The process is a little different for analog and digital , so this will be primarily from the digital perspective . The process begins by taking any source sound file , video file , Web page , etc . and representing it as a binary string . From there we usually first compress the string . How we compress the information , and how we transmit the information are completely separate . Which is generally justified by sourcechannel separation , which states that we suffer no loss in rate by doing so . From there we apply the error correction code . This is where most of the magic happens . Here we take a k string binary sequence , and transform it into a n symbol output sequence where each sequence is spaced far apart . Think 0 as 000 and 1 as 111 . There would have be two errors before I could no longer correct as 010 is most likely 000 and 110 is most likely 111 . So now that our code can be easily corrected , we begin the modulation process . There are many many different ways of doing this , and a lot of misinformation . Hence I will stick with the abstract . For each symbol we are going to send , we associate a certain waveform . By signal processing techniques we can arbitrarily shape this waveform so that it fits in a particular frequency range . If we want each symbol on a different frequency , that is FSK . If we want the symbols to look the same but have different heights , that is amplitude shift keying ASK . So on and so on . Regardless of modulation chosen , the important part is how well the symbols can be distinguished . Obviously right , if I send a 1 I want to receive a 1 with high probability . The type of modulation used depends on the circumstances . FSK is really only used for low power communications , since it allows for me to increase the distance between any two symbols simply by spacing them at frequencies that are further apart . In general , all modulations can be seen as derivatives of OFDM and QAM . You may have heard of OFDM before as protocol , I am not using it in that sense , but the theoretical meaning of it . What OFDM and how it works , and why it is gosh darn spiffy are unfortunately tangential to this discussion though . Recapping modulation , each symbol such as 0 or 1 has an associated signal such as sin or cos which is sent out . We choose the signals to have maximum separation at the demodulator . The demodulator is typically implemented with matched filters which look for the waveforn transmitted . You can think of them like a card board cut out . Does the picture fit in this cutout ? Yes , we ' ll it must be this symbol . No , let me grab another cut out . Matched filter banks supply us with the probability a certain symbol was transmitted . We then pass this to the error correction decoder , which uses the distance between valid input sequences to find the correct message and out put it to the end user . The ratio of bits k to the n symbols transmitted , is known as the code rate . Since we sent k bits in n symbols , we have kn bitssymbol . The maximum value possible is determined by the capacity of the channel . And trying to go above this rate , sends the probability of error to 1 , even for small values above the maximum rate . While the terminology varies , this is one thing people may mean when they say strong converse . Not all channels have a strong converse , but the point to point does . Once again , the major magic part is the error correction code . Usually wireless communication has some nasty symbol error rates , think 14 or 13 symbols are received in error . As much as you try and change modulation scheme you only get very minimal gains . On the other hand , the error correction code usually drops the errors to infinitesimal probabilities . It should be pointed this is a birds eye view of a somewhat simplified communication system . Each category I discussed still has active research associated with it . And , unlike perhaps AM and FM , are not as easily understood . I mean , that ' s why people can get PhDs in these fields .