Digital Signal Processing Reference
In-Depth Information
maximum latency
unencoded data ra
te
BER accepted by data link layer
granularity of coding rate
coding rate
link distance
transmission power
background channel noise
channel capacity (Shannon)
battery power
computational res
ources
viterbi decoder implementation
symbol rate
spectral footprint
Goal: maximize
effective throughput
analog circuit constraints
implementation losses
blocker levels
l
inearity
modulation type
modulation depth
bit-to-symbol mapping
resource-sharing
multi-user environment
multiplexing overhead
Figure 2.1.
Trade-offs and constraints in the design of a wireless application.
An ill-considered choice of one of these parameters results in a
suboptimal use of the capabilities of the wireless channel.
At this moment, it is certainly interesting to note that the data rate of the en-
coded bit stream itself can be higher than the maximum throughput capabilities
of the wireless channel. This observation can be explained by realizing that if
the coding rate
5
is less than unity, each of the data bits produced by the cod-
ing algorithm contains less than 1 equivalent bit of unencoded 'information'.
The remaining part is redundant information obtained from the same original
data. As such, more encoded bits are injected into the channel, but the effective
throughput of information always stays below the theoretical channel capacity.
2.1
Why error coding works
Remark that in most error coding schemes, it is not possible to relate a sin-
gle input bit to a certain number of encoded bits. The encoding algorithm will
spread the information of each unencoded bit over a longer sequence of en-
coded output bits. The length of the sequence over which the energy of one sin-
gle input bit is being spread strongly depends on the number of internal states
5
Typical values for coding rates are 1
/
2 (1 in, 2 out), 9
/
16, 2
/
3and3
/
4. A lower coding rate means that
the output bit stream contains more redundant information.
