Noise margins

In this realistic world, nothing is ideal. A signal travelling along a wire/cable/transmission line is susceptible to noise from the surroundings. Also, there is degradation in signal due to parasitic elements involved in the line. Moreover, the output signal produced by the transmitter itself only does resemble the ideal signal thereby worsening the scenario. There are repeaters/buffers along the line to minimize the impact of noise. But there is a limit up to which degradation is allowed beyond which the receiver is unable to sense the correct value of the signal. This degradation is measured in terms of noise margins. One can find the topic discussed in all the textbooks related to digital logic and system design might it be CMOS, TTL or any other logic family.

Let us illustrate the concept of noise margins with the help of an example. Let us assume that a signal has to travel from a transmitter to a receiver through an inter-connect element (or, commonly called as a net) which will only degrade the signal, since there is no active element in-between transmitter and receiver. The output signal produced by Transmitter (Tx) will deviate from ideal voltage levels as is shown in figures 1 and 2 for logic level ‘1’. In addition, there will be signal degradation by inter-connect element as well as noise induced from the surroundings. As a result, the band of voltages that can be present at the receiver input for logic ‘1’ will further widen. Now, there are two cases:

1. If the band voltages recognized as logic ‘1’ by the receiver is super-set of the band of voltages that can exist at the receiver input as shown in figure 1, receiver will recognize the transmitted logic ‘1’ for all the cases. This is the desired scenario as no logic ‘1’ transmitted will be missed by the receiver. This scenario is depicted in figure 1, wherein the noise induced by surroundings is such that the range of voltages present at the receiver does not violate the band of voltages recognized as voltage '1' by the receiver. So, it will be recognized correctly as logic '1' by the receiver.

Figure 1: Figure showing the noise induced is less than noise margin

2)  If the band of values recognized as logic ‘1’ by the receiver is a sub-set of the band of voltages that can exist at the receiver input as shown in figure 2, there will be some cases that will not be recognized as logic ‘1’, but are intended to be recognized. So, there will be a loss of information/incorrect transmission of information possible in such cases. This scenario is depicted in figure 2, wherein the noise induced by surroundings makes the band of voltage at the receiver's input larger than that can be decoded correctly as logic '1' by the receiver. So, there is no guarantee that the signal will be perceived as logic '1' by the receiver.

Figure 2: Figure showing the noise induced is greater than noise margin

Let us now label each of these regions to make the discussion more meaningful. The lowest voltage that will be produced as logic ‘1’ by the transmitter is termed as VOH and, let us say, highest is VDD. (We are here considered about lower level only). So, the range of voltages produced by the transmitter is (VDD – VOH).  And let the receiver accept voltages higher than VIH. So the range of voltages accepted by the receiver will be (VDD – VIH). So, the maximum degradation that can happen over the communication channel is (VOH – VIH) which is nothing but the noise margin. If the degradation is less than this figure, the logic ‘1’ will be recognized correctly by the receiver; otherwise it won’t. So, the noise margin equation can be given as below for logic '1':

Noise margin for logic '1' (NM) = VOH – VIH

Where

VOH = Lowest level of voltage that can be produced as logic '1' by the transmitter

VIH = Lowest level of voltage that can be recognized as logic '1' by the receiver

Similarly, for logic ‘0’, the range of outputs that can be produced by the transmitter is (0 - VOL) and the range of input voltages that can be detected by the receiver is (0 – VIL), thereby providing the noise margin as:

Noise margin (NM) = VIL – VOL

Where

VIL = Highest level of voltage that can be recognized as logic ‘0’ by the receiver.

VIH = Highest level of voltage that is produced as logic ‘0’ by the transmitter.

Figure 3 shows all these levels for the example we had taken earlier to demonstrate the concept of noise margins.

Figure 3: Noise margin

From out preceding discussion, if the degradation over the communication channel is more than noise margin, it will not be detected correctly by the receiver. So, it is imperative for the designer to design accordingly.

Definition of noise margin: Thus, we can conclude this post by defining noise margin as below:

"Noise margin is the difference between the worst signal voltage produced by the transmitter and the worst signal that can be detected by receiver."

Also read: 

• Latchup in CMOS devices
• Metal ECO - the process
• Regions of operation of MOS transistors
• False paths - what are they
• Latency and throughput - the two measures of system performance

Analog to Digital Converter

In real world, all signals like light, sound etc, are analog signals. These signals have to be converted into digital form so that they can be manipulated by digital equipment. Device used to convert analog signal into digital signal is called Analog to Digital Converter (ADC). An example of an analog to digital converter is a Scanner – It takes a picture (analog) as input and convert into digital picture. ADC is an electrical circuit that converts continuous time and continuous amplitude signal into discrete time and discrete amplitude signal.

Let us first discuss basic concept of analog to digital conversion. The process of digitizing the domain(time) is called sampling and the process of digitizing range(voltage/current) is called quantization.

Sampling : An ADC circuit samples analog signal from time to time. Then, each sample is converted into a number based on its voltage level. The frequency at which sampling occurs is called sampling rate or sampling frequency. e.g if sampling frequency is 22000 Hz, it means, in one second 22000 input points will be sampled and distance between two adjacent time points is 1/22000 seconds. Higher the sampling frequency, more perfect will be the analog signal produced by DAC (when it is required to reconstruct the analog signal from digital samples). But more memory will be needed to store these samples. So there is always a trade off between memory required to store samples and accuracy of signal. But to reproduce analog signal from digital samples, there should be some minimum number of samples. And

According to Nyquist sampling theorem, sampling rate must be at least twice the highest frequency component to avoid aliasing.

                                      Fs = 2Fmax

Quantization: Quantization is the process of converting continuous value signal into discrete value signal so that signal takes only finite set of values. Unlike sampling (where we saw that under some conditions, it is possible to reconstruct the signal), quantization results in some loss of information called quantization error. One of basic choice in quantization is the number of discrete quantization levels to use. Fundamental tradeoff in this choice is the resulting signal quality vs data(bits) needed to represent each sample. With L levels, number of bits required to represent each level,

                     
              N = logL/log2.

Analog to Digital Converter with 32 levels(5 bits)