CN111934795A - Method for estimating signal-to-noise ratio and interference power in interference environment - Google Patents

Method for estimating signal-to-noise ratio and interference power in interference environment Download PDF

Info

Publication number
CN111934795A
CN111934795A CN202010830436.9A CN202010830436A CN111934795A CN 111934795 A CN111934795 A CN 111934795A CN 202010830436 A CN202010830436 A CN 202010830436A CN 111934795 A CN111934795 A CN 111934795A
Authority
CN
China
Prior art keywords
interference
power
noise
signal
sequence
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202010830436.9A
Other languages
Chinese (zh)
Inventor
匡正
雷霞
蒋伟
樊宁波
许鹏飞
刘吉
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
University of Electronic Science and Technology of China
Xian Institute of Space Radio Technology
Original Assignee
University of Electronic Science and Technology of China
Xian Institute of Space Radio Technology
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by University of Electronic Science and Technology of China, Xian Institute of Space Radio Technology filed Critical University of Electronic Science and Technology of China
Priority to CN202010830436.9A priority Critical patent/CN111934795A/en
Publication of CN111934795A publication Critical patent/CN111934795A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/309—Measuring or estimating channel quality parameters
    • H04B17/336—Signal-to-interference ratio [SIR] or carrier-to-interference ratio [CIR]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/309—Measuring or estimating channel quality parameters
    • H04B17/345—Interference values
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/08—Testing, supervising or monitoring using real traffic

Abstract

The invention belongs to the technical field of wireless communication anti-interference, and relates to a method for estimating a signal-to-noise ratio and interference power in an interference environment. In LoS channel environment with interference source, the receiving end estimates the fading coefficient of the channel according to the maximum likelihood criterion and the characteristics of the pseudo-random sequence by extracting the pseudo-random sequence of the frame header, so as to obtain the signal power of the receiving end, then extracts the noise power and the interference power respectively according to the different frequency spectrum characteristics of the noise and the interference, and finally obtains the estimation of the signal-to-noise ratio and the interference power. The invention provides a signal-to-noise ratio and interference power estimation method based on maximum likelihood in an interference environment, and can achieve better estimation effect on the signal-to-noise ratio and the interference power.

