Mutual Information Metrics for Fast Link Adaptation in IEEE 802.11n

Jensen, Tobias Lindstrøm; Kant, Shashi; Wehinger, J.; Fleury, Bernard Henri

doi:10.1109/icc.2008.920

Cited by 24 publications

(23 citation statements)

References 7 publications

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“…4, the introduction of the additional term in (10) with λ(m) selected according to (11) significantly reduces the mean-square error (MSE) …”

Section: A Mean Mutual Information Per Coded Bit Mapping (Mmibm)mentioning

confidence: 99%

“…(13) The functions J(y) and J −1 (y) are given in (25) and (26) respectively in Appendix C. The parameter κ(m) is calibrated with the same method as used to obtain λ(m) (see (11)). For the special case of BPSK a modified version was already given in [9].…”

Section: B Mutual Information Effective Snr Mapping (Miesm)mentioning

confidence: 99%

“…We compare the effectiveness of these metrics by realistic throughput link-level simulations including channel estimation and feedback delay. We extend the investigations in [11] by comparing further metrics, presenting a solution to problems occurring with multiple packet lengths, and addressing the important issue of how to obtain accurate mappings. In contrast to [12] we include results on the PER estimation accuracy, obtain an exact expression for the MI between the coded bits and the log-likelihood ratios (LLRs), and provide comparison among state-of-the-art PER estimation methods, as opposed to the less accurate instantaneous SNR method [2].…”

Section: Introductionmentioning

confidence: 99%

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Fast Link Adaptation for MIMO OFDM

Jensen

Kant

Wehinger

et al. 2010

IEEE Trans. Veh. Technol.

102

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Abstract-We investigate link quality metrics (LQMs) based on raw bit-error-rate, effective signal-to-interference-and-noiseratio, and mutual-information (MI) for the purpose of fast link adaptation in communication systems employing orthogonal frequency division multiplexing and multiple-input multipleoutput (MIMO) antenna technology. From these LQMs the packet-error-rate (PER) can be estimated and exploited to select the modulation and coding scheme (MCS) among a class of candidate MCSs that achieves the maximum throughput for the current channel state under a specified target PER objective. We propose a novel MI-based LQM and compare the PERestimation accuracy obtained with this LQM with that resulting from using other LQMs by means of comprehensive Monte Carlo simulations. Search methods for the MCS in the class most suitable for a given channel state are presented. An algorithm for obtaining a practical upper bound on the throughput of any link adaptation scheme is proposed. The investigated LQMs are applied to the IEEE 802.11n standard with a 2x2 MIMO configuration and practical channel estimation. The proposed MI-based LQM yields the highest PER estimation accuracy and its throughput shows only 1.7 dB signal-to-noise-ratio (SNR) loss with respect to the upper bound, but up to 9.5 dB SNR gain compared to the MCS maximizing the throughput for the current noise variance.

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“…4, the introduction of the additional term in (10) with λ(m) selected according to (11) significantly reduces the mean-square error (MSE) …”

Section: A Mean Mutual Information Per Coded Bit Mapping (Mmibm)mentioning

confidence: 99%

Section: B Mutual Information Effective Snr Mapping (Miesm)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Fast Link Adaptation for MIMO OFDM

Jensen

Kant

Wehinger

et al. 2010

IEEE Trans. Veh. Technol.

102

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“…The effective SNR [22], [29]- [32], SNR eff , is a figure of merit of the OFDM scheme applied for block fading channels that maps the SNR for each subcarrier in a single SNR value that corresponds to the SNR of an AWGN channel.…”

Section: A Effective Snrmentioning

confidence: 99%

A comparison between OFDM and single-carrier with cyclic prefix using channel coding and frequency-selective block fading channels

Paula¹,

Panazio²

2011

Journal of Communication and Information Systems

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Abstract-This article aims to establish a performance comparison between the single-carrier with cyclic prefix (SCCP) and the orthogonal frequency division multiplexing (OFDM) for frequency selective block fading channels without channel information on the transmitter side and using error correcting codes. For the SCCP scheme, it will be considered both linear and decision-feedback equalizers implementations. We will assess both schemes bit-error rates and capacities for different modulations and coding rates using different approaches. Firstly, analytical results are obtained for a convex analysis framework based on the OFDM effective signal-to-noise ratio and the cutoff rate together with the Shannon capacity analysis. In addition, Monte Carlo simulations are evaluated, corroborating previous analytical results and giving further insights on the comparison.

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“…Authors in [10] propose an alternative measure called Mean MI Bit Mapping (MMIBM), as a link quality metric to be used for fast link adaptation and compare it against the MI effective SNR mapping (MIESM). In [11], we find a comparison between both measures by means of realistic link-level simulations including channel estimation and feedback delay. In addition, authors in [11] develop a methodology to obtain performance bounds for any fast link adaptation algorithm, i.e.…”

Section: Introductionmentioning

confidence: 99%