Design and Performance Analysis of Low-Complexity Pilot-Aided OFDM Channel Estimators

2008 IEEE Wireless Communications and Networking Conference

2008

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An accurate estimate of the channel frequency response (CFR) needed for OFDM equalisation can be obtained using the linear minimum mean square error (MMSE) algorithm. However, for an optimal operation such an estimator requires real-time inversion of the CFR correlation matrix that is found to be impractical due to considerable increase of the receiver's complexity. In this article, we develop the ways of design of the MMSE channel estimator yielding near-optimum performance and being computationally efficient at the same time. The proposed technique is based on the transform-domain processing and tracking of the correlation of the channel impulse response (CIR) observation. The former feature allows reducing the size of the correlation matrix, whereas the latter one leads to a design form with no matrix inversions. Simulations show that the developed algorithm achieves performance close to the optimal MMSE estimator and is particularly beneficial for both the sample-spaced and the non-sample-spaced sparse multipath channels.

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“…The formula (8) is known from the related work [10] as the constrained least squares (CLS) estimator for the equipowered pilot signals.…”

Section: A Reduced-complexity Recursive Mmse Algorithmmentioning

confidence: 99%

Section: B Computational Complexitymentioning

confidence: 99%

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Reduced-Complexity Recursive MMSE Channel Estimator for the Wireless OFDM Systems

2008 IEEE Wireless Communications and Networking Conference

2008

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“…Note also that at the higher operational p SNR values the MSE difference between various l λ distributions of L principal components becomes smaller due to domination of the ρ factor in(7).…”

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confidence: 94%

“…Their designs are based on polynomial models [3], maximum likelihood [4] [5], least squares (LS) [6] [7] and minimum mean square error (MMSE) [6][7] [8][9] [10] criteria. It is also straightforward to use these estimators in the SM-MIMO configuration if identification at each SL is performed independently from the other SLs.…”

Section: Introductionmentioning

confidence: 99%

Optimal Training for the SM-MIMO-OFDM Systems with MMSE Channel Estimation

6th Annual Communication Networks and Services Research Conference (Cnsr 2008)

2008

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Spatially multiplexed multiple-input-multiple-output orthogonal frequency division multiplexing (SM-MIMO-OFDM) systems are expected to provide a considerable increase of transmission capacity paving the way for the next generation broadband wireless communication standards. Considered MIMO-OFDM receiver performs estimation of the channel state information based on transmission of pilots concurrently with data symbols. The channel estimates are subsequently used for data detection. In this paper we discuss optimal placement and number of pilot subcarriers and derive the closed-form expression for the optimal power allocation between pilot and data symbols. The latter factor is important as under total transmit energy constraint there is a trade-off between boosting power of the pilot symbols to gain more accurate channel estimates and maintaining higher signal-to-noise ratio at the data subcarriers to minimise probability of detection error in the assumption of sufficiently reliable channel state information. KeywordsSpatial multiplexing, multipath channels, minimum mean squared error, pilot-to-data power ratio

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Optimisation of the pilot-to-data power ratio in the wireless MIMO-OFDM system with low-complexity MMSE channel estimation

Computer Communications

2009