基于FFT的OFDM系统信道估计Matlab实现.rar

% PILOT BASED CHANNEL ESTIMATION (FFT BASED) FOR OFDM SYSTEMS close all clear all clc SNR_dB = 40;% SNR PER BIT NUM_FRAMES = 10^2; FFT_LEN = 1024; NUM_PILOT = 256; NUM_BIT = 2*(FFT_LEN-NUM_PILOT); % NUMBER OF DATA BITS CHAN_LEN = 10; % NUMBER OF CHANNEL TAPS CP_LEN = CHAN_LEN-1; % LENGTH OF THE CYCLIC PREFIX FADE_VAR_1D = 0.5; % 1D FADE VARIANCE OF THE CHANNEL FADE_STD_DEV = sqrt(FADE_VAR_1D); % STANDARD DEVIATION OF THE FADING CHANNEL % SNR PER BIT PARAMETERS - OVERALL RATE IS 2 SNR = 10^(0.1*SNR_dB); % LINEAR SCALE NOISE_VAR_1D = 0.5*2*2*CHAN_LEN*FADE_VAR_1D/(2*SNR*FFT_LEN); % 1D AWGN NOISE VARIANCE NOISE_STD_DEV = sqrt(NOISE_VAR_1D); % NOISE STANDARD DEVIATION % PILOT AND DATA INDICES IN OFDM FRAME PILOT_INDEX = 1:FFT_LEN/NUM_PILOT:FFT_LEN; % PILOT POSITION INDICES DATA_INDEX = 1:FFT_LEN; DATA_INDEX(PILOT_INDEX) = []; % DATA POSITION INDICES tic() C_BER = 0; % bit errors in each frame for FRAME_CNT = 1:NUM_FRAMES %---- TRANSMITTER ----------------------------------------- % SOURCE A = randi([0 1],1,NUM_BIT); % QPSK MAPPING QPSK_SEQ = 1-2*A(1:2:end) + 1i*(1-2*A(2:2:end)); F_SIG_NO_CP = zeros(1,FFT_LEN); % F STANDS FOR FREQUENCY DOMAIN F_SIG_NO_CP(DATA_INDEX) = QPSK_SEQ; F_SIG_NO_CP(PILOT_INDEX) = (1+1i)*ones(1,NUM_PILOT); % IFFT T_SIG_NO_CP = ifft(F_SIG_NO_CP); % INSERTING CYCLIC PREFIX T_SIG_CP = [T_SIG_NO_CP(end-CP_LEN+1:end) T_SIG_NO_CP]; %--------------- CHANNEL ----------------------------------------- % RAYLEIGH FREQUENCY SELECTIVE FADING CHANNEL FADE_CHAN = normrnd(0,FADE_STD_DEV,1,CHAN_LEN)+1i*normrnd(0,FADE_STD_DEV,1,CHAN_LEN); % FADE CHANNEL OUTPUT CHAN_OP_TEMP = conv(T_SIG_CP,FADE_CHAN); % AWGN AWGN = normrnd(0,NOISE_STD_DEV,1,FFT_LEN+CP_LEN+CHAN_LEN-1)+1i*normrnd(0,NOISE_STD_DEV,1,FFT_LEN+CP_LEN+CHAN_LEN-1); % AWGN OUTPUT T_REC_SIG = CHAN_OP_TEMP + AWGN; %---------------- RECEIVER ------------------------------------------ % CP & TRANSIENT SAMPLES REMOVAL T_REC_SIG(1:CP_LEN) = []; T_REC_SIG_NO_CP = T_REC_SIG(1:FFT_LEN); % PERFORMING THE FFT F_REC_SIG_NO_CP = fft(T_REC_SIG_NO_CP); %-------------------------------------------------------------------------- % FFT BASED CHANNEL ESTIMATION E_F_PILOT_POS = F_REC_SIG_NO_CP(PILOT_INDEX)./(1+1i); % 1-TAP EQUALIZATION E_T_PILOT_POS = ifft(E_F_PILOT_POS); % L_p point IFFT % DISCARDING SAMPLES AFTER LOCATION CHAN_LEN E_H_CHAN_LEN = E_T_PILOT_POS(1:CHAN_LEN); % ZERO PADDING AND TAKING ITS IIT E_F_H = fft(E_H_CHAN_LEN,FFT_LEN); % zero padding and FFT_LEN point FFT % CHANNEL SUBCARRIERS AT DATA POSITIONS E_F_H_DATA_POS = E_F_H(DATA_INDEX); %-------------------------------------------------------------------------- % ML DETECTION QPSK_SYM = [1+1i 1-1i -1+1i -1-1i]; QPSK_SYM1 = QPSK_SYM(1)*ones(1,FFT_LEN-NUM_PILOT); QPSK_SYM2 = QPSK_SYM(2)*ones(1,FFT_LEN-NUM_PILOT); QPSK_SYM3 = QPSK_SYM(3)*ones(1,FFT_LEN-NUM_PILOT); QPSK_SYM4 = QPSK_SYM(4)*ones(1,FFT_LEN-NUM_PILOT); DIST = zeros(4,FFT_LEN-NUM_PILOT); DIST(1,:)=(abs(F_REC_SIG_NO_CP(DATA_INDEX) - E_F_H_DATA_POS.*QPSK_SYM1)).^2; DIST(2,:)=(abs(F_REC_SIG_NO_CP(DATA_INDEX) - E_F_H_DATA_POS.*QPSK_SYM2)).^2; DIST(3,:)=(abs(F_REC_SIG_NO_CP(DATA_INDEX) - E_F_H_DATA_POS.*QPSK_SYM3)).^2; DIST(4,:)=(abs(F_REC_SIG_NO_CP(DATA_INDEX) - E_F_H_DATA_POS.*QPSK_SYM4)).^2; % COMPARING EUCLIDEAN DISTANCE [~,INDICES] = min(DIST,[],1); % MAPPING INDICES TO QPSK SYMBOLS DEC_QPSK_MAP_SYM = QPSK_SYM(INDICES); % DEMAPPING QPSK SYMBOLS TO BITS DEC_A = zeros(1,NUM_BIT); DEC_A(1:2:end) = real(DEC_QPSK_MAP_SYM)<0; DEC_A(2:2:end) = imag(DEC_QPSK_MAP_SYM)<0; % CALCULATING BIT ERRORS IN EACH FRAME C_BER = C_BER + nnz(A-DEC_A); end toc() BER = C_BER/(NUM_BIT*NUM_FRAMES)