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<p>The rapid evolution of mobile communication technologies has led to a paradigm shift from simple voice-oriented devices to data-intensive smartphones, resulting in an exponential increase in wireless device usage. This surge in wireless communication has subsequently heightened the demand for base stations (BSs), which are responsible for approximately 60% of the overall energy consumption in wireless networks. In response, Green Cognitive Radio Networks (CRNs) have originated as a sustainable choice, employing energy-efficient strategies to optimize spectrum management. This paper investigates critical energy conservation strategies in Green CRNs, with a particular emphasis on enhancing Quality of Service (QoS) metrics such as channel availability and retainability. We introduce a Dynamic Channel Reservation (DCR) policy that adapts to varying network conditions by dynamically reserving channels to support ongoing real-time Secondary User (RSU) services, while also operating in two distinct working modes (WMs): WM1, which prioritizes retainability, and WM2, which maximizes channel availability. Additionally, a retrial policy is incorporated to further enhance the retainability of non-real-time SUs (NRSUs). The proposed system is modeled using a multi-dimensional continuous-time Markov chain (CTMC), and the analysis is performed using the uniformization technique to derive mathematical expressions for key transient metrics. Our numerical results underscore the effectiveness of the proposed DCR policy, retrial mechanisms, and sleep mode techniques in significantly improving the performance of CRNs. The study provides a comprehensive analysis of performance metrics including channel availability, retainability, throughput, energy-saving rate, channel utilization, and average latency, demonstrating the potential of the proposed scheme to advance energy efficiency and QoS in Green CRNs. The proposed strategy leads to up to 25% higher retainability and a 34% increase in throughput, highlighting its effectiveness in comparison with conventional schemes in CRN.</p>

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Energy-Efficient Dynamic Channel Reservation for QoS Provisioning in Green Cognitive Radio Networks with Multiple Sleep Modes for Heterogeneous Traffic

  • 期刊论文

  • 发表日期：

    2025年9月23日

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  • Pooja Balhara,
  • Rakhee Kulshrestha,
  • Shruti Goel

摘要

The rapid evolution of mobile communication technologies has led to a paradigm shift from simple voice-oriented devices to data-intensive smartphones, resulting in an exponential increase in wireless device usage. This surge in wireless communication has subsequently heightened the demand for base stations (BSs), which are responsible for approximately 60% of the overall energy consumption in wireless networks. In response, Green Cognitive Radio Networks (CRNs) have originated as a sustainable choice, employing energy-efficient strategies to optimize spectrum management. This paper investigates critical energy conservation strategies in Green CRNs, with a particular emphasis on enhancing Quality of Service (QoS) metrics such as channel availability and retainability. We introduce a Dynamic Channel Reservation (DCR) policy that adapts to varying network conditions by dynamically reserving channels to support ongoing real-time Secondary User (RSU) services, while also operating in two distinct working modes (WMs): WM1, which prioritizes retainability, and WM2, which maximizes channel availability. Additionally, a retrial policy is incorporated to further enhance the retainability of non-real-time SUs (NRSUs). The proposed system is modeled using a multi-dimensional continuous-time Markov chain (CTMC), and the analysis is performed using the uniformization technique to derive mathematical expressions for key transient metrics. Our numerical results underscore the effectiveness of the proposed DCR policy, retrial mechanisms, and sleep mode techniques in significantly improving the performance of CRNs. The study provides a comprehensive analysis of performance metrics including channel availability, retainability, throughput, energy-saving rate, channel utilization, and average latency, demonstrating the potential of the proposed scheme to advance energy efficiency and QoS in Green CRNs. The proposed strategy leads to up to 25% higher retainability and a 34% increase in throughput, highlighting its effectiveness in comparison with conventional schemes in CRN.