Abstract
Soft interference cancellers (SICs) have been proposed in the literature as a means for reducing the computational complexity of the so-called
turbo equalization receiver architecture. Soft-input-soft output (SISO)
equalization algorithms based on linear filters have a tremendous complexity advantage over trellis-diagram-based SISO equalizers, especially for
high-order modulations and long-delay spread frequency selective channels. In this paper, we modify the way in which the SIC incorporates soft
information. In existing literature the input to the cancellation filter is
the expectation of the symbols based solely on the apriori probabilities
coming from the decoder, whereas here we propose to use the conditional
expectation of those symbols, given both the apriori probabilities and
the received sequence. This modification results in performance gains at
the expense of increased computational complexity, as compared to previous SIC-based schemes. However, by introducing an approximation to
the aforementioned algorithm a linear complexity SISO equalizer can be
derived. Simulation results for an 8-PSK constellation and hostile radio channels have shown the effectiveness of the proposed algorithms in
mitigating the intersymbol interference (ISI).