Abstract
In this letter, a Sum-Product algorithm (SPA) utilizing soft distances is shown to be more resilient to impulsive noise than conventional likelihood-based SPAs, when the noise distribution is unknown. An efficient version of the soft distance SPA is also developed but with half the storage requirements and running time.
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