Low Complexity Turbo Equalization for High Data Rate Wireless Communications

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).