Application of vector signal analyzers in radio monitoring systems..
SILANTIEV Vladimir Anatolyevich,
Candidate of Technical Sciences
USE OF VECTOR SIGNAL ANALYZERS IN RADIO CONTROL SYSTEMS
Vector signal analyzers were created to study complex radio signals, such as signals with digital quadrature modulation, as well as high-frequency pulse and non-stationary processes. The parameters of such oscillations are difficult, if not impossible, to estimate using conventional devices. To obtain comprehensive information about the modulation and characteristics of a signal in the time and frequency domain, it is necessary to study a two-component (vector) process that reflects changes in the amplitude and phase of the original signal over time. The digital processing capabilities of modern vector analyzers make it possible to record such processes and extract all information about the parameters of the received signal. These capabilities deserve the attention of radio monitoring specialists, taking into account the problems that arise when analyzing signals from modern systems with time and code division of channels, pseudo-random frequency hopping and digital modulation.
Measuring Signal Parameters
Analysis of radio signal parameters along with their detection is one of the main operations of radio monitoring. During the analysis, the operator or computer program measures the characteristics of the detected radio signal of interest, such as the carrier frequency, level, shape and width of the spectrum, modulation parameters, etc. The results of these measurements are used to check the compliance of the parameters of the monitored systems with the established standards or serve as initial data for the procedures of classification and identification of signals and radio systems in which these signals are used.
To obtain detailed information about the received signals, it is necessary to study their behavior over time and perform spectral analysis in the frequency domain. If the detected signal is modulated, it is necessary to determine the type of modulation and evaluate the time and frequency parameters of the modulating processes.
Radio signal analysis equipment
To measure the entire set of radio signal parameters of interest to the radio monitoring system, it is necessary to use several specialized devices: spectrum analyzers, measuring receivers and modulation analyzers.
In the frequency domain, sequential spectrum analyzers are mainly used to study the shape of the spectrum, measure levels and carrier frequencies of radio signals. Such a device forms a spectral picture sequentially in the process of rebuilding the controlled generator of the frequency converter and measuring the levels at the output of the bandpass filter (Fig. 1a).
Fig. 1. Structural diagram of spectrum analyzers
of sequential (a) and parallel (b) type
A parallel analyzer evaluates the entire spectrum at once, since it contains a group of bandpass filters tuned to adjacent frequencies (Fig. 1b). Since the implementation of an analog structure of this type is difficult, in practice its digital equivalent is used in the form of an FFT analyzer, which calculates the spectrum using fast Fourier transform (FFT) algorithms. Compared with serial analog analyzers, digital parallel FFT analyzers have certain advantages: higher resolution and operating speed, the ability to analyze pulse and single signals. They are able to calculate not only the amplitude but also the phase spectrum, and simultaneously represent signals in the time and frequency domains. Unfortunately, parallel FFT analyzers, due to the limited capabilities of analog-to-digital converters (ADCs), operate only at relatively low frequencies.
The main advantage of the measuring receiver is its higher sensitivity compared to the spectrum analyzer and the presence of tunable bandpass (preselector) filters at the input, which significantly increase noise immunity in conditions of dense radio range loading, typical for radio monitoring tasks. The measuring receiver path, calibrated by gain and frequency, is used to evaluate the levels and frequencies of radio signals and has several standard demodulators for studying the modulation characteristics of the received signal in the time domain. At the same time, the capabilities of signal analysis in the frequency domain for devices of this class are usually limited.
Modulation analyzers are used to study processes at the outputs of standard demodulators. By selecting the required demodulator type, the operator receives information about the nature and parameters of the change in the amplitude, frequency or phase of the received signal.
Recently, due to the intensive development of mobile and satellite radio communication systems and the widespread introduction of promising digital methods of modulation and channel separation, the requirements for signal analysis equipment have changed significantly. New devices capable of operating effectively in three areas of radio signal representation at once: time, frequency, and in the area of modulating processes are replacing sequential spectrum analyzers and panoramic receivers with simple AM and FM demodulators.
