4,162 research outputs found
Training Optimization for Energy Harvesting Communication Systems
Energy harvesting (EH) has recently emerged as an effective way to solve the
lifetime challenge of wireless sensor networks, as it can continuously harvest
energy from the environment. Unfortunately, it is challenging to guarantee a
satisfactory short-term performance in EH communication systems because the
harvested energy is sporadic. In this paper, we consider the channel training
optimization problem in EH communication systems, i.e., how to obtain accurate
channel state information to improve the communication performance. In contrast
to conventional communication systems, the optimization of the training power
and training period in EH communication systems is a coupled problem, which
makes such optimization very challenging. We shall formulate the optimal
training design problem for EH communication systems, and propose two solutions
that adaptively adjust the training period and power based on either the
instantaneous energy profile or the average energy harvesting rate. Numerical
and simulation results will show that training optimization is important in EH
communication systems. In particular, it will be shown that for short block
lengths, training optimization is critical. In contrast, for long block
lengths, the optimal training period is not too sensitive to the value of the
block length nor to the energy profile. Therefore, a properly selected fixed
training period value can be used.Comment: 6 pages, 5 figures, Globecom 201
EC-CENTRIC: An Energy- and Context-Centric Perspective on IoT Systems and Protocol Design
The radio transceiver of an IoT device is often where most of the energy is consumed. For this reason, most research so far has focused on low power circuit and energy efficient physical layer designs, with the goal of reducing the average energy per information bit required for communication. While these efforts are valuable per se, their actual effectiveness can be partially neutralized by ill-designed network, processing and resource management solutions, which can become a primary factor of performance degradation, in terms of throughput, responsiveness and energy efficiency. The objective of this paper is to describe an energy-centric and context-aware optimization framework that accounts for the energy impact of the fundamental functionalities of an IoT system and that proceeds along three main technical thrusts: 1) balancing signal-dependent processing techniques (compression and feature extraction) and communication tasks; 2) jointly designing channel access and routing protocols to maximize the network lifetime; 3) providing self-adaptability to different operating conditions through the adoption of suitable learning architectures and of flexible/reconfigurable algorithms and protocols. After discussing this framework, we present some preliminary results that validate the effectiveness of our proposed line of action, and show how the use of adaptive signal processing and channel access techniques allows an IoT network to dynamically tune lifetime for signal distortion, according to the requirements dictated by the application
Full-Duplex Cooperative Cognitive Radio Networks with Wireless Energy Harvesting
This paper proposes and analyzes a new full-duplex (FD) cooperative cognitive
radio network with wireless energy harvesting (EH). We consider that the
secondary receiver is equipped with a FD radio and acts as a FD hybrid access
point (HAP), which aims to collect information from its associated EH secondary
transmitter (ST) and relay the signals. The ST is assumed to be equipped with
an EH unit and a rechargeable battery such that it can harvest and accumulate
energy from radio frequency (RF) signals transmitted by the primary transmitter
(PT) and the HAP. We develop a novel cooperative spectrum sharing (CSS)
protocol for the considered system. In the proposed protocol, thanks to its FD
capability, the HAP can receive the PT's signals and transmit energy-bearing
signals to charge the ST simultaneously, or forward the PT's signals and
receive the ST's signals at the same time. We derive analytical expressions for
the achievable throughput of both primary and secondary links by characterizing
the dynamic charging/discharging behaviors of the ST battery as a finite-state
Markov chain. We present numerical results to validate our theoretical analysis
and demonstrate the merits of the proposed protocol over its non-cooperative
counterpart.Comment: 6 pages, 3 figures, conferenc
Energy Harvesting Wireless Communications: A Review of Recent Advances
This article 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.Comment: To appear in the IEEE Journal of Selected Areas in Communications
(Special Issue: Wireless Communications Powered by Energy Harvesting and
Wireless Energy Transfer
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