Well, first, is your signal a random variable? Or more of a periodic signal (i.e. a sine wave)? If it's periodic, then just a simple FFT will suffice to give you the frequency. You only need to mess with power spectral density if you have a random signal.
As to why periodogram is not recommended... first, let's establish one fact: you can never actual measure power spectral density, because to do that you'd need an infinitely long sample of the data. You can only estimate power spectral density with a finite length sample. And, as it turns out, the periodogram is not a very good estimate. One is problem is that as you take longer and longer data samples, you would expect to get better and better estimates. But this does not happen with periodogram. The estimate remains noisy even for more and more data.
welch's method (pwelch()) is better because as you take more and more data, the estimate gets better. There are other methods, but pwelch is pretty reasonable, and I use it a lot.
Hope this helps. I've also got some tutorials on power spectral density on my website: http://www.mechanicalvibration.com/Random_vibrations.html
