Department of Communications and Computer Engineering Faculty of Engineering – Cairo University ELC N316 - Communications II

Department of Communications and Computer Engineering Faculty of Engineering – Cairo University ELC N316 - Communications II.

Course Logistics. Instructor: Dr. Ahmed Khattab E-mail: [email protected] Office Hours: Wednesday 3:30-5:00 or by email appointment. Office: 4th floor, Electronics and communications engineering building. Grade Distribution: Assignments (10%): 3 assignments that are turned in every 4 weeks. Quizzes (10%): 3 quizzes, best 2 out of 3 are counted. Midterm (20%) Lab Work (10%) Project(s) (10%): MATLAB-based project(s). Final (40%) Textbooks: “Communication Systems”, Simon Haykin , 4th , 5th editions. “Modern Digital and Analog Communication Systems”, B. P. Lathi , 3rd edition..

Course Outline. Baseband Data Transmission Matched filters and their properties. Error rate due to noise. Signal constellation and Gram-Schmidt orthogonalization procedure. MAP and ML decoding rules. Correlator receiver and probability of error calculation. Passband Data Transmission Digital Modulation schemes - Description of ASK, FSK, PSK and DPSK modulations. Their implementation , PSD c/ cs , B.W efficiency (spectral efficiency (. QAM system. Noise in digital modulation - Coherent detection of signals in noise-Probability of error. Non-coherent orthogonal modulation..

Introduction. Communication is a process by which information is exchanged between individuals through a common system of symbols, signs or behavior. Examples: Public switched telephone network (PSTN), mobile telephone communications (GSM, 3G, 4G…), WiFi , WiMAX, broadcast radio or television, navigation systems, ….

Today’s Class. What is a Digital Comminutions System (DCS)? DCS advantages and disadvantages Preliminaries and necessary review Classification of signals Random processes Noise in communication systems Signal transmission through linear systems Bandwidth of signals.

Digital Communications Systems. The course is aiming at introducing the fundamental issues in designing and analyzing a digital communication system..

Digital Communications Basics. A transmitter (TX) sends a waveform (symbol) from a finite set of possible waveforms during a finite time (symbol time). How does this compare to analog comm.? A channel distorts, attenuates, and adds noise to the transmitted waveform. A receiver (RX) should decide which waveform was transmitted from the noisy received signal. Probability of erroneous decision is an important measure of the DCS performance.

Digital Communications Systems. The course is aiming at introducing the fundamental issues in designing and analyzing a digital communication system..

DCS Advantages. Robustness: through error control coding Regenerative repeaters. Immunity to noise A bit is a bit (voice, data, video, ….) Efficient storage and retrieval. Better security (encryption) TDM Compression and Source Coding Adaptive Signal Processing Flexibility(Software-Defined Radio).

DCS Disadvantages. Quantization noise Complexity Higher bandwidth requirements.

Classification of Signals. Deterministic Signal No uncertainty about the signal value at any time Random Signal Some degree of uncertainty in the signal values (a different signal each time) Thermal noise in electronic circuit due to the random movement of electrons. Reflections of radio waves from different layers of ionosphere.

Classification of Signals. 12. Periodic and non-periodic signals x(t) t A periodic signal A non-periodic signal t a Analog and discrete signals x(t) x(t) t A discrete signal Analog signals.

Classification of Signals. Energy Signal A signal is an energy signal if, and only if, it has a finite but nonzero energy for all the time Power Signal A signal is a power signal if, and only if, it has a finite but nonzero power for all the time General Rule: Periodic and random signals are power signals. Signals that are both deterministic and non-periodic are energy signals..

Random Processes. 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.

The Autocorrelation Function. Autocorrelation of an energy signal Autocorrelation of a power signal Autocorrelation of a random signal For a WSS process (does not depend on the time origin):.

Autocorrelation Function Properties. For a real valued (and WSS in case of random signals): Autocorrelation functions 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..

Spectral Density. 17. Energy signals Energy spectral density (ESD): a Power signals 1 To/2 = föJ-To/2 = EN lcn12 Power spectral density (PSD): x(f) = Vx(f) = E lcn126(f-nf0) fo=1/T0 Random process Power spectral density (PSD):.

Noise in Communications Systems. Thermal noise is described be a zero-mean Gaussian random process: n(t) Its PSD is flat, and hence, it is called white noise.

Signal Transmission Through Linear Systems. Ideal distortion-less transmission All the frequency components of the signal does not only arrive with an identical time delay , but also are equally amplified or attenuated.

Ideal Filters. 20. Low-pass Band-pass h(t) o Non-causal! t High-pass.

Bandwidth of a Signal. Baseband versus bandpass Bandwidth Dilemma Band-limited signals are not realizable! Realizable signals have infinite bandwidth!.

Different Definitions of Bandwidth. 22. Half-power bandwidth Noise equivalent bandwidth Null-to-null bandwidth Fractional power containment bandwidth Bounded power spectral density Absolute bandwidth f Gz(f) (a) (b) (d) (e)50dB.

Formatting and Transmission of Baseband Signals. To transform an analog waveform into a form that is compatible with digital communications, the following steps are to be taken: Sampling Quantization and encoding Baseband transmission.

The Sampling Process. 24. x(t) domain = x txxt Ts 2Ts3Tst I's 2T.3T8t Frec uencv dotnain o.

Aliasing Effect. 25. s s s LP filter Nyquist rate S fs = 2fm aliasing fs > 2fm fs f.

Quantization. We are still not “digital” yet, why? Amplitude quantization is the process of mapping samples of a continuous amplitude waveform to a finite set of amplitudes..

Formatting and Transmission of Baseband Signals. 27.

Line Codes for Binary Transmission. 28. Binarydata 0 11 11 10 11 10 1 0 1 1 Unipolar NRZ Polar NRZ Unipolar RZ Bipolar RZ Split Phase - Manchester .Time.

Criteria for Comparing Line Codes. Spectral Characteristics Power spectral density and bandwidth efficiency Bandwidth should be as small as possible No DC component Power Efficiency The transmitted power should be as small as possible for a given BW and error probability Error detection/correction probability Should be easy to detect errors and possibly correct them Bit Synchronization Should be able to extract time (clock) information from the line code Implementation cost and complex ity.

Spectra of Line Codes. 30. •met 112 Unipolar NRZ Unipolar RZ 0.5 Polar NRZ 0.9 Bipolar RZ.

Example of M - ary PAM. 31. (rectangular pulse) '01' 3B iiiiiiiiiii.