CN109889286B - Signal-to-noise ratio estimation method based on pilot signal - Google Patents
Signal-to-noise ratio estimation method based on pilot signal Download PDFInfo
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Abstract
The invention discloses a signal-to-noise ratio estimation method based on pilot signals, which comprises the following steps: step (S1) of obtaining the channel estimation value of the position of the pilot signal
A step (S2) of estimating a channel based on the channel estimation value
Calculating to obtain the total power value P of the pilot signalsFirst power value P of noise interferencen1And a second power value Pn2And further obtaining the power value P of the noise interferencen(ii) a A step (S3) of obtaining the total power value P of the pilot signalsAnd the noise interference power value PnObtaining the SNR initial estimation valueinitial(ii) a Step (S4) uses correction factor delta to make the SNR initial estimation value SNRinitialCorrecting to obtain SNR estimation valuefinal. By the method, the signal-to-noise ratio estimation value is more accurate than the estimation value in the prior art; meanwhile, the method avoids the application of a divider, and is easy to realize in an actual system. Therefore, the method has higher use value and popularization value.
Description
Technical Field
The invention relates to a signal-to-noise ratio estimation method, in particular to a signal-to-noise ratio estimation method based on pilot signals.
Background
The Long Term Evolution (LTE) system introduces Orthogonal Frequency Division Multiplexing (OFDM) and multiple-Input multiple-Output (MIMO) key technologies, which significantly increases the spectrum efficiency and data transmission rate. The OFDM is one of the realization modes of the multi-carrier transmission scheme, the actual wireless channel is divided into a plurality of sub-carriers, and the sub-carriers are mutually orthogonal, so that the utilization rate of wireless spectrum resources is greatly improved. Meanwhile, according to the transmission quality of the channel and the change of the channel condition, the transmission parameters of the OFDM signals can be adaptively adjusted, so that the transmission rate and the transmission reliability of the system can be optimally combined.
Signal-to-Noise Ratio (SNR) is a Ratio of an average useful Signal to an average Noise interference power in a received Signal, and is one of important parameters for measuring channel quality, and more algorithms and applications need performance optimization based on SNR as prior knowledge, such as power control, adaptive modulation, Turbo Code decoding, adaptive handoff, and the like, and meanwhile, the SNR is directly related to a bit error rate and a frame error rate, and can be measured in real time, so that engineers can know real-time transmission characteristics of a system conveniently.
Algorithms for signal-to-noise ratio estimation can be generally divided into blind estimation methods and pilot-based data-aided methods. The blind estimation method has no auxiliary data, and correspondingly processes the received signal at the receiving end to obtain the estimated value of the signal-to-noise ratio. The pilot frequency data-based auxiliary method is to insert known pilot frequency signals into transmitted data and perform correlation operation at a receiving end to obtain an estimated signal-to-noise ratio value.
The snr estimate is estimated from the received signal and the optimized estimate must be unbiased with minimal variance, but the snr estimate must be in error for the following reasons. First, it is difficult for the filter to completely separate the additive gaussian noise and interference from the useful signal; secondly, the length of an observation vector window of the estimation algorithm is limited, and the size of the window and the size of an estimation error are in an inverse proportion relation; meanwhile, due to the random characteristics of signals and the diversity of modulation modes, the realization difficulty of a plurality of algorithms in an actual system is high. Therefore, there is a need for improvements to existing signal-to-noise ratio estimation methods.
