AU2019230458B2 - A high sensitivity and selectivity real-time spectrum analyser - Google Patents

A high sensitivity and selectivity real-time spectrum analyser Download PDF

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AU2019230458B2
AU2019230458B2 AU2019230458A AU2019230458A AU2019230458B2 AU 2019230458 B2 AU2019230458 B2 AU 2019230458B2 AU 2019230458 A AU2019230458 A AU 2019230458A AU 2019230458 A AU2019230458 A AU 2019230458A AU 2019230458 B2 AU2019230458 B2 AU 2019230458B2
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signal
segment
spectrum analyser
analyser
real
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AU2019230458A1 (en
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Vyacheslav Snitkovsky
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Jehmy Pty Ltd
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Jehmy Pty Ltd
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R23/00—Arrangements for measuring frequencies; Arrangements for analysing frequency spectra
    • G01R23/16—Spectrum analysis; Fourier analysis
    • G01R23/165—Spectrum analysis; Fourier analysis using filters
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B1/00—Details of transmission systems, not covered by a single one of groups H04B3/00 - H04B13/00; Details of transmission systems not characterised by the medium used for transmission
    • H04B1/06—Receivers
    • H04B1/10—Means associated with receiver for limiting or suppressing noise or interference
    • H04B1/1027—Means associated with receiver for limiting or suppressing noise or interference assessing signal quality or detecting noise/interference for the received signal
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R29/00—Arrangements for measuring or indicating electric quantities not covered by groups G01R19/00 - G01R27/00
    • G01R29/26—Measuring noise figure; Measuring signal-to-noise ratio
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R23/00—Arrangements for measuring frequencies; Arrangements for analysing frequency spectra
    • G01R23/16—Spectrum analysis; Fourier analysis
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R23/00—Arrangements for measuring frequencies; Arrangements for analysing frequency spectra
    • G01R23/16—Spectrum analysis; Fourier analysis
    • G01R23/20—Measurement of non-linear distortion
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • 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

Abstract

There is provided herein a spectrum analyser and a method of operation thereof which is able to receive and analyse interference signals in a way that is substantially immune to sporadic interferences, allowing for more accurate detection of the interferences of the surrounding electromagnetic environment and therefore the more accurate setting of communication equipment operational parameters accordingly including receiving frequency and selectivity. In embodiments, the present spectrum analyser is able to detect three or more sources of powerful interference.

