To emphasize the fact that every periodic signal has both a time
      and frequency domain representation, we can exploit both to
      encode information into a signal.  Refer to
      the Fundamental Model of Communication.  We have
      an information source, and want to construct a transmitter that
      produces a signal
      
	xt
       
	  x
	  t
	.  For the source, let's assume we have information to
      encode every TT seconds.  For
      example, we want to represent typed letters produced by an
      extremely good typist (a key is struck every
      TT seconds).  Let's consider the
      complex Fourier series formula in the light of trying to encode
      information.
      
 
      We use a finite sum here merely for simplicity (fewer parameters
      to determine).  An important aspect of the spectrum is that each
      frequency component
      
	
	   
	    c 
	    k
	  
	 
      
	   
	    c 
	    k
	  
	
      can be manipulated separately: Instead of finding the Fourier
      spectrum from a time-domain specification, let's construct it in
      the frequency domain by selecting the
      
	
	   
	    c 
	    k
	  
	 
      
	   
	    c 
	    k
	  
	
      according to some rule that relates coefficient values to the
      alphabet.  In defining this rule, we want to always create a
      real-valued signal
      
	xt
      
	  x
	  t
	.  
      Because of the Fourier spectrum's 
      
properties, 
      the spectrum must have conjugate symmetry.  This requirement
      means that we can only assign positive-indexed coefficients
      (positive frequencies), with negative-indexed ones equaling the
      complex conjugate of the corresponding positive-indexed ones.
    
    
 Assume we have 
      NN letters to encode: 
      
	
	    
	      a
	      1
	    
	  …
	    
	      a
	      N
	    
	  
      
	  
	    
	      a
	      1
	    
	  
	  …
	  
	    
	      a
	      N
	    
	  
	.  
      One simple encoding rule could be to make a single Fourier
      coefficient be non-zero and all others zero for each letter. For
      example, if
      
	
	  
	    a
	    n
	  
	
      
	  
	    a
	    n
	  
	 
      occurs, we make   
       
	
	    
	      c
	      n
	    
	  =1
      
	  
	  
	    
	      c
	      n
	    
	  
	  1
	 
      and  
       
	
	    
	      c
	      k
	    
	  =0
      
	  
	  
	    
	      c
	      k
	    
	  
	  0
	,
      
	k≠n
      
	  
	  k
	  n
	.  
      In this way, the
       
	
	  
	    n
	    th
	  
	
      
	  
	    n
	    th
	  
	 
      harmonic of the frequency  
      
	1T
      
	  
	  1
	  T
	
      is used to represent a letter.  Note that the
      bandwidth—the range of frequencies required for
      the encoding—equals
      
	NT
      
	  
	  N
	  T
	.  Another possibility is to consider the binary
      representation of the letter's index.  For example, if the
      letter
      
	
	  
	    a
	    13
	  
	
      
	  
	    a
	    13
	  
	 occurs, converting 1313 to
      its base 2 representation, we have
      
	13=11012
      
	  
	  13
	  1101
	.        
      We can use the pattern of zeros and ones to represent directly
      which Fourier coefficients we "turn on" (set equal to one) and
      which we "turn off."
    
    
	
	  Compare the bandwidth required for the direct encoding
	  scheme (one nonzero Fourier coefficient for each letter) to
	  the binary number scheme.  Compare the bandwidths for a
	  128-letter alphabet.  Since both schemes represent
	  information without loss -- we can determine the typed
	  letter uniquely from the signal's spectrum -- both are
	  viable.  Which makes more efficient use of bandwidth and
	  thus might be preferred?
	
       
	  NN signals directly encoded
	  require a bandwidth of 
	    NT
	  
	      
	      N
	      T
	    .  
	  Using a binary representation, we need   
	  
	    log
		  2
		NT 
	  
	      
	      
		
		
		  2
		
		N
	      
	      T
	    .  
	  For 
	  
	    N=128
	  
	      
	      N
	      128
	    , 
	  the binary-encoding scheme has a factor of   
	   
	    7128=0.05
	  
	      
	      
		
		7
		128
	      
	      0.05
	    
	  smaller bandwidth.  Clearly, binary encoding is superior.
	
 
    
    
	
	  Can you think of an information-encoding scheme that makes
	  even more efficient use of the spectrum?  In particular, can
	  we use only one Fourier coefficient to represent
	  NN letters uniquely?
	
       
	  We can use NN different
	  amplitude values at only one frequency to represent the
	  various letters.
	
 
    
    We can create an encoding scheme in the frequency domain to
      represent an alphabet of letters.  But, as this
      information-encoding scheme stands, we can represent one letter
      for all time.  However, we note that the Fourier coefficients
      depend only on the signal's characteristics
      over a single period.  We could change the signal's spectrum
      every TT as each letter is
      typed. In this way, we turn spectral coefficients on and off as
      letters are typed, thereby encoding the entire typed
      document. For the receiver (see the Fundamental Model of
      Communication) to retrieve the typed letter, it would
      simply use the Fourier formula for the complex Fourier spectrum
      for each TT-second interval to
      determine what each typed letter was.  Figure 1 shows such a signal in the time-domain.
    
    
    
      In this Fourier-series encoding scheme, we have used the fact
      that spectral coefficients can be independently specified and
      that they can be uniquely recovered from the time-domain signal
      over one "period."  Do note that the signal representing the
      entire document is no longer periodic. By understanding the
      Fourier series' properties (in particular that coefficients are
      determined only over a TT-second
      interval, we can construct a communications system. This
      approach represents a simplification of how modern modems
      represent text that they transmit over telephone lines.
    
   
        
"Electrical Engineering Digital Processing Systems in Braille."