mohatta2015.pdf

134 MAXIMUM LIKELIHOOD SEQUENCE DETECTION
16-QAM
0 5 10 15 20
Eb/NO (dB)
Figure 6.12 BER vs. E b /N 0 for 1G-QAM, root-raised-eosine pulso shaping (0.22 rolloff),
static, two-tap. symbol-spaced channel, with relative path strengths 0 and —1 dB, and path
angles 0 and !)() degrees, single feedback tap.
determined by summing the squares of the path coefficients. While the gain is
1.0 on average, it will take on random values. For each value, the channel gain
is used to scale the Eb/N» prior to evaluating the analytical expression. As the
analytical expression assumes no ISI, this gives the matched filter bound. Each
fading realization gives a different error rate. These error rates can then be averaged
in the simulator to determine an average error rate. Another way that matched
filter bound results were generated was by performing perfect ISI subtraction prior
to matched filtering (results labeled MFB).
Results for the TwoTSfade channel are given in Fig. 6.13. Note that the z-axis is
labeled average Eb/NO to emphasize that it is averaged over the fading. Compared
to the TwoTS results, the performance is worse for all receivers. While the fading
sometimes gives a higher SINR and sometimes a lower SINR, it is the lower SINR
error rates that dominate performance.
Compared to the static results, the gains of DFE over LE are smaller. This
is because performance is dominated by the cases when both paths fade, so that
the instantaneous SNR is lower and the performance differences between the two
approaches are less. Also notice that MF has a lower floor with fading.
With a fading channel, there are two reasons why certain fading realizations give
larger BER. One reason is that there is significant ISI (the two paths have similar
strengths). The other reason is that the total signal power is low (both paths fade
down at the same time). One way to isolate these two effects is to consider a system
with power control.