Description

A high sensitivity and selectivity real-time spectrum analyser
Field of the Invention
[1] This invention relates generally to frequency spectrum analysers and, in particular, a high sensitivity and selectivity real-time spectrum analyser.
Background of the Invention
[2] Operational parameters of electronic communication equipment need to be correctly configured according to electromagnetic interference (in terms of both frequency and power) from the surrounding electromagnetic environment.
[3] Such a configuration process typically entails electromagnetic interference measurements utilising a spectrum analyser and predicting (oftentimes guessing) the correct communication parameters.
[4] However, such a process is frequently error prone, resulting in the incorrect setting of operational frequencies, transmission power, sensitivity and selectivity of the receiver and the like.
[5] The present invention seeks to provide a real-time spectrum analyser, which will overcome or substantially ameliorate at least some of the deficiencies of the prior art, or to at least provide an alternative.
[6] It is to be understood that, if any prior art information is referred to herein, such reference does not constitute an admission that the information forms part of the common general knowledge in the art, in Australia or any other country.
Summary of the Disclosure
[7] There is provided herein a high sensitivity and selectivity real-time spectrum analyser which calculates an acceptable signal-to-noise ratio probability distribution utilising a particular interference probability distribution calculation derived herein for the configuration of communication receiver operational parameters, including selectivity and receiving frequency.
[8] The spectrum analyser comprises a frequency band switch and transceiver which measures the power and frequency of signals received by the signal receiver across the required frequency range. The analyser then uses the interference probability distribution calculation to detect sources of interference, including particularly powerful interference in a way that is substantially immune to sporadic appearance and disappearance of measured interferences allowing for more accurate calculation of the relevant interferences and setting of communication equipment operational parameters.
[9] According to one aspect, there is provided a real-time spectrum analyser comprising: a signal receiver comprising an antenna and signal pre-processor; a switch and transceiver operably coupled to the signal pre-processor; a processor operably coupled to the transceiver: wherein the analyser is configured for: receiving signals using the signal receiver; measuring the number of signals received at a plurality of power and frequency bands using the switch and transceiver; storing the number of signals in respective segments of a power by frequency data matrix in memory; calculating a mean for each segment; calculating a variance for each segment; calculating a common mean of a Gaussian distribution as a sum of the mean for each segment; calculating a common variance of the Gaussian distribution as a sum of the variance for each segment; and calculating an acceptable signal-to-noise ratio probability distribution function according to a probability integral quotient of the difference between a chosen interference power at which the ratio signal/noise is reduced to the permissible value and the common mean and the common variance.
[10] The analyser may be configured for calculating the mean for each segment as twice a minimum power threshold of the segment.
[11] The segments may have 5dBm intervals and wherein the analyser is configured for calculating the square of the variance for each segment as a third of the square of the minimum power threshold.
[12] The analyser may be configured for calculating the mean for each segment as half a minimum power threshold of the segment.
[13] The segments may have 5dBm intervals and wherein the analyser is configured for calculating the square of the variance for each segment as a twelfth of the square of the minimum power threshold.
[14] The real-time spectrum analyser may further be configured for configuring at least one of selectivity and receiving frequency of a receiver in accordance with the probability distribution.
[15] Configuring the receiving frequency may comprise setting the receiving frequency at a frequency of the probability distribution which falls beneath the acceptable signal-to-noise ratio.
[16] The acceptable signal-to-noise ratio may be a bit error rate (BER).
[17] The signals may comprise a common signal and three or more interference signals and wherein the acceptable signal-to-noise probability distribution is F (Er) = F ((Er-mu)/ou) where F ((Er- mu)/ou) is a probability integral where Er is the acceptable signal-to-noise ratio, mu is the sum of the means of the common signal and the interference signals; and ou is the sum of the variances of the common signal and the interference signals.
[18] The common signal may have a Gaussian frequency distribution.
[19] The interference signals signal may have a Gaussian frequency distribution.
[20] The minimum power may be 0.
[21] Other aspects of the invention are also disclosed. Brief Description of the Drawings
[22] Notwithstanding any other forms which may fall within the scope of the present invention, preferred embodiments of the disclosure will now be described, by way of example only, with reference to the accompanying drawings in which:
[23] Figure 1 shows a functional schematic of a real-time spectrum analyser in accordance with an embodiment.
Description of Embodiments
[24] Figure 1 illustrates a functional schematic of a real-time spectrum analyser 100 in accordance with an embodiment.
