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Rapid Homogeneous Detection of Biological Assays Using Magnetic Modulation Biosensing System
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Efficient Deep Learning-Based Detection Scheme for MIMO Communication Systems.

Roilhi F Ibarra-Hernández1, Francisco R Castillo-Soria1, Carlos A Gutiérrez1

  • 1Faculty of Science, Autonomous University of San Luis Potosí, Av. Chapultepec 1570, Privadas del Pedregal, San Luis Potosí 78295, Mexico.

Sensors (Basel, Switzerland)
|February 13, 2025
PubMed
Summary
This summary is machine-generated.

Deep learning (DL) offers efficient signal detection for Multiple-Input Multiple-Output (MIMO) systems. Novel DL schemes reduce complexity and bit error rate (BER) for future wireless communications.

Keywords:
BER performanceMIMO systemsML criteriondeep learningdetectiondetection complexitylabeling

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Area of Science:

  • Wireless Communication
  • Signal Processing
  • Machine Learning

Background:

  • Multiple-Input Multiple-Output (MIMO) is crucial for next-gen wireless systems.
  • Detector complexity in MIMO systems increases with antenna count, posing challenges for massive MIMO.
  • Balancing detection complexity and bit error rate (BER) is essential.

Purpose of the Study:

  • To develop an efficient deep learning (DL)-based signal detection strategy for MIMO systems.
  • To introduce novel DL schemes that improve upon conventional methods in terms of complexity and performance.
  • To evaluate the trade-off between detection complexity and BER performance.

Main Methods:

  • A DL-based signal detection strategy incorporating a novel input signal labeling preprocessing stage.
  • Proposal and evaluation of two new schemes: OH per antenna (OHA) and direct symbol encoding (DSE).
  • Comparison of proposed schemes against conventional one-hot (OH) and maximum likelihood (ML) methods.

Main Results:

  • The OHA and DSE schemes achieved an F1-score of 0.97 in classification performance.
  • Both proposed schemes exhibit lower computational complexity than conventional OH and ML schemes.
  • BER performance losses for OHA and DSE are less than 1 dB and 2 dB, respectively, compared to the OH scheme.

Conclusions:

  • The proposed DL-based strategy effectively reduces detection complexity in MIMO systems.
  • The OHA and DSE schemes offer a favorable trade-off between BER performance and computational cost.
  • This approach is suitable for adaptive wireless systems with limited computational resources.