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Related Concept Videos

Upsampling01:22

Upsampling

Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...
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Downsampling01:20

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SINR-Based User Clustering for Downlink NOMA Systems with Limited Channel Information.

Wonkyu Kim1, Ngoc-Thanh Nguyen2, Taehyun Jeon1

  • 1Department of Electrical and Information Engineering, Seoul National University of Science and Technology, Seoul 01811, Republic of Korea.

Sensors (Basel, Switzerland)
|May 27, 2026
PubMed
Summary

This study introduces a novel user clustering and power allocation scheme for hybrid beamforming and non-orthogonal multiple access systems operating with partial channel state information. The proposed method enhances system throughput and fairness by optimizing user selection based on signal-to-interference-plus-noise ratio feedback.

Keywords:
clusteringhybrid beamformingmmWavenon-orthogonal multiple accesspower allocation

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Area of Science:

  • Wireless Communication Systems
  • Signal Processing
  • Information Theory

Background:

  • Next-generation wireless systems require high spectrum efficiency.
  • Hybrid beamforming (HBF) and non-orthogonal multiple access (NOMA) integration offers a solution.
  • Existing clustering methods often neglect practical constraints like partial channel state information (CSI).

Purpose of the Study:

  • To develop a user clustering and power allocation scheme for HBF-NOMA under partial CSI.
  • To maximize system throughput while ensuring fairness.
  • To address the limitations of perfect CSI assumptions in realistic wireless environments.

Main Methods:

  • An opportunistic beamforming (OBF) framework utilizing signal-to-interference-plus-noise ratio (SINR) feedback for channel estimation and HBF precoder design.
  • User clustering and power allocation (PA) based on OBF-derived SINR feedback.
  • A novel NOMA scheme prioritizing high SINR users for throughput maximization and fairness enhancement.
  • Power allocation ensuring minimum successive interference cancellation (SIC) power requirements for stable decoding.

Main Results:

  • The proposed clustering scheme significantly enhances system sum-rate compared to conventional SINR-based methods.
  • The approach effectively maintains fairness among users.
  • The method operates effectively in partial CSI environments, reducing feedback overhead.

Conclusions:

  • The developed HBF-NOMA scheme offers a practical and efficient approach for future wireless communication systems.
  • This strategy improves overall system performance, balancing throughput and fairness.
  • It provides a viable solution for NOMA deployment in realistic partial CSI conditions.