13 research outputs found
A survey of network lifetime maximization techniques in wireless sensor networks
Emerging technologies, such as the Internet of things, smart applications, smart grids and machine-to-machine networks stimulate the deployment of autonomous, selfconfiguring, large-scale wireless sensor networks (WSNs). Efficient energy utilization is crucially important in order to maintain a fully operational network for the longest period of time possible. Therefore, network lifetime (NL) maximization techniques have attracted a lot of research attention owing to their importance in terms of extending the flawless operation of battery-constrained WSNs. In this paper, we review the recent developments in WSNs, including their applications, design constraints and lifetime estimation models. Commencing with the portrayal of rich variety definitions of NL design objective used for WSNs, the family of NL maximization techniques is introduced and some design guidelines with examples are provided to show the potential improvements of the different design criteri
Integrated Circuits and Systems for Smart Sensory Applications
Connected intelligent sensing reshapes our society by empowering people with increasing new ways of mutual interactions. As integration technologies keep their scaling roadmap, the horizon of sensory applications is rapidly widening, thanks to myriad light-weight low-power or, in same cases even self-powered, smart devices with high-connectivity capabilities. CMOS integrated circuits technology is the best candidate to supply the required smartness and to pioneer these emerging sensory systems. As a result, new challenges are arising around the design of these integrated circuits and systems for sensory applications in terms of low-power edge computing, power management strategies, low-range wireless communications, integration with sensing devices. In this Special Issue recent advances in application-specific integrated circuits (ASIC) and systems for smart sensory applications in the following five emerging topics: (I) dedicated short-range communications transceivers; (II) digital smart sensors, (III) implantable neural interfaces, (IV) Power Management Strategies in wireless sensor nodes and (V) neuromorphic hardware
Universal Transceivers: Opportunities and Future Directions for the Internet of Everything (IoE)
The Internet of Everything (IoE) is a recently introduced information and
communication technology (ICT) framework promising for extending the human
connectivity to the entire universe, which itself can be regarded as a natural
IoE, an interconnected network of everything we perceive. The countless number
of opportunities that can be enabled by IoE through a blend of heterogeneous
ICT technologies across different scales and environments and a seamless
interface with the natural IoE impose several fundamental challenges, such as
interoperability, ubiquitous connectivity, energy efficiency, and
miniaturization. The key to address these challenges is to advance our
communication technology to match the multi-scale, multi-modal, and dynamic
features of the natural IoE. To this end, we introduce a new communication
device concept, namely the universal IoE transceiver, that encompasses
transceiver architectures that are characterized by multi-modality in
communication (with modalities such as molecular, RF/THz, optical and acoustic)
and in energy harvesting (with modalities such as mechanical, solar,
biochemical), modularity, tunability, and scalability. Focusing on these
fundamental traits, we provide an overview of the opportunities that can be
opened up by micro/nanoscale universal transceiver architectures towards
realizing the IoE applications. We also discuss the most pressing challenges in
implementing such transceivers and briefly review the open research directions.
Our discussion is particularly focused on the opportunities and challenges
pertaining to the IoE physical layer, which can enable the efficient and
effective design of higher-level techniques. We believe that such universal
transceivers can pave the way for seamless connection and communication with
the universe at a deeper level and pioneer the construction of the forthcoming
IoE landscape
Low Power Memory/Memristor Devices and Systems
This reprint focusses on achieving low-power computation using memristive devices. The topic was designed as a convenient reference point: it contains a mix of techniques starting from the fundamental manufacturing of memristive devices all the way to applications such as physically unclonable functions, and also covers perspectives on, e.g., in-memory computing, which is inextricably linked with emerging memory devices such as memristors. Finally, the reprint contains a few articles representing how other communities (from typical CMOS design to photonics) are fighting on their own fronts in the quest towards low-power computation, as a comparison with the memristor literature. We hope that readers will enjoy discovering the articles within
Power Converters in Power Electronics
In recent years, power converters have played an important role in power electronics technology for different applications, such as renewable energy systems, electric vehicles, pulsed power generation, and biomedical sciences. Power converters, in the realm of power electronics, are becoming essential for generating electrical power energy in various ways. This Special Issue focuses on the development of novel power converter topologies in power electronics. The topics of interest include, but are not limited to: Z-source converters; multilevel power converter topologies; switched-capacitor-based power converters; power converters for battery management systems; power converters in wireless power transfer techniques; the reliability of power conversion systems; and modulation techniques for advanced power converters
Energy efficiency and interference management in long term evolution-advanced networks.
