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An effective link error prediction technique for MIMO-OFDM systems with ML receiver

Authors: Sung-Hyun Moon; Kyoung-Jae Lee; Jihoon Kim; Inkyu Lee;

An effective link error prediction technique for MIMO-OFDM systems with ML receiver

Abstract

In this paper, we propose an accurate link performance abstraction technique for multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing systems with maximum likelihood (ML) receiver. The performance of ML detection (MLD) is estimated by using capacity bounds of two simple linear receivers. To this end, we give a simple parametrization to compute the desired per-stream signal-to-noise ratio (SNR) values, which can be applied for both vertically and horizontally coded MIMO systems. Based on the per-stream SNR estimates, the block error rate performance for each encoding block is finally obtained using the received-bit information rate metrics. From extensive simulations, we verify that the proposed method is accurate in the MIMO-MLD link evaluation with very low computational complexity.

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selected citations
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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!
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