PER-prediction for PHY mode selection in OFDM communication systems

Lampe, M.; Giebel, T.; Rohling, Hermann; Zirwas, Wolfgang

doi:10.1109/glocom.2003.1258196

Cited by 42 publications

(33 citation statements)

References 5 publications

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“…To reduce the complexity of the PER prediction, a common approach is to map these parameters onto a single link quality metric (LQM) [3][4][5][6][7] which could be associated to the PER by means of a look-up table. For each MCS, it is possible to define a range of LQM values over which the MCS maximizes throughput.…”

Section: St P R(p Ermentioning

confidence: 99%

Link adaptation based on adaptive modulation and coding for multiple-antenna OFDM system

Tan

Sun

2008

IEEE J. Select. Areas Commun.

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Abstract-In this paper, we study the problem of link adaptation based on adaptive modulation and coding for multipleantenna OFDM system in slow fading channel. Based on the extrinsic information transfer analysis, we give an accurate packet error rate prediction with channel estimation errors. This method uses Gaussian approximation to characterize the output of the detector and decoder. We also discuss approaches for searching and selecting the best modulation and coding scheme for the link adaptation algorithm. Finally, the performance of the proposed link adaptation algorithm is studied for the IEEE 802.11n multiple-antenna OFDM system. Good system throughput are achieved using the proposed method, compared to the SNR based algorithm Index Terms-MIMO-OFDM, adaptive modulation and coding, Gaussian approximation, PER prediction.

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Section: St P R(p Ermentioning

confidence: 99%

Link adaptation based on adaptive modulation and coding for multiple-antenna OFDM system

Tan

Sun

2008

IEEE J. Select. Areas Commun.

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“…Robust one-dimensional mappings have been widely studied in the literature, considering methods such as uncoded BER/RawBER [6], effective SNR [7], mutual-information (MI) [8], [9] and PER indicator [10]. We propose a novel link quality metric (LQM) for MIMO-OFDM to be used for FLA. We call it mean MI bit mapping (MMIBM).…”

Section: Introductionmentioning

confidence: 99%

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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“…Due to frequency selectivity, the qualities of the sub-carriers within a SB may differ; the indicator x i,n should provide a good collective representation of the qualities for all the sub-carriers within the n-th SB Blankenship et al (2004); Ericsson (2003); Lampe & Rohling (2003). For convenience, we assume that the MCS rate R (c) j log 2 M j increases monotonically with j and that the rate of MCS 1 is zero.…”

Section: System Modelmentioning

confidence: 99%

Downlink Resource Scheduling in an LTE System

Kwan¹,

Leung²,

Zhang³

2010

Mobile and Wireless Communications Physical Layer Development and Implementatiom

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The problem of allocating resources to multiple users on the downlink of a Long Term Evolution (LTE) cellular communication system is discussed. An optimal (maximum throughput) multiuser scheduler is proposed and its performance is evaluated. Numerical results show that the system performance improves with increasing correlation among OFDMA subcarriers. It is found that a limited amount of feedback information can provide a relatively good performance. A sub-optimal scheduler with a lower computational complexity is also proposed, and shown to provide good performance. The sub-optimal scheme is especially attractive when the number of users is large, as the complexity of the optimal scheme may then be unacceptably high in many practical situations. The performance of a scheduler which addresses fairness among users is also presented.

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PER-prediction for PHY mode selection in OFDM communication systems

Cited by 42 publications

References 5 publications

Link adaptation based on adaptive modulation and coding for multiple-antenna OFDM system

Link adaptation based on adaptive modulation and coding for multiple-antenna OFDM system

Fast Link Adaptation for MIMO OFDM

Downlink Resource Scheduling in an LTE System

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