Definition Of Analog Signals

An electromagnetic or electrical current known as a signal is used to transfer data from one system or network to another. Although it can sometimes take other forms, such as current, a signal in electronics is often a time-varying voltage that is also an electromagnetic wave carrying information. Analog and digital signals are the two primary forms of signals used in electronics.

An analog signal has a restricted number of possible values within a continuous range that is time-varying and typically limited to a certain range (for example, +12V to -12V). An analog signal, such as electricity flowing over a wire, exploits a specific property of the medium to transmit the signal's information. To represent the information in an electrical signal, the signal's voltage, current, or frequency may be changed. In reaction to changes in light, sound, temperature, position, pressure, or other physical phenomena, analog signals are frequently calculated responses.

In many engineering systems and applications, the representation of physical values using analog signals is fundamental. The word "analog" comes from the word "analogy," so an analog signal is an electrical representation of the original physical quantity.

Figure 1: Analog signal

Continuous-Time And Continuous-Value Signals

The continuous nature of both the time and value of analog signals makes them distinctive. Let's examine each of these two qualities in more detail:

Continuous-Time: Analog signals are present at all times, see Figure 1. For instance, as the current varies, the voltage across a resistor changes gradually rather than abruptly. Analog signals can correctly represent time-varying quantities due to their continuous character.

Continuous-Value: Within a certain range, analog signals can have any value. For instance, rather than being limited to a range of acceptable levels, the amplitude of an electrical signal that represents sound can take on any value between the power supply's limits. Given that the values are not quantized, this implies an unlimited resolution.

Examples: Sound Waves, Analog Television

Sound Waves: Sound waves are one of the analog signals that are easiest to understand. The continuous variation in the air pressure produces sound waves. The voltage or current produced when these sound waves are converted to electrical signals via a microphone is an analog representation of the sound, with amplitude and time both continually varying.

Analog Television: Both the audio and the visual signals are broadcast as continuous analog transmissions in typical analog television. Continuous variations in the carrier wave's amplitude or frequency serve as a representation of the video's alterations in brightness and color information.

Definition Of Digital Signals

Any signal that encodes data as a series of discrete numbers is referred to as a digital signal. A digital signal can only have one value at a time, chosen from a limited range of possible values. The physical quantity that corresponds to the information in digital signals can be any of the following:

• Variable electric current or voltage
• Acoustic pressure
• Phase or polarization of an electromagnetic field
• The magnetization of a magnetic storage media

All digital electronics, including computing hardware and data transfer devices, employ digital signals. Digital signals can have a limited range of discrete values when plotted on a voltage vs. time graph (see Figure 2).

Understanding the fundamental characteristics of digital signals, which serve as the digital equivalent to the analog signals covered in the previous section, is crucial as we delve deeper into the complexities of analog-to-digital conversion.

Figure 2: Digital signal

Discrete-Time And Discrete-Value Signals

Discrete-Time: Digital signals are defined at precise points in time as opposed to analog signals, which are continuous in time. Having discrete time means that anything is defined at discrete intervals. The term "sample" often refers to each event where the signal contains a value.

Discrete-Value: Digital signals have discrete values in addition to discrete time. Digital signals can only take on a limited set of values, in contrast to analog signals, which can take any value within a certain range. These values are typically represented in digital systems as binary numbers, such as 0s and 1s.

Examples: LTE Transmission, Digital Audio

LTE Transmission: A standard for wireless broadband communication for mobile devices and data terminals is called Long-Term Evolution (LTE). Digital signals are utilized in LTE transmission to transmit binary data wirelessly. In order to represent binary data, these digital signals change a carrier wave's amplitude, frequency, or phase. For instance, the amplitude and phase of the carrier wave are changed to represent binary data in Quadrature Amplitude Modulation (QAM), which is used in LTE.

Digital Audio: A great illustration of how digital signals are used is in digital audio. Digitization is the procedure used to transform analog audio signals into digital ones, including those produced by microphones. This entails discretely sampling the audio signal and quantizing every sample to a discrete range of values. Due to its noise resistance and simplicity of manipulation, digital audio has established itself as the industry standard in contemporary recording and playback systems.

Digital signals do not directly represent the physical quantities they represent, in contrast to analog signals. Instead, they are an approximation created by quantizing the quantity to a set of discrete values and sampling it at periodic intervals. However, digital signals are better suited for modern computing applications because they are more noise-resistant and can be handled and stored more effectively. The interaction between analog and digital signals and the significance of their conversion will be further explained as we go through this chapter.

Note: Since actual signals cannot have any discontinuities, there are no signals that are truly digital. In reality, there are only analog signals. Digital signals are those that convey digital data, like FSK wireless signals, and analog signals are those that carry analog data, like FM radio transmissions.

Advantages And Disadvantages Of Analog Systems

A sizable portion of contemporary human history has been devoted to the usage of analog systems, which are based on continuous-time and continuous-value signals. Analog systems play a significant part in many applications, despite the fact that digital systems are now more common. The goal of this section is to clarify the benefits and drawbacks of analog systems in order to provide a better understanding of why switching to digital systems is frequently beneficial.

Advantages Of Analog Systems

Natural Representation: Due to the continuous nature of many natural occurrences, analog signals are frequently a more accurate representation of physical values. For instance, sound waves may be captured and reproduced very accurately by analog audio systems because they are fundamentally analog.

