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Geometrical Synthesis of Sparse Antenna Arrays Using Compressive Sensing for 5G IoT Applications.

Giulia Buttazzoni1, Fulvio Babich1, Francesca Vatta1

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Summary

This study introduces a new algorithm for sparse antenna arrays to support 5G Internet of Things (IoT) communications. It efficiently designs low-cost beamforming antenna systems for millimeter-wave (mmWave) frequencies.

Keywords:
antenna arrayscompressive sensinggeometrical synthesispower pattern synthesissparse arrays

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Area of Science:

  • Electrical Engineering
  • Wireless Communications
  • Antenna Theory

Background:

  • The fifth-generation (5G) cellular network aims to support billions of Internet of Things (IoT) devices.
  • Millimeter-wave (mmWave) channels, crucial for 5G, suffer from significant signal attenuation.
  • Beamforming antenna systems are necessary to overcome these mmWave channel losses.

Purpose of the Study:

  • To propose an iterative algorithm for designing sparse antenna arrays.
  • To enable derivation of antenna element number, amplitudes, phases, and positions.
  • To meet far-field pattern constraints for 5G mmWave IoT applications.

Main Methods:

  • Utilizes a compressive sensing approach.
  • Transforms a non-convex optimization problem into a convex one.
  • Employs an iterative algorithm for sparse antenna array synthesis.

Main Results:

  • Successfully derives optimal sparse antenna array parameters.
  • Demonstrates suitability for 5G IoT mmWave applications through numerical examples.
  • Compares favorably against existing methods for pattern and aperture synthesis.

Conclusions:

  • The proposed iterative algorithm is effective for designing sparse antenna arrays for 5G mmWave IoT.
  • The method addresses the need for low-cost, beamforming antenna systems in future wireless networks.
  • The convex optimization formulation simplifies the design process for complex antenna configurations.