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Fast Beam Training Technique for Millimeter-Wave Cellular Systems with an Intelligent Reflective Surface
Qasim Sultan1, Yeong-Jun Kim2, Mohammed-Saquib Khan1
1School of Electrical and Electronics Engineering, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 06974, Korea.
Sensors (Basel, Switzerland)
|July 24, 2021
Summary
This study introduces a fast beam training technique for intelligent reflecting surface (IRS)-assisted millimeter-wave (mmWave) systems. The method simultaneously detects optimal beam pairs, significantly reducing overall training time.
Area of Science:
- Wireless Communication Systems
- Signal Processing
Background:
- Intelligent Reflecting Surfaces (IRS) enhance coverage and efficiency in wireless systems.
- IRS-assisted mmWave systems face long beam training times due to sequential link optimization.
- Current protocols struggle with the complexity of multiple base stations and mobile stations.
Purpose of the Study:
- To develop a fast beam training technique for IRS-assisted mmWave cellular systems.
- To enable simultaneous beam pair detection for Base Station (BS)-IRS and IRS-Mobile Station (MS) links.
- To reduce the overall beam training duration in complex multi-cell environments.
Main Methods:
- Proposed a novel fast beam training technique utilizing a uniform rectangular array.
- Introduced two distinct Beam Training Signals (BTSs): Zadoff-Chu sequence based BTS (ZC-BTS) and m-sequence based BTS (m-BTS).
- Analyzed the correlation properties and symbol time offset effects of ZC-BTS and m-BTS in multi-cell, multi-beam scenarios.
Main Results:
- The proposed technique successfully detects BS-IRS and IRS-MS beam pairs simultaneously.
- ZC-BTS and m-BTS effectively distinguish beams in multi-cell, multi-beam environments.
- Simulation results demonstrate a significant reduction in beam training time.
Conclusions:
- The presented fast beam training technique is effective for IRS-assisted mmWave systems.
- Simultaneous beam pair detection offers substantial improvements in training efficiency.
- The proposed BTSs and analysis provide a viable solution for complex wireless networks.
