Miss the first segment? Here it is: Part I
Sources of Timing Jitter, Amplitude Noise, and Signal Integrity
Jitter and noise are deviations from an ideal signal. Jitter and noise can have many causes. The physical nature of various noise and jitter sources for a communication system can be classified into two major classes: intrinsic and nonintrinsic. The intrinsic type has to do with the physical properties of electrons and "holes" in electrical or semiconductor devices. The nonintrinsic type are design-related and may be eliminated. These types are discussed in detail in the following sections.
Intrinsic Noise and Jitter
Intrinsic noise is fundamentally caused by the randomness and fluctuation of electrons and "holes" existing in all the electronic/optical/semiconductor circuits/devices. Intrinsic noise can be minimized but cannot be completely removed from devices or systems. Therefore, this kind of noise puts a fundamental limit on device and system performance and dynamic range. Typical intrinsic noises in electrical-optical devices include thermal noise, shot noise, and flick noise.
Thermal Noise
Thermal noise is caused by the random motion of charge carriers under the thermal equilibrium condition. The kinetic energy of those randomly fluctuating charge carriers is proportional to their temperature, as well as to their mean-square velocity. The power spectrum density (PSD) of the thermal noise is white and apparently proportional to its temperature. Thermal noise places a fundamental limit on the signal-to-noise ratio (SNR) performance because it exists in all electric/optical/semiconductor devices having a nonzero absolute temperature. Johnson4 first discovered that the noise in a conductor depends on temperature and resistor under the thermal equilibrium condition. Nyquist5 shortly after developed a theory to explain Johnson's discovery based on the second law of thermodynamics. Because of their pioneering contributions, thermal noise is sometimes called Johnson noise or Nyquist noise.
Shot Noise
Shot noise is produced by individual quantized carrier flow (current) in a potential barrier with a random generation time or spatial distribution. In other words, shot noise is basically due to random flow fluctuation. Schottky6 first studied shot noise in vacuum tube diodes and later it was also found in P-N junction in a semiconductor transistor. Shot noise is directly proportional to DC bias current, as well as the charge of the carrier. Shot noise is typically larger than thermal noise in semiconductor devices.
Flick Noise
Flick noise is a phenomenon that is found to have a noise power spectrum inversely proportional to the frequency over a wide range of frequencies. Johnson was the first to observe flick noise in an electronic system.7 Flick noise can be found in all active devices, and some passive devices such as carbon resistors.
DC current is necessary to produce flick noise. No universally accepted theory explains the cause and mechanism of flick noise, unlike the causes of thermal and shot noise. As a result, the quantitative study of flick noise is mostly empirical. It has been found that the PSD of flick noise is proportional to 1/f α, where α is around 1. Because of this reason, flick noise is also called 1/f noise. One common interpretation of flick noise is the "trap and release" theory. It is believed that the flow of carriers due to the DC current can be trapped due to contamination and defects in devices. However, the "trap and release" process is random, giving rise to the flick noise that is most significant at low frequencies.8
Translation of Noise to Timing Jitter
Noise is typically described using physical quantities or parameters. In communication, computer, and electronic systems, those quantities may include voltage, current, or power. We use the generic term of amplitude to represent those physical quantities. Assuming that the amplitude noise ΔA(t) is superimposed on the amplitude waveform of A0(t) so that the total waveform has the following form:
the corresponding timing jitter can be estimated through the linear small-signal perturbation theory as the following:
where k = (dA0(t)/dt) is the slope or slew rate of the waveform.
This linear amplitude noise to timing jitter conversion is shown in Figure 5.
Figure 5. Amplitude noise to timing jitter conversion through the linear perturbation model.
You can see that for amplitude noise ΔA, the corresponding timing jitter decreases as the slope increases, and vice versa. To maintain a smaller timing jitter conversion, a large slope or fast slew rate is favored. In the context of a digital signal, this implies a small rise/fall time.
