Modern communications systems are exceptionally complex. They typically use sophisticated RF combination techniques like adaptive and complex modulation, frequency hopping, and bursting. When it comes to wireless systems, it is fiendishly complex to predict the propagation of radio waves and detect the presence of interfering signals unless you employ special test equipment. It is necessary to comprehend how frequency, modulation, and amplitude behave over long and short time intervals. Spectrum analyzers can discover the elusive effects inherent in RF signals, trigger on such effects, and seamlessly place them into memory. They can also analyze them in modulation, code, frequency, time, and statistical domains. This Learning Module covers the basics of Spectrum Analyzers, including their functions and operation.
Upon completion of this module, you will be able to:
What is a spectrum analyzer? A spectrum analyzer measures the amplitude of an input signal versus frequency within the full frequency range of the instrument. The primary use is to measure the power of the spectrum of known and unknown signals. Spectrum analyzers can be used for:
Spectrum Analyzers facilitate the comprehension and subsequent analysis of RF signals behavior. The scope of this learning module is to cover the basics of Spectrum Analyzers, including their architecture, types, functions, and operation.
A spectrum analyzer (SA), in concise terms, is simply a device that analyzes a system of oscillations, particularly sound, into its discrete components. The device displays the signal strength or amplitude as the latter changes with signal frequency. The electronics industry employs spectrum analyzers to examine the frequency spectrum of radio frequencies and also audio signals. The device displays the signal's elements and even the performance of the signal-producing circuits.
- 4.1 Do You Need a Spectrum Analyzer, or Will an Oscilloscope do?
Since it is impossible to know in advance the nature of signals, having access to both a spectrum analyzer and an oscilloscope allows for accurate signal characterization. An oscilloscope displays the signal concerning time, while a spectrum analyzer shows the same concerning frequency. An oscilloscope is used to find the wanted relative time delay existing between two signals. A spectrum analyzer helps to observe a signal's frequency properties.
Spectrum analyzers measure the magnitude of any input signal against frequency within the instrument's full frequency range. Their principal use is the measurement of spectrum power for both known and also unknown signals. The signal's amplitude is displayed on the vertical axis and frequency on the horizontal axis. Oscilloscopes examine electrical signals in the time domain. Spectrum analyzers do the same in the frequency domain (Figure 1).
- 4.2 Spectrum Analyzer Applications
Spectrum analyzers find use in general-purpose spectrum analysis, EMC-compliance testing, RF record and playback, spectrum monitoring, radar and electronic warfare, radiolocation and interference hunting, and troubleshooting. They are used for multiple measurements like frequency response, interference sources related to telecommunication, occupied bandwidth, noise and distortion characteristics of all types of radio-frequency circuitry, and EMC-compliant basic pre-compliance testing.
Spectrum analyzers verify that the devices used to design, test, and also manufacture equipment like cell phones and TV broadcast systems generate proper signals at intended frequencies and levels. The reviewed device must comply with regulatory laws by operating only at their assigned frequency and by staying within allocated channel bandwidth. Any unwanted emissions must not damage other systems' operations, ranging from the parametric to the standards-compliant wireless measurements such as phase noise, W-CDMA, noise figure, analog demodulation - LTE/LTE-Advanced, pulse analysis, and more.
A Spectrum Analyzer is a vital instrument to have when you test radio frequency, RF modules, circuits, and units. It shows amplitude against frequency and plays a key function in locating spurious signals and the measurement and display of signal bandwidths. RF circuits can be properly investigated only when you know how to properly use a Spectrum Analyzer.
A spectrum analyzer shows the signal's frequency content, with the horizontal (X) axis indicating the signal frequency and vertical (Y) axis the amplitude. The controllable settings are frequency resolution, RF attenuation, video bandwidth, frequency display range, resolution bandwidth, sweep time, and reference level. The input frequency range, in light of multiple spectrum analyzers configurations, may be subdivided into:
The AF range to approximately 1MHz covers all low-frequency electronics, and also acoustics and mechanics. Wireless communication applications are mostly in the RF range, like TV broadcasts, mobile communications, and sound. The frequency bands in millimeter-wave or microwave range, in contrast, are used mostly for broadband applications.
