weighting each bit by the inverse of the variance. This requires the variance to be measured on a
bit by bit basis, which significantly complicates the receiver. This is similar to the chip decision
used in SESS because a rake receiver uses a sequence of soft decision receiver outputs to make a
bit decision. If any of these soft decision receiver outputs have a large variance, much like the bit
decision used in SESS, it will greatly affect the output of the bit.
From this chapter it can be seen that noise or fading in a channel with jamming affects
the BER at lower SNR greatly. The effect at high SNR is less seen, which skews the worst-case
jamming, making it no longer an inverse relationship with the envelope of the curves. Chip
decision is a sub-optimal way that can be used to help fight the worst-case jamming conditions.
It does not always outperform bit decision, as in many conditions the bit decision remains the
better system. The worst-case jamming depends on prior knowledge of the system, the decision
to use chip based decisions requires knowledge of the jamming. With knowledge of the duty
cycle, a decision could be made to switch to chip based decision to help improve performance.
Another method employs using algorithms that readjust the weight of the chips at the equalizer,
known as least mean square algorithms. If the peak power of the jammer is limited it is going to
affect the jamming performance at low ρ in both chip and bit decision. The bottom line is that
without knowing the specifics of a jamming channel (i.e. capabilities of jammer, current jammer
state, etc.), it is very difficult to determine which model is superior.