EKT 431: Digital Communications CHAPTER 1 Signals and Spectra School of Computer and Communication Engineering, Amir Razif Arief b. Jamil Abdullah EKT 431: Digital Communications

Coursework Contribution Lab: 30% Project 1 Project 2 Project 3 Assignments, Attendance & Quizzes: 10% Assignments; minimum 4. Attendance; subjected to university regulation. Quizzes; minimum 8. Test: 10 % Two tests. Exam: 50% Lecturer: Amir Razif Arief b. Jamil Abdullah Office: Grnd Floor, House #8A, KKF, Kuala Perlis E-mail: amirrazif@unimap.edu.my Office tel#: 04-9854251 @ 019 4659277 HP#: Upon Request Teaching Engineer: Mohd Fairuz b. Mohd Fadzil Office: House #1, KKF, Kuala Perlis 2006-01-24 Lecture 1

Practical information Course material Course text book: “Digital Communications: Fundamentals and Applications” by Bernard Sklar,Prentice Hall, 2005, ISBN: 0-13-084788-7 Reference Books; “Introduction to Digital Communications”, by Pursley M.B, IE Pearson Hall 2005 “Information Transmission, Modulation and Noise”, by M.Schwartz, Mc Graw Hill 2005 “Digital Communications”, by Proakis, John G. International Eddition, Mc GrawHill 3rd Ed. 1995 2006-01-24 Lecture 1

Outcome To understand and use various terminologies in Digital Communications. To be able to explain the differences between analog and digital communications. To describe the basic building blocks of a digital communication system and the performance objectives for good communication. To analyze the signals transmission via channel. To study the base band data transmission, digital modulation and spread spectrum communications. To explore the basic principles of telephony system.

Today, we are going to talk about: What are the features of a digital communication system? Why “digital” instead of “analog”? What do we need to know before taking off toward designing a DCS? Classification of signals Random processes Autocorrelation Power and energy spectral densities Noise in communication systems Signal transmission through linear systems Bandwidth of a signal DCS=Digital Comm System 2006-01-24 Lecture 1

Introduction Deal with transformation of information; voice, video or data, over a channel that consists of wire, waveguide and space. Digital communication systems are becoming attractive because of the growing demand for data communication and digital transmission offers data processing options.

Revision Signals & Systems Fourier transform, signal analysis Communications Systems PAM, PWM, PPM, PCM, ASK, FSK, PSK, line coding Communication Network LAN, wireless network, circuit switching, multiple access

Scope of the course Communications is a process by which information is exchanged between individuals through a common system of symbols, signs, or behaviour. Communication systems are reliable, economical and efficient means of communications Public switched telephone network (PSTN), mobile telephone communication (GSM, 3G, ...), broadcast radio or television, navigation systems, ... The course is aiming at introducing fundamental issues in designing a (digital) communication system 2006-01-24 Lecture 1

Scope of the course ... Example of a (digital) communication system: Cellular wireless communication systems BS Base Station (BS)‏ UE UE UE User Equipment (UE)‏ 2006-01-24 Lecture 1

Scope of the course … Learning fundamental issues in designing a digital communication system (DCS): Utilized techniques Formatting and source coding Modulation (Baseband and bandpass signaling)‏ Channel coding Equalization Synchronization .... Design goals Trade-off between various parameters 2006-01-24 Lecture 1

Block Diagram of DCS General structure of a communication system SOURCE Info. Transmitter Transmitted signal Received Receiver info. Noise Channel Source User Transmitter Formatter Source encoder Channel Modulator Receiver Formatter Source decoder Channel Demodulator 2006-01-24 Lecture 1

Block Diagram and Transformation The upper block are the signal transformation from source to transmitter (XMT); format, source encode, encrypt, channel encode, multiplex, pulse modulated, band pass modulated, frequency spread and multiple excess. The lower block are the signal transformation from receiver (RCV) to sink; reversing the signal processing of the upper block. For wireless communication; (i) transmitter consist of frequency up-conversion stage to a radio frequency, high power amplifier and antenna. (ii) receiver consist of antenna and low noise amplifier (LNA).

Signal processing steps; Cont’d… Signal processing steps; (i) input information source is convert to binary digits (bits) (ii) bits grouped to form message symbol (mi ) (iii) system using channel coding; sequence of message symbol transform to sequence of channel symbol (ui ) or bit stream. The key signal processing blocks of DCS are formatting, modulation, demodulation/detection and synchronization. (1) Formatting: transform source information into bits. Information is inform of bit stream up to pulse-modulation block. (2) Modulation: process of converting the channel symbol to waveform compatible to transmission channel. - binary representation  baseband waveform

- line code, M-ary pulse modulation. (4) Band Pass Modulation: Cont’d… (3) Pulse Modulation: - transform form binary representation to baseband waveform. Include filtering to minimize the binary waveform. When pulse modulation is applied to binary symbols result in pulse-code modulation (PCM). - line code, M-ary pulse modulation. (4) Band Pass Modulation: - required if the transmission medium do not support the propagation of pulse-like waveform. Equalization - implemented to compensate for any signal distortion caused by non-ideal hc(t). Source Codin - produce AD conversion and remove redundant information. - channel coding can reduce the probability of error and reduce snr. Multiplexing - combine signal of different characteristics or sources to share communication resources. Encryption; - provides communication privacy, prevent intrusion.

