hello, any of you has experience with different methods for symbol
synchronization so you can help me to implement one of them in a receiver
for bpsk modulation?
i've implemented a costas loop for carrier recovery and the code i've found
for symbol synchronization is too heavy and takes too much time. this is
the matlab code:
tnow=del*oversampling+1; tau=0; xs=zeros(1,length(y)); %
initialize variables
tausave=zeros(1,length(y)); tausave(1)=tau; i=0;
mu=0.05; % algorithm stepsize
delta=0.1; % time for derivative
while tnow<length(y)-del*oversampling % run iteration
i=i+1;
xs(i)=interpsinc(y,tnow+tau,del); % interpolated value at
tnow+tau
x_deltap=interpsinc(y,tnow+tau+delta,del); % get value to the right
x_deltam=interpsinc(y,tnow+tau-delta,del); % get value to the left
dx=x_deltap-x_deltam; % calculate numerical
derivative
tau=tau+mu*dx*xs(i); % alg update (energy)
tnow=tnow+oversampling; tausave(i)=tau; % save for plotting
end
pam_rx=xs; % Decisão de Símbolo Recebido
bits_rx=pam_rx>0; %Estimação dos bits recebidos;
ah, the interpsinc function is:
function y=interposinc(x, t, l, beta)
% interpolate to find a single point using the direct method
% x = sampled data
% t = place at which value desired
% l = one sided length of data to interpolate
% beta = rolloff factor for SRRC function
% = 0 is a sinc
if nargin==3, beta=0; end; % if unspecified, beta is 0
tnow=round(t); % create indices tnow=integer part
tau=t-round(t); % plus tau=fractional part
s_tau=srrc(l,beta,1,tau); % interpolating sinc at offset tau
x_tau=conv(x(tnow-l:tnow+l),s_tau); % interpolate the signal
y=x_tau(2*l+1); % the new sample
if any of you have an idea of how i can do it without doing so many
interpolations, please help me.
symbol synchronization method for SDR in Matlab?
Started by ●March 16, 2011
Reply by ●March 20, 20112011-03-20
On Mar 16, 3:22�pm, "algora" <cgalgora@n_o_s_p_a_m.uclv.edu.cu> wrote:> hello, any of you has experience with different methods for symbol > synchronization so you can help me to implement one of them in a receiver > for bpsk modulation? > i've implemented a costas loop for carrier recovery and the code i've found > for symbol synchronization is too heavy and takes too much time. this is > the matlab code: > > tnow=del*oversampling+1; tau=0; xs=zeros(1,length(y)); � � � � � % > initialize variables > tausave=zeros(1,length(y)); tausave(1)=tau; i=0; > mu=0.05; � � � � � � � � � � � � � � � � � �% algorithm stepsize > delta=0.1; � � � � � � � � � � � � � � � � �% time for derivative > while tnow<length(y)-del*oversampling � � � % run iteration > � i=i+1; > � xs(i)=interpsinc(y,tnow+tau,del); � � � � � % interpolated value at > tnow+tau > � x_deltap=interpsinc(y,tnow+tau+delta,del); �% get value to the right > � x_deltam=interpsinc(y,tnow+tau-delta,del); �% get value to the left > � dx=x_deltap-x_deltam; � � � � � � � � � � % calculate numerical > derivative � > � tau=tau+mu*dx*xs(i); � � � � � � � � � � �% alg update (energy) > � tnow=tnow+oversampling; tausave(i)=tau; � � � � � � �% save for plotting > end > > pam_rx=xs; � � � � � � � � � � � � � � � % Decis�o de S�mbolo Recebido > > bits_rx=pam_rx>0; � � � � � � � � � � � � %Estima��o dos bits recebidos; > > ah, the interpsinc function is: > function y=interposinc(x, t, l, beta) > % interpolate to find a single point using the direct method > % � � � �x = sampled data > % � � � �t = place at which value desired > % � � � �l = one sided length of data to interpolate > % � � � �beta = rolloff factor for SRRC function > % � � � � � � = 0 is a sinc > if nargin==3, beta=0; end; � � � � �% if unspecified, beta is 0 > tnow=round(t); � � � � � � � � � � �% create indices tnow=integer part > tau=t-round(t); � � � � � � � � � � % plus tau=fractional part > s_tau=srrc(l,beta,1,tau); � � � � � % interpolating sinc at offset tau > x_tau=conv(x(tnow-l:tnow+l),s_tau); % interpolate the signal > y=x_tau(2*l+1); � � � � � � � � � � % the new sample > > if any of you have an idea of how i can do it without doing so many > interpolations, please help me.Change the timing compensation to something simpler, like a zero-order, first-order, or a polynomial interpolator. The performance depends on your oversampling factor and your target SNR.
