Researchers have developed a groundbreaking technique that integrates active intelligent reflecting surfaces (IRS) into energy harvesting-cognitive radio sensor networks (EH-CRSNs) to dramatically improve their efficiency and sustainability. By optimizing the deployment and configuration of active IRS, the researchers were able to maximize the net energy gain of the system, prolonging the network’s lifetime. This innovative approach holds immense potential for transforming the future of wireless communication and sensor networks, paving the way for more sustainable and reliable environmental monitoring and data collection. Cognitive radio, Wireless sensor networks, Energy harvesting, Intelligent reflecting surface
Harnessing the Power of Active Intelligent Reflecting Surfaces for Sustainable Cognitive Radio Sensor Networks
Cognitive radio sensor networks (CRSNs) have emerged as a promising solution to the growing demand for efficient and reliable wireless communication, particularly in environmental monitoring and data collection applications. These networks combine the capabilities of cognitive radio technology with wireless sensor networks, allowing sensor nodes to opportunistically access idle licensed spectrum bands without disrupting primary users. However, the limited battery capacity of CRSN nodes and their energy-intensive cognitive functions have posed significant challenges to the network’s longevity.
Energy harvesting (EH) has been identified as a viable solution to address this issue, enabling CRSN nodes to harvest energy from various environmental sources, such as solar and wind energy, or even from radio frequency (RF) signals. This harvested energy can then be used to recharge the nodes’ batteries, extending the network’s lifespan and contributing to its sustainability.

To further enhance the efficiency and performance of EH-CRSNs, researchers have recently integrated intelligent reflecting surfaces (IRS) into the system. IRS are planar surfaces composed of numerous reflective elements that can intelligently manipulate the wireless communication environment, improving the efficiency of both wireless energy transfer (WET) and wireless information transmission (WIT).
Traditionally, passive IRS have been explored in EH-CRSNs and other wireless communication systems, as they can introduce controllable phase shifts to the reflected signals, enabling constructive signal combining at the receiver. However, passive IRS suffer from the “multiplicative fading” effect, where the path loss of the cascaded reflection link is the product of the individual path losses, significantly limiting their performance.
To address this limitation, the researchers in this study have introduced the concept of active IRS, which are equipped with reflective elements that can actively amplify the incident signals. By intelligently configuring the reflection coefficients of the active IRS, the researchers were able to enhance both the downlink energy harvesting and the uplink data transmission in EH-CRSNs, ultimately maximizing the system’s net energy gain.

Fig. 1
Optimizing Active IRS Deployment and Beamforming
The key focus of this research was to develop a joint passive beamforming and IRS deployment mechanism that can determine the optimal location for the active IRS and configure its reflection coefficient matrices to maximize the net energy gain of the EH-CRSN system.
The researchers formulated a constrained non-convex optimization problem, where the objective was to maximize the difference between the cumulative energy harvested by all CRSN nodes in the downlink and the energy consumed by cluster heads during uplink data transmissions. To solve this problem, they divided it into two sub-problems: maximizing the energy harvested in the downlink and minimizing the energy consumed in the uplink.
By leveraging the semi-definite relaxation (SDR) algorithm, the researchers were able to convert the non-convex optimization problem into a convex form, which could then be efficiently solved. The solution provided the optimal reflection coefficient matrices for both the downlink energy harvesting and the uplink data transmission phases.
Factors Influencing the Optimal Active IRS Deployment
The researchers investigated how various factors, such as the number of active reflective elements, the amplification power budget of the active IRS, the number of clusters in the CRSN, and the transmit power of the sink, influence the optimal deployment location of the active IRS.
Their findings revealed that:
– As the number of active reflective elements increases, the optimal deployment location of the active IRS shifts closer to the CRSN nodes, balancing the energy harvesting and data transmission performance.
– A higher amplification power budget for the active IRS allows it to be deployed closer to the CRSN nodes, further enhancing the energy harvesting efficiency.
– An increase in the number of clusters in the CRSN leads to the optimal deployment location of the active IRS moving closer to the sink, prioritizing the reduction of energy consumption during uplink data transmissions.
– The transmit power of the sink has a negligible impact on the optimal deployment location, as the active IRS is consistently positioned near the sink to optimize both downlink energy harvesting and uplink data transmission.
Significant Performance Improvements and Future Potential
The simulation results confirmed the effectiveness of the proposed joint passive beamforming and IRS deployment mechanism. Compared to various benchmark mechanisms, the researchers’ approach achieved up to a 29.33% enhancement in the net energy gain of the EH-CRSN system, demonstrating the substantial benefits of active IRS integration.
This innovative research paves the way for a new era of sustainable and efficient wireless communication networks, particularly in environmental monitoring and data collection applications. By harnessing the power of active IRS, the researchers have shown how EH-CRSNs can significantly extend their network lifetime, reducing the need for frequent battery replacements and contributing to a more environmentally friendly future.
Looking ahead, the researchers plan to further explore the optimization of active IRS deployment to achieve a more balanced distribution of residual energy among CRSN nodes, further enhancing the overall network lifespan. Additionally, they aim to develop a dedicated clustering protocol for active IRS-assisted EH-CRSNs, which could further reduce the energy consumption during uplink data transmissions.
Author credit: This article is based on research by Jihong Wang, Yanan Zhu.
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