The design of Medium Access Control (MAC) protocols for wireless sensor networks (WSNs) has been conventionally tackled by assuming battery-powered devices and by adopting the network lifetime as the main performance criterion. While WSNs operated by energy-harvesting (EH) devices are not limited by network lifetime, they pose new design challenges due to the uncertain amount of energy that can be harvested from the environment. Novel design criteria are thus required to capture the trade-offs between the potentially infinite network lifetime and the uncertain energy availability. This paper addresses the analysis and design of WSNs with EH devices by focusing on conventional MAC protocols, namely TDMA, framed-ALOHA (FA) and dynamic-FA (DFA), and by accounting for the performance trade-offs and design issues arising due to EH. A novel metric, referred to as delivery probability, is introduced to measure the capability of a MAC protocol to deliver the measurement of any sensor in the network to the intended destination (or fusion center, FC). The interplay between delivery efficiency and time efficiency (i.e., the data collection rate at the FC), is investigated analytically using Markov models. Numerical results validate the analysis and emphasize the critical importance of accounting for both delivery probability and time efficiency in the design of EH-WSNs.

The Dynamic Framed-ALOHA (DFA) protocol is studied for wireless sensor networks with energy limitations and energy-harvesting capability. The performance of DFA in this scenario is evaluated in terms of the time efficiency (or throughput), which is routinely used to evaluate medium access protocols, and by introducing a new metric, referred to as detection efficiency, which is tailored to scenarios with energy constraints. Specifically, detection efficiency measures the ability of a multiple access protocol to collect data from nodes without depleting their energy reserves. Analysis is first performed by assuming that DFA is operated with a perfect backlog (i.e., number of sensors left to be interrogated) knowledge. Then, a low-complexity backlog estimation algorithm is presented, which is shown by numerical results to perform close to the ideal case of perfect backlog knowledge.

A critical performance criterion in backscatter modulation-based RFID sensor networks is the distance at which a RFID reader can reliably communicate with passive RFID sensors (or tags). This paper proposes to introduce a power amplifier (PA) and an energy storage device (such as a capacitor or a battery), in the hardware architecture of conventional passive RFID tags, with the aim of allowing amplification of the backscatter signal to increase the read range. This new tag architecture, referred to as Amplified Backscattering via Energy Harvesting (ABEH), can still be considered as passive, since the energy storage device is charged exclusively by harvesting energy from the RF-signal transmitted by the reader and received by the tag during idle periods. The harvested and stored energy is then used by the tags to opportunistically amplify the backscatter signal. It is noted that this architecture is significantly different from active RFID tags where the battery, charged at the time of installation, is used to supply a complete onboard transceiver so that no backscatter modulation is employed. Energy scheduling strategies, based on the trade-off between energy harvesting rate and successful transmission probability, are proposed. Performance analysis of tags with the proposed ABEH architecture is carried out over quasi-static fading channels by framing the design problem as a Markov Decision Process. Numerical results show remarkable improvement of the ABEH approach with respect to conventional passive RFID tags and provide insight into the effect of system parameters on the energy scheduling.