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Institutional Repository [SANDBOX]
Technical University of Crete
Technical University of Crete
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| URI: | http://purl.tuc.gr/dl/dias/98B935A1-77F9-434B-BCAF-B133C81B9013 | ||
| Year | 2012 | ||
| Type of Item | Conference Full Paper | ||
| License |
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| Bibliographic Citation | D. S. Papailiopoulos, G. Abou Elkheir, and G. N. Karystinos, “Maximum-likelihood blind PAM detection,” in Proc. IEEE - International Conference on Communications,(ICC '12) pp. 2283-2287, doi: 10.1109/ICC.2012.6364631 https://doi.org/10.1109/ICC.2012.6364631 | ||
| Appears in Collections |
Blind sequence detection offers significant gains over conventional symbol-by-symbol detection when channel knowledge is not available at the receiver. However, maximum-likelihood (ML) blind sequence detection is often intractable due to exponential complexity in the sequence length. In this work, we develop a polynomial-time ML blind sequence detector for pulse-amplitude modulation (PAM) transmissions in Rayleigh fading. Our detector follows an auxiliary-angle approach that reduces the exponential-size space of solution vectors to a polynomial-size set of candidate sequences; we prove that this significantly smaller set always contains the ML PAM sequence. Hence, with overall polynomial complexity the proposed detector solves the problem of identifying the ML PAM sequence in unknown Rayleigh fading.
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