-vector, determining the sub-channel signal-to-noise ratio of which the variation trend does not meet the monotonicity requirement, generating the sub-channel signal-to-noise ratio according to a linear or nonlinear variation rule to replace the sub-channel signal-to-noise ratio which does not meet the monotonicity requirement, and forming the signal-to-noise ratio sub-vector of which the length is the number of sub-channels contained in the system and has monotonicity.
11. The method of claim 9 or 10, wherein said determining channel transmission quality based on said snr subvector comprises:
and determining one or two of effective signal-to-noise ratio and block error rate under different coding modulation modes and different power boosting factors according to the signal-to-noise ratio sub-vector.
12. A system for determining channel transmission quality, comprising:
the receiving end equipment is used for selecting the signal-to-noise ratio of the sub-channel according to the threshold, forming a signal-to-noise ratio sub-vector and carrying out nonlinear transformation on the formed signal-to-noise ratio sub-vector; performing polynomial fitting on the signal-to-noise ratio sub-vector after nonlinear transformation to obtain a feedback parameter, and sending the feedback parameter;
the sending end equipment is used for obtaining the feedback parameters sent by the receiving end equipment and constructing vectors corresponding to the sending end equipment according to the feedback parameters and fitting polynomials; and carrying out inverse transformation of nonlinear transformation on the constructed vector to obtain a signal-to-noise ratio sub-vector formed by signal-to-noise ratios of a plurality of parallel sub-channels, and determining the channel transmission quality according to the signal-to-noise ratio sub-vector.
13. A receiving-end device, comprising:
the selection module is used for selecting the signal-to-noise ratio of the sub-channel according to the threshold to form a signal-to-noise ratio sub-vector;
the transformation module is used for carrying out nonlinear transformation on the signal-to-noise ratio sub-vector formed by the selection module;
the fitting module is used for carrying out polynomial fitting on the signal-to-noise ratio sub-vector converted by the conversion module to obtain a feedback parameter;
and the sending module is used for sending the feedback parameters obtained by the fitting module to sending end equipment.
14. The receiving-end device of claim 13, further comprising:
and the sequencing module is used for sequencing the signal-to-noise ratio of the parallel sub-channels.
15. The receiving-end device of claim 14, wherein the thresholds include a signal-to-noise ratio threshold and a dimension threshold, and the selecting module comprises:
a signal-to-noise ratio selection sub-module, configured to select a sub-channel signal-to-noise ratio smaller than the signal-to-noise ratio threshold from the sub-channel signal-to-noise ratios sorted by the sorting module;
a first selection sub-module, configured to, when the dimension of the signal-to-noise ratio sub-vector formed by the sub-channel signal-to-noise ratios smaller than the signal-to-noise ratio threshold selected by the signal-to-noise ratio selection sub-module is smaller than the dimension threshold, select, according to the dimension threshold, a corresponding number of sub-channel signal-to-noise ratios in the ordered signal-to-noise ratios in order from small to large in the sub-channel signal-to-noise ratios larger than the signal-to-noise ratio threshold, and form a signal-to-noise ratio sub-vector, so that the dimension of;
and the second selection sub-module is used for selecting the sub-channel signal-to-noise ratio smaller than the signal-to-noise ratio threshold to form a signal-to-noise ratio sub-vector when the dimension of the signal-to-noise ratio sub-vector formed by the sub-channel signal-to-noise ratio smaller than the signal-to-noise ratio threshold selected by the signal-to-noise ratio selection sub-module is larger than the dimension threshold.
16. The receiving-end device of claim 14, wherein the threshold is specifically a signal-to-noise ratio threshold,
the selecting module is specifically configured to select a sub-channel signal-to-noise ratio from the sub-channel signal-to-noise ratios sorted by the sorting module according to the signal-to-noise ratio threshold, so as to form a signal-to-noise ratio sub-vector.
17. The receiving-end apparatus of claim 14, wherein the threshold is specifically a dimension threshold,
the selection module is specifically configured to select a sub-channel signal-to-noise ratio from the signal-to-noise ratios sorted by the sorting module according to the dimension threshold, so as to form a signal-to-noise ratio sub-vector.
18. A transmitting-end device, comprising:
the receiving module is used for obtaining feedback parameters sent by receiving end equipment;
the construction module is used for constructing a vector corresponding to the sending end equipment according to the feedback parameters obtained by the receiving module and a fitting polynomial;
the inverse transformation module is used for carrying out inverse transformation of nonlinear transformation on the vector constructed by the construction module to obtain a signal-to-noise ratio sub-vector formed by signal-to-noise ratios of a plurality of parallel sub-channels;
and the transmission quality determining module is used for determining the channel transmission quality according to the signal-to-noise ratio sub-vector obtained by the inverse transformation module.
19. The sender device of claim 18, further comprising:
and the detection module is used for detecting and processing the sub-channel signal-to-noise ratio in the signal-to-noise ratio sub-vector obtained by the inverse transformation module, determining the sub-channel signal-to-noise ratio of which the variation trend does not meet the monotonicity requirement, generating the sub-channel signal-to-noise ratio according to a linear or nonlinear variation rule to replace the sub-channel signal-to-noise ratio which does not meet the monotonicity requirement, and forming the signal-to-noise ratio sub-vector with the length being the number of sub-channels contained in the system and.
20. The sending-end device of claim 19, wherein the transmission quality determining module is specifically configured to determine one or both of an effective snr and a block error rate under different modulation schemes and different power boosting factors according to the snr subvector detected and processed by the detecting module.
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| CN102075272B (en) * | 2011-01-26 | 2013-06-05 | 清华大学 | Method for predicting receiving performance of receiver in multi-path channel transmission |
| CN110868273B (en) * | 2019-11-29 | 2022-03-04 | 中国电子科技集团公司第五十四研究所 | Joint decoding method for multipath received signals |
| CN114866171B (en) * | 2021-02-03 | 2023-09-01 | 广州海格通信集团股份有限公司 | Signal statistics method, device, computer equipment and storage medium |
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| CN104753636B (en) * | 2013-12-31 | 2018-03-23 | 展讯通信（上海）有限公司 | The feedback method that channel quality indicates in communication system and device, communication terminal |
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