lab4_wireless

lab4_wireless - UCSB Spring 2010 ECE 146B: Laboratory...

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Unformatted text preview: UCSB Spring 2010 ECE 146B: Laboratory Assignment 4 Lab Objectives: Introduction to modeling and performance evaluation for signaling on wireless fading channels. Let us consider the following simple model of a wireless channel (obtained after filtering and sampling at the symbol rate, and assuming that there is no ISI). If { b [ n ] } is the transmitted symbol sequence, then the complex-valued received sequence is given by y [ n ] = h [ n ] b [ n ] + w [ n ] (1) where { w [ n ] = w c [ n ] + jw s [ n ] } is an iid complex Gaussian noise sequence with w c [ n ], w s [ n ] i.i.d. N (0 , 2 = N 2 ) random variables. We say that w [ n ] has variance 2 per dimension. The channel sequence { h [ n ] } is a time-varying sequence of complex gains. Rayleigh fading: The channel gain sequence { h [ n ] = h c [ n ] + jh s [ n ] } , where { h c [ n ] } and { h s [ n ] } are zero mean, independent and identically distributed colored Gaussian random processes. The reason this is called Rayleigh fading is that | h [ n ] | = radicalbig h 2 c [ n ] + h 2 s [ n ] is a Rayleigh random variable. Remark: The Gaussianity arises because the overall channel gain results from a superposition of gains from multiple reflections off scatterers. Simulation of Rayleigh fading: We will use a simple first-order autoregressive (AR(1)) model, wherein the colored channel gain sequence { h [ n ] } is obtained by passing white Gaussian noise through a first-order recursive filter, as follows: h c [ n ] = h c [ n- 1] + u [ n ] h s [ n ] = h s [ n- 1] + v [ n ] (2) where { u [ n ] } and { v [ n ] } are independent real-valued white Gaussian sequences, with i.i.d. N (0 , 2 ) elements. The parameter (0 < < 1) determines how rapidly the channel varies. Setting up fading simulator (a) Set up the AR(1) Rayleigh fading model in matlab, with and 2 as programmable parameters....
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lab4_wireless - UCSB Spring 2010 ECE 146B: Laboratory...

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