- 5.1 Spectrum Analyzer types
Spectrum Analyzers come in three broad categories based on their architecture:
Swept Spectrum Analyzers, Vector Signal Analyzers, and other traditional tools offer signal snapshots in the modulation or frequency domain. One of the drawbacks of "signal snapshots" is that they can be inadequate to describe the dynamic nature of modern RF signals. It is vital for scientists and engineers to reliably detect and then characterize RF signals, which vary over time - an activity challenging to do with traditional measurement tools.
An RTSA discovers elusive effects within RF signals, initiates action on those effects, engages in seamless memory capture, and also analyzes signals in frequency, code, time, modulation, and statistical domains. The design of RTSA architecture is specially made to overcome SA and VSA measurement limitations to better solve the challenges linked with dynamic and transient RF signals.
An RTSA uses real-time digital signal processing (DSP) to conduct signal analysis before memory storage. Real-time processing permits a user to discover those events that are invisible to all other architectures, and also trigger such events, allowing their selective capture to memory. The memory data can then be comprehensively analyzed through the use of batch processing in multiple domains.
- 5.2 Instrument Architectures
It helps to have a working knowledge of the different kinds of traditional RF signal analyzers to understand how RF Spectrum Analyzers function.
a. Swept Spectrum Analyzers (SA): This traditional architecture enabled engineers to accomplish frequency-domain measurements for the first time. These machines are ideal for observing controlled and static signals.
A swept tuned superheterodyne spectrum analyzer is an assemblage of an RF input attenuator that reduces high-level input signals' amplitude, a mixer which combines the frequency of input and local oscillator to frequency shift input signal, and a variable IF gain circuit that amplifies mixer output before passing the same to the IF filter.
The IF filter is described as a bandpass filter whose bandwidth can be adjusted from the front panel of the spectrum analyzer. This is referred to as resolution bandwidth (RBW). A detector or log amplifier responds to the IF signal level and performs a logarithmic conversion. A video filter uses low-pass filtering to the first average and then smoothes the displayed trace. A sweep generator controls the frequency of the local oscillator and refresh rate. A local oscillator is swept to generate normal display or be held constant in the zero-span mode.
Although this technique offers a high dynamic range, the disadvantage of such an arrangement is that one can only calculate amplitude data for one frequency point at any time. The measurements, as a consequence, are valid for comparatively stable input signals.
b. Vector Signal Analyzers: Vector measurements provide both phase information and magnitude and are crucial to analyzing signals carrying digital modulation. A VSA digitizes all RF power within the instrument's passband and places the digitized waveform into memory. This waveform contains phase information and magnitude. The DSP can use both of them for demodulation, display processing, or measurements. The wideband IF signal is digitized by the ADC inside the VSA. Numerical solutions are performed for down-conversion, detection, and filtering. Fast Fourier Transform (FFT) algorithms transform from time to frequency domain. The VSA measures the modulation parameters like FM deviation, error vector magnitude, and code domain power.
Although the VSA can store waveforms in its memory, it suffers from a limited ability to analyze transient events. In typical VSA free run mode, the acquired signals should be stored in memory before they are processed. This serial batch processing makes the instrument blind to any events that occur between acquisitions. It is hard to find occasional or single events. Triggering of such rare events could be used to isolate such events in memory. The restricted triggering capabilities of VSAs constitutes a major problem. Such an incapacity makes a VSA incompatible for present-day dynamic RF environments.
c. Real-Time Spectrum Analyzers: The RTSA is specifically designed to capture and analyze transient and dynamic RF signals. The fundamental notion of an RTSA is to trigger an RF signal event, then seamlessly capture digitized data to memory, and subsequently offer a built-in analysis of that data in multiple domains. The entire frequency range of the instrument can be tuned into the RF front end, which down-converts the RF input signal to fixed IF related to maximum real-time bandwidth of the RTSA. This signal is subsequently filtered and digitized by an ADC and then passed to the DSP engine, which administers the triggering, analysis, and memory functions of the instrument.
