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Linear expansions for frequency selective channels in OFDM

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Linear expansions for frequency selective channels in OFDM.pdf (294.2Kb)
Date
2006
Author
Şenol, Hande
Çırpan, Hakan Ali
Panayırcı, Erdal
Abstract
Modeling the frequency selective fading channels as random processes we employ a linear expansion based on the Karhumen-Loeve (KL) series representation involving a complete set of orthogonal deterministic vectors with a corresponding uncorrelated random coefficients. Focusing on OFDM transmissions through frequency selective fading this paper pursues a computationally efficient pilot-aided linear minimum mean square error (MMSE) uncorrelated KL series expansion coefficients estimation algorithm. Based on such an expansion no matrix inversion is required in the proposed MMSE estimator. Moreover truncation in the linear expansion of channel is achieved by exploiting the optimal truncation property of the KL expansion resulting in a smaller computational load on the estimation algorithm. The performance of the proposed approach is studied through analytical and experimental results. We first exploit the performance of the MMSE channel estimator based on the evaluation of minimum Bayesian MSE. We also provide performance analysis results studying the influence of the effect of SNR and correlation mismatch on the estimator performance. Simulation results confirm our theoretical results and illustrate that the proposed algorithm is capable of tracking fast fading and improving performance. (c) 2005 Elsevier GmbH. All rights reserved.

Source

AEU-International Journal of Electronics and Communications

Issue

3

Volume

60

Pages

224-234

URI

https://hdl.handle.net/20.500.12469/1243
https://dx.doi.org/10.1016/j.aeue.2005.03.008

Collections

  • Araştırma Çıktıları / Scopus [1565]
  • Araştırma Çıktıları / WOS [1518]
  • Bilgisayar Mühendisliği / Computer Engineering [188]
  • Elektrik-Elektronik Mühendisliği / Electrical - Electronics Engineering [321]

Keywords

Bayesian channel estimation
OFDM systems
Linear expansions

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