Technical Insights > RF + Microwave

The Four Ws of Noise Figure

2019-10-23  |  8 min read 

Modern receiving systems must often process very weak signals, but the noise added by system components tends to obscure those very weak signals.

Sensitivity, bit error ratio (BER), and most importantly, our topic for today, noise figure are system parameters that characterize the ability for a receiving system to process low-level signals.

In this blog, we’ll discuss the WHAT, WHY, WHEN and WHERE of characterizing your system’s noise figure (NF) to process low-level signals and improve your product design.

 

What

Noise figure, also known as noise factor, can be defined as the degradation of (or decrease in) the signal-to-noise ratio (SNR) as a signal passes through a system network.

Noise figure is unique in that it is suitable not only for characterizing individual components such as a low-noise amplifier, downcoverter, and IF filters, but also the whole system itself. In our case the “network” is a spectrum or signal analyzer (SA).

Basically, a lower figure value means the network adds very little noise (good) and a higher noise figure value means it adds a lot of noise (bad). The concept fits only those networks that process signals and have at least one input and one output port.

Figure 1 provides the fundamental expression for noise figure.

 

Figure 1. Noise figure is the ratio of the respective signal-to-noise power ratios at the input and output when the input source temperature is 290 °K.

 

Additionally, noise figure is usually expressed in decibels:

             NF (in dB) = 10 log (F) = 10 log (No) – 10 log (Ni)

 

Why and When

Noise figure is a key system parameter when handling small signals, and it lets us make comparisons by quantifying the added noise. Knowing the noise figure value, we can calculate a system’s sensitivity from its bandwidth.

It’s important to remember that a system’s noise figure is separate and distinct from its gain. Once noise is added to the signal, subsequent gain stages amplify signal and noise by the same amount, and this does not change the SNR.

Figure 2.a below shows an input to an amplifier, and the peak is 40 dB above the noise floor; Figure 2.b shows the resulting output signal. Gain has boosted the signal and noise levels by 20 dB and added its own noise. As a result, the peak of the output signal is now only 30 dB above the noise floor. Because degradation in the SNR is 10 dB, the amplifier has a 10 dB noise figure.

 

Relative signal and noise levels compared at the input and output of an amplifier. The noise level increases more than the signal level, due to the noise added by the amplifier.

 

Figure 2. Examples of a signal at an amplifier’s input (a) and (b) its output. Note that the noise level rises more than the signal level due to noise added by the amplifier circuits. This change in signal and noise is the amplifier noise figure.

 

By controlling the noise figure and gain of system components, an RF designer directly controls the noise figure of the overall system and once you’ve characterized what your noise figure value is, system sensitivity can be easily estimated from the system bandwidth.

 

Where (& How)

The open question: Where are the system noise sources that affect noise figure? Most noise consists of spontaneous fluctuations caused by ordinary phenomena in the electrical equipment, and this noise is generally flat. We perform measurements on this noise to characterize noise figure. These noise sources fit into two main categories: thermal noise and shot noise.

One more note: It’s important to consider that some of the power measured in a noise figure measurement may be some type of interference rather than noise. Therefore, it’s critical to be alert for and guard against this by performing measurements in shielded rooms to ensure we’re seeing only the spontaneous noise we want to measure.

Noise figure measurements can be made using a signal analyzer, noise source, and dedicated noise figure measurement application.

 

 

Figure 3. A high-level view of the 2-steps required in making noise figure measurements on a DUT using a signal analyzer, noise source, and dedicated noise figure application.

 

The most popular common method for measuring noise figure is the Y-Factor method which entails 2-steps: calibration and the DUT’s noise figure measurement. The signal analyzer is first calibrated by connecting a noise source to the front-end of the signal analyzer. In the 2nd step, the DUT is then connected to the front-end of the signal analyzer and the noise source is connected at the input of the DUT – the signal analyzer’s noise figure measurement application can then characterize the noise figure of the DUT.

 

Wrapping Up

To review, noise figure is a measure of the degradation of the signal-to-noise ratio (SNR) as a signal passes through a system or device. You can make noise figure measurements on complete systems or components. The noise figure tells us the relative amount of noise being added to a signal as it travels through the system or device. A low noise figure value indicates better performance of your DUT.

Noise figure is a quick and easy measurement for characterizing the degradation of your device’s signal-to-noise ratio (SNR) as a signal passes through a system or device – telling you the relative amount of noise being added to our signal. And, as your considering your design, remember that noise figure is one method you can use to improve the performance of your device.

If you’d like to learn more about characterizing noise figure and improving your product designs, check out Keysight application notes titled Three Hints for Better Noise Figure Measurements and Noise and Noise Figure: Improving and Simplifying Measurements which include great explanations and how-to techniques. You’ll find both in our growing collection of spectrum analysis technical literature on our spectrum analysis content page.

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