Say a narrow band signal n(t) has Power Spectral Density (PSD) S(f).
If the signal n(t) got multiplied by cos(2πFt), then what will the PSD of resulting signal in terms of S(f) be? Will this be S(f+F)+S(f−F)2 ?
Answer
Almost, but let's start at the beginning. If the random process N(t) has a power spectrum then it is at least wide-sense stationary (WSS), i.e., its mean and its autocorrelation function do not depend on time. However, the process
Z(t)=N(t)cos(2πfct)
is not stationary, and, consequently, it has no power spectrum (the mean of the random process Z(t) is given by E[N(t)cos(2πfct)]=E[N(t)]cos(2πfct) which clearly depends on time even if E[N(t)] does not, a similar reasoning can be made for the autocorrelation function).
Luckily, we're usually not interested in the power spectrum of the process (1), but rather in the power spectrum of the process
Y(t)=N(t)cos(2πfct+θ)
where θ is a random phase which is independent of N(t) and which is uniformly distributed on [0,2π). This random phase reflects the uncertainty of the carrier phase with respect to the process N(t). So adding a random phase is not only a "trick" that works well, but it actually reflects the nature of a modulated random process much better than the process (1), which assumes a known relationship between the carrier phase and the signal.
The process given by (2) is WSS, and its autocorrelation function can be computed as follows:
RYY(τ)=E[Y(t)Y(t+τ)]=E[N(t)cos(2πfct+θ)N(t+τ)cos(2πfc(t+τ)+θ)]=12E[N(t)N(t+τ)(cos(2πfcτ)+cos(2πfc(2t+τ)+2θ))]=12RNN(τ)cos(2πfcτ)+12RNN(τ)E[cos(2πfc(2t+τ)+2θ)]⏟=0=12RNN(τ)cos(2πfcτ)
where I've used the independence of N(t) and θ, and where RNN(τ)=E[N(t)N(t+τ)].
Finally, the power spectrum of Y(t) is given by the Fourier transform of (3):
SYY(f)=14[SNN(f−fc)+SNN(f+fc)]
where SNN(f) is the power spectrum of N(t).
In sum, if we add a random phase to the carrier then the modulated process is also WSS (if the baseband process is WSS), and its power spectrum is given by (4).
No comments:
Post a Comment