ECE-9-fundamentals-of-Data-Communications
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Title: ECE 9: CODING and Modulation Technique
Author: Jonnel K. Pabico
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Binary Sequence: Long string of binary numbers presented (101010110...)
Concepts Covered: Binary sequences used for error control in communications.
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Bit Error Rate (BER) and Probability of Error
Definit ion: Probability of error, often referred to as Bit Error Rate (BER).
Characterization: Represented as a bit error ratio, calculated as the ratio of number of bit errors to total bits transferred.
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Importance of BER
Key Parameter: Fundamental in evaluating the number of bits received in data stream during communication.
Causes of Errors: Errors can occur due to noise, interference, distortion, and bit synchronization.
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BER Parameters
Variables:
ϵ = bit error rate
erfc = Gaussian error function
Eb = energy per bit
No = noise power spectral density.
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Repeat of BER Parameters
Reiteration of the parameters and their significance in evaluating bit error rates.
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Packet Error Probability (PER)
Definition: PER is the expected value of packet error ratio, representing errors in data packets.
Calculation: Packet error ratio is determined by the ratio of incorrectly received packets to total packets received.
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Packet Error Probability Formula
Formula:
PE = 1 - (1 - Pe)^N
Variables:
N = length of data packet
PE = probability of packet error
Pe = bit error probability, which is the average value of BER.
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Visual Aids
Antenna Layout: Images presented of antennas in different sectors, indicating a communication scenario.
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Probability of Error Continuation
Further exploration or depiction regarding the probability of error.
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Data Communications Definition
Concept: Data refers to information stored digitally.
Terminology: "Data" is the plural; a single unit is termed "datum.”
Process Defined: Data communications is the transfer of digital information, primarily in binary form.
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Purpose of Data Communications
Objective: Main goal is the transfer of digital information from one point to another, summarized as transmission, reception, and processing of digital information.
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Fundamental Concepts of Data Communications
Includes:
Data communications code
Error control (error detection and correction)
Character synchronization
Multiplexing
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Data Communications Codes
Examples:
Baudot Code
ASCII Code
EBCDIC Codes
Bar Codes
QR Codes
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Baudot Code
Classification: First fixed-length character code designed for machines.
Development: Invented by Thomas Murray in 1875, named after Emile Baudot.
Characteristics: Five-bit code primarily used in low-speed teletype equipment, also known as fixed-length source code.
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More on Baudot Code
Application: Mainly used in teletype and radio teletype systems.
Standardization: Latest version recognized by CCITT as International Alphabet No. 2.
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Visual Reference
Figure A: Unspecified content or visual related to the topic.
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ASCII (American Standard Code for Information Interchange)
Standardization Year: Adopted in 1963 in the USA.
Versions: Progressed through 1965, 1967, and 1977, with 1977 being recommended by ITU.
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ASCII Technical Details
Bits: Utilizes 7 bits; b7 serves as a parity bit.
Order Symbolization: b0 - b6 denote order rather than value.
Transmission Order: The lowest bit is transmitted first.
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Binary Code Representation
Structure: Shows binary code mapping across bits and characters alongside hexadecimal equivalents.
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More on Binary Code
Continuing detailing on character binary code with hex representations.
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Continuing Binary Code Discussion
Further details on binary code and its applications in computing and data representation.
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EBCDIC Overview
Definition: Extended Binary Coded Decimal Interchange Code.
Bits: Uses 8 bits, primarily in IBM mainframe computers.
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EBCDIC Characteristics
Special Codes: Unspecific codes can be assigned to functions; chosen name highlights its binary compatibility.
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Bar Codes Introduction
Definition: Black-and-white striped identifiers on products.
Usage Start: Developed in early 1970s but became widespread in the mid-1980s.
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Bar Codes Functionality
Data Encoding: Widths of bars and spaces denote binary values; can store various data (cost, inventory, etc.).
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Bar Code Formats
Various formats are based on stored data types and system requirements.
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Discrete Bar Code Classification
Definition: Discrete bar codes have spacing between characters.
Example: Code 39 is a notable discrete format.
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Code 39 Specifications
Characteristics: Developed in 1975, supports 43 characters (numbers, letters, symbols).
Applicability: Widely used in industrial fields, particularly automotive and electronics.
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Structure of Code 39
Unique Pattern: Standard based on bars and spaces to represent characters.
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Character Binary Code Representation
Detailed binary representation for characters, outlining their binary codes.
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Continuation of Character Binary Codes
Content: Example of expanded character binary representations.
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Continuous Bar Code Classification
Definition: Continuous bar codes do not include spacings between characters; example is UPC.
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Parts of UPC Bar Codes
Components: Guard bars, manufacturer code, item number, and check digit.
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Bar Code Reading Steps
Foundation: Description of lines, spaces, and their significance in barcode reading.
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Bar Code Beginning and End
Discusses structural patterns with specific code starts, focusing on identifiers.
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Code Representation for Numbers
Details: Each number is expressed through specific line patterns.
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Example Bar Code
Illustration: Specific example of a barcode for a given product.
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2D Bar Code Characteristics
Definition: 2D bar codes store data in two dimensions.
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QR Codes Overview
Examined: As a type of 2D barcode with larger capacity than standard bar codes.
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Error Control Introduction
Context: Need for error management in varying communication circuit lengths.
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Error Types in Data Communication
Definition of single-bit, multiple-bit, and burst errors in transmission.
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Error Performance Measurement
Differentiation between probability of error (theoretical) vs. bit error rate (actual).
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Evaluating System Performance
BER Insight: Recaps BER measurements in comparison to probability of errors.
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Error Detection Defined
Purpose: Monitoring transmission to indicate errors, without identifying specifics.
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Redundancy Checking Explained
Concept: Utilization of redundancy in error detection, along with types of checks employed.
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VRC and LRC Example
Practical example given using ASCII-encoded data, applying parity checks.
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Checksum Basics
Describes checksum's role in redundancy error checking, detailing its calculations.
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Checksum Validation
Compares checksums to detect transmission errors effectively.
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Cyclic Redundancy Checking (CRC) Introduction
Prominence: Most reliable method for error detection in data streams.
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CRC Technical Formulae
Mathematical expressions introducing the concept of cyclic block codes.
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Mathematical Representation of CRC
Outlines data polynomial and its relation to the generator polynomial in CRC.
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Detailed CRC Processes and Examples
Steps: Methodology showing binary division for CRC calculations.
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Further BCS Determination Steps
Continues demonstrating CRC application with detailed calculations and representations.
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Error Correction Mechanisms
Differentiates between lost and damaged messages within data communication.
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Redundancy in Error Correction
Highlights the importance of recognizing lost vs. damaged messages for effective communication.
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Character Synchronization Definition
Meaning: Synchronization in data involves identifying character boundaries in messages.
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Methods for Synchronization
Describes the two common approaches for achieving synchronization in data communications: asynchronous and synchronous.
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Asynchronous Serial Data
Definition: Transmission format defined by framing characters with specific start and stop bits.
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Characteristics of Asynchronous Data Format
Details: Describes frame structure including start, idle, stop, and parity bits.
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Data Format Analysis Example
Breakdown of a bit sequence with an emphasis on identifying characters and their components.
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Asynchronous Characters Clarification
Illustration: Analysis of how asynchronous characters are structured and transmitted.
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Synchronous Serial Data Identification
Analysis: Identifying each character in a given ASCII-encoded sequence under synchronous conditions.