79 research outputs found
RF-Powered Cognitive Radio Networks: Technical Challenges and Limitations
The increasing demand for spectral and energy efficient communication
networks has spurred a great interest in energy harvesting (EH) cognitive radio
networks (CRNs). Such a revolutionary technology represents a paradigm shift in
the development of wireless networks, as it can simultaneously enable the
efficient use of the available spectrum and the exploitation of radio frequency
(RF) energy in order to reduce the reliance on traditional energy sources. This
is mainly triggered by the recent advancements in microelectronics that puts
forward RF energy harvesting as a plausible technique in the near future. On
the other hand, it is suggested that the operation of a network relying on
harvested energy needs to be redesigned to allow the network to reliably
function in the long term. To this end, the aim of this survey paper is to
provide a comprehensive overview of the recent development and the challenges
regarding the operation of CRNs powered by RF energy. In addition, the
potential open issues that might be considered for the future research are also
discussed in this paper.Comment: 8 pages, 2 figures, 1 table, Accepted in IEEE Communications Magazin
Energy Detection of Unknown Signals over Cascaded Fading Channels
Energy detection is a favorable mechanism in several applications relating to
the identification of deterministic unknown signals such as in radar systems
and cognitive radio communications. The present work quantifies the detrimental
effects of cascaded multipath fading on energy detection and investigates the
corresponding performance capability. A novel analytic solution is firstly
derived for a generic integral that involves a product of the Meijer
function, the Marcum function and arbitrary power terms. This solution
is subsequently employed in the derivation of an exact closed-form expression
for the average probability of detection of unknown signals over *Rayleigh
channels. The offered results are also extended to the case of square-law
selection, which is a relatively simple and effective diversity method. It is
shown that the detection performance is considerably degraded by the number of
cascaded channels and that these effects can be effectively mitigated by a
non-substantial increase of diversity branches.Comment: 12 page
Blockchain-enabled Clustered and Scalable Federated Learning (BCS-FL) Framework in UAV Networks
Privacy, scalability, and reliability are significant challenges in unmanned
aerial vehicle (UAV) networks as distributed systems, especially when employing
machine learning (ML) technologies with substantial data exchange. Recently,
the application of federated learning (FL) to UAV networks has improved
collaboration, privacy, resilience, and adaptability, making it a promising
framework for UAV applications. However, implementing FL for UAV networks
introduces drawbacks such as communication overhead, synchronization issues,
scalability limitations, and resource constraints. To address these challenges,
this paper presents the Blockchain-enabled Clustered and Scalable Federated
Learning (BCS-FL) framework for UAV networks. This improves the
decentralization, coordination, scalability, and efficiency of FL in
large-scale UAV networks. The framework partitions UAV networks into separate
clusters, coordinated by cluster head UAVs (CHs), to establish a connected
graph. Clustering enables efficient coordination of updates to the ML model.
Additionally, hybrid inter-cluster and intra-cluster model aggregation schemes
generate the global model after each training round, improving collaboration
and knowledge sharing among clusters. The numerical findings illustrate the
achievement of convergence while also emphasizing the trade-offs between the
effectiveness of training and communication efficiency.Comment: 6 pages, 7 figures, 2023 IEEE International Workshop on Computer
Aided Modeling and Design of Communication Links and Networks (IEEE CAMAD),
Edinburgh U
Internet of Mirrors for Connected Healthcare and Beauty: A Prospective Vision
With the shift towards smart objects and automated services in many
industries, the health and beauty industries are also becoming increasingly
involved in AI-driven smart systems. There is a rising market demand for
personalised services and a need for unified platforms in many sectors,
specifically the cosmetics and healthcare industries. Alongside this rising
demand, there are two major gaps when considering the integration of autonomous
systems within these sectors. Firstly, the existing smart systems in the
cosmetics industry are limited to single-purpose products and the employed
technologies are not widespread enough to support the growing consumer demand
for personalisation. Secondly, despite the rise of smart devices in healthcare,
the current state-of-the-art services do not fulfil the accessibility demands
and holistic nature of healthcare. To bridge these gaps, we propose integrating
autonomous systems with health and beauty services through a unified visual
platform coined as the Internet-of-Mirrors (IoM), an interconnected system of
smart mirrors with sensing and communication capabilities where the smart
mirror functions as an immersive visual dashboard to provide personalised
services for health and beauty consultations and routines. We aim to present an
overview of current state-of-the-art technologies that will enable the
development of the IoM as well as provide a practical vision of this system
with innovative scenarios to give a forward-looking vision for assistive
technologies. We also discuss the missing capabilities and challenges the
development of the IoM would face and outline future research directions that
will support the realisation of our proposed framework.Comment: 21 pages, 6 figure
Performance analysis of SWIPT relay networks with noncoherent modulation
