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Link error prediction methods for multicarrier systems

Authors: Y.W. Blankenship; P.J. Sartori; B.K. Classon; V. Desai; K.L. Baum;

Link error prediction methods for multicarrier systems

Abstract

Multicarrier modulations such as OFDM with adaptive modulation and coding (AMC) are well suited for high data rate broadband systems that operate in multipath environments and are considered as promising candidates for future generation cellular systems (e.g., 4G). Cellular system performance is normally investigated with system level simulations that are computationally complex. For broadband multicarrier systems, incorporating a detailed physical layer emulator into the system simulator becomes impractical, so there is a need for simplified link performance predictors. However, due to the large variability of the channel in the frequency domain, two links with the same average SNR can experience drastically different performance, thus making it difficult to accurately predict the instantaneous link performance such as the frame error rate. In this paper, the accuracy of two FER prediction methods is studied: Packet error rate indicator (PER-indicator) and exponential effective SIR mapping (Exp-ESM). Both methods are shown to have accuracy within a few tenths of a dB under a wide range of modulation schemes, coding rates and channel types. These methods are then extended to handle more advanced link enhancements such as hybrid ARQ and Alamouti encoding. The Exp-ESM method has slightly better accuracy than the PER-indicator, and is the preferred link error predictor for a system simulator.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
77
Top 10%
Top 0.1%
Top 10%
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