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Multivariate clustering for maximizing the small cell users’ performance based on the dynamic interference alignment

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A Correction to this article was published on 22 July 2023

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Abstract

Interference alignment (IA) ideas have been used into wireless communication in recent years to increase network users' capacity, sum rate, and spectral efficiency. This manuscript presents a multi-variate clustering (MC) for small-cell user communications through dynamic interference alignment (DIA). The clustering and interference alignment process focuses on retaining cluster stability and communication reliability by mitigating interference that is both intra and inter-cluster. The stability of the cluster is evaluated using the quality factor that is useful in mitigating intrauser interference. The inter-user interference is thwarted by classifying the transmitting signal based on time sequence and processing it through an appropriate cancellation matrix and rank-based analysis. Regardless of the user and cell density, the pre-coding process is based on this rank-based examination of the obtained power. The proposed MC-DIA is capable of handling both intra and inter-cluster interference for the allocated channels in the small cell scenarios. Experimentation results showed that the MC-DIA achieved a spectral efficiency of 84%. The proposed scheme performances are verified utilizing the simulation for metrics sum rate, spectral efficiency, and average degree of freedom (DoF).

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Data sharing is not applicable to this article as no new data were created or analyzed in this study.

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Authors and Affiliations

  1. Department of Data Science and Business Systems, School of Computing, College of Engineering and Technology, SRM Institute of Science and Technology, Kattankulathur, Chengalpattu, India

    Prabakar Dakshinamoorthy

  2. Department of Electronics and Communication Engineering, Puducherry Technological University, Puducherry, India

    Saminadan Vaitilingam

  3. Department of Artificial Intelligence and Machine Learning, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, Tamil Nadu, India

    Ramesh Sundar

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  1. Prabakar Dakshinamoorthy
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  2. Saminadan Vaitilingam
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  3. Ramesh Sundar
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Correspondence to Prabakar Dakshinamoorthy.

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Dakshinamoorthy, P., Vaitilingam, S. & Sundar, R. Multivariate clustering for maximizing the small cell users’ performance based on the dynamic interference alignment. Wireless Netw 29, 3063–3074 (2023). https://doi.org/10.1007/s11276-023-03298-5

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