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arXiv · 1610.03362

Modulation Classification via Subspace Detection in MIMO Systems

Hadi Sarieddeen·Mohammad M. Mansour·Ali Chehab
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Abstract

The problem of efficient modulation classification (MC) in multiple-input multiple-output (MIMO) systems is considered. Per-layer likelihood-based MC is proposed by employing subspace decomposition to partially decouple the transmitted streams. When detecting the modulation type of the stream of interest, a dense constellation is assumed on all remaining streams. The proposed classifier outperforms existing MC schemes at a lower complexity cost, and can be efficiently implemented in the context of joint MC and subspace data detection.

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Hadi Sarieddeen, Mohammad M. Mansour, Ali Chehab. 2016-10-11. Modulation Classification via Subspace Detection in MIMO Systems. https://arxiv.org/abs/1610.03362

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