Tree-search based quasi-ML detection for high-speed railway channel

Seong Guen Park, Jongwoo Lee, Taehyun Jeon

Research output: Contribution to journalArticlepeer-review

Abstract

The data traffic is expected to increase due to its various functions related to the railway system. One of the solutions is the adoption of the SDM (Spatial Division Multiplexing) which improves the data rate with multiple antennas. However, the computational load of the system should be tolerable for the detection of the data. In this paper, the QRM-MLD is considered which one of the sub-optimal detection techniques. Simulation is carried out to analyze the performance of the QRM-MLD in the viaduct scenario. The results show that consideration of the detection complexity as well as the target SNR should be taken into account for achieving the required performance in the high-speed railway channels.

Original languageEnglish
Pages (from-to)1107-1111
Number of pages5
JournalInformation (Japan)
Volume18
Issue number3
StatePublished - 1 Mar 2015

Keywords

  • K-factor
  • QRM-MLD
  • Rician fading model
  • SDM

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