EE 179
Digital and Analog Communication Systems
Homework #2 Solutions
April 21, 2014
Handout #16
1. Operations on signals (Lathi & Ding 2.3-3). For the signal g(t) shown below, sketch:
a. g(t 4);
b. g(t/1.5);
c. g(2t 4);
d. g(2 t).
Hint: Recall that repla
Forward error correction
From Wikipedia, the free encyclopedia
Jump to: navigation, search
In telecommunication and information theory, forward error correction (FEC) is a system of
error control for data transmission, whereby the sender adds redundant da
Signals and Systems
Demystified
David McMahon
New York Chicago San Francisco Lisbon London Madrid
Mexico City Milan New Delhi San Juan Seoul
Singapore Sydney Toronto
CONTENTS
Preface
CHAPTER
CHAPTER
1
2
IX
Introduction
Continuous and Discrete Signals
Ener
Sampling and
Aliasing
Chapter
4
With this chapter we move the focus from signal modeling and
analysis, to converting signals back and forth between the analog
(continuous-time) and digital (discrete-time) domains. Back in
Chapter 2 the systems blocks C-to
SUBMITTED TO THE IEEE TRANSACTIONS ON INFORMATION THEORY SEPTEMBER 2005
1
Incremental Redundancy Hybrid ARQ with
LDPC and Raptor Codes
Emina Soljanin, Nedeljko Varnica, and Philip Whiting
Abstract
Two incremental redundancy hybrid ARQ (IR-HARQ) schemes ar
Subject: Communication Theory
Code: 18481
Institution: Escuela Politcnica Superior
Degree: Telecommunication Technologies and Services Engineering
Level: Graduate
Type: Training Module Common to the Telecommunications Branch
ECTS: 6
1.
COURSE TITLE
Commun
Experiments in Sampling, Reconstruction, and Filtering
KST, 4/2002
Introduction
This note describes some simple experiments in MATLAB to illustrate the sampling and reconstruction
processes, and the implementation of filtering concepts.
The required theor
Teaching Digital and Analog Modulation to
Undergradute Information Technology Students
Using Matlab and Simulink
1
M. Boulmalf1, Y. Semmar2 , A. Lakas3, and K. Shuaib3
School of Science & Engineering, Al Akhawayn University in Ifrane, Morocco
2
College of
Fundamental Frequency of Continuous Signals
To identify the period T , the frequency f = 1/T , or the angular frequency = 2f = 2/T of a
given sinusoidal or complex exponential signal, it is always helpful to write it in any of the following
forms:
sin(t)
272
CHAPTER
5 Peer-to-Peer Protocols
In the case of reliable service, both approaches are implemented. In situations where errors are infrequent, end-to-end mechanisms are preferred. The
TCP reliable stream service introduced later in this chapter provide
MATCHED FILTERS
The matched filter is the optimal linear filter
for maximizing the signal to noise ratio (SNR)
in the presence of additive stochastic noise.
Matched filters are commonly used in radar,
in which a signal is sent out, and we measure
the refl
COMBINING ADAPTIVE MODULATION AND CODING WITH
TRUNCATED ARQ ENHANCES THROUGHPUT
Qingwen Liu, Shengli Zhou, and Georgios B. Giannakis
Dept. of ECE, Univ. of Minnesota, 200 Union Street SE, Minneapolis, MN 55455
ABSTRACT
We develop a cross-layer design whic
The potential and limitations of adaptive modulation"
‘ oVer slow Rayleigh fading channels '
J .M. Torrance: D. Didascalouland L. HanzoI
Abstract
The upper-bound performance of adaptive modulation in Rayleigh channels is given and the results of Optimisat
C H A P T E R
10
Power Spectral Density
INTRODUCTION
Understanding how the strength of a signal is distributed in the frequency domain,
relative to the strengths of other ambient signals, is central to the design of any
LTI lter intended to extract or sup
MCS 320
Introduction to Symbolic Computation
Spring 2008
MATLAB Lecture 7. Signal Processing in MATLAB
We have seen how to t data with polyt and how to design shapes with spline. In this lecture we
cover another way to deal with approximate data, which is
EE 179, Lecture 4, Handout #6
Review of Last Lecture
Signals can be categorized:
real-valued vs. complex-valued
analog vs. digital
continuous time vs. discrete time
deterministic vs. random
Signals can be measured:
mathematically, by functionals
physicall
EE 179, Lecture 5, Handout #7
Review: Fourier Series of Square Wave
Square wave with period 2.
