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Efficient Preamble Design Technique for Millimeter-Wave Cellular Systems with Beamforming.

Dae Geun Han1, Yeong Jun Kim2, Yong Soo Cho3

  • 1School of Electrical and Electronic Engnineering, Chung-Ang University, Seoul 156-756, Korea. dae450@naver.com.

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|July 26, 2016
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Summary
This summary is machine-generated.

This study introduces a new preamble design for millimeter-wave (mmWave) cellular systems using Zadoff-Chu sequences. The technique efficiently reduces complexity in cell ID and beam ID detection without performance loss.

Keywords:
OFDMZadoff-Chu sequencebeam-trainingbeamformingmillimeter-wave

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Area of Science:

  • Wireless communication
  • Signal processing
  • Telecommunications engineering

Background:

  • Millimeter-wave (mmWave) cellular systems offer high bandwidth but face challenges in beam training.
  • Code Division Multiplexing (CDM)-based preambles reduce processing time but increase computational complexity for Cell ID (CID) and Beam ID (BID) searches.

Purpose of the Study:

  • To propose a novel preamble design for mmWave systems to enhance the number of detectable Cell/Beam IDs (CBIDs).
  • To develop an efficient CBID detection technique for the proposed preamble.
  • To reduce the computational complexity of CBID detection without compromising system performance.

Main Methods:

  • A new preamble sequence is constructed by combining two Zadoff-Chu (ZC) sequences.
  • An efficient CBID detection algorithm is developed for the proposed preamble structure.
  • Simulations were conducted using a simplified mmWave cellular system model.

Main Results:

  • The proposed preamble design significantly increases the number of available CBIDs.
  • The developed CBID detection technique offers a substantial reduction in computational complexity.
  • Simulations show no noticeable performance degradation compared to existing methods.

Conclusions:

  • The novel preamble design and detection technique effectively address the complexity challenges in mmWave cellular systems.
  • This approach enables more efficient beam training and system operation in mmWave networks.
  • The proposed method provides a practical solution for scalable mmWave deployments.