Hi... I am struggling to understand the following: If r(t) = sum_i{s(t)*h_i(t-tau_i)} + n(t) is the received signal where h_i(t) is the overall channel impulse response, the MLSE Viterbi algorithm is simply done by calculating branch metrics of the form |r(t)-noiseless_r(t)|, where noiseless_r(t) is a reconstructed version of r(t) using the estimated channel impulse response taps h_est_i(t). Since these branch metrics direcly use r(t), without any matched filtering with h*(t) (the impulse response matched to the overall channel response h(t), where is the matched filtering done that is supposed to be required by the MLSE equalizer?? Thanks for helping me understand this ! Cheers. Guy

# Where is the matched filtering operation in this?

Started by ●November 6, 2008

Reply by ●November 7, 20082008-11-07

There is no matched filtering here if we use "euclidean metric". But we don't usually use "euclidean metric" in MLSE equalizer due to the complexity. What we usually use is the "matched filter metric" or "ungerboeck metric". Then r(t) is indeed convolved with h_est_i(t). Regards Piyush On Nov 6, 6:22�pm, "zolguy" <zol...@hotmail.com> wrote:> Hi... > I am struggling to understand the following: > > If r(t) = sum_i{s(t)*h_i(t-tau_i)} + n(t) is the received signal where > h_i(t) is the overall channel impulse response, the MLSE Viterbi algorithm > is simply done by calculating branch metrics of the form > |r(t)-noiseless_r(t)|, where noiseless_r(t) is a reconstructed version of > r(t) using the estimated channel impulse response taps h_est_i(t). > > Since these branch metrics direcly use r(t), without any matched filtering > with h*(t) (the impulse response matched to the overall channel response > h(t), where is the matched filtering done that is supposed to be required > by the MLSE equalizer?? > > Thanks for helping me understand this ! > > Cheers. > > Guy