[25] The spectrum analyser 100 comprises a signal receiver comprising an antenna 103 and signal preprocessing which may comprise a combination of bandpass filters 102, attenuators 103 and low noise amplifiers 104. The attenuators 103 may provide a linear mode for the low noise amplifier 104 and mixer 107.
[26] The preprocessed signals are filtered into a series of frequency ranges utilising the mixer 107, switches 108 and intermediate frequency filters 109. A synthesizer 112 may obtain an intermediate frequency (IF), to provide high receiver selectivity.
[27] The transceiver 111 measures the power (Received signal strength indication - RSSI) of the received signals at the various frequency ranges across the entire frequency range.
[28] The spectrum analyser 100 further comprises a processor 113 which may take the form of a Field-programmable gate array (FPGA) device or the like. The processor 113 comprises a microprocessor 117 for processing digital data. In operable communication with the processor 117 across a system bus is a memory device 114 for storing digital data including computer program code controllers and associated data. In operation, the microprocessor 117 fetches these computer program code instructions and associated data from the memory device 114 for interpretation and execution.
[29] The processor 130 may further comprise an I/O interface 116 in operable communication with the micro processor 117 for interfacing with the various components shown.
[30] The processor 113 may receive the measurements from the transceiver 111 and store frequency matrix data 115 representing the number of signals detected within power and frequency band segments the memory device 114 as follows:
Table 1 - freq u en cy m a trix da ta 1 15
[31] For the data matrix 115, the Y axis represents power of interferences (such as, for example, divided into 5dBm segments) and the X axis represents discrete frequency ranges of the entire frequency range (such as, for example, divided into 10MHz segments).
[32] As such, each segment of the matrix 115 contains the number of frequencies having a frequency and power of the segment. For example, Nij represents the amount of interference of a segment having arbitrary coordinates ij.
[33] Signals may be sampled for a predetermined period to populate the data matrix 115 appropriately.
[34] The memory device 114 may further comprise an acceptable signal-to-noise ratio probability distribution calculation controller 118 which is executed by the microprocessor 117 for calculating an acceptable signal-to-noise ratio probability distribution.
[35] The acceptable signal-to-noise ratio probability distribution is calculated in accordance with a particular acceptable signal-to-noise ratio probability distribution function 120 derived hereunder.
[36] The calculated acceptable signal-to-noise ratio probability distribution may then be input into a computing device 121 for the calculation of the appropriate communication equipment operational parameters which, in embodiments, may be sent across a data network 122, such as the Internet.
Probability distribution function
[37] The processor 113 uses a particular acceptable signal-to-noise ratio probability distribution function to calculate the acceptable signal-to-noise ratio probability distribution utilising the measured signal parameters data matrix 115 which substantially immunises the spectrum analyser 100 against sporadic interference allowing for a more accurate calculation of the interferences of the surrounding electromagnetic environment.
[38] Furthermore, the acceptable signal-to-noise ratio probability distribution function employed by the processor 113 allows for the detection of powerful interferences. [39] As interferences may have Frequency Shift Keying (FSK) and/or Phase Shift Keying (PSK) modulation, a uniform distribution of interferences is:
[40] w(Ei ) = (1)
E2 -E1
[41] Where E , Ei are maximum and minimum of power in each segment of the matrix 115.
[42] Considering that each signal is uniform distributed and that in each segment there are several signals, the common signal distribution is therefore a Gaussian distribution:
[44] To determine the mean m and variance s for the common signal the mean mi and variance O of signals in each segment is calculated, where:
[46] Flowever, in the matrix— = 3 and therefore m =2Ei. Furthermore:
E
E E 2
[48] Flowever, in the matrix— = 3 and therefore a-,2=— = 033E2 t
E 3
[49] The common signal of the whole frequency range is the sum of independent signals, and therefore the mean m and variance o2 of the common signal is the sum of the means of variances mi and Oi2 of each segment:
[51] Er is denoted to represent the interference power at which the ratio signal/noise is reduced to an acceptable ratio.
[52] Therefore, the acceptable signal-to-noise ratio probability distribution function is as follows:
[53] the probability
integral.
[54] F determines the probability of receiving interferences having a total power of less than Er.
[55] In other words, in the absence of interference, we assume that the correct receiving criterion is a bit error rate (BER), which is a function of the signal-to-noise ratio or signal-to-interference ratio.
[56] For example, the BER criterion could be BER=10 4. Furthermore, the selectivity of the receiver is determined by the magnitude of Er. This means that if the power of the interference P< Er, then the receiving error rate is acceptable, i.e. the BER=10 4 or less.
[57] Flowever, if the interference power P>Er, then the BER increases, to, for example BER=10 3. [58] As such, the probability integral F in equation (5) is the probability that P < Er such that the BER=10 4 or less. In other words, the probability integral F represents the probability of receiving a signal with an allowable number of errors, or with an allowable ratio signal-to-noise ratio.
