Abstract
Latent structure in the signals transmitted through dispersive channels (real or complex) was exploited to formulate the maximum a posteriori probability (MAP) equalization in closed form, which allowed robust integer processing and some benchmark results. Emphasis is mostly on the adaptive implementation of the equalizer on unknown channels, with particular attention to complexity and bit error rate (BER) performance. The latent structure, laid as rules underlying the channel templates, allowed further the design of an original robust hyper-sphere-based complexity reduction algorithm wherein the hyper-sphere radius is self-adjusting. Simulation results are provided on the algorithm behavior and on performance of the proposed adaptive equalizer.
Published Version
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