2008/11/05 by Romain Couillet, Merouane Debbah, Mérouane Debbah +2
Computer Science · Engineering · Mathematics · #Advanced Wireless Communication Techniques #FOS: Computer and information sciences #FOS: Mathematics #Information Theory (cs.IT) #Probability (math.PR) #Wireless Communication Security Techniques #Wireless Signal Modulation Classification #cs.IT #math.IT #math.PR
paper · pdf · doi:10.48550/arxiv.0811.0778
15 pages, 11 figures
arxiv created 2008/11/05 · openalex publication_date 2008/11/05 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In this work, a new Bayesian framework for OFDM channel estimation is proposed. Using Jaynes' maximum entropy principle to derive prior information, we successively tackle the situations when only the channel delay spread is a priori known, then when it is not known. Exploitation of the time-frequency dimensions are also considered in this framework, to derive the optimal channel estimation associated to some performance measure under any state of knowledge. Simulations corroborate the optimality claim and always prove as good or better in performance than classical estimators.