Digital Signal Processing

Digital signals processing refers to a category of electronic devices that represent and process information that are in discrete signal level (digital) formats. Digital signal processing refers to the manipulation of digital signals to change their content and to add error detection and correction capability.

Digital signals typically vary in two levels; on (logic 1) and off (logic 0). A bit is the smallest part of a digital signal, typically called a data bit. A bit typically can assume two levels: either a zero (0) or a one (1). A byte is an agreed-upon group of bits, typically eight. A byte typically represents one alphabetic or special character, two decimal digits, or eight binary bits of information.

When analog signals are converted to digital format, the digital signals represent the original analog waveform. Just like analog signals that may be processed by filters, shaping circuits, combiners and amplifiers, digital signals can be processed to produce similar functions. However, because the signal is in digital form, these functions are performed by software programs that manipulate the data.

Unlike analog signals, digital signals can be recreated to their original form. This process is called signal regeneration. To increase the efficiency of a transmission signal (allow more users per channel), digital signals can be analyzed for redundancy and the digital signal data can be compressed. Digital signals can also be processed in a way that helps overcome the effects signal distortion that can result in the incorrect determination of a digital signal (whether a zero or one had been sent). This is called error detection and error correction processing. When digital signals represent the original analog signal, advanced echo canceling software programs can be used to reduce the effects of echoes that are caused by feedback in the audio and transmission system. Some systems use dedicated digital signal processors (DSPs) to manipulate the incoming digital information via a program (stored instructions) that produce a new digital output. This allows software programs to perform many functions (such as signal filtering) that previously required complex dedicated electronic circuits.

Digitization of an Analog Signal

Analog signals must be converted to digital form for use in a digital wireless system. To convert analog signals to digital form, the analog signal is digitized by using an analog-to-digital (pronounced A to D) converter. The A/D converter periodically senses (samples) the level of the analog signal and creates a binary number or series of digital pulses that represent the level of the signal.

The common conversion process is Pulse Code Modulation (PCM). For most PCM systems, the typical analog sampling rate occurs at 8000 times a second. Each sample produces 8 bits digital that results in a digital data rate (bit stream) of 64 thousand bits per second (kbps).

Figure below shows how an analog signal is converted to a digital signal. This diagram shows that an acoustic (sound) signal is converted to an audio electrical signal (continuously varying signal) by a microphone. This signal is sent through an audio band-pass filter that only allows frequency ranges within the desired audio band (removes unwanted noise and other non-audio frequency components). The audio signal is then sampled every 125 microseconds (8,000 times per second) and converted into 8 digital bits. The digital bits represent the amplitude of the input analog signal.

Signal Digitization

Digital bytes of information are converted to specific voltage levels based on the value (weighting) of the binary bit position. In the binary system, the value of the next sequential bit is 2 times larger. For PCM systems that are used for telephone audio signals, the weighting of bits within a byte of information (8 bits) is different than the binary system. The companding process increases the dynamic range of a digital signal that represents an analog signal; smaller bits are given larger values that than their binary equivalent. This skewing of weighing value give better dynamic range. This companding process increases the dynamic range of a binary signal by assigning different weighted values to each bit of information than is defined by the binary system.

Two common encoding laws are Mu-Law and A-Law encoding. Mu-Law encoding is primarily used in the Americas and A-Law encoding is used in the rest of the world. When different types of encoding systems are used, a converter is used to translate the different coding levels.

Digital Signal Regeneration
To overcome the effects of noise on transmitted signals, digital transmission systems use digital signal regeneration to restore the quality of the signal as it moves through a network. Digital signal regeneration is the process of reception and restoration of a digital pulse or lightwave signal to its original form after its amplitude, waveform, or timing have been degraded by normal factors during transmission. The resultant signal is virtually free of noise or distortion.

Figure below shows the process of digital signal regeneration. This example shows an original digital signal (a) and added noise (b) to produce a combined digital signal with noise (c). The regeneration process detects maximum and minimum expected values (threshold points) and recreates the original digital signal (d).

Digital Signal Regeneration

Data Compression

To increase the amount of information that a transmission system can transfer, digital systems may use data compression. Data compression is a processing technique for encoding information so that fewer data bits of information are required to represent a given amount of data. Compression allows the transmission of more data over a given amount of time and circuit capacity. It also reduces the amount of memory required for data storage.

Digital compression analyzes a digital signal for either redundant information (repeated 1’s or 0’s) or may analyze the information content of the digital signal into component parts (such as speech patterns or video frames). All of this processing allows the data transmission rate to be reduced by sending only the characteristics of the signal rather than the complete digital signal. Some data compression systems can only reduce data rates by a factor of 2:1 (e.g., ADPCM audio compression) while advanced digital audio compression can only reduce data rates by a factor of approximately 200:1 (e.g., MPEG video compression). When used in combination of data compression and decompression, the device is called a COder/DECoder (CoDec).