Description

Method for estimating signal-to-noise ratio and interference power in interference environment
Technical Field
The invention belongs to the technical field of wireless communication anti-interference, and relates to a method for estimating a signal-to-noise ratio and interference power in an interference environment.
Background
More and more man-made and non-man-made interference sources appear in a wireless communication environment, and great challenges are brought to an anti-interference communication system. With the development of artificial intelligence, the research of anti-interference technology is focused on intelligent anti-interference technology. By sensing the surrounding interference environment, the intelligent anti-interference decision system implements a corresponding anti-interference strategy according to the interference sensing result. Therefore, the interference sensing technology is one of the key technologies for anti-interference communication. Interference sensing includes interference detection, interference identification, Signal Noise Ratio (SNR), and estimation of interference power.
The adaptive modulation technology is a typical anti-interference method, and adaptively adjusts the encoding mode of an initiating terminal according to the channel environment of current information transmission. The receiver calculates and processes the received signal, feeds back the channel information and the interference perception information to the sender, and the sender analyzes and processes the fed-back information and dynamically adjusts the transmission modulation coding mode according to the state of the current environment, so that the information is transmitted more effectively on the premise of ensuring the reliable transmission of the system. Therefore, how to accurately acquire the channel state and the interference information is a key technology for intelligent anti-interference. In a Line of Sight (LoS) communication environment with interference, typical measures for measuring the channel transmission environment are the signal-to-noise ratio and the interference power.
Disclosure of Invention
Aiming at obtaining indexes for evaluating a communication channel environment in an interference environment, the invention provides a maximum likelihood estimation method by utilizing a signal-to-noise ratio and interference power based on a pseudorandom synchronization sequence. In LoS channel environment with interference source, the receiving end estimates the fading coefficient of the channel according to the maximum likelihood criterion and the characteristics of the pseudo-random sequence by extracting the pseudo-random sequence of the frame header, so as to obtain the signal power of the receiving end, then extracts the noise power and the interference power respectively according to the different frequency spectrum characteristics of the noise and the interference, and finally obtains the estimation of the signal-to-noise ratio and the interference power.
The technical scheme of the invention is that the method for estimating the signal-to-noise ratio and the interference power in the interference environment is used for an LoS transmission communication system with interference, the system equalization and synchronization error are assumed to be small enough, the system has perfect timing synchronization, and the influence brought by a channel can be approximated to multiplicative channel fading factors, and the method comprises the following steps:
s1, the receiving end extracts a pseudo-random m sequence:
r(n)＝ρd(n)+w(n)+j(n)
wherein, r (n) represents the interfered sequence where the m sequence extracted by the receiving end is located, ρ represents the channel fading coefficient, d (n) represents the m sequence sent by the sending end, w (n) represents the white gaussian noise generated by the receiving end, and j (n) represents the additive influence caused by the interference;
s2, signal power estimation method based on maximum likelihood criterion, using m sequence d (n) sent by sending end and extracted interfered sequence r (n) in same position to multiply and generate new sequence r1(n) r (n) d (n), the received sequence and the newly generated sequence are described as:
Figure BDA0002637744030000021
the two sequences are accumulated separately:
Figure BDA0002637744030000022
wherein N is the length of the m sequence;
the m-sequence is known, and the likelihood function is obtained according to the maximum likelihood criterion as follows:
Figure BDA0002637744030000023
wherein the content of the first and second substances,
Figure BDA0002637744030000024
representing the noise power;
the log-likelihood function is then:
Figure BDA0002637744030000025
respectively deriving the fading coefficients ρ to be estimated, and making the fading coefficients to be 0 to obtain estimates of the fading coefficients:
Figure BDA0002637744030000031
the following expression is obtained by simplifying and deforming the method:
Figure BDA0002637744030000032
namely, it is
Figure BDA0002637744030000033
Where E () is an operation for obtaining an expected average value, and there are three unknown coefficients for the above two equations, but considering a certain interference signal, and the interference signal is independent from the pseudo-random m sequence, it can be considered that E [ j (n) d (n) ═ E [ j (n) ] E [ d (n) ], and the estimation result of the fading coefficient can be directly obtained as:
Figure BDA0002637744030000034
wherein
Figure BDA0002637744030000035
Representing the estimated value of the fading coefficient, the estimate of the signal power is:
Figure BDA0002637744030000036
wherein | | | is a modulo operation;
s3, in case a signal power estimate has been obtained, the sum of the noise power and the interference power is:
Figure BDA0002637744030000037
wherein
Figure BDA0002637744030000038
Which is indicative of the power of the noise,
