mohatta2015.pdf
signal processing from power amplifier operation control point of view
signal processing from power amplifier operation control point of view
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176 PRACTICAL CONSIDERATIONS<br />
adaptive MMSE linear equalization<br />
direct adaptation<br />
indirect adaptation<br />
parametric estimation<br />
nonparametric estimation<br />
Figure 8.1<br />
Design choiera for adaptive MMSE LE.<br />
Which adaptation approach we should use depends on several things. First, it<br />
depends on the transmit signal structure. Some systems are designed with a certain<br />
adaptation approach in mind. For example, periodic placement of pilot symbol<br />
clusters is convenient for indirect adaptation, as the channel can be estimated at<br />
each pilot symbol cluster and interpolated over the intervening intervals. A second<br />
consideration is performance, which tends to favor indirect adaptation. When the<br />
channel is varying rapidly, it can be easier to track the channel coefficients rather<br />
than the equalizer weights. A third consideration is complexity, which tends to<br />
favor direct adaptation.<br />
So far, we've focused on MMSE linear equalization. For DFE, we can use direct<br />
or indirect adaptation to determine the forward filter and backward filter weights.<br />
For MLSD, MAPSD, and MAPPD, we can use channel estimation and noise power<br />
estimation (for MAPSD and MAPPD) to obtain the necessary parameters.<br />
8.2.1.1 Channel quality In addition to parameters needed to equalize the received<br />
signal, one may also need to estimate channel quality. While there are various<br />
definitions of channel quality, we are interested in the definition that includes the<br />
effects of the equalizer. For example, channel quality could be defined as the output<br />
SINR of a linear equalizer.<br />
Estimating channel quality is important because the receiver may need to feed<br />
back such information to the transmitter, in essence telling the transmitter how<br />
well the equalizer is doing (or will do in the future). This information can be used<br />
at the transmitter to adapt the transmit power (power control) or the data rate<br />
(rate adaptation).<br />
8.2.2 Equalizer selection<br />
So we have learned about MF, LE, DFE, MLSD, MAPSD, and MAPPD. Which<br />
one should we build? There is no easy answer, but there are basically two things<br />
to consider: performance and complexity. Complexity translates into cost, size and<br />
power consumption of the device you are building. Performance translates into<br />
coverage (at which locations will the receiver work) for services like speech and<br />
data rate (how fast the data is sent) for services like Internet web browsing. In<br />
general, the better an equalizer performs, the more complex it is. Thus, there is a<br />
trade-off between performance and complexity.