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Complex Baseband Representation of Bandpass Signals  4.9

                      integer, e.g., 2 cos(2πn) = 2 and sin(2πn) = 0. Likewise t = n/f m + 1/(4 f m ) corresponds
                      to the point x z (t) = (0, 1).




          4.4 Spectral Characteristics of the Complex Envelope
          4.4.1 Basics
                      It is of interest to derive the spectral representation of the complex baseband
                      signal, x z (t), and compare it to the spectral representation of the bandpass
                      signal, x c (t). Assuming x z (t) is an energy signal, the Fourier transform of x z (t)
                      is given by

                                               X z (f ) = X I (f ) + jX Q (f )            (4.9)

                      where X I (f ) and X Q (f ) are the Fourier transform of x I (t) and x Q (t), respec-
                      tively, and the energy spectrum is given by

                                                2                             ∗
                                                                              Q
                                 G x z  (f ) =|X z (f )| = G x I  (f ) + G x Q (f ) + 2 [X I (f )X (f )]  (4.10)
                                          (f ) are the energy spectrum of x I (t) and x Q (t), respectively.
                      where G x I  (f ) and G x Q
                      The signals x I (t) and x Q (t) are lowpass signals with a one-sided bandwidth of
                                                                (f ) can only take nonzero values
                      less than B T /2 so consequently X z (f ) and G x z
                      for | f | < B T /2.



                      EXAMPLE 4.3
                      Consider the case when x I (t) is set to be the message signal from Example 2.3 (com-
                      puter generated voice saying “bingo”) and x Q (t) = cos(2000πt). X I (f ) will be a lowpass
                      spectrum with a bandwidth of 2500 Hz while X Q (f ) will have two impulses located
                      at ±1000 Hz. Figure 4.8 shows the measured complex envelope energy spectrum for
                      these lowpass signals. The complex envelope energy spectrum has a relation to the
                      voice spectrum and the sinusoidal spectrum exactly as predicted in Eq. (4.10). Note
                      here B T = 5000 Hz.


                        Equation (4.9) gives a simple way to transform between the lowpass signal
                      spectrums to the complex envelope spectrum. A similar simple formula exists
                      for the opposite transformation. Note that x I (t) and x Q (t) are both real signals
                      so that X I (f ) and X Q (f ) are Hermitian symmetric functions of frequency. It is
                      straightforward to show


                                                          ∗
                                                                   ∗
                                              X z (− f ) = X (f ) + jX (f )
                                                                   Q
                                                          I
                                                                                         (4.11)
                                                ∗
                                              X (− f ) = X I (f ) − jX Q (f )
                                                z
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