Information content of a random variable Random variable x Outcome of a random experiment Discrete R V takes on values from a finite set of possible outcomes PMF: P(X=y)=Py) How much information is contained in the event X=y? Will the sun rise today Revealing the outcome of this experiment provides no information Will the Celtics win the NBa championship? Since this is unlikely, revealing yes provides more information than revealing Events that are less likely contain more information than likely events
Sampling Sampling provides a discrete-time representation of a continuous waveform Sample points are real-valued numbers In order to transmit over a digital system we must first convert into discrete valued numbers
The signal suffers an attenuation loss l Received power PR= PT/L Received snr=E,/No, Eb=Pr/Rb Antennas are used to compensate for attenuation loss Capture as much of the signal as possible
Noise is additional\unwanted \signal that interferes with the transmitted signal Generated by electronic devices The noise is a random process Each\sample \ of n(tis a random variable Typically, the noise process is modeled as\Additive White Gaussian noise”(AWGN) White: Flat frequency spectrur Gaussian noise distribution
