Para acceder a los documentos con el texto completo, por favor, siga el siguiente enlace: http://hdl.handle.net/10230/20435

Sequential estimation of multipath MIMO-OFDM channels
Angelosante, Daniele; Biglieri, Ezio; Lops, Marco
Universitat Pompeu Fabra
Wireless “MIMO” systems, employing multiple transmit and receive antennas, promise a significant increase of channel capacity, while orthogonal frequency-division multiplexing (OFDM) is attracting a good deal of attention due to its robustness to multipath fading. Thus, the combination of both techniques is an attractive proposition for radio transmission. The goal of this paper is the description and analysis of a new and novel pilot-aided estimator of multipath block-fading channels. Typical models leading to estimation algorithms assume the number of multipath components and delays to be constant (and often known), while their amplitudes are allowed to vary with time. Our estimator is focused instead on the more realistic assumption that the number of channel taps is also unknown and varies with time following a known probabilistic model. The estimation problem arising from these assumptions is solved using Random-Set Theory (RST), whereby one regards the multipath-channel response as a single set-valued random entity.Within this framework, Bayesian recursive equations determine the evolution with time of the channel estimator. Due to the lack of a closed form for the solution of Bayesian equations, a (Rao–Blackwellized) particle filter (RBPF) implementation ofthe channel estimator is advocated. Since the resulting estimator exhibits a complexity which grows exponentially with the number of multipath components, a simplified version is also introduced. Simulation results describing the performance of our channel estimator demonstrate its effectiveness.
The work of E. Biglieri was supported by the Spanish Ministery of Education and Science under Project TEC2006-01428/TCM, and by the STREP project No. IST-026905 (MASCOT) within the 6th framework program of the European Commission.
02-07-2013
Sistemes MIMO
Comunicació sense fil, Sistemes de
Bayes theory
Channel estimation
MIMO-OFDM
Particle filtering
Random finite set theory
Sequential Monte Carlo
© 2009 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.The final published article can be found at http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=4808329
Artículo
info:eu-repo/semantics/publishedVersion
Institute of Electrical and Electronics Engineers (IEEE)
         

Mostrar el registro completo del ítem