Doctoral Degree. University of KwaZulu-Natal, Durban.Cellular networks are continuously undergoing fast extraordinary evolution to overcome
technological challenges. The fourth generation (4G) or Long Term Evolution-Advanced
(LTE-Advanced) networks offer improvements in performance through increase in network density,
while allowing self-organisation and self-healing. The LTE-Advanced architecture is heterogeneous,
consisting of different radio access technologies (RATs), such as macrocell, smallcells, cooperative
relay nodes (RNs), having various capabilities, and coexisting in the same geographical coverage
area. These network improvements come with different challenges that affect users’ quality of
service (QoS) and network performance. These challenges include; interference management, high
energy consumption and poor coverage of marginal users. Hence, developing mitigation schemes for
these identified challenges is the focus of this thesis.
The exponential growth of mobile broadband data usage and poor networks’ performance along
the cell edges, result in a large increase of the energy consumption for both base stations (BSs) and
users. This due to improper RN placement or deployment that creates severe inter-cell and intracell
interferences in the networks. It is therefore, necessary to investigate appropriate RN placement
techniques which offer efficient coverage extension while reducing energy consumption and mitigating
interference in LTE-Advanced femtocell networks. This work proposes energy efficient and optimal
RN placement (EEORNP) algorithm based on greedy algorithm to assure improved and effective
coverage extension. The performance of the proposed algorithm is investigated in terms of coverage
percentage and number of RN needed to cover marginalised users and found to outperform other RN
placement schemes.
Transceiver design has gained importance as one of the effective tools of interference
management. Centralised transceiver design techniques have been used to improve network
performance for LTE-Advanced networks in terms of mean square error (MSE), bit error rate (BER)
and sum-rate. The centralised transceiver design techniques are not effective and computationally
feasible for distributed cooperative heterogeneous networks, the systems considered in this thesis.
This work proposes decentralised transceivers design based on the least-square (LS) and minimum MSE (MMSE) pilot-aided channel estimations for interference management in uplink
LTE-Advanced femtocell networks. The decentralised transceiver algorithms are designed for the
femtocells, the macrocell user equipments (MUEs), RNs and the cell edge macrocell UEs (CUEs) in
the half-duplex cooperative relaying systems. The BER performances of the proposed algorithms
with the effect of channel estimation are investigated.
Finally, the EE optimisation is investigated in half-duplex multi-user multiple-input
multiple-output (MU-MIMO) relay systems. The EE optimisation is divided into sub-optimal EE
problems due to the distributed architecture of the MU-MIMO relay systems. The decentralised
approach is employed to design the transceivers such as MUEs, CUEs, RN and femtocells for the
different sub-optimal EE problems. The EE objective functions are formulated as convex
optimisation problems subject to the QoS and transmit powers constraints in case of perfect channel
state information (CSI). The non-convexity of the formulated EE optimisation problems is
surmounted by introducing the EE parameter substractive function into each proposed algorithms.
These EE parameters are updated using the Dinkelbach’s algorithm. The EE optimisation of the
proposed algorithms is achieved after finding the optimal transceivers where the unknown
interference terms in the transmit signals are designed with the zero-forcing (ZF) assumption and
estimation errors are added to improve the EE performances. With the aid of simulation results, the
performance of the proposed decentralised schemes are derived in terms of average EE evaluation
and found to be better than existing algorithms
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