Nicolo Michelusi

Bio: Nicolo Michelusi is an academic researcher from Arizona State University. The author has contributed to research in topics: Overhead (computing) & Throughput. The author has an hindex of 19, co-authored 122 publications receiving 1689 citations. Previous affiliations of Nicolo Michelusi include University of Padua & Purdue University.

Designing intelligent energy harvesting communication systems

Abstract: From being a scientific curiosity only a few years ago, energy harvesting (EH) is well on its way to becoming a game-changing technology in the field of autonomous wireless networked systems. The promise of long-term, uninterrupted and self-sustainable operation in a diverse array of applications has captured the interest of academia and industry alike. Yet the road to the ultimate network of perpetual communicating devices is plagued with potholes: ambient energy is intermittent and scarce, energy storage capacity is limited, and devices are constrained in size and complexity. In dealing with these challenges, this article will cover recent developments in the design of intelligent energy management policies for EH wireless devices and discuss pressing research questions in this rapidly growing field.

Transmission Policies for Energy Harvesting Sensors with Time-Correlated Energy Supply

Abstract: This paper considers a wireless sensor powered by an energy harvesting device, which reports data of varying importance to its receiver. Modeling the ambient energy supply by a two-state Markov chain ("GOOD" and "BAD"), assuming a finite battery capacity constraint, and associating data transmission with a given energy cost, we propose low-complexity transmission policies, that achieve near-optimal performance in terms of the average long-term importance of the reported data. In particular, we derive the performance of the Balanced Policy (BP), which adapts the transmission probability to the harvesting state, such that energy harvesting and consumption are balanced. Our analysis demonstrates that the performance of the BP largely depends on the power-to-depletion, defined as the power that a fully charged battery can supply on average over a BAD period. Numerical results show that the optimal BP achieves near-optimal performance and that a BP which avoids energy overflow further reduces the gap with respect to the globally optimal policy. A heuristic BP, based on the analysis of a system with a deterministic and periodic energy supply, is also proposed, and the parallels between the deterministic system and its stochastic counterpart are discussed.

Energy Management Policies for Harvesting-Based Wireless Sensor Devices with Battery Degradation

Abstract: Energy Harvesting Wireless Sensor Devices are increasingly being considered for deployment in sensor networks, due to their demonstrated advantages of prolonged lifetime and autonomous operation. However, irreversible degradation mechanisms jeopardize battery lifetime, calling for intelligent management policies, which minimize the impact of these phenomena while guaranteeing a minimum Quality of Service (QoS). This paper explores a mathematical characterization of these devices, focusing on the interplay between the battery discharge policy and the irreversible degradation of the storage capacity. We propose a stochastic Markov chain framework, suitable for policy optimization, which captures the degradation status of the battery. We present a general result of Markov chains, which exploits the timescale separation between the communication time-slot of the device and the battery degradation process, and enables an efficient optimization. We show that this model fits well the behavior of real batteries for what concerns their storage capacity degradation over time. We demonstrate that a degradation-aware policy significantly improves the lifetime of the sensor compared to "greedy" policies, while guaranteeing the minimum required QoS. Finally, a simple heuristic policy, which never discharges the battery below a given threshold, is shown to achieve near-optimal performance in terms of battery lifetime.

On optimal transmission policies for energy harvesting devices

Abstract: We consider an energy harvesting device whose state at a given time is determined by its energy level and an “importance” value, associated to the transmission of a data packet to the receiver at that particular time. We consider policies that, at each time, elect whether to transmit the data packet or not, based on the current energy level and data importance, so as to maximize the long-term average transmitted data importance. Under the assumption of i.i.d. Bernoulli energy arrivals, we show that the sensor should report only data with an importance value above a given threshold, which is a strictly decreasing function of the energy level, and we derive upper and lower bounds on the thresholds for any energy level. Leveraging on these findings, we construct a suboptimal policy that performs very close to the optimal one, at a fraction of the complexity. Finally, we demonstrate that a threshold policy, which on the average transmits with probability equal to the average energy arrival rate is asymptotically optimal as the energy storage capacity grows large.

On optimal transmission policies for energy harvesting devices: The case of two users

Abstract: We consider an energy harvesting device whose state at a given time is determined by its energy level and an “importance” value, associated to the transmission of a data packet to the receiver at that particular time. We consider policies that, at each time, elect whether to transmit the data packet or not, based on the current energy level and data importance, so as to maximize the long-term average transmitted data importance. Under the assumption of i.i.d. Bernoulli energy arrivals, we show that the sensor should report only data with an importance value above a given threshold, which is a strictly decreasing function of the energy level, and we derive upper and lower bounds on the thresholds for any energy level. Leveraging on these findings, we construct a suboptimal policy that performs very close to the optimal one, at a fraction of the complexity. Finally, we demonstrate that a threshold policy, which on the average transmits with probability equal to the average energy arrival rate is asymptotically optimal as the energy storage capacity grows large.

I and i

Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

On the capacity of a cellular CDMA system

Abstract: It is shown that, particularly for terrestrial cellular telephony, the interference-suppression feature of CDMA (code division multiple access) can result in a many-fold increase in capacity over analog and even over competing digital techniques. A single-cell system, such as a hubbed satellite network, is addressed, and the basic expression for capacity is developed. The corresponding expressions for a multiple-cell system are derived. and the distribution on the number of users supportable per cell is determined. It is concluded that properly augmented and power-controlled multiple-cell CDMA promises a quantum increase in current cellular capacity. >

Energy Harvesting Wireless Communications: A Review of Recent Advances

Abstract: This paper summarizes recent contributions in the broad area of energy harvesting wireless communications. In particular, we provide the current state of the art for wireless networks composed of energy harvesting nodes, starting from the information-theoretic performance limits to transmission scheduling policies and resource allocation, medium access, and networking issues. The emerging related area of energy transfer for self-sustaining energy harvesting wireless networks is considered in detail covering both energy cooperation aspects and simultaneous energy and information transfer. Various potential models with energy harvesting nodes at different network scales are reviewed, as well as models for energy consumption at the nodes.

A Survey of Energy-Efficient Techniques for 5G Networks and Challenges Ahead

Abstract: After about a decade of intense research, spurred by both economic and operational considerations, and by environmental concerns, energy efficiency has now become a key pillar in the design of communication networks. With the advent of the fifth generation of wireless networks, with millions more base stations and billions of connected devices, the need for energy-efficient system design and operation will be even more compelling. This survey provides an overview of energy-efficient wireless communications, reviews seminal and recent contribution to the state-of-the-art, including the papers published in this special issue, and discusses the most relevant research challenges to be addressed in the future.