Minimize Noise Figure Uncertainties

Technical Overviews

Select From Three Flexible Solutions That Cover a Wide Range of Needs

Noise figure is often the key to characterizing a receiver and its ability to detect weak incoming signals in the presence of self-generated noise. The process of reducing noise figure begins with a solid understanding of the uncertainties in your components, subsystems and test setups. Quantifying those unknowns depends on flexible tools that provide accurate, reliable results.

Keysight’s noise figure solution set – instruments, applications and accessories – helps you optimize test setups and identify unwanted sources of noise. We’ve been providing noise-figure test solutions for more than 50 years, beginning with basic noise meters and evolving into modern solutions based on spectrum, network, and noise-figure analyzers.

This technical overview begins with a brief noise figure primer on pages 3 through 11. Pages 12 through 19 present our current product lineup and will help you find the best solution for your application – whether you’re designing for good, better or best performance in your device.

A list of related resources is included on page 20. Our series of seven application notes can help you develop a deeper understanding of noise figure and its inherent challenges.

Noise Figure Overview

Noise figure is one of the key parameters used to characterize the ability of receivers and their lower-level components to process weak signals in the presence of thermal noise. For example, when measuring low-noise amplifiers (LNAs), noise figure describes the signal-to-noise degradation that occurs due to the internally-generated noise of the active devices within an LNA.

Accurate measurements of noise figure are crucial in product design and development. Highly accurate measurements allow for better agreement between simulations and measurements, and may help uncover noise contributors that were not considered in the simulation. Before selecting the most appropriate instrument for your application, it is important to understand two key topics: how noise figure measurements are made and the uncertainties inherent in those measurements. Noise figure measurement uncertainty depends not only on the test equipment, but is also a function of the characteristics of the device under test (DUT)—for example, S-parameters and noise parameters.

There are two main methods in use today to measure noise figure. The most prevalent method is called the Y-factor or hot/cold-source technique. It uses a noise source placed at the input of the DUT, providing two levels of input noise. This method yields noise figure and scalar gain of the DUT, and is used with both spectrum and noise figure analyzer solutions. The Y-factor technique is easy to use, and it provides good measurement accuracy, especially when the noise source has a good source match and can be connected directly to the DUT.

The other method used is called the cold-source or direct-noise method. Instead of using a noise source at the DUT’s input, only a known termination (usually 50 Ω) is needed. However, the cold-source method requires an independent measurement of the DUT’s gain. This method works well with vector network analyzers, because vector error correction can be used to produce very accurate gain (S21) measurements. When using the PNA-X signal analyzer, the combination of vector error correction and the PNA-X’s unique source-correction method provides the highest noise figure measurement accuracy in the industry. The other advantage of the cold-source method is that both S-parameter and noise figure measurements can be made with a single connection to the DUT. During system calibration, a noise source is required.

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