A "real-time" digital system simulation is one where operating speed matches the real system which it simulates. The real-time signal analysis must be sufficiently fast to accurately process every signal component in the interested frequency band. Such a definition implies:
The input signal must be swiftly sampled so that it satisfies the Nyquist criteria (e.g., determines approximate transient conditions via stability margins). It means the sampling frequency should be at all times twice the bandwidth of interest.
The Real-Time Spectrum Analyzer (RTSA) architecture is designed to sidestep the limitations of both the SA and the VSA. The RTSA uses real-time Digital Signal Processing (DSP) to perform signal analysis. This is done before memory storage, as opposed to VSAs post-acquisition processing. Such real-time processing permits users to find events invisible to all other architectures and then trigger such events, allowing selective capture to memory. Subsequent batch processing thoroughly analyzes the data in several domains. A real-time DSP engine can be used to execute multiple analysis tasks, including calibration and signal conditioning.
- 5.3 Selecting a Spectrum Analyzer
Spectrum analyzer selection is based on the equipment's conformance test to a particular measurement performance or test standard requirement as defined by manufacturing. A product's actual performance, however, often forces the designer to comprehensively test any device much beyond the testing standards' restricted scope to validate all intended operational modes. The use of digital RF technologies enables swift operational changes. It may also create intermittent or transient behaviors, reducing system effectiveness. Periodic manufacturing failures are a possibility. Digital RF enables increasingly powerful and specialized integrated circuits to execute traditional analog radio duties. The list of digital RF technology achievements includes filtering, adaptive modulation, adaptive linearization, and direct synthesis. Since science can sense the environment and adapt to it, critical spectrum resources are better utilized, and system performance goes up. There is also an uptick in the throughput.
Digital RF enjoys the advantage of time, an acknowledged element in the RF world. Modern equipment causes signals which are variable over time. The RF signals must conform to exacting spectral performance over time. Your spectrum analyzer tools must keep pace with your design's changing demands. Standards are insufficient when seen from the perspective of product behavior definition, and thus cannot be the sole factor in spectrum analyzer selection.
Modern SAs use swift digital signal processing, where an input signal gets sampled at any suitable point with the help of the A/D converter and then further processed through a digital signal processor. The local oscillator (LO) gets locked to a specific reference frequency through a phase-locked loop (PLL), and then tuned by changing the division factors. The PLL technique provides the benefit of noticeably higher frequency accuracy compared to what can be achievable with analog tuning. Compact designs are possible, as LC displays can now be used instead of the old cathode-ray tube.
A modern SA must manage multiple tasks to assist you to meet your measurement needs. These could be application-specific measurements like adjacent channel power (ACP), phase noise, or noise figure. It should offer industry defined digital modulation analysis measurements like LTE, cdma2000®, 802.11, GSM, or Bluetooth®. The SA can also perform printing, data transfer, vector signal analysis, saving, operation over GPIB, and LAN or the Internet. It permits you to update the instrument firmware so that you can add new capabilities and features, in addition to repairing defects. Provisions get made for self-calibration, diagnostics, troubleshooting, and repairs other than recognizing and operating with optional hardware and their operations to add capabilities. You can make measurements in the field with a rugged and battery-powered handheld spectrum analyzer that correlates with data absorbed with the help of high-performance bench-top equipment.
Other available optional measurement capabilities for a broad swathe of wireless communications standards include Multi-standard radio (MSR), LTE/LTE-Advanced, WLAN, GSM/EDGE, CDMA2000, 1xEV-DO, 1xEV-DV, cdmaOne, NADC, PDC, TD-SCDMA, W-CDMA, and HSDPA.
The SA selection procedure must take into account the test frequency range and other parameters. The dimension should be measured as required. The Active Probe needed for the SA should offer high input impedance ranging from 5 Hz to 500 MHz. It improves the circuit design and also provides precise in-circuit measurements.
Validation and high-speed digital design tasks use active differential probes. These have a low noise floor and flat frequency response. A high-frequency probe enables in-circuit measurements with exceptional frequency response. Unity gain ensures high accuracy. For spectrum analyzers, preamplifiers make the ideal choice, as they offer excellent gain and flatness combined with probe-power bias connection, which eliminates any further DC power supply requirement.
