Although the design intervals defined by the endpoints in
Table III give excellent performance over a wide range of
channel parameters, we investigated the possibility of having
the cognitive radio adjust the intervals in response to the
information that it learns from past transmissions. In particular,
we verified that a simple learning algorithm is effective in correcting
poor choices for the endpoints of the design intervals.
For this investigation, we intentionally selected endpoints that
would at times cause the protocol to use a code-modulation
combination whose rate is too high, which increases the packet
error probability and reduces the throughput. We describe
the algorithm for an adaptive transmission protocol that uses
the error count together with adjusted decision intervals to
choose among code-modulation combinations Dk, 1≤k≤n.If combination Dk is used for packet i and the resulting error
count is zi, then γ1,k,i and γ2,k,i denote the endpoints of the
decision intervals that are used with zi to decide which codemodulation
combination to select for packet i+1.
|
