21

# 3.4 Introduction to Iterative Detectors

# Iterative decoding can be described as a decoding technique utilizing a soft-output

decoding algorithm that is iterated several times to improve the bit error performance of a coding

scheme, with the goal of obtaining true maximum-likelihood decoding, with less decoder

complexity [4]. Because there is memory within the SESS modulation, it is a natural candidate

for the Maximum Likelihood Sequence Estimation (MLSE) detection based on the Viterbi

algorithm. MLSE detection improves the system performance by estimating the sequence of the

received signals. However, the number of states in the Viterbi algorithm decoder grows

exponentially with the spreading factor, as can be seen in the trellis diagram of SESS when N = 4

in Figure 8 on the next page [24]. An iterative detection scheme can be used instead to reduce

the complexity to a linear order of the spreading factor, which achieves performance very close

to that of the MLSE detector. The iterative detector is also able to be improved in fading

channels by adding a chip-interleaver as discussed in [25].

3.5 Iterative Detector Design

# As describe in the previous section, the iterative decoder has a complexity linear to that

of the spreading code. The design used requires N+1 storage of the received data bits. The

definition of a SESS systems states that the spreading codes are generated from the information

being transmitted. If we view the first bit after the encoder (called Bit 1), then we can write the