2.0 Core Concepts: Signals and Noise

A strategic understanding of signal characteristics and the pervasive impact of noise is critical for designing and evaluating any communication system. The interplay between the signal carrying the information and the noise corrupting it dictates the performance, reliability, and ultimate effectiveness of a modulation scheme. Mastering these fundamentals is the first step toward selecting the appropriate technique for a given application.

Signal Classification

Signals are broadly classified based on their fundamental properties. The most important distinctions are between analog and digital signals, and between periodic and aperiodic signals.

• An Analog Signal is a continuous time-varying signal that represents a time-varying quantity. Its value changes continuously over time, mirroring the information it represents.
• A Digital Signal is discrete or non-continuous in nature. It is represented by a sequence of individual, separate values, with the most common form being binary digits (1s and 0s).
• A Periodic Signal is any signal, whether analog or digital, that repeats its pattern over a specific period of time.
• An Aperiodic Signal is a signal that does not repeat its pattern over time.

The Challenge of Noise

In system design, Noise is fundamentally any unwanted energy that corrupts the information-bearing signal. Its stochastic nature makes it the primary limiting factor in system performance, dictating receiver sensitivity thresholds and ultimately constraining the achievable channel capacity. It can enter the system at the channel or the receiver, altering the message and degrading the quality of communication. Noise is typically random and unpredictable, manifesting as the “hiss” in a radio receiver or the “flicker” on a television screen.

The primary effects of noise are significant:

• It limits the operating range of systems by setting a lower boundary on the weakest signal an amplifier can process.
• It affects the sensitivity of receivers, which is the minimum input signal strength necessary to achieve a specified quality of output.

Noise can originate from a variety of sources, which are categorized as either external or internal.

• External Sources: This noise is generated outside the communication system itself and includes:
  • Atmospheric Noise: Caused by irregularities in the atmosphere.
  • Extra-terrestrial Noise: Originating from sources like the sun (solar noise) or space (cosmic noise).
  • Industrial Noise: Generated by machinery and industrial processes.
• Internal Sources: This noise is generated by the electronic components within the receiver during operation. Key examples include:
  • Thermal Noise: Caused by the thermal agitation of electrons in conductors.
  • Shot Noise: Arising from the random movement of electrons and holes in semiconductor devices.
  • Transit-time Noise: Occurs during the transition of charge carriers.

Quantifying Performance: Signal-to-Noise Ratio (SNR)

To measure the quality of a received signal and the performance of a communication device, engineers use standardized metrics.

• Signal-to-Noise Ratio (SNR) is defined as the ratio of the signal power to the noise power. A higher SNR value indicates a higher-quality signal with less corruption from noise.
• Figure of Merit (F) describes the performance of a device by quantifying how it affects the signal quality. It is defined as the ratio of the output SNR to the input SNR.

With these fundamental concepts of signals and noise established, we can now explore the specific modulation techniques developed to encode information onto signals, beginning with the foundational methods of continuous-wave analog modulation.