[59] This integral of the distribution function in equation 5 is calculated using the probability integral F, which has tabular values.
[60] Note that in most cases the distribution function is Gaussian as above, but in in the case of two powerful jamming sources of interference as described below, the distribution function is the sum of Gaussian and Rayleigh distributions.
[61] In either case however, acceptable signal-to-noise ratio probability distribution function is calculated as an integral of the distribution function. In other words, the acceptable signal-to-noise ratio probability distribution function is the quantitative characteristic of the receiver's resistance to interference with the available selectivity parameters.
[62] Knowing the acceptable signal-to-noise ratio probability distribution function, the selectivity or receiving frequency of the receiver may be adjusted.
Acceptable signal-to-noise ratio probability distribution function for one powerful source of interference
[63] When receiving a powerful interference signal, the signal received by the signal receiver is the sum of interferences represented in matrix Ev and the powerful interference signal Ep
[64] E (t) = Ev (t) + Ep (t)
[65] Furthermore, Ev (t) has a Gaussian distribution according to function (2) with mean m and variance o2.
[66] Now, the powerful interference has a uniform distribution as follows:
[67] w(^e) =— I— (6) wherein and ElQ represent the maximum and minimum power of the
source of the interference.
[68] Because the minimum power is not limited, it is defined as 0.
[69] As such, the distribution function applicable when receiving one source of interference is a composition of the uniform and Gaussian distributions as follow:
[73] The integrand is Gaussian distribution of (E— £' e)and therefore: [75] As such, for one source of strong interference, the acceptable signal-to-noise ratio probability distribution function is as follows:
Acceptable signal-to-noise ratio probability distribution function with two powerful sources of interference
[77] As in the previous case, considering that the powerful interference signals are uniformly distributed:
[79] The distribution function is therefore the sum of two signals with uniform distribution.
[80] w (E) = J_ w1(Ei) W2(E - E dEi or
0 for E<EI+E3 for E2+E3£ E £ E + E 4
E4-E3
0 f o r E>E2+E4
[82] Again, because the minimum power is not limited, it defined as 0 and therefore EΊ=E3=0
[83] Then the function (10) is converted as
0 E<0
[84] w ( E) = - - 0= E £ E (11) Ez £ E £ E 4
0 E>E2+E4
[85] For signals with power E2 £ E £ E 4 the probability distribution is calculated as per function (7)
[87] As such, the acceptable signal-to-noise ratio probability distribution function for two sources of strong interference is calculated as:
[89] For signals with power 0£ E £ E 2
[93] Function (15) can be represented as the sum of integrals
[94]
[95]
[96] The integrand in the first term is a Gaussian distribution of random variable B and the integrand in the second term is Rayleigh distribution where
[98] Therefore, function (16) converts to:
[100] As such, the acceptable signal-to-noise ratio probability distribution function for two sources of strong interference is calculated as:
Acceptable signal-to-noise ratio probability distribution function for three or more powerful interference signals
[102] Assuming again that a powerful interference signal is uniformly distributed, that there are three or more powerful interference signals, that the common signal distribution is a Gaussian distribution and that the minimum power is not limited (being defined as 0), therefore, according to functions (3) and (4):
[103] mi=- and s2 ί = ^
[104] For N powerful interference signals, the common signal distribution is a Gaussian distribution:
[108] The sum of the two Gaussian distribution signals also has a Gaussian distribution:
[110] Where [111] mu = m + rri! and s2 = s2 + s2 1 where m and a2 are for common interferences and mi and s2i are for powerful interferences.
[112] As such the acceptable signal-to-noise ratio probability distribution for several powerful interference signals is:
[114] As such, the present spectrum analyser 100 may compute the acceptable signal-to-noise ratio probability distribution 118 in accordance with the above acceptable signal-to-noise ratio probability distribution and the values recorded within the frequency matrix 115. These calculate probabilities may be output to a computer device 121 to calculate of the appropriate communication equipment operational parameters.
[115] The foregoing description, for purposes of explanation, used specific nomenclature to provide a thorough understanding of the invention. However, it will be apparent to one skilled in the art that specific details are not required in order to practice the invention. Thus, the foregoing descriptions of specific embodiments of the invention are presented for purposes of illustration and description. They are not intended to be exhaustive or to limit the invention to the precise forms disclosed; obviously, many modifications and variations are possible in view of the above teachings. The embodiments were chosen and described in order to best explain the principles of the invention and its practical applications, they thereby enable others skilled in the art to best utilize the invention and various embodiments with various modifications as are suited to the particular use contemplated. It is intended that the following claims and their equivalents define the scope of the invention.

