Kay_algorithm.rar_kay_kay offset_qpsk载波_载波频偏_频偏估计

function fre_offset_estimation = Kay_algorithm(received_signal,pulse_wave,training_data) %-------------------------------------------------------------------------- % 函数功能：Kay算法频率偏移估计 % 输入参数：received_signal：从信道接收的QPSK信号 % pulse_wave：基带成型脉冲，作为MF的冲激响应 % training_data：训练符号集，用于辅助估计频率偏移 % 输出参数：fre_offset_estimation：频率偏移估计 %-------------------------------------------------------------------------- global fs fc fb pulse_type training_symbol_num; received_signal = received_signal(1,1:training_symbol_num*fs/fb); %只提取接收信号中包含训练符号的部分进行处理 t = 0 : 1/fs : (length(received_signal)-1)/fs; %-----------------I路和Q路信号分别解调------------------% I_base_signal = sqrt(2) * received_signal .* cos(2*pi*fc*t); %I路信号解调 Q_base_signal = -sqrt(2) * received_signal .* sin(2*pi*fc*t); %Q路信号解调 if strcmp(pulse_type,'rect')==1 inf_signal_I = filter(pulse_wave,1,[I_base_signal,zeros(1,16*fs/fb)])./length(pulse_wave); %用矩形成型脉冲进行匹配滤波时，为了避免星座图的幅度失真，需要除以归一化因子length(pulse_wave)，另外对I路信号补零是为了避免使用filter函数对输出信号进行截断，如果使用conv函数可以不用补零 inf_signal_Q = filter(pulse_wave,1,[Q_base_signal,zeros(1,16*fs/fb)])./length(pulse_wave); else inf_signal_I = filter(pulse_wave,1,[I_base_signal,zeros(1,16*fs/fb)]); %用根方升余弦成型脉冲进行匹配滤波 inf_signal_Q = filter(pulse_wave,1,[Q_base_signal,zeros(1,16*fs/fb)]); end data_sample_flag = length(pulse_wave): fs/(fb) : length(pulse_wave)+(training_symbol_num-1)*(fs/fb)+1; %确定采样位置 sampled_point_I = inf_signal_I(1,data_sample_flag); %对I、Q两路匹配滤波器输出进行采样 sampled_point_Q = inf_signal_Q(1,data_sample_flag); demodulation_data = sampled_point_I + sqrt(-1).*sampled_point_Q; %获得x(k),用于进行频偏估计 %-----------利用Kay算法进行频偏估计-------------% Z_vector = demodulation_data .* (training_data').'; %先求出z(k) gama=zeros(1,training_symbol_num); arg=zeros(1,training_symbol_num); mult=zeros(1,training_symbol_num); for k=2:training_symbol_num gama(k)=3*training_symbol_num*(training_symbol_num^2-(2*k-training_symbol_num)^2)/((training_symbol_num^2)*2*(training_symbol_num^2-1)); arg(k)=angle(Z_vector(k)*Z_vector(k-1)'); mult(k)=gama(k)*arg(k); end fre_offset_estimation = fb * sum(mult.')/(2*pi); end