Since the wireless environment is time varying (i.e., delay spread, interference, and
so on) the STE weights should also adapt to the changing environment. The ESM collects the
eigenspectrum, operates on the subspaces and creates a structured covariance matrix. The term
structured is used here to emphasize that the estimated matrix is manipulated to contain the
desired properties.
In the following sections, we will present certain statistics of the space-time equalizer weights.
Specifically, the eigenspectra will be presented for a given channel condition. These results will show
that reduced rank signal processing techniques can perform better than the full rank techniques,
depending on the channel conditions.
6.2.1 Flat Fading Environment
In this section, we will derive the STE weights and present some simulation results. In doing so, we
hope to provide some insight into the effects of the environment on the receiver. This section will consider
a flat fading channel without the presence of interference. The signal at each of the two receive
antennas is given below, assuming independent fading on each antenna and s(k) representing the
desired signal.
(6.52)
(6.53)
The signal-to noise-ratio on each antenna is given as
(6.
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