fskdemod

Frequency shift keying demodulation

Syntax

z = fskdemod(y,M,freq_sep,nsamp)

z = fskdemod(y,M,freq_sep,nsamp,Fs)

z = fskdemod(y,M,freq_sep,nsamp,Fs,symorder)

Description

z = fskdemod(y,M,freq_sep,nsamp) noncoherently demodulates the complex envelope y of a signal using the frequency shift key method.

z = fskdemod(y,M,freq_sep,nsamp,Fs) specifies the sampling frequency in Hz.

z = fskdemod(y,M,freq_sep,nsamp,Fs,symorder) specifies how the function assigns binary words to corresponding integers.

Examples

Modulation and Demodulation of an FSK Signal in AWGN

Pass an FSK signal through an AWGN channel and estimate the resulting bit error rate (BER). Compare the estimated BER to the theoretical value.

Set the simulation parameters.

M = 2;         % Modulation order
k = log2(M);   % Bits per symbol
EbNo = 5;      % Eb/No (dB)
Fs = 16;       % Sample rate (Hz)
nsamp = 8;     % Number of samples per symbol
freqsep = 10;  % Frequency separation (Hz)

Generate random data symbols.

data = randi([0 M-1],5000,1);

Apply FSK modulation.

txsig = fskmod(data,M,freqsep,nsamp,Fs);

Pass the signal through an AWGN channel

rxSig  = awgn(txsig,EbNo+10*log10(k)-10*log10(nsamp),...
    'measured',[],'dB');

Demodulate the received signal.

dataOut = fskdemod(rxSig,M,freqsep,nsamp,Fs);

Calculate the bit error rate.

[num,BER] = biterr(data,dataOut);

Determine the theoretical BER and compare it to the estimated BER. Your BER value might vary because the example uses random numbers.

BER_theory = berawgn(EbNo,'fsk',M,'noncoherent');
[BER BER_theory]

ans = 1×2

    0.1000    0.1029

Input Arguments

y — FSK-modulated output signal

vector | matrix

Complex baseband representation of a FSK-modulated signal, specified as vector or matrix of complex values. If y is a matrix with multiple rows and columns, fskdemod processes the columns independently.

Data Types: double | single
Complex Number Support: Yes

M — Modulation order

integer power of two

Modulation order, specified as an integer power of two.

Example: 2 | 4 | 16

Data Types: double

symorder — Symbol order

'bin' (default) | 'gray'

Symbol order, specified as 'bin' or 'gray'. This argument specifies how the function assigns binary vectors to corresponding integers.

• If symorder is 'bin', the function uses a binary-coded ordering.

• If symorder is 'gray', the function uses a Gray-coded ordering.

Data Types: char

freq_sep — Desired separation between frequencies

positive scalar

Desired separation between frequencies, specified in Hz. By the Nyquist sampling theorem, freq_sep and M must satisfy (M-1)*freq_sep <= 1.

Data Types: double

nsamp — Number of samples per output symbol

positive scalar greater than 1

Number of samples per output symbol, specified as a positive scalar greater than 1.

Data Types: double

Fs — Sample rate

1 Hz (default) | positive scalar

Sample rate, specified as a positive scalar.

Data Types: double

Output Arguments

z — Output signal

vector | matrix

Output signal, returned as a vector or matrix of positive integers. The elements of z have values in the range of [0, M – 1].

Example: randi([0 3],100,1)

Data Types: double

References

[1] Sklar, Bernard. Digital Communications: Fundamentals and Applications. 2nd ed. Upper Saddle River, N.J: Prentice-Hall PTR, 2001.

Version History

Introduced before R2006a