Digital Communication System Important features of a DCS: The transmitter sends a waveform from a finite set of possible waveforms during a limited time The channel distorts, attenuates the transmitted signal and adds noise to it. The receiver decides which waveform was transmitted given the noisy received signal The probability of erroneous decision is an important measure for the system performance 2006-01-24 Lecture 1

Digital versus Analog Advantages of digital communications: Regenerator receiver Signal; original-> distortion-> degraded-> badly degraded.., -> amplified & regenerated Different kinds of digital signal are treated identically. Original pulse Regenerated pulse Propagation distance Data Voice Media A bit is a bit! Page 3-4 2006-01-24 Lecture 1

Digital versus Analog ..cont’d Digital signals are regenerated. Less distortion due to ‘1’ and ‘0’ state. Availability of error detection and correction. Digital is more reliable, cheap cost and more flexible compare to analog. Different types of digital signals; data, telegraph, telephone television, have identical signal transmission a bit. Protect against interference, jamming and provide encryption/privacy. Distorted analog signal cannot be removed by amplification and cannot be regenerated.

Classification of Signals Deterministic and random signals Deterministic signal: No uncertainty with respect to the signal value at any time. Random signal: Some degree of uncertainty in signal values before it actually occurs. Thermal noise in electronic circuits due to the random movement of electrons Reflection of radio waves from different layers of ionosphere p14 2006-01-24 Lecture 1

Classification of Signals … Periodic and non-periodic signals Analog and discrete signals A non-periodic signal A periodic signal A discrete signal Analog signals P14. Discrete exists only at discrete times 2006-01-24 Lecture 1

Classification of Signals .. Energy and power signals A signal is an energy signal if, and only if, it has nonzero but finite energy for all time: A signal is a power signal if, and only if, it has finite but nonzero power for all time: General rule: Periodic and random signals are power signals. Signals that are both deterministic and non-periodic are energy signals. P16. Check last item! 2006-01-24 Lecture 1

Random Process A random process is a collection of time functions, or signals, corresponding to various outcomes of a random experiment. For each outcome, there exists a deterministic function, which is called a sample function or a realization. Random variables time (t)‏ Real number Sample functions or realizations (deterministic function)‏ p22 2006-01-24 Lecture 1

Random Process … Strictly stationary: If none of the statistics of the random process are affected by a shift in the time origin. Wide sense stationary (WSS): If the mean and autocorrelation functions do not change with a shift in the origin time. Cyclostationary: If the mean and autocorrelation functions are periodic in time. Ergodic process: A random process is ergodic in mean and autocorrelation, if and, respectively. Strict? 2006-01-24 Lecture 1

Autocorrelation Defn: autocorrelation refers to the matching of a signal with a delayed version of itself. Autocorrelation of an energy signal Autocorrelation of a power signal For a periodic signal: Autocorrelation of a random signal For a WSS process: 2006-01-24 Lecture 1

Spectral Density Energy signals: Energy spectral density (ESD): Power signals: Power spectral density (PSD): Random process: 2006-01-24 Lecture 1

Properties of an Autocorrelation function For real-valued (and WSS in case of random signals): Autocorrelation and spectral density form a Fourier transform pair. Autocorrelation is symmetric around zero. Its maximum value occurs at the origin. Its value at the origin is equal to the average power or energy. 2006-01-24 Lecture 1

Noise in Communication Systems Thermal noise; thermal motion of electrons in all disipative components, is described by a zero-mean Gaussian random process, n(t). Its PSD is flat, hence, it is called white noise. n- Gaussian probability density function [w/Hz] Power spectral density Autocorrelation function Probability density function 2006-01-24 Lecture 1

Signal Transmission through Linear Systems Deterministic signals: Random signals: Ideal distortion less transmission: All the frequency components of the signal not only arrive with an identical time delay, but also are amplified or attenuated equally. Input Output Linear system 2006-01-24 Lecture 1

Signal Transmission … - cont’d Ideal filters: Realizable filters: RC filters Butterworth filter Low-pass Non-causal! Band-pass High-pass 2006-01-24 Lecture 1

Bandwidth of signal Baseband versus bandpass: Bandwidth dilemma: Bandlimited signals are not realizable! Realizable signals have infinite bandwidth! Baseband signal Bandpass Local oscillator 2006-01-24 Lecture 1

Bandwidth of Signal … Different definition of bandwidth: Half-power bandwidth Noise equivalent bandwidth Null-to-null bandwidth Fractional power containment bandwidth Bounded power spectral density Absolute bandwidth (a)‏ (b)‏ (c)‏ (d)‏ (e)50dB 2006-01-24 Lecture 1