2,347 research outputs found
MIMO-OFDM Based Energy Harvesting Cooperative Communications Using Coalitional Game Algorithm
This document is the Accepted Manuscript version. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.In this paper, we consider the problem of cooperative communication between relays and base station in an advanced MIMO-OFDM framework, under the assumption that the relays are supplied by electric power drawn from energy harvesting (EH) sources. In particular, we focus on the relay selection, with the goal to guarantee the required performance in terms of capacity. In order to maximize the data throughput under the EH constraint, we model the transmission scheme as a non-transferable coalition formation game, with characteristic function based on an approximated capacity expression. Then, we introduce a powerful mathematical tool inherent to coalitional game theory, namely: the Shapley value (Sv) to provide a reliable solution concept to the game. The selected relays will form a virtual dynamically-configuredMIMO network that is able to transmit data to destination using efficient space-time coding techniques. Numerical results, obtained by simulating the EH-powered cooperativeMIMO-OFDMtransmission with Algebraic Space-Time Coding (ASTC), prove that the proposed coalitional game-based relay selection allows to achieve performance very close to that obtained by the same system operated by guaranteed power supply. The proposed methodology is finally compared with some recent related state-of-the-art techniques showing clear advantages in terms of link performance and goodput.Peer reviewe
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
Optimizing Wirelessly Powered Crowd Sensing: Trading energy for data
To overcome the limited coverage in traditional wireless sensor networks,
\emph{mobile crowd sensing} (MCS) has emerged as a new sensing paradigm. To
achieve longer battery lives of user devices and incentive human involvement,
this paper presents a novel approach that seamlessly integrates MCS with
wireless power transfer, called \emph{wirelessly powered crowd sensing} (WPCS),
for supporting crowd sensing with energy consumption and offering rewards as
incentives. The optimization problem is formulated to simultaneously maximize
the data utility and minimize the energy consumption for service operator, by
jointly controlling wireless-power allocation at the \emph{access point} (AP)
as well as sensing-data size, compression ratio, and sensor-transmission
duration at \emph{mobile sensor} (MS). Given the fixed compression ratios, the
optimal power allocation policy is shown to have a \emph{threshold}-based
structure with respect to a defined \emph{crowd-sensing priority} function for
each MS. Given fixed sensing-data utilities, the compression policy achieves
the optimal compression ratio. Extensive simulations are also presented to
verify the efficiency of the contributed mechanisms.Comment: arXiv admin note: text overlap with arXiv:1711.0206
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