Claims (12)

Claims
1. A real-time spectrum analyser comprising: a signal receiver comprising an antenna and signal pre-processor; a switch and transceiver operably coupled to the signal pre-processor; wherein the analyser is configured for: receiving signals using the signal receiver; measuring the number of signals received at a plurality of power and frequency bands using the switch and transceiver; storing the number of signals in respective segments of a power by frequency data matrix in memory; calculating a mean for each segment; calculating a variance for each segment; calculating a common mean of a Gaussian distribution as a sum of the mean for each segment; calculating a common variance of the Gaussian distribution as a sum of the variance for each segment; and calculating an acceptable signal-to-noise ratio probability distribution function according to a probability integral quotient of the difference between a chosen interference power at which the ratio signal/noise is reduced to the permissible value and the common mean and the common variance.
2. A spectrum analyser as claimed in claim 1, wherein the analyser is configured for calculating the mean for each segment as twice a minimum power threshold of the segment.
3. A spectrum analyser as claimed in claim 1, wherein the segments have 5dBm intervals and wherein the analyser is configured for calculating the square of the variance for each segment as a third of the square of the minimum power threshold.
4. A spectrum analyser as claimed in claim 1, wherein the analyser is configured for calculating the mean for each segment as half a minimum power threshold of the segment.
5. A spectrum analyser as claimed in claim 1, wherein the segments have 5dBm intervals and wherein the analyser is configured for calculating the square of the variance for each segment as a twelfth of the square of the minimum power threshold.
6. A real-time spectrum analyser as claimed in claim 1, wherein the real-time spectrum analyser is further configured for configuring at least one of selectivity and receiving frequency of a receiver in accordance with the probability distribution.
7. A real-time spectrum analyser as claimed in claim 6, wherein configuring the receiving frequency comprises setting the receiving frequency at a frequency of the probability distribution which falls beneath the acceptable signal-to-noise ratio.
8. A real-time spectrum analyser as claimed in claim 7, wherein the acceptable signal-to-noise ratio is a bit error rate (BER).
9. A real-time spectrum analyser as claimed in claim 1, wherein the signals comprise a common signal and three or more interference signals and wherein the acceptable signal-to-noise probability distribution is:
F (Er) = F (^) Where:
E
F (—— -) is a probability integral where:
Er is the acceptable signal-to-noise ratio
mu is the sum of the means of the common signal and the interference signals; and
ou is the sum of the variances of the common signal and the interference signals.
10. A real-time spectrum analyser as claimed in claim 9, wherein the common signal has a Gaussian frequency distribution.
11. A real-time spectrum analyser as claimed in claim 9, wherein the interference signals signal has a Gaussian frequency distribution.
12. A real-time spectrum analyser as claimed in claim 9, wherein the minimum power is 0.
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PCT/AU2019/050195 WO2019169442A1 (en) 2018-03-08 2019-03-07 A high sensitivity and selectivity real-time spectrum analyser

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Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2012049680A1 (en) * 2010-10-14 2012-04-19 Elbit Systems Ltd. Wideband signal analyzer
WO2018035560A1 (en) * 2016-08-22 2018-03-01 The University Of Sydney Optical rf spectrum analyser

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2012049680A1 (en) * 2010-10-14 2012-04-19 Elbit Systems Ltd. Wideband signal analyzer
WO2018035560A1 (en) * 2016-08-22 2018-03-01 The University Of Sydney Optical rf spectrum analyser

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