3,989 research outputs found
Wireless Information and Energy Transfer for Two-Hop Non-Regenerative MIMO-OFDM Relay Networks
This paper investigates the simultaneous wireless information and energy
transfer for the non-regenerative multipleinput multiple-output orthogonal
frequency-division multiplexing (MIMO-OFDM) relaying system. By considering two
practical receiver architectures, we present two protocols, time switchingbased
relaying (TSR) and power splitting-based relaying (PSR). To explore the system
performance limit, we formulate two optimization problems to maximize the
end-to-end achievable information rate with the full channel state information
(CSI) assumption. Since both problems are non-convex and have no known solution
method, we firstly derive some explicit results by theoretical analysis and
then design effective algorithms for them. Numerical results show that the
performances of both protocols are greatly affected by the relay position.
Specifically, PSR and TSR show very different behaviors to the variation of
relay position. The achievable information rate of PSR monotonically decreases
when the relay moves from the source towards the destination, but for TSR, the
performance is relatively worse when the relay is placed in the middle of the
source and the destination. This is the first time to observe such a
phenomenon. In addition, it is also shown that PSR always outperforms TSR in
such a MIMO-OFDM relaying system. Moreover, the effect of the number of
antennas and the number of subcarriers are also discussed.Comment: 16 pages, 12 figures, to appear in IEEE Selected Areas in
Communication
Resource Allocation in Wireless Networks with RF Energy Harvesting and Transfer
Radio frequency (RF) energy harvesting and transfer techniques have recently
become alternative methods to power the next generation of wireless networks.
As this emerging technology enables proactive replenishment of wireless
devices, it is advantageous in supporting applications with quality-of-service
(QoS) requirement. This article focuses on the resource allocation issues in
wireless networks with RF energy harvesting capability, referred to as RF
energy harvesting networks (RF-EHNs). First, we present an overview of the
RF-EHNs, followed by a review of a variety of issues regarding resource
allocation. Then, we present a case study of designing in the receiver
operation policy, which is of paramount importance in the RF-EHNs. We focus on
QoS support and service differentiation, which have not been addressed by
previous literatures. Furthermore, we outline some open research directions.Comment: To appear in IEEE Networ
Throughput Maximization for UAV-Aided Backscatter Communication Networks
This paper investigates unmanned aerial vehicle (UAV)-aided backscatter communication (BackCom) networks, where the UAV is leveraged to help the backscatter device (BD) forward signals to the receiver. Based on the presence or absence of a direct link between BD and receiver, two protocols, namely transmit-backscatter (TB) protocol and transmit-backscatter-relay (TBR) protocol, are proposed to utilize the UAV to assist the BD. In particular, we formulate the system throughput maximization problems for the two protocols by jointly optimizing the time allocation, reflection coefficient and UAV trajectory. Different static/dynamic circuit power consumption models for the two protocols are analyzed. The resulting optimization problems are shown to be non-convex, which are challenging to solve. We first consider the dynamic circuit power consumption model, and decompose the original problems into three sub-problems, namely time allocation optimization with fixed UAV trajectory and reflection coefficient, reflection coefficient optimization with fixed UAV trajectory and time allocation, and UAV trajectory optimization with fixed reflection coefficient and time allocation. Then, an efficient iterative algorithm is proposed for both protocols by leveraging the block coordinate descent method and successive convex approximation (SCA) techniques. In addition, for the static circuit power consumption model, we obtain the optimal time allocation with a given reflection coefficient and UAV trajectory and the optimal reflection coefficient with low computational complexity by using the Lagrangian dual method. Simulation results show that the proposed protocols are able to achieve significant throughput gains over the compared benchmarks
A critical analysis of research potential, challenges and future directives in industrial wireless sensor networks
In recent years, Industrial Wireless Sensor Networks (IWSNs) have emerged as an important research theme with applications spanning a wide range of industries including automation, monitoring, process control, feedback systems and automotive. Wide scope of IWSNs applications ranging from small production units, large oil and gas industries to nuclear fission control, enables a fast-paced research in this field. Though IWSNs offer advantages of low cost, flexibility, scalability, self-healing, easy deployment and reformation, yet they pose certain limitations on available potential and introduce challenges on multiple fronts due to their susceptibility to highly complex and uncertain industrial environments. In this paper a detailed discussion on design objectives, challenges and solutions, for IWSNs, are presented. A careful evaluation of industrial systems, deadlines and possible hazards in industrial atmosphere are discussed. The paper also presents a thorough review of the existing standards and industrial protocols and gives a critical evaluation of potential of these standards and protocols along with a detailed discussion on available hardware platforms, specific industrial energy harvesting techniques and their capabilities. The paper lists main service providers for IWSNs solutions and gives insight of future trends and research gaps in the field of IWSNs
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
Energy Management Policies for Energy-Neutral Source-Channel Coding
In cyber-physical systems where sensors measure the temporal evolution of a
given phenomenon of interest and radio communication takes place over short
distances, the energy spent for source acquisition and compression may be
comparable with that used for transmission. Additionally, in order to avoid
limited lifetime issues, sensors may be powered via energy harvesting and thus
collect all the energy they need from the environment. This work addresses the
problem of energy allocation over source acquisition/compression and
transmission for energy-harvesting sensors. At first, focusing on a
single-sensor, energy management policies are identified that guarantee a
maximal average distortion while at the same time ensuring the stability of the
queue connecting source and channel encoders. It is shown that the identified
class of policies is optimal in the sense that it stabilizes the queue whenever
this is feasible by any other technique that satisfies the same average
distortion constraint. Moreover, this class of policies performs an independent
resource optimization for the source and channel encoders. Analog transmission
techniques as well as suboptimal strategies that do not use the energy buffer
(battery) or use it only for adapting either source or channel encoder energy
allocation are also studied for performance comparison. The problem of
optimizing the desired trade-off between average distortion and delay is then
formulated and solved via dynamic programming tools. Finally, a system with
multiple sensors is considered and time-division scheduling strategies are
derived that are able to maintain the stability of all data queues and to meet
the average distortion constraints at all sensors whenever it is feasible.Comment: Submitted to IEEE Transactions on Communications in March 2011; last
update in July 201
Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications
Wireless sensor networks monitor dynamic environments that change rapidly
over time. This dynamic behavior is either caused by external factors or
initiated by the system designers themselves. To adapt to such conditions,
sensor networks often adopt machine learning techniques to eliminate the need
for unnecessary redesign. Machine learning also inspires many practical
solutions that maximize resource utilization and prolong the lifespan of the
network. In this paper, we present an extensive literature review over the
period 2002-2013 of machine learning methods that were used to address common
issues in wireless sensor networks (WSNs). The advantages and disadvantages of
each proposed algorithm are evaluated against the corresponding problem. We
also provide a comparative guide to aid WSN designers in developing suitable
machine learning solutions for their specific application challenges.Comment: Accepted for publication in IEEE Communications Surveys and Tutorial
- …