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<p>The rapid expansion of the Internet of Things (IoT) and the proliferation of associated wireless devices have intensified the demand for efficient spectrum utilization, presenting significant challenges to scalability and throughput in dense IoT networks. The integration of non-orthogonal multiple access (NOMA) with the IEEE 802.11ah standard addresses these challenges. NOMA enhances spectral efficiency through superposition coding and successive interference cancellation, while the restricted access window (RAW) mechanism of IEEE 802.11ah optimizes channel contention in high-density environments. In this work, we propose a novel field programmable gate array (FPGA) based user pairing scheme that enables real-time, low-latency adaptability by matching devices based on their transmission requirements. The results demonstrate that the proposed pairing scheme, when integrated with RAW-NOMA, significantly improves channel utilization and achieves the fastest pairing performance compared to software-based pairing approaches.</p>

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FPGA based user pairing scheme for NOMA based on transmission requirements of devices in IEEE 802.11ah based IoT networks

  • 期刊论文

  • 发表日期：

    2025年10月18日

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  • S S V D S Aravind,
  • V Avinash,
  • Mahesh Miriyala,
  • Veerapu Goutham

摘要

The rapid expansion of the Internet of Things (IoT) and the proliferation of associated wireless devices have intensified the demand for efficient spectrum utilization, presenting significant challenges to scalability and throughput in dense IoT networks. The integration of non-orthogonal multiple access (NOMA) with the IEEE 802.11ah standard addresses these challenges. NOMA enhances spectral efficiency through superposition coding and successive interference cancellation, while the restricted access window (RAW) mechanism of IEEE 802.11ah optimizes channel contention in high-density environments. In this work, we propose a novel field programmable gate array (FPGA) based user pairing scheme that enables real-time, low-latency adaptability by matching devices based on their transmission requirements. The results demonstrate that the proposed pairing scheme, when integrated with RAW-NOMA, significantly improves channel utilization and achieves the fastest pairing performance compared to software-based pairing approaches.