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<p>This paper presents a novel cognitive reconfigurable ultra-wideband (UWB) bandpass filter (BPF) featuring quantum-inspired adaptive multi-notch suppression capabilities utilizing hybrid split-ring resonator (SRR) and defected microstrip structure (DMS) resonators, specifically designed for sixth-generation (6G) heterogeneous network applications. The proposed architecture integrates cognitive sensing mechanisms with quantum particle swarm optimization (QPSO) algorithms to dynamically reconfigure notch frequencies in real-time, enabling intelligent interference mitigation across multiple wireless standards coexisting within the 3.1–10.6&#xa0;GHz UWB spectrum. The hybrid SRR-DMS topology achieves superior performance metrics including fractional bandwidth (FBW) of 112.3%, insertion loss below 0.65 dB, and return loss exceeding 18 dB across the passband. The quantum-inspired optimization framework enables adaptive generation of triple-notch bands at 5.2&#xa0;GHz (WLAN), 5.8&#xa0;GHz (WLAN/WiMAX), and 7.5&#xa0;GHz (satellite downlink) with notch depths greater than 35 dB and notch bandwidth tunability ranging from 200&#xa0;MHz to 800&#xa0;MHz. The cognitive engine employs a deep reinforcement learning-enhanced spectrum sensing module achieving 98.7% detection probability at -15 dB signal-to-noise ratio. Simulation results demonstrate excellent agreement with theoretical predictions, confirming the filter’s suitability for cognitive radio-based 6G heterogeneous networks requiring dynamic spectrum access and interference management.</p>

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Quantum-inspired reconfigurable UWB bandpass filter with adaptive triple-notch suppression for cognitive radio networks

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月29日

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  • Anil Gaur,
  • Neelu Trivedi,
  • Shekhar Yadav,
  • Dinesh Kumar Nishad,
  • Molla Addisu Mossie,
  • Sandeep Gupta

摘要

This paper presents a novel cognitive reconfigurable ultra-wideband (UWB) bandpass filter (BPF) featuring quantum-inspired adaptive multi-notch suppression capabilities utilizing hybrid split-ring resonator (SRR) and defected microstrip structure (DMS) resonators, specifically designed for sixth-generation (6G) heterogeneous network applications. The proposed architecture integrates cognitive sensing mechanisms with quantum particle swarm optimization (QPSO) algorithms to dynamically reconfigure notch frequencies in real-time, enabling intelligent interference mitigation across multiple wireless standards coexisting within the 3.1–10.6 GHz UWB spectrum. The hybrid SRR-DMS topology achieves superior performance metrics including fractional bandwidth (FBW) of 112.3%, insertion loss below 0.65 dB, and return loss exceeding 18 dB across the passband. The quantum-inspired optimization framework enables adaptive generation of triple-notch bands at 5.2 GHz (WLAN), 5.8 GHz (WLAN/WiMAX), and 7.5 GHz (satellite downlink) with notch depths greater than 35 dB and notch bandwidth tunability ranging from 200 MHz to 800 MHz. The cognitive engine employs a deep reinforcement learning-enhanced spectrum sensing module achieving 98.7% detection probability at -15 dB signal-to-noise ratio. Simulation results demonstrate excellent agreement with theoretical predictions, confirming the filter’s suitability for cognitive radio-based 6G heterogeneous networks requiring dynamic spectrum access and interference management.