An analytical framework for evaluating the outage probability of ambient Internet of Things device classes communicating directly with a base station is presented and it is highlighted that the optimal device choice depends critically on the operating regime and application demands.
Abstract
This paper presents an analytical framework for evaluating the outage probability of ambient Internet of Things (A-IoT) device classes communicating directly with a base station. Device 1 is a passive backscatter device with minimal storage, while Device 2 is equipped with a supercapacitor that enables energy buffering and optional amplification. The proposed framework jointly accounts for carrier-detection sensitivity, energy harvesting constraints, supercapacitor energy dynamics, and an energy-aware amplification policy, while the energy evolution of buffered devices is modeled using a discrete-time Markov chain (DTMC). The results highlight the interplay between energy availability and communication reliability. Device 2 achieves superior performance in energy-rich regimes due to buffering and amplification gains, whereas Device 1 becomes more robust in energy-constrained regimes, particularly at larger distances or under high payload requirements. These findings highlight that the optimal device choice depends critically on the operating regime and application demands.
This paper derives the energy model for single-node communication and extends it to multiple-sensor-node communication where several sensors concurrently transmit their information and derives an energy model for a battery-free sensor node that relies on the energy harvested from ambient sources to drive its operation.
Siaka Konaté, Changli Li, Drissa Traoré et al.· Computer Networks and Commun...· 0 citations
This letter investigates an uncrewed aerial vehicle (UAV)-enabled Internet of Things (IoT) architecture that integrates wake-up radio (WuR) and energy harvesting for sustainable device operation, and reveals a tradeoff between transmission frequency and energy consumption.
Anthony Khairallah, Nour Kouzayha, Tareq Y. Al-Naffouri et al.· IEEE Wireless Communications...· 0 citations
The rapid expansion of the Internet of Things (IoT) has led to the proliferation of interconnected devices that generate and exchange vast amounts of data. Efficient data transmission in IoT networks is a crucial factor in ensuring energy conservation, as most IoT devices operate on battery power and are often deployed in remote locations. Energy-efficient data transmission protocols are essential in prolonging the lifespan of these devices, reducing operational costs, and improving network efficiency. This paper explores various energy-efficient data transmission protocols tailored for IoT networks, focusing on mechanisms such as duty cycling, data aggregation, adaptive transmission power, and sleep scheduling. The discussion encompasses recent advancements in the field, comparative analyses of different protocols, and their effectiveness in real-world IoT applications. Additionally, it presents an evaluation of trade-offs between energy efficiency and data reliability, latency, and security. A detailed methodology section outlines experimental setups used to assess protocol performance, followed by a results and discussion section that highlights key findings. The study concludes with insights on future directions and potential improvements in energy-efficient transmission protocols for IoT networks.
Emily Johnson· International Journal of Dat...· 0 citations
The rapid expansion of the Internet of Things (IoT) has led to the proliferation of interconnected devices that generate and exchange vast amounts of data. Efficient data transmission in IoT networks is a crucial factor in ensuring energy conservation, as most IoT devices operate on battery power and are often deployed in remote locations. Energy-efficient data transmission protocols are essential in prolonging the lifespan of these devices, reducing operational costs, and improving network efficiency. This paper explores various energy-efficient data transmission protocols tailored for IoT networks, focusing on mechanisms such as duty cycling, data aggregation, adaptive transmission power, and sleep scheduling. The discussion encompasses recent advancements in the field, comparative analyses of different protocols, and their effectiveness in real-world IoT applications. Additionally, it presents an evaluation of trade-offs between energy efficiency and data reliability, latency, and security. A detailed methodology section outlines experimental setups used to assess protocol performance, followed by a results and discussion section that highlights key findings. The study concludes with insights on future directions and potential improvements in energy-efficient transmission protocols for IoT networks.
I. Moore· International Journal of Mod...· 0 citations
We enable backscatter communication in the battery-less mobile Internet of Things (IoT). Backscatter communication is extensively studied in static settings. Existing designs are, however, fundamentally mismatched with mobility and time-varying energy patterns. Channel conditions rapidly fluctuate, impacting the achievable data rates and thus transmission costs. Energy availability varies unpredictably, possibly forcing devices to remain quiescent to recharge energy buffers. The two issues compound each other: while recharging, a battery-less mobile IoT device may miss more favorable channel conditions. We design a lightweight decision system that dynamically determines when to transmit by checking short-term trends in signal strength, while using Non-volatile Memory (NVM) to retain packets in unfavorable channel conditions and across energy failures. Using a prototype we built and real-world mobility and power traces, we compare our design against a rate-adaptive baseline that only considers the instantaneous channel conditions. Experimental results show that our system improves throughput by up to 5.16x while reducing transmission energy consumption by up to 47.3%, with only 0.23% - 7.3% additional energy overhead.
Wei-Ning Song, Thiemo Voigt, S. Kaxiras et al.· 0 citations
The growing deployment of Internet of Things (IoT) devices has intensified the demand for energy-efficient communication systems that ensure reliable operation under stringent power and maintenance constraints. Traditional transceiver designs often struggle to achieve long-term energy sustainability, resulting in frequent battery replacements, high operational costs, and service disruptions, particularly in remote or difficult-toaccess IoT deployments. This paper presents a novel energyefficient transceiver architecture tailored for IoT applications, integrating hybrid modulation with intelligent power amplifier (PA) control to reduce energy consumption. By selectively deactivating the PA for statistically dominant “typical” symbols, the proposed system achieves up to 30% energy savings without sacrificing communication quality. To support efficient signal decoding, two receiver architectures are introduced: (i) an energy detectionbased approach with a closed-form Bit Error Rate (BER) model, and (ii) a deep learning-based approach leveraging denoising and classification for enhanced robustness. Simulation results confirm that the proposed design maintains BER performance comparable to conventional schemes while preserving spectral efficiency and significantly extending battery life. This solution offers a scalable, low-power communication method suitable for IoT deployments that require reliable and long-duration operation.
Ahmed Badawy, Muhammad Jamal Shehab, Amr Mohamed· International Conference on...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