Vector analysis of radio signals
To represent any radio signal, it is enough to know its carrier frequency and a two-component vector process, the complex envelope. Despite the fact that the carrier frequency can be very high, the complex envelope remains a relatively low-frequency signal that can be converted into digital form. One of the possible schemes for vector analysis of radio signals is shown in Fig. 2. To expand the frequency range, a down- or up-converter is usually included at the input of the vector analyzer, which transfers the spectrum of the input radio signal to a fixed intermediate frequency. Various devices are used as such converters, from simple circuits based on mixers and generators to specialized systems. The functions of the converters are often performed by calibrated input paths of spectrum analyzers or wide-range receivers with an output at an intermediate frequency of 10.7 or 21.4 MHz.
The quadrature demodulator operates at an intermediate frequency and extracts the real (I) and imaginary (Q) parts of the complex signal envelope in a frequency band called the parallel processing band. After analog-to-digital conversion, the digital realizations of I and Q are recorded in the memory of the digital signal processor (DSP). With the I/Q realizations at its disposal, the processor calculates the spectrum of the input radio signal, as well as the modulation functions that describe the time behavior of the amplitude, frequency, and phase of the received signal.
Fig. 2. Structure of a vector signal analyzer with a frequency converter
The process of measuring radio signal parameters with a digital vector analyzer consists of two stages: recording and processing. At the first stage, the analyzer selects, converts into digital form and places into memory the realization of the complex envelope of a radio signal of a given duration. At the second stage, the received data are processed and prepared for display. Processing (for example, spectrum calculation) of the current realization can be performed in parallel with the process of recording the next one. If the time of calculations and transmission of results to the consumer is less than the duration of a separate realization, the analysis will be performed without gaps in real time (Fig. 3a). This mode is used for continuous display and demodulation of stationary processes. In some cases, for example, when analyzing pulse or single signals, only individual time fragments are registered in memory (Fig. 3b), the processing of which can take a significant amount of time. In this mode, it is possible to significantly expand the band of analyzed frequencies, and the duration of the analyzed fragment will be determined by the memory capacity of the DSP.
Fig. 3. Continuous digital processing of signals in real time (a) and recording of individual fragments with subsequent processing (b)
Let's list the main features that distinguish vector analyzers from traditional devices for studying radio signal parameters:
-
Unlike meters that operate with scalar (one-dimensional) processes, a vector analyzer processes complex envelopes representing the amplitude and phase of a radio signal. This allows you to study amplitude and phase spectra, as well as simultaneously isolate the amplitude, phase, and frequency of a radio signal and display them as spectral, time, or vector diagrams.
-
Due to digital recording, a vector analyzer performs parallel spectrum analysis in real time without the information loss typical of serial spectrum analyzers, and also represents the input radio signal simultaneously in the time and frequency domains.
-
Digital recording and storage in memory of successive radio signal realizations provides unique opportunities in terms of detection and study of characteristics of non-stationary, pulsed and single radio signals in the spectral analysis mode with “time selection”.
Parameters of vector radio signal analyzers
One of the main parameters of a vector analyzer is the parallel processing bandwidth, which depends on the ADC speed and the DSP performance. To study and demodulate high-speed radio interface signals and signals with spread spectrum, parallel analysis bandwidths of several MHz are required. At the same time, expanding the parallel analysis bandwidth and using an ADC with a higher sampling frequency can negatively affect the dynamic range and frequency resolution of the analyzer. The bandwidth during real-time processing reflects the ability of the device to analyze continuous stationary signals in real time. In wideband analyzers, this bandwidth can be significantly smaller than the parallel processing bandwidth. The duration of the recorded implementations is associated only with the memory capacity of the DSP and determines the capabilities of the device to record and detect pulse and single signals.
The remaining parameters of the analyzer: operating frequency range, sensitivity, range of measured levels and dynamic range at the input are entirely determined by the type of frequency converter used. Measuring signal levels and frequencies requires calibration of its gain, as well as the use of frequency synthesizers with the required stability and phase noise level.
