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MIMO Detector Based on Viterbi Algorithm

Authors: Jin Lee; Sin-Chong Park;

MIMO Detector Based on Viterbi Algorithm

Abstract

Suboptimal detectors of multiple-input multiple-output (MIMO) have been studied because the implementation of the optimum detector, the maximum-likelihood (ML) detector, has so far been considered infeasible for high-rate system. Sphere decoder (SD) using depth-first tree searching and K-best algorithm are used for near optimum detector. SD has the non-deterministic computational throughput and K-best requires the sorting unit whose complexity is significantly high when a large K is used together with high modulation constellation. In this paper, we propose a MIMO detector employing Viterbi algorithm instead of tree searching. This detector can keep the computational throughput constant and reduce the complexity because the sorting is not required. In the simulation, we analyze the advantage and the drawback of the proposed detector in the environment of IEEE 802.11n system.

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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!
1
Average
Average
Average
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