No Quantization Noise: Quantization noise, which can be a problem in digital systems, is not present in analog signals since they are not quantized to discrete values.

Lower Latency: Due to the lack of signal processing or conversion processes, which can create delays, analog systems frequently display lower latency than digital systems.

Disadvantages Of Analog Systems

Susceptibility to Noise: Signals are sensitive to interference and noise. This is especially problematic when transmitting analog signals that have been amplified because doing so enhances both the noise and the signal.

Limited Signal Processing: Compared to digital systems, the implementation of complex signal processing in analog systems is frequently more difficult and expensive.

Difficulty in Storage and Reproduction: Analog signals are challenging to store for extended periods of time without deterioration. Additionally, quality is lost every time an analog signal is copied or reproduced.

Lack of Flexibility and Scalability: It might be challenging to adapt analog systems for new activities because they are frequently created for a narrow range of applications. Additionally, scaling up an analog system—for example, by expanding the number of communication channels—can be time-consuming and expensive.

Advantages And Disadvantages Of Digital Systems

Digital systems have taken over as the main technology in a variety of applications and sectors in the modern period. Signals used by digital systems have discrete time and amplitude values. Despite their widespread acceptance, it is crucial to be aware of both their advantages and disadvantages.

Advantages Of Digital Systems

Resistance to Noise: Compared to analog systems, digital systems are significantly more resistant to noise. A digital signal can be perfectly recovered because it is made up of discrete values (often 0s and 1s), so long as the noise doesn't modify the values significantly. Unlike analog signals, which are boosted during transmission, digital signals are regenerated. Regeneration prevents noise from spreading and enables the recovery of the digital signal. Additionally, error correction codes provide error recovery while error detection codes enable the discovery of errors that occurred during transmission.

Signal Processing and Analysis: Modern approaches for signal processing and analysis are applicable to digital systems. This makes it possible to use filters, Fourier transforms, and different algorithms to improve or analyze the signal, frequently in real-time.

Easy Storage and Replication: Digital data may be compactly stored and duplicated without losing any quality. This has proven especially ground-breaking for audio and visual media.

Flexibility and Scalability: Without modifying the hardware, digital systems are easily reprogrammable and adaptable to many applications. They are hence scalable and adaptable by nature.

Integration with Digital Computing Systems: Modern computers are naturally compatible with digital signals, which makes integration and the creation of complicated applications easier.

Disadvantages Of Digital Systems

Quantization Noise and Error: The process of converting a continuous analog signal to a digital signal involves quantization noise and inaccuracy since digital systems only support discrete signal levels.

Potential for Latency: Digital systems can create latency, particularly when converting signals from analog to digital and in situations involving sophisticated signal processing.

Power Consumption: Digital systems can use more power than analog ones, depending on the application, especially when processing high-speed data.

Susceptibility to Magnetic Fields: Strong magnetic fields have the potential to destroy digital data that is stored on magnetic media, such as hard drives.

Hybrid Systems (Analog and Digital Combined)

It is not always easy to distinguish between analog and digital systems, and in reality, engineers frequently use hybrid systems that combine analog and digital parts. The framework, capabilities, and applicability of hybrid systems are clarified in this subsection.

Systems that are hybrids combine analog and digital components. An analog electrical signal that represents sound waves, for instance, can be transformed into a digital format for processing or storage, and then back into an analog signal for playback. Both digital-to-analog converters (DACs) and analog-to-digital converters (ADCs) are used in this procedure.

Utilizing the benefits of both technologies, analog and digital components integrated into a system can do the following:

Improved Noise Immunity: Early in the processing chain, an analog signal can be converted to a digital format, allowing the system to carry out future processing in a noise-resistant way.

Advanced Processing Capabilities: The hybrid system's digital components are capable of running sophisticated algorithms for signal amplification, filtering, and analysis.

Precise Control and Calibration: With pure analog components, it may be difficult or impossible to accomplish fine control and calibration, but hybrid systems can do so by using digital processing.

Flexible Implementation: Hybrid systems can be quickly modified and reconfigured through software updates without requiring changes to the hardware thanks to the use of microcontrollers and digital signal processors (DSPs).

Examples Of Hybrid Systems

Digital Oscilloscopes: Signal processing in the digital domain is done by digital oscilloscopes. The oscilloscope's input converts analog signals to digital representation. The signal is then subjected to sophisticated digital processing algorithms for analysis, after which it is frequently shown on the screen in analog form.

Software Defined Radios (SDRs): These gadgets are capable of receiving analog radio wave signals, digitizing them, and then processing them to decode various modulation types. Additionally, they are capable of taking a digital signal, converting it to analog, modulating it onto a carrier wave, and transmitting it. Analog and digital components are combined in SDRs. Digital hardware is used to implement wireless radio functionalities that were previously implemented in analog hardware (such as filters, detectors, etc.). Hardware does not constrain the features and capability of SDRs. Instead, a combination of hardware and software governs the features. New versions of software offer enhanced performance and additional features.

Digital Audio Workstations (DAWs): For editing, mixing, and effect processing in DAWs, analog audio signals are captured using a microphone and transformed to digital format. The signal can be converted back to analog for playback once all editing is finished.

Communication Systems: Hybrid technologies are used in many contemporary communication systems. The communication medium is interfaced via analog front-ends, and modulation and encoding are handled digitally.