Depending on the parallel analysis bandwidth, modern vector analyzers measure the power of spectral components with a dynamic range of 60 to 90 dB. The 89410A vector processing unit of the 89400 series, manufactured in particular by Agilent Technologies (USA), operates with a parallel analysis bandwidth when recording implementations in memory of 3–7 MHz and 78 kHz when recording in real time. The memory capacity of implementations is up to 1 million samples. The device is used with 89431A or 89430 A frequency downconverters (range up to 2.65 and 1.8 GHz, respectively). Input sensitivity is -159 dBm/Hz, the level of side components is -70 dBc. The 89411A converter of this series is designed to interface the vector processing unit with radio receivers and spectrum analyzers that have an intermediate frequency output of 21.4 MHz.
Specialists from Tektronix (USA) call such devices real-time spectrum analyzers (RTSA – Real Time Spectrum Analyzer). Analyzers 3066 and 3086 of this company operate at frequencies from 10 MHz to 3 GHz. Memory of implementations is up to 16 MB. Parallel analysis is performed in a band of up to 5 MHz with a frequency resolution of up to 5 kHz. Measurement of levels from -50 to +30 dBm. The level of intrinsic noise at the input is -140 dBm/Hz.
Vector analyzers in radio monitoring systems
In a radio monitoring system, a vector analyzer can be used with its own frequency converter or connected to the intermediate frequency output of a standard spectrum analyzer or panoramic radio receiver of the system. As a result, it is possible not only to significantly increase the speed and accuracy of signal parameter evaluation, but also to obtain a number of completely new capabilities that are not available to traditional analysis tools.
Parallel spectrum analysis
In serial spectrum analyzers, the resolution (analysis bandwidth) is determined by the bandwidth of the analog bandpass filters (Fig. 1a), the number and parameters of which determine the available analysis bands. Digital parallel analyzers change the resolution programmatically, and the implementation of narrow analysis bands does not cause such difficulties as in analyzers with discrete filters. The frequency resolution of a vector analyzer depends only on the dimension (number of points) of the FFT algorithm:
frequency resolution = (parallel processing frequency band)/(FFT dimension).
For example, for a 200 kHz parallel processing bandwidth, a 2048-point FFT algorithm will provide a frequency resolution of about 100 Hz. Such parameters make it possible to study the signal spectra of narrowband frequency-division multiplexing systems (Fig. 4), as well as measure the spectrum width and carrier frequencies with an accuracy of up to 100 Hz.
Fig. 4. Spectra of frequency-manipulated signals from two adjacent narrowband stations (2048-point FFT with a resolution of 100 Hz, parallel analysis bandwidth of 50 kHz)
As with any spectrum analyzer, sensitivity improves proportionally to the reduction of the analysis bandwidth. For example, switching from a 10-kHz analysis bandwidth to a 100 Hz bandwidth will increase sensitivity in this band by 20 dB.
Another important advantage of parallel analysis compared to sequential is the relative increase in the speed of spectrum construction, which becomes especially significant with small analysis bandwidths. As is known, the minimum review time of a sequential analyzer is limited by the value:
sequential analysis time = (span)/[0.5*(span)2].
In particular, to construct a spectrum in a 200 kHz span with a resolution of 100 Hz, a sequential analyzer will need about 40 seconds.
The parallel analyzer works much faster. To calculate the spectrum, the DSP must register a realization with a number of samples equal to the FFT dimension. The samples are received at the ADC sampling frequency, approximately equal to the parallel processing bandwidth. As a result, the minimum parallel analysis time will be:
Parallel analysis time = (FFT dimension)/(parallel processing bandwidth).
Taking into account the time spent on processing and transferring data to the computer, this time will be from 10 to 40 ms.
Panoramic spectrum analysis and signal level measurement
The bandwidth of parallel spectrum analysis usually does not exceed several MHz. To form spectral panoramas in wide frequency ranges, some vector analyzers can perform the functions of serial spectrum analyzers or combine serial and parallel modes. In serial mode, the analyzer's DSP performs direct measurements of the average signal power in the parallel processing band when the frequency converter is tuned with a step equal to this band (Fig. 5).
