This section provides overview, applications, and principles of signal analyzers. Also, please take a look at the list of 24 signal analyzer manufacturers and their company rankings.
A spectrum analyzer measures the amplitude versus frequency of an incoming signal over the entire frequency range in a measuring instrument. It can measure the spectrum strength of known and unknown signals. Vector signal analyzer measure the amplitude and phase of an input signal at a single frequency within the IF bandwidth of the instrument.
The signal analyzer performs these spectrum analyzer and vector signal analyzer functions simultaneously. It can make in-channel measurements of known signals (error vector amplitude, code domain power, spectrum flatness, etc.).
The combination of these two allows for advanced time domain analysis in addition to the frequency domain spectrum measurements performed by the spectrum analyzer.
It can also be said to be a measurement instrument that analyzes the modulation quality of complex digitally modulated signals, such as cellular phones, using sophisticated signal analysis processing.
This includes testing RF characteristics of terminals and transmitting machines in digital wireless systems. Specifically, these include carrier frequency, channel bandwidth, channel power, occupied bandwidth, and adjacent channel leakage power ratio. Spectrum analyzers can also measure spurious and harmonics over a wide frequency range from RF to microwave bands, which is a key feature of superheterodyne spectrum analyzers.
The input RF signal is converted to a digital IQ data format, captured, and digitally processed at high speed. Therefore, multifaceted time-based analysis of signals such as modulated waves can be performed.
In addition to spectrum characteristics, the modulation quality of digitally modulated signals that are used in communication systems must be measured to maintain stable communication. In this respect, the signal analyzers can also measure the modulation quality of digitally modulated signals by combining it with various vector analysis applications.
Signal analyzers are a device that captures memory for a certain amount of time with the frequency of the measured signal just converted. Signal analyzers can be broadly classified into three processes to obtain results: digitizing and storing, converting frequency, and converting to spectrum, etc.
First, the measurement signal enters the input section of the signal analyzers and is converted to an intermediate frequency (IF) in the frequency conversion section.
Next, the IF-converted measurement signal is converted to digital data. The digitized time-series waveform data is immediately loaded into the internal memory, but the data itself can be stored separately on a hard disk.
Signal analyzers have the advantage of high-speed processing, but they are also characterized by high repeatability. They are suited for analysis and analysis with high-resolution standards such as millimeter wave (wavelength range from 1 cm to 1 mm) and submillimeter wave (wavelength range from 1 mm to around 0.1 mm), so they are used in research fields.
This section describes the differences between signal analyzers and specram analyzers.
The first major difference is that signal analyzers have functions that allow more advanced modulation waveform analysis than spectrum analyzers. Specifically, signal analyzers can perform very advanced analysis in the time domain measurement and analysis of the horizontal time axis.
The reason for this analysis is the signal analyzer's own unique signal processing method, which, in addition to the spectrum analyzer's superheterodyne method, uses a high-speed A-D converter to convert the signal to a digital signal (DSP), loads the data into memory, and performs a high-speed processing Fourier transform (FFT). This is the unique signal processing method of the signal analyzers itself.
This enables the analysis of digital modulation waveforms such as LTE and 5G, which have complex time response components that are impossible to analyze with conventional spectrum analyzers due to time response limitations.
Signal analyzers were previously called VSAs (Vector Signal Analyzers), partly because they can evaluate and analyze IQ constellations, or EVM (Error Vector Magnitude), which is also called modulation accuracy. However, as digital modulation has become more complex, signal analyzers are now commonly called signal analyzers rather than VSAs.
Spectrum analysis, in which the horizontal axis is frequency, is especially useful for evaluating ACLR (adjacent channel leakage power), which represents signal distortion in digitally modulated waveforms. Time domain analysis, in which the horizontal axis is time, is useful for analyzing PvT (PowerVs Time) waveforms for each slot during 5G modulation.
Other uses include evaluation of modulation accuracy EVM and CCDF (Complementary Cumulative Distribution Function) evaluation analysis, which are familiar measurements in the world of mobile communications.
The internal memory and digital processing power required for analysis varies greatly depending on the supported functions and frequency range, and the price range tends to be wide. The standard price range for the latest modulation-compatible models is in the several million yen range, while older models or those with limited functions may cost several hundred thousand yen.
*Including some distributors, etc.
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