PSK.zip_PSK_Will

function y = my_rrcosflt(x, fd, fs, beta, delay, fsflag) % MY_RRCOSFLT Filter the input signal using a root raised cosine filter. % Y = MY_RRCOSFLT(X, Fd, Fs, BETA, DELAY) filters the input signal X % using a root raised cosine FIR filter. The sample frequency for the % input, X, is Fd (Hz). The sample frequency for the output, Y, is % Fs (Hz). Fs must be an integer multiple of Fd. The rolloff factor BETA % determines the width of the transition band of the filter. DELAY is % the time delay from the beginning of the filter to the peak of the % impulse response, expressed as the number of input sample periods, % i.e., the delay in seconds is DELAY/Fd. % % BETA, the rolloff factor, specifies the excess bandwidth of the % filter. BETA must be in the range [0,1]. For example, BETA = .5 means % that the bandwidth of the filter is 1.5 times the input sampling % frequency, Fd. This also means that the transition band of the filter % extends from .5 * Fd to 1.5 * Fd. Typical values for BETA are between % 0.2 to 0.5. % % DELAY determines the length of the filter impulse response used to % filter X. This length is Fs/Fd * (2 * DELAY) + 1. % % Y is the output of the upsamled, filtered input stream X. The length % of the vector Y is % Fs/Fd * (length(X) + 2 * DELAY). % % Y = MY_RRCOSFLT(X, Fd, Fs, BETA, DELAY, 'Fs') assumes that the input % signal X is already at sampling frequency Fs. % % The input X can be a row or a column vector, the output Y is always a % column vector. %santosh shah, The LNM IIT Jaipur (India)([email protected]) 25/04/07 % Check arguments if (fs / fd ~= floor(fs/fd)) error('Fs/Fd must be an integer.'); else upfactor = fs / fd; end if beta < 0 || beta > 1 error('The rolloff factor BETA must be in the range [0,1].'); end if (delay < 0) || delay ~= floor(delay) error('DELAY must be a positive integer.'); end if nargin >= 6 if strcmpi(fsflag, 'Fs') fsflag = true; else error('Invalid value for FSFLAG'); end else fsflag = false; end % Upsample input signal unless fsflag is set if fsflag xup = x; else xup = upsample(x, upfactor); end % Create the filter f = my_rrc(fd, fs, beta, delay); % Filter the input signal and convert to column vector y = conv(xup, f); y = y(:); end function f = my_rrc(fd, fs, beta, delay) % MY_RRC Produces the impulse response of a root raised cosine filter % F = MY_RRC(Fd, Fs, BETA, DELAY) is the impulse response of a root % raised cosine FIR filter with rolloff factor BETA and delay DELAY. BETA = beta; DELAY = delay; FD = fd; FS = fs; % time vector Td = 1/FD; % Length of actual filter coefficients (rest is zero) rrclen = FS/FD * DELAY * 2 + 1; % Create vector of time instants (make it a column vector to behave as the % MATLAB function rcosflt) t = linspace(-DELAY*Td, DELAY*Td, rrclen)'; rrc_num = 4*BETA / (pi*sqrt(Td)) * ... (cos((1+BETA)*pi*t/Td) + (1-BETA)*pi/(4*BETA) * ... sinc((1 - BETA)*t/Td)); rrc_denom = (1 - (4*BETA * t/Td).^2); rrc = rrc_num ./ rrc_denom; % Determine if there is a singularity (at positions t = +/- 1/(4*BETA)) % The value at these points can be obtained by the De l'Hopital rule. ind = find(abs(t) == Td/(4*BETA)); if ~isempty(ind) rrc(ind) = 4*BETA / (pi * sqrt(Td)) * ... ( (-2 + pi)*cos(pi / (4*BETA)) + ... (2+pi) * sin(pi / (4*BETA))) / (4*sqrt(2)); end % Normalize f = rrc / sqrt(FS); end