Why am I getting this error "not enough argument"

6 次查看（过去 30 天）
Hanojhan Rajahrajasingh
回答： Chunru 2022-10-13
Ran in:
close all ;
m =512; % Total number of OFDM symbols
N =1024; % Length of each OFDM symbol
M =4; % Size of the Constellation ( M can be 4 , 8 , 16 , 32 , 64 , 128 , 256)
pilotFrequency =8 ; % Pilot Symbol insertion frequency
E =2; % Energy of each Pilot Symbol
Ncp =256 ; % Length of the Cyclic Prefix
%Tx = qammod ('M',M ) ; % Choosing the modulation format as M - ary Quadrature Amplitude Modulation (M- QAM )
%Rx = qamdemod ('M',M) ; % Fixing up the demodulation format at the receiving end as M - ary QAM
% ACO - OFDM Transmitter
Data = randi ([0,M-1] ,m , N ); % Generation of Random bits Matrix of size m by N
for k1 =1: m
for m1 =1: N
if mod ( m1 ,2) ==0 % Performing Modulo operation to extract the even subcarriers
Data ( k1 , m1 ) =0; % Setting the Even Subcarriers to Zero
end
end
end
DataMod = qammod( Data , M);
%DataMod = modulate ( Tx , Data ) ; % Performing Data Modulation
DataMod_serialtoparallel = DataMod .'; % Performing Serial to Parallel Conversion
PLoc = 1: pilotFrequency :N ; % Fixing the location of Pilot carrires
DLoc = setxor (1: N , PLoc ) ; % Fixing the location of Data subcarriers
DataMod_serialtoparallel ( PLoc ,:) = E *DataMod_serialtoparallel ( PLoc ,:) ; % Inserting Pilot carriers
datamat = DataMod_serialtoparallel ; % Assigning the total data including the pilots to a variable called datamat
% Computation of Hermitian Symmetry Criteria
datamat (1 ,:) =0; % Assigning the First subcarrier to Zero
datamat (513 ,:) =0; % Assigning the Middle Subcarrier to Zero
datamat (514:1024 ,:) = flipud ( conj ( datamat (2:512 ,:) )) ; %Illustrating that only half of the subcarriers are exploited for data transmission as the remaining half are flipped omplex conjugate versions of the previous ones .
d_ifft = ifft (( datamat ) ) ; % Computation of IFFT operation
% Ensuring that only the positive portion of the signal is transmitted
for k2 =1: N
for m2 =1: m
if( d_ifft ( k2 , m2 ) <0)
d_ifft ( k2 , m2 ) =0;
end
end
end
d_ifft_paralleltoserial = d_ifft .'; % Parallel to Serial Conversion
CP_part = d_ifft_paralleltoserial (: ,end - Ncp +1: end) ; % Addition of Cyclic Prefix
ACOOFDM_CP =[ CP_part d_ifft_paralleltoserial ]; % Transmissin of ACO - OFDM signal
% VLC Channel Modeling
theta = 70; %LED semi - angle
ml = - log10 (2) / log10 ( cos ( theta ) ) ; % Computation of Lambertian Mode Number
APD =0.01; % Area of the photodiode
lx =5; ly =5; lz =3; % Size of the Dimensions of the Indoor Room Environment
h =2.15;
[ XT , YT ]= meshgrid ([ - lx /4 lx /4] ,[ - ly /4 ly /4]) ;
Nx = lx *5; Ny = ly *5;
x = linspace ( - lx /2 , lx /2 , Nx ) ;
y = linspace ( - ly /2 , ly /2 , Ny ) ;
[ XR , YR ]= meshgrid (x , y ) ;
D1 = sqrt (( XR - XT (1 ,1) ) .^2+( YR - YT (1 ,1) ) .^2+ h ^2) ; D2 = sqrt (( XR - XT (2 ,2) ) .^2+( YR - YT (2 ,2) ) .^2+ h ^2) ;
cosphi_A1 = h ./ D1 ;
receiver_angle = acosd ( cosphi_A1 ) ;
H_A1 =3600*(( ml +1) * APD .* cosphi_A1 .^( ml +1) ./(2* pi .* D1.^2) +( ml +1) * APD .* cosphi_A1 .^( ml +1) ./(2* pi .^2* D1.^2* D2 .^2) ) ; % Computation of VLC channel Impulse Response taking into consideration Non Line of Sight ( NLOS ) Environment
H_A2 = H_A1./ norm ( H_A1 )
H_A2 = 25×25