In this paper, we investigate the performance of noncoherent modulation in simultaneous wireless information and power transfer (SWIPT) relay networks. Noncoherent modulation schemes eliminate the need for instantaneous channel state information (CSI) estimation, and therefore, minimise the overall energy consumption of the network. In particular, we adopt a moments-based approach to develop a comprehensive novel analytical framework for the analysis of the outage probability, achievable throughput, and average symbol error rate (ASER) of a dual-hop SWIPT relay system considering the time switching (TS) and power splitting (PS) receiver architectures. In addition, through the derivation of new asymptotic analytical results for the outage probability and ASER, we analytically demonstrate that the diversity order of the considered system is non-integer less than 1 in the high SNR regime. Our results show that there is a unique value for the PS ratio that minimises the outage probability of the system, while this is not the case for the TS protocol. We also demonstrate that, in terms of system throughput, the TS relaying scheme is superior to the PS relaying scheme at lower SNR values. An extensive Monte Carlo simulation study is presented to corroborate the proposed analytical model
Performance of reconfigurable intelligent surfaces in the presence of generalized Gaussian noise
In this letter, we investigate the performance of reconfigurable intelligent surface (RIS)-assisted communications, under the assumption of generalized Gaussian noise (GGN), over Rayleigh fading channels. Specifically, we consider an RIS, equipped with N reflecting elements, and derive a novel closed-form expression for the symbol error rate (SER) of arbitrary modulation schemes. The usefulness of the derived new expression is that it can be used to capture the SER performance in the presence of special additive noise distributions such as Gamma, Laplacian, and Gaussian noise. These special cases are also considered and their associated asymptotic SER expressions are derived, and then employed to quantify the achievable diversity order of the system. The theoretical framework is corroborated by numerical results, which reveal that the shaping parameter of the GGN (α) has a negligible effect on the diversity order of RIS-assisted systems, particularly for large α values. Accordingly, the maximum achievable diversity order is determined by N
Performance analysis of SWIPT relaying systems in the presence of impulsive noise
We develop an analytical framework to characterize the effect of impulsive noise on the performance of relay-assisted simultaneous wireless information and power transfer (SWIPT) systems. We derive novel closed-form expressions for the pairwise error probability (PEP) considering two variants based on the availability of channel state information (CSI), namely, blind re-laying and CSI-assisted relaying. We further consider two energy harvesting (EH) techniques, i.e., instantaneous EH (IEH) and average EH (AEH). Capitalizing on the derived analytical results, we present a detailed numerical investigation of the diversity order for the underlying scenarios under the impulsive noise assumption. For the case when two relays and the availability of a direct link, it is demonstrated that the considered SWIPT system with blind AEH-relaying is able to achieve an asymptotic diversity order of less than 3, which is equal to the diversity order achieved by CSI-assisted IEH-relaying. This result suggests that, by employing the blind AEH relaying, the power consumption of the network can be reduced, due to eliminating the need of CSI estimation. This can be achieved without any performance loss. Our results further show that placing the relays close to the source can significantly mitigate the detrimental effects of impulsive noise. Extensive Monte Carlo simulation results are presented to validate the accuracy of the proposed analytical framework
A Blockchain-Enabled Framework of UAV Coordination for Post-Disaster Networks
Emergency communication is critical but challenging after natural disasters
when ground infrastructure is devastated. Unmanned aerial vehicles (UAVs) offer
enormous potential for agile relief coordination in these scenarios. However,
effectively leveraging UAV fleets poses additional challenges around security,
privacy, and efficient collaboration across response agencies. This paper
presents a robust blockchain-enabled framework to address these challenges by
integrating a consortium blockchain model, smart contracts, and cryptographic
techniques to securely coordinate UAV fleets for disaster response.
Specifically, we make two key contributions: a consortium blockchain
architecture for secure and private multi-agency coordination; and an optimized
consensus protocol balancing efficiency and fault tolerance using a delegated
proof of stake practical byzantine fault tolerance (DPoS-PBFT). Comprehensive
simulations showcase the framework's ability to enhance transparency,
automation, scalability, and cyber-attack resilience for UAV coordination in
post-disaster networks.Comment: 6 pages, 4 figures,IEEE 99th Vehicular Technology Conference:
VTC2024-Spring, Singapor
Performance of reconfigurable intelligent surfaces in the presence of generalized Gaussian noise
In this letter, we investigate the performance of reconfigurable intelligent surface (RIS)-assisted communications, under the assumption of generalized Gaussian noise (GGN), over Rayleigh fading channels. Specifically, we consider an RIS, equipped with N reflecting elements, and derive a novel closed-form expression for the symbol error rate (SER) of arbitrary modulation schemes. The usefulness of the derived new expression is that it can be used to capture the SER performance in the presence of special additive noise distributions such as Gamma, Laplacian, and Gaussian noise. These special cases are also considered and their associated asymptotic SER expressions are derived, and then employed to quantify the achievable diversity order of the system. The theoretical framework is corroborated by numerical results, which reveal that the shaping parameter of the GGN (α) has a negligible effect on the diversity order of RIS-assisted systems, particularly for large α values. Accordingly, the maximum achievable diversity order is determined by N
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