Figure BDA0002637744030000039
representing the interference power, NL is the total length of time the signal is transmitted; the flat characteristic of Gaussian white noise frequency spectrum is used to distinguish the noise power on the frequency domain
Figure BDA00026377440300000310
And interference power
Figure BDA00026377440300000311
And obtaining a sequence estimation of noise plus interference without signals according to the obtained estimation of the fading coefficient:
Figure BDA0002637744030000041
wherein w (n) is a white gaussian noise signal, j (n) is an interference signal, and the frequency domain signal x (k) is obtained by performing DFT on x (n) in the time domain:
Figure BDA0002637744030000042
biniis the ith segment of the segmentation, L is the sequence length of each segment, finds the m segments with the minimum length, and arranges the m segments in ascending order; estimating the average of the noise as a whole by the noise power of m segments according to the flat characteristic of the noise spectrumAverage power
Figure BDA0002637744030000043
Figure BDA0002637744030000044
Subtracting the power of the noise from the total power according to the independence of the noise and the interference
Figure BDA0002637744030000045
Deriving interference power
Figure BDA0002637744030000046
The resulting signal-to-noise ratio and interference power are:
Figure BDA0002637744030000047
the invention has the beneficial effects that: in a communication environment with a fixed interference source, a typical interference power and signal-to-noise ratio estimation method is not available temporarily, but the invention provides a signal-to-noise ratio and interference power estimation method based on maximum likelihood in the interference environment, and a better estimation effect can be achieved for the signal-to-noise ratio and the interference power.
Drawings
Fig. 1 is a system block diagram of a method for estimating a signal-to-noise ratio and an interference power in an interference environment according to the present invention;
FIG. 2 is a comparison graph of mean square error performance of signal-to-noise ratio estimates for synchronization sequences of different lengths;
fig. 3 is a comparison graph of mean square error performance of interference power estimates for synchronization sequences of different lengths.
Detailed Description
The practical applicability of the invention is illustrated by way of simulation examples in conjunction with the accompanying drawings.
As shown in fig. 1, the method for estimating the signal-to-noise ratio and the interference power based on the maximum likelihood under the adaptive link decision proposed by the present invention includes:
1. the sequence R (n) which is received and has time-frequency synchronization and the original synchronization head sequence d (n) are obtained at the input end.
2. The received signal is extracted to obtain synchronous sequence part, and the original synchronous sequence is used to calculate its expected average value
3. And (3) calculating an expected average value of the r (n) of the extracted synchronization head part of the received signal, and calculating the expected average value of the sequence k (n) obtained by point multiplication of the r (n) and the synchronization head sequence d (n).
4. Substituting the estimation formula of the derived fading coefficient into the calculation of the signal fading
5. Obtaining an estimated value of the power of the signal according to the amplitude value of the fading, subtracting the product of the estimated fading and the synchronous head from the received sequence r (n) to obtain a sum sequence NandJ (n) of the noise sequence and the interference signal sequence
6. Fourier transform is carried out on the sum sequence of the interference and the noise nandj (n) to obtain the frequency spectrum nandj (k), and the average of the square of the amplitude of nandj (n) is obtained to obtain the total power of the noise and the interference
7. The magnitude of nandj (k) is squared and averaged into L segments
8. Sorting the ascending order, re-labeling, selecting m sections to calculate the mean value and dividing the mean value by the number of time domain points to obtain the noise power
9. And subtracting the noise power from the sum of the noise power and the interference power to obtain the interference power, and dividing the signal power by the noise power to obtain the signal-to-noise ratio (SNR).
For a given interferer and random white gaussian noise, simulations were performed according to the above method, and the simulation steps are summarized in table 1.
Table 1: signal-to-noise ratio and interference power estimation method based on maximum likelihood
Figure BDA0002637744030000051
Figure BDA0002637744030000061
In the simulation, three synchronous m sequences with different lengths are adopted, and the lengths are 127, 255 and 4095 respectively. Simulation results of four typical interferences, namely single-tone interference, multi-tone interference, swept frequency interference and partial band interference, have similar conclusions without loss of generality, and a simulation result graph is given by taking partial band interference as an example in the invention.
Fig. 1 shows a comparison of Normalized Mean Square Error (NMSE) performance of the inventive scheme using three different length sync m-sequences for signal-to-noise ratio estimation.
Fig. 2 shows a comparison of Mean Square Error (MSE) performance for interference power estimation using three different length synchronization m-sequences in the scheme of the present invention.
As can be seen from fig. 1 and fig. 2, the signal-to-noise ratio estimation and interference power estimation method based on the maximum likelihood criterion provided by the present invention improves the estimation performance with the increase of the length of the synchronization sequence and the increase of the signal-to-noise ratio.