0.0343 0.0396 0.0448 0.0497 0.0536 0.0561 0.0570 0.0561 0.0536 0.0497 0.0449 0.0396 0.0343 0.0293 0.0247 0.0207 0.0172 0.0142 0.0118 0.0098 0.0081 0.0067 0.0056 0.0047 0.0039 0.0396 0.0461 0.0528 0.0589 0.0639 0.0672 0.0684 0.0672 0.0639 0.0589 0.0528 0.0462 0.0396 0.0335 0.0279 0.0232 0.0191 0.0157 0.0129 0.0106 0.0087 0.0072 0.0060 0.0050 0.0041 0.0448 0.0528 0.0608 0.0684 0.0746 0.0788 0.0803 0.0788 0.0746 0.0684 0.0608 0.0528 0.0449 0.0376 0.0311 0.0255 0.0209 0.0170 0.0139 0.0113 0.0093 0.0076 0.0063 0.0052 0.0043 0.0497 0.0589 0.0684 0.0774 0.0849 0.0899 0.0917 0.0899 0.0849 0.0774 0.0684 0.0589 0.0497 0.0413 0.0339 0.0276 0.0224 0.0182 0.0148 0.0120 0.0098 0.0080 0.0066 0.0054 0.0045 0.0536 0.0639 0.0746 0.0849 0.0935 0.0993 0.1013 0.0993 0.0935 0.0849 0.0747 0.0639 0.0536 0.0442 0.0361 0.0293 0.0237 0.0191 0.0154 0.0125 0.0101 0.0083 0.0068 0.0056 0.0046 0.0561 0.0672 0.0788 0.0899 0.0993 0.1056 0.1078 0.1056 0.0993 0.0899 0.0788 0.0672 0.0562 0.0462 0.0376 0.0304 0.0244 0.0197 0.0158 0.0128 0.0104 0.0084 0.0069 0.0057 0.0047 0.0570 0.0684 0.0802 0.0917 0.1013 0.1078 0.1101 0.1078 0.1013 0.0917 0.0803 0.0684 0.0571 0.0469 0.0381 0.0307 0.0247 0.0199 0.0160 0.0129 0.0104 0.0085 0.0069 0.0057 0.0047 0.0561 0.0672 0.0788 0.0899 0.0993 0.1056 0.1078 0.1056 0.0993 0.0899 0.0788 0.0672 0.0562 0.0462 0.0376 0.0304 0.0244 0.0197 0.0158 0.0128 0.0104 0.0084 0.0069 0.0057 0.0047 0.0536 0.0639 0.0746 0.0849 0.0935 0.0993 0.1013 0.0993 0.0935 0.0849 0.0747 0.0639 0.0536 0.0442 0.0361 0.0293 0.0237 0.0191 0.0154 0.0125 0.0101 0.0083 0.0068 0.0056 0.0046 0.0497 0.0589 0.0684 0.0774 0.0849 0.0899 0.0917 0.0899 0.0849 0.0774 0.0684 0.0589 0.0497 0.0413 0.0339 0.0276 0.0224 0.0182 0.0148 0.0120 0.0098 0.0080 0.0066 0.0054 0.0045
d_channell = filter ( H_A2 (1 ,1:2) ,1 , ACOOFDM_CP .') .';
% Illustration of channel effect on the transmitted ACO - OFDM signal
count =0;
snr_vector =0:1:30; % size of signal to noise ratio (SNR ) vector
for snr = snr_vector
SNR = snr + 10* log10 ( log2 (M ) ) ;
count = count +1 ;
ACOOFDM_with_chann = awgn(d_channell , SNR ,'measured') ; % Addition of AWGN
% Receiver of ACO - OFDM
ACOOFDM_removal_CP = ACOOFDM_with_chann (: , Ncp+1: N + Ncp );
% Removal of Cyclic Prefix
ACOOFDM_serialtoparallel = ACOOFDM_removal_CP .'; %Serial to Parallel Conversion
ACOOFDM_parallel_fft = fft ( ACOOFDM_serialtoparallel) ;
% Computation of FFT operation
% Channel Estimation
TransmittedPilots = DataMod_serialtoparallel ( PLoc,:) ; % Extracting the transmitted pilots
ReceivedPilots = ACOOFDM_parallel_fft ( PLoc ,:) ;
%Extracting the received pilot tones effected by channel
H_LS = ReceivedPilots ./ TransmittedPilots ; % Least Square Channel Estimation
for r =1:m
H_MMSE(: , r ) = MMSEesti(ReceivedPilots (: , r ) ,TransmittedPilots (: , r ), N, pilotFrequency, H_A2 (1 ,1:2), SNR);% Minimum Mean SquareError ( MMSE ) Channel Estimation
end
for q =1:m
HData_LS(: , q ) = interpolate ( H_LS (: , q ) .', PLoc ,N ,'spline ') ; % Interpolation
end
HData_LS_parallel1 = HData_LS .'; % Parallel to Serial Conversion
HData_MMSE_parallel1 = H_MMSE .';
ACOOFDM_SERIAL_LS = demodulate ( Rx ,(ACOOFDM_parallel_fft .') ./ HData_LS_parallel1 ) ; % Demodulation
ACOOFDM_SERIAL_MMSE = demodulate (Rx ,(ACOOFDM_parallel_fft .') ./( HData_MMSE_parallel1) ) ;
% Recovery of Pilots from the Original Transmitted signal and Received Signal
Data_no_pilots = Data (: , DLoc ) ;
Recovered_Pilot_LS = ACOOFDM_SERIAL_LS (: , DLoc ) ;
Recovered_Pilot_MMSE = ACOOFDM_SERIAL_MMSE (: , DLoc ) ;
% Computation of Bit Error Rate
[~ , recoveredLS( count ) ]= biterr ( Data_no_pilots(: ,2:255) , Recovered_Pilot_LS (: ,2:255) ) ;
[~ , recoveredMMSE( count ) ]= biterr ( Data_no_pilots (: ,2:255) , Recovered_Pilot_MMSE (: ,2:255) ) ;
end
Not enough input arguments.