Fig. 5. Panoramic display of the spectrum in the 800-MHz band with a resolution of 1.6 MHz, obtained by a vector analyzer with averaging over 16 realizations
In terms of the speed of forming spectral panoramas with wide analysis bands, vector analyzers are inferior to sequential spectrum analyzers. At the same time, using a frequency converter with controlled preselector filters, it is possible to significantly improve sensitivity and ensure protection of the radio monitoring complex with wide-range antennas from overloads. In addition, the frequency synthesizer of such a converter will maintain high tuning stability at all points of the frequency range under study, and digital averaging (accumulation) algorithms of the vector analyzer will increase the signal-to-noise ratio and reduce measurement errors of input levels.
Serial-parallel spectrum analysis is used at medium resolution values. In this mode, the FFT processor calculates band-limited spectrum fragments at each step of the frequency converter tuning, and the control program then “glues” individual sections together and displays the full spectral picture on the screen (Fig. 6).
Fig. 6. The spectrum of the full television signal is constructed in a 10 MHz bandpass in the serial-parallel analysis mode. At each of the 50 consecutive 200 kHz tuning steps, a 16-point DFT is performed
Analysis of radio signals in time
Spectrum analysis is an important, but far from the only procedure used in signal detection and analysis in radio monitoring systems. Of no less interest are changes in radio signal parameters over time. Usually, time characteristics are estimated only in the area of modulating processes using one of the standard demodulators, for example, amplitude or frequency. However, such an approach may be ineffective for modern radio systems in which information is transmitted using quadrature (vector) modulation, which generally involves simultaneous changes in the amplitude and phase of the radio signal.
The vector analyzer records the complex envelope of the radio signal and therefore represents changes in its parameters over time without the loss of information typical of scalar demodulators. Several different formats are provided for displaying the complex envelope. The in-phase and quadrature components at the output of the quadrature demodulator, representing the real and imaginary parts of the complex envelope of the input radio signal, respectively, can be displayed as oscillograms in Cartesian coordinates (Fig. 7). If the oscillogram is synchronized with the clock frequency of the received signal with discrete manipulation, the display takes the form of the so-called “eye” diagram.
Fig. 7. Oscillogram of the in-phase component of the GSM communication system signal with time division of channels (recording of one implementation with a duration of 8 ms and display of a 2-ms section with a resolution of 4 μs)
The vector format is more informative for digitally modulated signals – a representation of a complex envelope in polar coordinates on a complex plane. The vector modulus reflects the instantaneous amplitude (envelope) of the radio signal, and the angle is the current phase value. Analysis of the trajectories of a complex vector with time changes allows us to recognize the type of modulation and evaluate its parameters. For example, a signal with a constant amplitude and frequency modulation looks like a circle with a center at the origin.
However, the main advantages of the vector representation are obtained when analyzing signals with multi-position phase and amplitude-phase manipulation. Depending on the transmitted symbol, the phase and amplitude values of such signals fall on certain points of the complex plane. The trajectories that the signal vector passes between these points (the so-called star diagrams) can be used to judge the nature and quality of the modulation (Fig. 8).
Fig. 8. Phase points and trajectory reflecting changes in the amplitude and phase of a signal with a four-position differential quadrature phase shift keying and a shift of p/4, which is used in the DAMPS (IS-54) mobile communications system, over an interval of 8 ms.
Modulation Parameter Analysis. Frequency Measurement
By registering radio signal realizations, the digital processor of the analyzer operates as a “software radio”. This term means, in particular, that the adjustment of such reception parameters as tuning frequency, bandwidth and demodulator type is performed programmatically without any changes in the hardware. Software implementation of the demodulator functions allows for real-time selection and evaluation of the parameters of three modulating processes at once: amplitude, phase and frequency, as well as measuring their characteristics, for example, the amplitude modulation (AM) depth or frequency deviation (Fig. 9).
Fig. 9. Oscillogram of the change in the amplitude of the television image signal in the parallel analysis band of 200 kHz
These operations correspond to the functions of standard analog demodulators: amplitude, frequency and phase. More complex algorithms, including clock, symbol and frame synchronization, are used for demodulation and decoding of signals with digital quadrature manipulation.
