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Scalability Improvement of IEEE 802.11ah IoT Networks

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Abstract

In this paper, we propose a non-orthogonal multiple access (NOMA) based grouping method for IEEE 802.11ah, a promising platform for the internet of things (IoT). The grouping method improves the scalability of IoT networks, by reducing collisions in the access points (APs). The proposed method puts those IoT devices (IoT-Ds) whose channel gains are far enough from each other, i.e., who satisfy NOMA constraints, in the same group. Therefore, using successive interference cancellation (SIC), the AP is able to decode the simultaneous signal transmissions from IoT-Ds in a group. To assign IoT-Ds into groups and determine their transmission power, we formulate a total throughput maximization problem as a joint optimal grouping and power allocation problem, which is a non-convex mixed-integer programming problem. We convert it to a convex problem using quadratic fractional programming, and then we solve it using augmented Lagrange multiplier (ALM) method. Moreover, to reduce the complexity of the solution, we propose a fast grouping method to allocate power to each group in parallel. Simulation results show that the proposed methods have outstanding performance compared to conventional association identifier (AID)-based grouping method; besides, scalability of the network in terms of throughput, power consumption and channel utilization improves dramatically because of the collision reduction of IoT-Ds, which is achieved by deploying NOMA and SIC. Furthermore, the fast grouping method decreases the computational complexity greatly at the expense of a small reduction in network performance.

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Funding

This work was supported partially by financial support of the Research and Technology Deputy Chair of the University of Sistan and Baluchestan. The authors have no relevant financial or non-financial interests to disclose. The research does not have associated data set to be shared, and the numerical assumptions of the simulation have been addressed in the manuscript.

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Authors and Affiliations

  1. University of Sistan and Baluchestan, Zahedan, Iran

    Motahareh Naghzali & Mehri Mehrjoo

  2. Velayat University, Iranshahr, Iran

    Mahdi Kazeminia

Authors
  1. Motahareh Naghzali
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  2. Mahdi Kazeminia
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  3. Mehri Mehrjoo
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Correspondence to Mehri Mehrjoo.

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Naghzali, M., Kazeminia, M. & Mehrjoo, M. Scalability Improvement of IEEE 802.11ah IoT Networks. Wireless Pers Commun 129, 729–746 (2023). https://doi.org/10.1007/s11277-022-10153-x

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