When a digital signal is compressed for voice communications, it is called a voice coder (Vo-coder) or speech coder. The Vo-coder is a digital signal processing device that analyzes speech signals so that it can produce a lower data rate compressed digital signal. The difference between standard data compression and voice data compression is the analysis of the information source (speech) and elimination of compression process for non-voice signals. Speech coding usually involves the use of data tables (called code books) that represent information parts that can be associated with human sound. Because non-human sounds can be eliminated from the code book, this allows the number of bits can be used to create a compressed digital voice signal to be reduced.

Figure below shows the digital voice compression process. In this example, a digital signal is continuously applied to a digital signal analysis device. The analysis portion of the speech coder extracts the amplitude, pitch, and other key parameters of the signal and then looks up related values in the code book for the portion of sound it has analyzed. Only key parameters and code book values are transmitted. This results in data compression ratios of 4:1 to over 16:1.

Digital Voice Compression

Error Detection and Error Correction
To help reduce the effects of errors on data transmission, error detection, and error protection systems are used in most communication systems. Error detection systems use a process of adding some data bits to the transmitted data signal that are used to help determine if bits were received in error due to distorted transmission. Error correction is made possible by sending bits that have a relationship to the data that is contained in the desired data block or message. These related bits permit a receiver of information to use these extra information bits to detect and/or correct for errors that may have occurred during data transmission.

A common measurement of the performance of a communication system is the amount of bits received in error, called the bit error rate (BER). The BER is the ratio of bits received in error compared to the total number of bits received.

Error detection processing involves the creation of additional bits that are sent with the original data. The additional check bits are created by using a formula calculation on the digital signal prior to sending the data. After the digital signal is received, the formula can be used again to create check bits from the received digital signal. If the check bits match, the original digital signal was received correctly. If the check bits do not match, some (or all) of the digital signal was received in error. This process is called error detection.

Some digital systems use sophisticated mathematical formulas to create the check bits so that the check bits can be used to make corrections (or predictions of the correct bits) to the received digital signal. This process is called error correction.

Figure below shows the basic error detection and correction process. This diagram shows that a sequence of digital bits is supplied to a computing device that produces a check bit sequence. The check bit sequence is sent in addition to the original digital bits. When the check bits are received, the same formula is used to check to see if any of the bits received were in error.

Error Detection and Correction

Echo Cancellation

Echo cancellation is a process of extracting a delayed version of an original transmitted signal (audio echo) from the received signal. Echoes may be created through acoustic feedback where some of the audio signal transferring from a speaker into a microphone.

Echoed signals cause distortion and may be removed by performing via advanced signal analysis and filtering. Figure 3.18 shows an example of the echo cancellation process. This diagram shows how the combining of two signals, the original plus a delayed version of the original produces a complex signal. The echo canceling system analyzes the complex signal and uses the signal analysis to create variations of the likely echo signal. This prediction of echoed signal is subtracted from the complex signal to reproduce the original signal without the echo.

Echo Cancellation

Echoed signals can also occur in signals other than audio signals. When echoes occur on radio channels (the broadband signal), it is usually the result of the same signal that travels on different paths to reach its destination. This is called multipath propagation. Echo canceling can be used to reduce the effects of radio multipath propagation.

Digital Signal Processor (DSP)

A digital signal processor (DSP) is an electronics device or assembly (typically an integrated circuit) that is designed to process signals through the use of embedded microprocessor instructions. The use of DSPs in communication circuits allows manufacturers to quickly and reliably develop advanced communications systems through the use of software programs. The software programs (often called modules) perform advanced signal processing functions that previously complex dedicated electronics circuits. Although manufacturers may develop their own software modules, DSP software modules are often developed by other companies that specialize in specific types of communication technologies. For example, a manufacturer may purchase a software module for echo canceling from one DSP software module developer and a modulator software module from a different DSP software module developer. Because DSPs use these software modules, if new technologies such as speech compression, channel coding, or modulation techniques are developed, the manufacturer only has to change the software programs in the DSP to utilize the new technology.

Figure below shows typical digital signal processor that is used in a digital communication system. This diagram shows that a DSP contains a signal input and output lines, a microprocessor assembly, interrupt lines from assemblies that may require processing, and software program instructions. This diagram shows that this DSP has 3 software programs, digital signal compression, channel coding, and modulation coding. The digital signal compression software analyzes the digital audio signal and compresses the information to a lower data transmission rate. The channel coding adds control signals and error protection bits. The modulation coding formats (shapes) the output signal so it can be directly applied to an RF modulator assembly. This diagram also shows that an optional interface is included to allow updating of the software programs that are stored in the DSP.

Digital Signal Processor (DSP)

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