Claims (1)

1. A method for estimating signal-to-noise ratio and interference power in interference environment, which is used for LoS transmission communication system with interference, and is characterized in that the influence brought by the channel in the system is assumed to be approximately multiplicative channel fading factor, the method comprises the following steps:
s1, the receiving end extracts a pseudo-random m sequence:
r(n)＝ρd(n)+w(n)+j(n)
wherein, r (n) represents the interfered sequence where the m sequence extracted by the receiving end is located, ρ represents the channel fading coefficient, d (n) represents the m sequence sent by the sending end, w (n) represents the white gaussian noise generated by the receiving end, and j (n) represents the additive influence caused by the interference;
s2, generating a new sequence r according to the m sequence d (n) sent by the sending end and the extracted interfered sequence r (n) at the same position1(n) r (n) d (n), the received sequence and the newly generated sequence are described as:
Figure FDA0002637744020000011
the two sequences are accumulated separately:
Figure FDA0002637744020000012
wherein N is the length of the m sequence;
the m-sequence is known, and the likelihood function is obtained according to the maximum likelihood criterion as follows:
Figure FDA0002637744020000013
wherein the content of the first and second substances,
Figure FDA0002637744020000014
representing the noise power;
the log-likelihood function is then:
Figure FDA0002637744020000021
respectively deriving the fading coefficients ρ to be estimated, and making the fading coefficients to be 0 to obtain estimates of the fading coefficients:
Figure FDA0002637744020000022
the following expression is obtained by simplifying and deforming the method:
Figure FDA0002637744020000023
namely, it is
Figure FDA0002637744020000024
Wherein E () is an operation of obtaining an expected average value, and E [ j (n) d (n) ═ E [ j (n)) ] E [ d (n)) ], the estimation result of the fading coefficient obtained by solving is:
Figure FDA0002637744020000025
wherein
Figure FDA0002637744020000026
Representing the estimated value of the fading coefficient, the estimate of the signal power is:
Figure FDA0002637744020000027
wherein | | | is a modulo operation;
s3, estimating the signal power according to the obtained signal power, wherein the sum of the noise power and the interference power is:
Figure FDA0002637744020000031
wherein
Figure FDA0002637744020000032
Which is indicative of the power of the noise,
Figure FDA0002637744020000033
representing the interference power, NL is the total length of time the signal is transmitted;
and obtaining a sequence estimation of noise plus interference without signals according to the obtained estimation of the fading coefficient:
Figure FDA0002637744020000034
wherein w (n) is a white gaussian noise signal, j (n) is an interference signal, and the frequency domain signal x (k) is obtained by performing DFT on x (n) in the time domain:
Figure FDA0002637744020000035
biniis the ith segment of the segmentation, L is the sequence length of each segment, finds the m segments with the minimum length, and arranges the m segments in ascending order; according to the flat characteristic of the noise spectrum, the average power of the whole noise is estimated by the noise power of m sections
Figure FDA0002637744020000036
Figure FDA0002637744020000037
Subtracting the power of the noise from the total power according to the independence of the noise and the interference
Figure FDA0002637744020000038
Deriving interference power
Figure FDA0002637744020000039
The resulting signal-to-noise ratio and interference power are expressed as:
Figure FDA00026377440200000310
CN202010830436.9A 2020-08-18 2020-08-18 Method for estimating signal-to-noise ratio and interference power in interference environment Pending CN111934795A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202010830436.9A CN111934795A (en) 2020-08-18 2020-08-18 Method for estimating signal-to-noise ratio and interference power in interference environment

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202010830436.9A CN111934795A (en) 2020-08-18 2020-08-18 Method for estimating signal-to-noise ratio and interference power in interference environment

Publications (1)

Publication Number Publication Date
CN111934795A true CN111934795A (en) 2020-11-13

Family

ID=73304486

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202010830436.9A Pending CN111934795A (en) 2020-08-18 2020-08-18 Method for estimating signal-to-noise ratio and interference power in interference environment

Country Status (1)

Country Link
CN (1) CN111934795A (en)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114374448A (en) * 2022-01-10 2022-04-19 中国电子科技集团公司第五十四研究所 Signal-to-noise ratio resolving method based on interference avoidance
CN115173975A (en) * 2022-07-06 2022-10-11 北京航空航天大学 Method, device and equipment for detecting interference signal and storage medium

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20060018412A1 (en) * 2004-07-22 2006-01-26 Samsung Electronics Co., Ltd. Method for estimating maximum likelihood frequency offset in mobile communication system in fast rayleigh fading channel environment
CN107947830A (en) * 2017-11-15 2018-04-20 电子科技大学 A kind of radio-frequency fingerprint recognition methods for resisting multi-path jamming
CN109379154A (en) * 2018-10-11 2019-02-22 重庆邮电大学 A kind of safe transmission scheme based on time reversal technology
CN110381503A (en) * 2019-06-21 2019-10-25 西安交通大学 The interference blocking scheme switching method of millimeter wave cellular network uplink safe transmission
CN110988854A (en) * 2019-12-24 2020-04-10 西安电子科技大学 Robust self-adaptive beam forming algorithm based on alternative direction multiplier method

