Packet Scheduling Using SVM Models in Wireless Communication Networks

Sovit Bhandari,
Hong Ping Zhao,
Hoon Kim,
Pervez Khan,
Sana Ullah,

Abstract


This paper addresses a support vector machine (SVM) model-based packet scheduling in wireless communication networks. The linear SVM, as well as the polynomial SVM model-based proportional fair scheduling (SVM-PFS), are suggested. Moreover, their performances are analyzed for various system and machine learning parameters such as the average window, signal to interference ratio (SIR) and the degree of a polynomial. From the computer simulations, the performance measurements of PFS, such as, user selection fairness and user throughput are calculated, which proves that performance of SVM-PFS approaches to that of the conventional metric-based PFS in most cases, while the simulation results show that the polynomial SVM-PFS outperforms the linear SVM-PFS. It is also shown that the SVM-PFS performs better under higher SIR or larger average window.


Citation Format:
Sovit Bhandari, Hong Ping Zhao, Hoon Kim, Pervez Khan, Sana Ullah, "Packet Scheduling Using SVM Models in Wireless Communication Networks," Journal of Internet Technology, vol. 20, no. 5 , pp. 1505-1512, Sep. 2019.

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