MIMO OFDM LSE 信道估计附matlab代码.zip

%% Help % In this code we consider the least square error channel estimation for a % MIMO OFDM system. The user have access to the design parameters of % the MIMO OFDM system and the channel state information. The L-tap % Rayleigh fading channel is considered between any pair of the transmit and % receive antenna. The mean squared error of the LSE channel obtained % by the simulation result is compared with theory. % % source paper : "Optimal Training Design for MIMO OFDM Systems in Mobile Wireless Channels" % % Author : Hamid Ramezani % Author's contact : http://ens.ewi.tudelft.nl/~ramezani/ % Matlab Vession : 7.13.0.564 (R2011b) % %====================================================================== % Inputs %====================================================================== % Input parameters are (if not set the defalt value will be set) % ofdm.Nb = 1e2; % number of blocks % ofdm.Nt = 2; % number of transmit antennas % ofdm.Nr = 4; % number of receive antennas % ofdm.K = 128; % number of subcarriers % ofdm.G = 1/4; % Guard interval percentage % ofdm.Mod = 4; % QPSK Modulation % ofdm.PSpace = 1; % subcarrier space between two pilots % channel parameters % chan.SNR_dB = 15; % signal to noise ratio % chan.L = 6; % number of taps in each transmit-receive antenna % control parameters % ofdm.ifDemodulateData = 1; % (1,0) if 1, the code demodulates the transmitted via LS data and calculates the BER % ofdm.ifDisplayResults = 1; % (1,0) if 1, display the results in the command window %====================================================================== % Outputs %====================================================================== % The main outputs are listed below % chan.MSE_Theory % Minimum squared error of LSE channel estimation in theory % chan.MSE_Simulation % Minimum squared error of LSE channel estimation in simulations % ofdm.BER % Bit Error Rate if ofdm.ifDemodulateData = 1