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Cluster Head Selection in Device to Device (D2D) Communication Based on Weighted Network Performance Factor

Author

Listed:
  • Victor Eze Idigo

    (Nnamdi Azikwe University (Unizik), Nigeria)

  • Ikechukwu Harrison Ezeh

    (Federal University of Technology, Nigeria)

  • Augustine Chukwuemeka Okwudili Azubogu

    (Nnamdi Azikwe University (Unizik), Nigeria)

  • Victor Ndubuisi Okorogu

    (Nnamdi Azikwe University (Unizik), Nigeria)

  • Scholastica Ukamaka Nnebe

    (Nnamdi Azikwe University (Unizik), Nigeria)

Abstract

In this study, an unsupervised machine learning algorithm, Self Organizing Map was utilized to cluster D2D User Equipment using their network values as inputs. A weighting factor referred to as Hardware Sensing Factor (HSF) was formulated to take into account the device’s channel quality and the status of its underlying hardware circuitry. The values of the HSF were used as inputs to cluster the devices and to select cluster head for each cluster. The performance of SOM when HSF was input was compared with the performance when RSSI, RSRP or RSRQ was used as input. The comparison showed that the use of HSF as input to SOM cluster algorithm gave better cluster performance than the use of respective network values such as RSSI, RSRP or RSRQ. In addition, the use of HSF as input data to both SOM and K-Means algorithms showed that SOM cluster formation has better performance than K-Means algorithm.

Suggested Citation

  • Victor Eze Idigo & Ikechukwu Harrison Ezeh & Augustine Chukwuemeka Okwudili Azubogu & Victor Ndubuisi Okorogu & Scholastica Ukamaka Nnebe, 2023. "Cluster Head Selection in Device to Device (D2D) Communication Based on Weighted Network Performance Factor," European Journal of Electrical Engineering and Computer Science, European Open Science, vol. 7(6), pages 19-26, November.
    • Handle: RePEc:epw:ejece0:v:7:y:2023:i:6:id:19564
    DOI: 10.24018/ejece.2023.7.6.564
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