Error in solution>MMSEesti (line 120)
snr = 10.^(SNR*0.1); Np=Nfft/Nps; k=1:Np;
% Plotting the BER curves
semilogy ( snr_vector , recoveredLS ,'rd -','LineWidth ' ,2) ;
hold on ;
semilogy ( snr_vector , recoveredMMSE ,'gs -','LineWidth ',2) ;
axis ([0 30 10^ -4 1]) ;
grid on ;
function [H_MMSE] = MMSEesti(Y,Xp,pilot_loc,Nfft,Nps,h,SNR)
% MMSE channel estimation function
% Inputs:
% Y = Frequency-domain received signal
% Xp = Pilot signal
% pilot_loc = Pilot location
% Nfft = FFT size
% Nps = Pilot spacing
% h = Channel impulse response
% SNR = Signal-to-Noise Ratio[dB]
% output:
% H_MMSE = MMSE channel estimate
snr = 10.^(SNR*0.1); Np=Nfft/Nps; k=1:Np;
H_tilde = Y(1,pilot_loc(k))./Xp(k); % LS estimate Eq.(6.12) or (6.8)
k=0:length(h)-1; %k_ts = k*ts;
hh = h*h'; tmp = h.*conj(h).*k; %tmp = h.*conj(h).*k_ts;
r = sum(tmp)/hh; r2 = tmp*k.'/hh; %r2 = tmp*k_ts.’/hh;
tau_rms = sqrt(r2-r^2); % rms delay
df = 1/Nfft; %1/(ts*Nfft);
j2pi_tau_df = 1i*2*pi*tau_rms*df;
K1 = repmat([0:Nfft-1].',1,Np); K2 = repmat([0:Np-1],Nfft,1);
rf = 1./(1+j2pi_tau_df*Nps*(K1-K2)); % Eq.(6.17a)
K3 = repmat([0:Np-1].',1,Np); K4 = repmat([0:Np-1],Np,1);
rf2 = 1./(1+j2pi_tau_df*Nps*(K3-K4)); % Eq.(6.17a)
Rhp = rf;
Rpp = rf2 + eye(length(H_tilde),length(H_tilde))/snr; % Eq.(6.14)
H_MMSE = transpose(Rhp*inv(Rpp)*H_tilde.'); % MMSE estimate Eq.(6.15)
function [H_interpolated] = interpolate(H,pilot_loc,Nfft,method)
% Input: H = Channel estimate using pilot sequence
% pilot_loc = Location of pilot sequence
% Nfft = FFT size
% method = ’linear’/’spline’
% Output: H_interpolated = interpolated channel
if pilot_loc(1)>1
slope = (H(2)-H_est(1))/(pilot_loc(2)-pilot_loc(1));
H = [H(1)-slope*(pilot_loc(1)-1) H]; pilot_loc = [1 pilot_loc];
end
if pilot_loc(end) <Nfft
slope = (H(end)-H(end-1))/(pilot_loc(end)-pilot_loc(end-1));
H = [H H(end)+slope*(Nfft-pilot_loc(end))];
pilot_loc = [pilot_loc Nfft];
end
if lower(method(1))=='l', H_interpolated=interp1(pilot_loc,H,[1:Nfft]);
else
H_interpolated = interp1(pilot_loc,H,[1:Nfft],'spline');
end
end
end

请先登录，再回答此问题。

回答（1 个）

Chunru
Chunru 2022-10-13
The number of input arguments is 6:
for r =1:m
H_MMSE(: , r ) = MMSEesti(ReceivedPilots (: , r ), TransmittedPilots (: , r ), N, ...
pilotFrequency, H_A2(1 ,1:2), SNR); % Minimum Mean SquareError ( MMSE ) Channel Estimation
end
But the function definition specifies 7 input arguments
function [H_MMSE] = MMSEesti(Y,Xp,pilot_loc,Nfft,Nps,h,SNR)

类别

在 Help Center 和 File Exchange 中查找有关 Test and Measurement 的更多信息

标签

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by