1
0.5
0
8
6
4
2
0
2
4
6
8
Square wave with period 2 is determined by values in [, ]:
w(t) =
1 |t| < /2
0 < |t| < /2
Square wave is a 1-bit quantization of cosin
EE 179, Lecture 6, Handout #9
Review: Fourier Series Notations
Trigonometric series:
an cos n0 t + bn sin n0 t
a0 +
n=1
or
n=1
n=1
bn sin 2nf0 t
an cos 2nf0 t +
a0 +
Compact trigonometric series:
Cn sin(2nf0 t + n )
C0 +
n=1
Exponential Fourier series:
Dn
EE 179
Digital and Analog Communication Systems
Homework #3
Due Wednesday, April 23
April 16, 2014
Handout #13
1. DSB-SC modulator (Lathi & Ding 4.2-3). You are asked to design a DSB-SC modulator to generate
a modulated signal km(t) cos(c t + ), where m(t
EE 179
Digital and Analog Communication Systems
Homework #2
Due Wednesday, April 16
April 9, 2014
Handout #8
1. Operations on signals (Lathi & Ding 2.3-3). For the signal g(t) shown below, sketch:
a. g(t 4);
b. g(t/1.5);
c. g(2t 4);
d. g(2 t).
Hint: Recal
EE 179, Lecture 7, Handout #10
Important Fourier Transforms
Shifted impulse (t t0 ):
Fcfw_(t t0 ) =
(t t0 )ej2f t dt = ej2f t0
This is a complex exponential in frequency. By duality,
Fcfw_ej2f0 t = (f f0 )
Sinuoids:
1
Fcfw_cos 2f0 t = Fcfw_ 1 (ej2f0 t +
Matched-Filter Detection on Mac
27. Matched-Filter Detection
Random Signals Through Linear Systems Consider the effect of passing a random signal (message or noise) through a linear system with a transfer function H(f), as shown in Figure 27.1 (a). Let G
1
International Journal of Communication Networks and Information Security (IJCNIS)
Vol. 1, No. 2, August 2009
Adaptive Modulation for OFDM Systems
J.Faezah1, and K.Sabira2
1
Centre for Foundations Studies and Extension Education, Multimedia University,
7
Random Puncturing for Secrecy
Jo o Almeida, Jo o Barros
a
a
Instituto de Telecomunicacoes,
Departamento de Engenharia Electrot cnica e de Computadores, Faculdade de Engenharia da Universidade do Porto
e
Email: [email protected], [email protected]
Abstr
Matched Filters
1. Consider the signal s (t ) shown in Fig. 1.
(a) Determine the impulse response of a filter matched to this signal and sketch it as
a function of time.
(b) Plot the matched filter output as a function of time.
s1 (t )
A/ 2
T /2
T
t
A/ 2
Overview of AMC in LTE
Gwanmo Ku
Adaptive Signal Processing and Information Theory Research Group
Jun. 15, 2012
Outline
2/17
LTE Basic
Why LTE
LTE Network / Resources / Frame Structure
LTE in US (Verizon)
AMC in LTE
Why AMC?
Channel Condition : CQI Report
University of Waterloo
Coding & Signal Transmission Laboratory
Department of Electrical & Computer Engineering
Waterloo, Ontario, Canada, N2L 3G1
Technical Report UW-E&CE#2002-15
Adaptive Modulation and Coding in 3G
Wireless Systems
James Yang, Amir K. Kh
Laboratory Exercise in Digital Communications
SIGNEMatched Filters
Name:
Signature:
Personal id number:
Date:
Passed:
1
Objectives
In this lab exercise a simple digital communications system is investigated.
The error performance is tested using an additi