Interferer Detection and Cancellation in TDMA-Systems
Centre for Mathematical Sciences
Lund Institute of Technology,
In this thesis we investigate algorithms that reduce the influence of
interference in receivers in current Time Division Multiple Access systems
for mobile communications. We study the important case when the receiver
has just one antenna since this is the most common case in mobile receivers
of today. Further we have assumed that there is only one strong interferer.
First we determine if an interferer is present or not. We solve the problem
by tests based on assumptions on normality and properties of the covariance
function of the signal. With the assumption that the interferer transmits
during several bursts in a row we can detect and reject the hypothesis of
interference or no interference with high probability by using several of
the tests in combination.
When an interferer is detected we detect its training sequence and its relative
position to the desired signal. We have invented an algorithm that can detect
the sequence and the position with high probability for interesting signal
to interference ratio. The only assumptions are that the interferer must
be active during several bursts in a row and that the drift in time of the
interferer relative to the desired signal is slow.
Under the idealized case, i.e. synchronized interferer and signal and known
interferer training sequence, we show what can be gained in bit error rates
with two algorithms that are extensions of the Viterbi decoder, compared
with the Viterbi decoder. These algorithms take the interferer into account
and with that information the bit error rate is reduced dramatically for
low signal to interference ratio.
We also show what is lost in bit error rates when the two training sequences
only are partly overlapping compared with the synchronized case. Since the
bit error rate strongly depends on the channel estimates we improve the channel
estimates with a more powerful algorithm.
The most difficult channel estimation problem is when the two training sequences
do not overlap. First we show that the naive iterative estimation method
does not work. Then we give an algorithm that estimate both channel and symbols
at the same time which leads to satisfying channel estimates. That algorithm
can reduce the bit error rate dramatically for some cases of phase-shift
modulated signal compared with the one that are obtained with the Viterbi