- 5.4 Tips for a better spectrum analyzer experience
A spectrum analyzer usually comes with several challenges. The input level may cause complications. This input usually directly connects to a high-performance mixer. Excess power usage may lead to mixer failure, and costly repairs. To avoid such a situation, the output should pass through an attenuator during transmitter tests. The attenuator must be present to reduce high power levels (if any) so the input will not be overloaded.
When you test for spurious signals, it may not be immediately obvious as to whether the signals were generated internally or their source is the unit under test (UUT). Overloads may spook the spectrum analyzer and generate spurious signals. The rule of thumb is to reduce the input attenuator level by 10 dB. If there is a 10 dB drop during spurious level, then the signal is UUT-generated. If the drop is more than 10 dB, the spurious signals are generated inside the spectrum analyzer. If you observe the latter, reduce the input attenuator to the parameter where the spurious signals generated by the spectrum analyzer cease to be visible.
The latest software running on the spectrum analyzer must be up-to-date. Manufacturers periodically update the software to fix coding errors, as well as for performance enhancement.
- 5.5 Calibration
Spectrum analyzer circuit performance can drift with changing temperature conditions and over time. This drift influences analyzer measurement accuracy. If the measurements are inaccurate, the tested devices may have inadequate performance. Since the SA is used to test other machines, you must have confidence in its accuracy. As an increasing number of signals are clumped into the same space, even small deviations may cascade into substantial problems. It is essential to calibrate the spectrum analyzer at intervals mentioned by the equipment manufacturer, and it must be ensured that all critical functional parameters of the spectrum analyzer are operating within specification.
Calibration verifies whether spectrum analyzer performance is within specifications. It can be time-consuming and needs extensive test equipment. Performance tests must be done to check the concerned analyzer against its stated specifications once a year. There should be a periodic alignment of the spectrum analyzer to compensate for aging effects and thermal drift.
Amplitude Modulation (AM): The process by which the sine wave's amplitude (the carrier) is varied as per the second electrical signal's instantaneous voltage. The second signal is the modulating signal.
Fast Fourier Transform (FFT): A computationally efficient method of computing a Discrete Fourier Transform (DFT). A common FFT algorithm requires that the number of input and output samples are equal and a power of 2 (2,4,8,16,...).
Frequency Modulation (FM): The process in which the frequency of an electrical signal (the carrier) is varied according to the instantaneous voltage of a second electrical signal (the modulating signal).
Superheterodyne: A radio receiver that combines a locally generated frequency with the carrier frequency to produce a lower-frequency signal (IF, or intermediate frequency) that is easier to demodulate than the original modulated carrier.
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1) From the selection below, choose the option that best defines real-time bandwidth:
2) True or False: Spectrum analyzers can be used to discover frequency utilization and interference in a target area.
3) Spectrum Analyzers can be used in which of the following applications?
4) The Spectrum Analyzer has a frequency range of ______
5) True or False: A Swept Spectrum Analyzer is typically adequate for decribing the dynamic nature of RF signals.
6) The function of the RF input attenuator of a swept tuned superheterodyne spectrum analyzer is:
7) The Real-Time Spectrum Analyzer has a measurement range of ______
8) Fast Fourier Transform (FFT) algorithms transform from ______ to _______ domain.
9) True or False: The fundamental notion of a Real-Time Spectrum Analyzer is to trigger an RF signal event, then seamlessly capture digitized data to memory, and subsequently offer a built-in analysis of that data in multiple domains.
10) The noise floor is the level of noise __________ to a system that represents the _________ limit at which input signals can be observed; ultimately limited by thermal noise (kTB).
11) True or False: While a Vector Signal Analyzer has the ability to store waveforms in memory, it is limited in its ability to analyze transient events.
12) A spectrum analyzer is used to measure _________ information of a signal, whereas oscilloscopes are used to measure the ________ information of a signal.
13) What is the acquistion bandwidth of the Spectrum Analyzer?
14) True or False: Real-Time Seamless Capture is the ability to acquire and store an uninterrupted series of time-domain samples that represent the behavior of an RF signal over a long period.
15) It is important to keep a spectrum analyzer calibrated, because spectrum analyzer circuit performance can drift with changing _________ conditions and over time.