Description: This demo shows the BER performance of linear, decision feedback (DFE), and maximum likelihood sequence estimation (MLSE) equalizers when operating in a static channel with a deep null. The MLSE equalizer is invoked first with perfect channel knowledge, then with an imperfect, although straightforward, channel estimation algorithm. The BER results are determined through Monte Carlo simulation. The demo shows how to use these equalizers seamlessly across multiple blocks of data, where equalizer state must be maintained between data blocks.
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eqberdemo\eqberdemo.asv
.........\eqberdemo.html
.........\eqberdemo.m
.........\eqberdemo.png
.........\eqberdemo_01.png
.........\eqberdemo_02.png
.........\eqberdemo_03.png
.........\eqberdemo_04.png
.........\eqberdemo_05.png
.........\eqberdemo_06.png
.........\eqberdemo_07.png
.........\eqberdemo_08.png
.........\eqberdemo_09.png
.........\eqberdemo_10.png
.........\eqberdemo_11.png
.........\eqberdemo_12.png
.........\eqberdemo_13.png
.........\eqberREADME.txt
.........\eqber_adaptive.html
.........\eqber_adaptive.m
.........\eqber_graphics.m
.........\eqber_mlse.html
.........\eqber_mlse.m
.........\eqber_siggen.html
.........\eqber_siggen.m
.........\figposition.m
.........\test\fun_sa.m
.........\....\UWA_channel.m
.........\test
eqberdemo
67506279MMSE_T_F.zip
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