Disclosure of Invention
The invention aims to provide a signal-to-noise ratio estimation method based on a pilot signal, which mainly solves the problems that the existing signal-to-noise ratio method is low in estimation precision of the signal-to-noise ratio of a received signal and the algorithm is difficult to realize in an actual system.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows:
a signal-to-noise ratio estimation method based on pilot signals comprises the following steps:
(S1) calculating a channel estimation value of a position of a pilot signal in a subframe of the received signal
Wherein, m and k respectively indicate that the corresponding pilot signals are positioned on the mth row pilot symbol and the kth pilot subcarrier;
(S2) based on the obtained channel estimation value
Calculating to obtain the total power value P of the pilot signal in the sub-framesFirst power value P of noise interferencen1And a second power value P of noise interferencen2；
(S3) obtaining a first power value P based on the noise interferencen1And a second power value P of noise interferencen2Obtaining the power value P of the pilot signal noise interference in the sub-framen；
(S4) obtaining the total power value PsAnd a noise interference power value PnAnd calculating to obtain an initial estimation value SNR of the signal-to-noise ratioinitial；
(S5) using correction factor delta to the SNR initial estimation value SNRinitialCorrecting and calculating to obtain SNR estimation valuefinal。
Further, in the step (S2), the total power value P of the pilot signal in the sub-framesAccording to the relational expression
Obtaining a first power value P of the noise interferencen1According to the relational expression
Obtaining a second power value P of the noise interferencen2According to the relational expression
Thus obtaining the product.
Further, in the step (S3), the power value P of the noise interferencenAccording to the relation Pn＝(Pn1+Pn2) And/2 obtaining.
Further, in the step (S4), the SNR initial estimation value is SNRinitialAccording to the relation SNRinitial＝(Ps-Pn)/PnThus obtaining the product.
Further, the SNR estimation value SNRfinalUsing the correction factor delta according to the relation SNRfinal＝SNRinitialδ was obtained.
Further, the correction factor δ is obtained according to a relation δ — N/M, where N is the number of transmission subcarriers and M is the number of FFT points.
Compared with the prior art, the invention has the following beneficial effects:
the signal-to-noise ratio estimation method of the invention subtracts the power of noise and interference from the total received power of the pilot signal to obtain the received power of the pilot signal, and represents the noise interference power by using the difference value of the channel estimation value to offset the noise and interference which can not be eliminated by the filter, thereby improving the estimation precision, avoiding the application of a divider at the same time and being easy to realize in an actual system.
Drawings
Fig. 1 is a schematic diagram of a pilot signal insertion method according to an embodiment of the present invention.
Fig. 2 is a flow chart of the snr estimation method of the present invention.
FIG. 3 is a graph showing the comparison between the results obtained by the example of the present invention and those obtained by the prior art.
Fig. 4 is a schematic diagram of an average EVM performance simulation according to an embodiment of the present invention and the prior art.
Detailed Description
The signal-to-noise ratio estimation method of the invention can be applied to the downlink of the LTE system, but is not limited to the downlink of the LTE system. The signal-to-noise ratio estimation method of the present invention is described in detail below by taking LTE downlink signal-to-noise ratio estimation as an example, wherein a pilot signal modulation mode adopts QPSK (quadrature phase shift keying, a digital modulation mode), a transmission link system bandwidth adopts 10M bandwidth, the number of subcarriers is 432, and the number of FFT (fast fourier transform) points is 1024. The pilot signal adopts a scattered pilot insertion mode, the time domain pilot interval is 6 symbols, and the frequency domain pilot interval is 6 subcarriers.
Examples
As shown in fig. 1-4, the signal-to-noise ratio estimation method based on pilot signals disclosed in the present invention includes the following steps:
(S1) calculating a channel estimation value of a position of a pilot signal in a subframe of the received signal
Wherein m and k respectively indicate that the corresponding pilot signals are located on the mth column pilot symbol and the kth pilot subcarrier. Channel estimation value
Can be calculated by LS (Least Square), MMSE (Minimum Mean Square Error) and other channel estimation methods.