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20060018412A1 (en) * 2004-07-22 2006-01-26 Samsung Electronics Co., Ltd. Method for estimating maximum likelihood frequency offset in mobile communication system in fast rayleigh fading channel environment
CN107947830A (en) * 2017-11-15 2018-04-20 电子科技大学 A kind of radio-frequency fingerprint recognition methods for resisting multi-path jamming
CN109379154A (en) * 2018-10-11 2019-02-22 重庆邮电大学 A kind of safe transmission scheme based on time reversal technology
CN110381503A (en) * 2019-06-21 2019-10-25 西安交通大学 The interference blocking scheme switching method of millimeter wave cellular network uplink safe transmission
CN110988854A (en) * 2019-12-24 2020-04-10 西安电子科技大学 Robust self-adaptive beam forming algorithm based on alternative direction multiplier method

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
原艳南: "基于机器学习的智能决策关键技术研究", 《中国优秀硕士学位论文全文数据库信息科技辑》 *
许华等: "MPSK信号的最大似然SNR估计方法", 《电子与信息学报》 *

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114374448A (en) * 2022-01-10 2022-04-19 中国电子科技集团公司第五十四研究所 Signal-to-noise ratio resolving method based on interference avoidance
CN114374448B (en) * 2022-01-10 2024-01-05 中国电子科技集团公司第五十四研究所 Signal-to-noise ratio resolving method based on interference avoidance
CN115173975A (en) * 2022-07-06 2022-10-11 北京航空航天大学 Method, device and equipment for detecting interference signal and storage medium
CN115173975B (en) * 2022-07-06 2024-02-06 北京航空航天大学 Method, device, equipment and storage medium for detecting interference signal

Similar Documents

Publication Publication Date Title
KR100944699B1 (en) Reception quality measuring apparatus and reception quality measuring method
CN109450486B (en) Digital self-interference cancellation method for asynchronous simultaneous same-frequency full-duplex underwater acoustic communication system
CN111934795A (en) Method for estimating signal-to-noise ratio and interference power in interference environment
CN112654057B (en) Bandwidth and rate self-adaptive communication method based on channel detection
CN104717174A (en) Orthogonal frequency division multiplexing (OFDM) anti-interference synchronization method under complex multipath channel
Yu et al. Channel estimation using dual-dependent pilots in FBMC/OQAM systems
CN112910816B (en) Filter bank multi-carrier timing synchronization method based on phase weighting conjugate symmetry
CN102035765A (en) MMSE (Minimum Mean Squared Error) channel estimation method based on maximum time delay real time estimation
CN116055271A (en) Burst signal detection method of double sliding windows under specific waveform structure
CN102098114B (en) Method and device for measuring signal-to-noise ratio of system
CN102377726B (en) Timing synchronization method of OFDM (Orthogonal Frequency Division Multiplexing) system
CN108377158B (en) Multi-band division and aggregation method for realizing spread spectrum signal
CN1402919A (en) Bit error estimates from pilot signals
CN109257149A (en) A kind of data receiver method and data reception device
CN102143116B (en) Orthogonal frequency division multiplexing (OFDM) signal cyclostationarity-based blind signal to noise ratio estimation method
CN101895487A (en) Confidence-based method and device for suppressing noises in channel estimation results
CN104468432A (en) Channel estimation denosing method for single carrier frequency domain equalization under shortwave communication channel
CN101286958B (en) Terrestrial broadcasting channel estimating method for digital television and device thereof
CN111327547B (en) Time domain channel estimation device with threshold denoising processing
He et al. M-ary CDMA multiuser underwater acoustic communication and its experimental results
CN104270328A (en) Method for estimating signal-to-noise ratio in real time
CN104684071B (en) The up Timing Synchronization trackings of LTE
WO2019205312A1 (en) Gray sequence-based signal-to-noise ratio estimation method
CN104301262B (en) A kind of single-carrier frequency domain balance ultra-wide broadband system channel estimation methods
CN112511193B (en) Broadband carrier (HPLC) module based on error feedback algorithm

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
WD01 Invention patent application deemed withdrawn after publication

Application publication date: 20201113

WD01 Invention patent application deemed withdrawn after publication