ece4305_lab3

ece4305_lab3 - ECE4305: Software-Defined Radio Systems and...

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Unformatted text preview: ECE4305: Software-Defined Radio Systems and Analysis Lab 3: Receiver Structure & Waveform Synthesis of a Transmitter and a Receiver D-Term 2010 Objective This laboratory will cover basic receiver structures and implementations. It will also show how to construct a series of basis functions that can be combined to produce orthogonal waveforms. In the experimental part of the lab you will implement two different receiver structures and then, if possible, observe their performance during over the air transmission. Contents 1 Theoretical Preparation 2 1.1 Gram-Schmidt Orthogonaliztion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.2 Maximum Likelihood Detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.3 MAP Detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.4 Basic Receiver Realizations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.4.1 Matched Filter Realization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.4.2 Correlator Realization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 1.5 Problems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2 Software Implementation 9 2.1 Correlator Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.2 Maximum-likelihood Decoder Implementation . . . . . . . . . . . . . . . . . . . . . . 10 2.3 Correlator Realization of a Receiver in Simulink . . . . . . . . . . . . . . . . . . . . . 11 3 Software-defined Radio Experimentation 13 3.1 Python Tutorial and Correlation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 3.2 Pulse Shaping and Matched Filtering . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 3.3 More Parameter Testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 3.4 Useful GRC Blocks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 4 Analysis and Synthesis 17 5 Lab Report Instructions 17 1 1 Theoretical Preparation Signals can be represented as either waveforms or vectors. Waveform representations are defined by the Fourier series of a signal, or the sum of sins and cosines that make a particular shape. As a vector, a signal is represented as series of orthonormal vectors. This part of the lab will show how to derive these vectors and their basis functions. It will then show two receiver designs and their implementations. 1.1 Gram-Schmidt Orthogonaliztion To derive a set of orthogonal basis functions 1 (t), 2 (t), ..., i (t) from set of energy signals denoted by S 1 (t), S 2 ( t ), ..., S M ( t ) we will use the following functions: g i ( t ) = S i ( t ) i 1 summationdisplay j =1 S ij j ( t ) (1) where: S ij = integraldisplay T S i ( t ) j dt,j = 1 , 2 ,...,i 1 . (2) Using these two functions, we define our basis function i as: i = g i ( t ) radicalBig integraltext T g 2 i ( t ) dt ,i = 1 , 2 ,...,N.,....
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This note was uploaded on 01/13/2011 for the course ECE 4305 taught by Professor Wy during the Spring '10 term at WPI.

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ece4305_lab3 - ECE4305: Software-Defined Radio Systems and...

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