(S2) channel estimation values obtained from the step (S1)
By means of a relational expression
Calculating to obtain the total power value P of all pilot signals in the subframesWherein L is the number of pilot signals on a row of pilot symbols; by means of a relational expression
And
respectively calculating to obtain first power values P of noise interferencen1And a second power value P of noise interferencen2。
(S3) obtaining the first power value P of the noise interference according to the step (S2)n1And a second power value P of noise interferencen2By the relation Pn＝(Pn1+Pn2) /2 obtaining the power P of the noise disturbancen。
(S4) obtaining the total power value PsAnd a noise interference power value PnBy the relation SNRinitial＝(Ps-Pn)/PnCalculating to obtain SNR initial estimation valueinitial。
(S5) calculating SNR initial estimation value due to error influence caused by interferenceinitialThe value is more linear than the actual signal-to-noise ratio value, so the correction factor delta is used for the SNR of the initial estimation value of the signal-to-noise ratioinitiaCorrecting to obtain SNR estimation valuefinal，SNRfinal＝SNRinitialδ, wherein the correction factor δ is obtained according to the relation δ — N/M, N is the number of transmission subcarriers 432, and M is the number of FFT points 1024, that is, δ — 432/1024.
Fig. 3 shows a comparison between the estimated value obtained by the snr estimation algorithm of the present embodiment, the uncorrected snr estimated value, and the estimated value obtained by the boumaard snr estimation algorithm, which shows that the snr estimation algorithm of the present embodiment has better estimation performance than the boumaard snr estimation algorithm, the estimated value is more accurate, and the corrected estimated value is closer to the actual snr value than the uncorrected estimated value; fig. 4 shows the average EVM (Error Vector Magnitude) performance simulation of the snr estimation algorithm and the bounard snr estimation algorithm in this embodiment, and it can be seen that the snr estimation algorithm in this embodiment has better average EVM performance in both the low snr interval and the high snr interval.
Through the steps, the signal-to-noise ratio estimation method improves the estimation precision, avoids the application of a divider, and is easy to realize in an actual system. Therefore, the method has higher use value and popularization value.
The above-mentioned embodiment is only one of the preferred embodiments of the present invention, and should not be used to limit the scope of the present invention, but all the insubstantial modifications or changes made within the spirit and scope of the main design of the present invention, which still solve the technical problems consistent with the present invention, should be included in the scope of the present invention.
Claims (2)
1. A signal-to-noise ratio estimation method based on pilot signals is characterized by comprising the following steps:
(S1) calculating a channel estimation value of a position of a pilot signal in a subframe of the received signal
Wherein, m and k respectively indicate that the corresponding pilot signals are positioned on the mth row pilot symbol and the kth pilot subcarrier;
(S2) based on the obtained channel estimation value
Calculating to obtain the total power value P of the pilot signal in the sub-framesFirst power value P of noise interferencen1And a second power value P of noise interferencen2(ii) a Wherein the total power value P of the pilot signal in the sub-framesAccording to the relational expression
Obtaining a first power value P of the noise interferencen1According to the relational expression
Obtaining a second power value P of the noise interferencen2According to the relational expression
Obtaining; wherein, L is the number of pilot signals in a subframe;
(S3) obtaining a first power value P based on the noise interferencen1And a second power value P of noise interferencen2Obtaining the power value P of the pilot signal noise interference in the sub-framen(ii) a Wherein the power value P of the noise interferencenAccording to the relation Pn＝(Pn1+Pn2) Obtaining;
(S4) obtaining the total power value PsAnd a noise interference power value PnAnd calculating to obtain an initial estimation value SNR of the signal-to-noise ratioinitial；
(S5) using correction factor delta to the SNR initial estimation value SNRinitialCorrecting and calculating to obtain SNR estimation valuefinal(ii) a Wherein the SNR estimate SNR isfinalAccording to the relation SNRfinal＝SNRinitialObtaining delta; the correction factor δ is obtained according to a relation δ — N/M, where N is the number of transmission subcarriers and M is the number of FFT points.
2. The method of claim 1, wherein in said step (S4), said SNR initial estimation value SNR isinitialAccording to the relation SNRinitial＝(Ps-Pn)/PnThus obtaining the product.
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