Conclusion and Future Work
8.2 Potential Future Work
There are several possible extension for our research:
• Construct MMSE error model to discuss how to improve the performance.
• Try other kinds of techniques to estimate channel response that more suitable for MIMO system.
• Optimize the performance on DSP.
• In this thesis, we do not consider the influence of intercarrier interference (ICI). The ICI simulation can be involved in the future.
• Use model base method to calculate cross-correlation to improve Wiener filtering.
If we want to use model base method, the first thing we want to know is the maximum Doppler frequency of the mobile station. In [30] shows the method that using pilots to calculate velocity. Since we know the time domain correlation is
rt(l) = J0(2πfmaxlTs) (8.1)
then we can calculate the pilot correlation in time domain, and find out which neighbor two pilots correlation cause zero crossing and the time cause zero crossing called T0. Since The smallest positive zero crossing point of the Bessel function J0(x) occurs at x = 2.405. An estimation for the user maximum Doppler frequency can be obtained by
fmax = 2.405 2πT0
. (8.2)
But its defect is that it needs long time buffer to get real time domain correlation. Besides time domain correlation, we also need to know frequency domain correlation. As mention in chpter 3, for an exponentially decaying multipath power delay profile, the frequency domain correlation is
rf(k) = 1
1 + j2πτrmsk/T. (8.3)
In [31] it mention the meathod of calculating τrms by using pilots.
By utilizing above two methods, we might improve the Wiener filtering by using model base method.
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