I'm studying on designing 9-tap zero forcing equalizer to remove ISI in the channel. I assumed that the channel response is $h[n] = [0.41, 0.815, 0.41]$ and I tried to calculate bit error rate. When I choose $h[n]=[0.21, 0.815, 0.21]$ for example, I get good results. BER goes to 1e-4 for high SNR values. But the code below gives bit error rate of 0.5 when the channel response is $[0.41, 0.815, 0.41]$. Can anybody help me about this problem? I did something wrong but I couldn't find it.
N = 10^4; % number of bits or symbols Eb_N0_dB = [0:2:10]; % multiple Eb/N0 values for ii = 1:length(Eb_N0_dB) % Transmitter ip = rand(1,N)>0.5; % generating 0,1 with equal probability s = 2*ip-1; % BPSK modulation 0 -> -1; 1 -> 1 % Channel model, multipath channel ht = [0.41 0.815 0.41] chanOut = conv(s,ht); n = 1/sqrt(2)*[randn(1,N+length(ht)-1) + j*randn(1,N+length(ht)-1)]; % white gaussian noise, 0dB variance % Noise addition y = chanOut + 10^(-Eb_N0_dB(ii)/20)*n; % additive white gaussian noise kk=4; % 9-tap filter L = length(ht); hM = toeplitz([ht([2:end]) zeros(1,2*kk+1-L+1)], [ ht([2:-1:1]) zeros(1,2*kk+1-L+1) ]); d = zeros(1,2*kk+1); d(kk+1) = 1; c = [inv(hM)*d.'].'; % matched filter yFilt = conv(y,c); yFilt = yFilt(kk+2:end); yFilt = conv(yFilt,ones(1,1)); % convolution ySamp = yFilt(1:1:N); % sampling at time T % receiver - hard decision decoding ipHat = real(ySamp)>0; % % counting the errors nErr(1,ii) = size(find([ip-ipHat]),2); end simBer = nErr/N; % simulated ber