During the measurements, the analyzer evaluates the statistical characteristics of the modulation parameters, such as the average value, maximum and standard deviation. Calculating the time-average frequency value provides another way to estimate the carrier frequency of the modulated signal, which is characterized by higher accuracy compared to spectral measurements. Figure 10 shows an example of a personal radio call station signal spectrum and the corresponding time implementation, reflecting the result of the digital FM demodulator. The accuracy of the carrier frequency estimate based on the spectrum does not exceed the analysis bandwidth (in this case, 100 Hz), whereas with sufficient averaging this error can be reduced to several Hz.
Fig. 10. Oscillogram of the change in the frequency of the personal radio call signal, obtained using a digital frequency demodulator. The demodulator calculates the average and root-mean-square and maximum value of the deviation of the signal frequency from the analyzer tuning frequency
Spectral analysis with time selection
Sequential spectrum analysis gives good results only when studying continuous stationary signals. Signals from packet, time-division multiplexing and/or pseudo-random carrier-frequency hopping communication systems appear in the coverage area only for a short time. Therefore, an undistorted representation of such signals in the frequency domain can only be obtained using parallel analysis. Moreover, since the moment of appearance and duration of a pulsed signal are generally unknown, its detection and parameter estimation have to be performed simultaneously. For this purpose, the vector analyzer uses a special mode with continuous recording of successive realizations of the complex envelope in the buffer memory. By performing parallel spectrum analysis and calculating the modulating processes for each realization, it is possible to detect the signal and obtain an idea of the evolution of its spectral and temporal characteristics over time.
The frequency and temporal resolution of this mode is determined by the number of samples in one realization: the greater it is, the higher the frequency resolution and, correspondingly, the lower the time resolution. The total number of realizations that can be simultaneously stored in the buffer memory depends on its capacity and determines the duration of the time interval under study.
The results of parallel spectrum analysis are reflected in three-dimensional diagrams in the coordinates frequency, time, level. These diagrams are presented on the monitor screen in the form of spectrograms or “cascade displays of spectra (Fig. 11).
Fig. 11. The spectrogram (in a separate window on the right) reflects the operation of two personal radio call stations on the frequency-time plane. Each horizontal line of the spectrogram displays one realization of the spectrum (on the left)
On the spectrogram, the spectrum of an individual implementation is represented by a horizontal line on the frequency-time plane, the color change of which conveys the relative values of the levels (an increase in the level from the minimum to the maximum corresponds, for example, to a transition from violet to red). Registration of implementations in the buffer memory is carried out continuously and can be stopped by the operator or by a trigger signal with some delay relative to the moment of occurrence of the event of interest, for example, an increase in the implementation energy in a certain frequency region. After this, it is possible to study the characteristics of the detected signal in the past and in the future, that is, at the moments of time before and after the stop of registration. For each implementation selected on the spectrogram, the vector analyzer can simultaneously display its spectrum, time or vector diagram, as well as one or more modulating processes (Fig. 12a, b). This way, it is possible to find the moments of the appearance and end of the transmission of a pulse and single signal, determine the intervals of transmission of preambles and synchronizing sequences by the spectrum, recognize the type of modulation and, based on the received data, perform demodulation and decoding of information.
Fig. 12 a) The spectrogram shows the implementation corresponding to the beginning of the session of transmission of the personal radio call message. The spectrum of this implementation shows that at these moments an unmodulated carrier is transmitted
Fig. 12b) Simultaneous display of the signal in the frequency domain and in the domain of modulating processes. The implementation corresponding to the middle of the session of transmission of the personal radio call message is selected on the spectrogram. The signal at the output of the frequency demodulator for this implementation corresponds to the moments of data transmission at a rate of 1.2 kbit/s, and the frequency deviation is 4.4 kHz
Conclusion
Vector analysis is a powerful tool for studying and measuring the characteristics of radio signals in the entire used frequency range from several kHz to tens and hundreds of GHz. Vector analyzers are widely used in the design and testing of modern radio equipment. These devices also have significant potential in the field of radio monitoring and radio intelligence. The use of vector analyzers allows, in particular, to solve serious problems of detection and analysis of signals of modern digital communication networks using time and code division of channels, pseudo-random frequency hopping, multi-position amplitude-phase modulation and other promising methods of information transmission.