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<p>The rapid advancement of Internet of Things (IoT) and sensor networks has led to the emergence of Wireless Powered Communication Networks (WPCNs), offering significant potential through wireless energy transfer for energy-constrained devices. However, WPCNs face new challenges in multi-user scheduling due to factors like energy collection efficiency and resource allocation, which are crucial for optimizing network performance. This paper addresses the multi-user scheduling challenge in WPCNs, focusing on optimizing network performance by maximizing total weighted throughput and minimizing energy consumption. We propose a network model considering non-linear energy collection efficiency and employ a Lagrange multiplier algorithm to balance energy consumption and data transmission. MATLAB simulations demonstrate that our algorithm outperforms traditional methods, reducing total energy consumption by 25% while increasing network throughput by 15%. The findings provide theoretical and practical insights for WPCNs optimization and deployment. Future research will explore algorithm optimization, practical deployment strategies, and network security to advance wireless power network technology.</p>

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Optimization of multi-user scheduling in WPCNs

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年4月30日

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  • Lina Yuan,
  • Huajun Chen,
  • Tingsui Liu,
  • Ging Gong

摘要

The rapid advancement of Internet of Things (IoT) and sensor networks has led to the emergence of Wireless Powered Communication Networks (WPCNs), offering significant potential through wireless energy transfer for energy-constrained devices. However, WPCNs face new challenges in multi-user scheduling due to factors like energy collection efficiency and resource allocation, which are crucial for optimizing network performance. This paper addresses the multi-user scheduling challenge in WPCNs, focusing on optimizing network performance by maximizing total weighted throughput and minimizing energy consumption. We propose a network model considering non-linear energy collection efficiency and employ a Lagrange multiplier algorithm to balance energy consumption and data transmission. MATLAB simulations demonstrate that our algorithm outperforms traditional methods, reducing total energy consumption by 25% while increasing network throughput by 15%. The findings provide theoretical and practical insights for WPCNs optimization and deployment. Future research will explore algorithm optimization, practical deployment strategies, and network security to advance wireless power network technology.