Energy-Efficient Resource Allocation Algorithm for CR-WSN-Based Smart Irrigation System under Realistic Scenarios

Abstract

Cognitive radio wireless sensor networks (CR-WSNs) are a type of WSNs that use cognitive radio technology to enhance the spectrum utilization and energy efficiency. This paper proposes an energy-efficient resource allocation algorithm (EERAA) to prolong the lifetime of a WSN-based smart irrigation system under realistic scenarios. In the proposed algorithm, power allocation and subcarrier assignment are performed consecutively. Considering the impact of the intercarrier interference (ICI) caused by timing offset, the problem of maximizing network-averaged capacity is formulated considering power and interference constraints in realistic scenarios. The obtained results reveal that the proposed algorithm attempts to maximize the averaged capacity of the CR-WSN subject to the total power constraint and tolerable interference. Numerically, the proposed algorithm can reduce the network energy consumption by up to 30%, compared with conventional approaches, while maintaining a high level of system performance in terms of secondary users’ (SUs) averaged capacity.

Hybrid Energy Powered Smart Irrigation System for Smallholder Farmers: Installation Site and Crop Selection

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“…This paradigm shifts towards data-driven decision-making and not only boosts efficiency but also holds the potential to address the global challenges of food security in the face of growing population and changing climate conditions. The success of smart agriculture critically hinges on robust and high-bandwidth connectivity to facilitate seamless data transmission between various devices and central management systems [6][7][8][9][10].…”

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