Unmanned Aerial Vehicle-Assisted Terahertz-Visible Light Communication Systems: An In-Depth Performance Analysis.

This paper investigates the performance of dual-hop unmanned aerial vehicle (UAV)-assisted communication channels, employing a decode-and-forward (DF) relay architecture. The system leverages terahertz (THz) communication for the primary hop and visible light communication (VLC) for the secondary hop. We conduct an in-depth analysis by deriving closed-form expressions for the end-to-end (E2E) bit error rate (BER). Additionally, we use a Monte Carlo simulation approach to generate best-fitting curves, validating our analytical expressions. A performance evaluation through BER and outage probability metrics demonstrates the effectiveness of the proposed system. Specifically, our results indicate that the proposed system outperforms Free-Space Optics (FSO)-VLC and Radio-Frequency (RF)-VLC at a higher signal-to-noise ratio (SNR). The results of this study provide valuable insights into the feasibility and limitations of UAV-assisted THz-VLC communication systems.

Backscatter Assisted NOMA-PLNC Based Wireless Networks.

In this paper, sum capacity maximization of the non-orthogonal multiple access (NOMA)-based wireless network is studied in the presence of ambient backscattering (ABS). Assuming that ABS is located next to far nodes, it improves the signal strength of far node cluster. By applying suitable successive interference cancellation (SIC) operation, far node cluster act as an internet of things (IoT) reader. Moreover, to improve the uplink performance of the nodes, a physical layer network coding (PLNC) scheme is applied in the proposed network. Power optimization is employed at the access point (AP) to enhance the downlink performance with total transmit power constraint and minimum data rate requirement per user constraint using Lagrangian's function. In addition, end-to-end outage performance of the proposed wireless network is analyzed to enhance each wireless link capacity. Numerical results evident that the outage performance of the proposed network is significantly improved while using the ABS. Furthermore, the average bit error rate (BER) performance of the proposed wireless network is studied to improve the reliability. Simulation results are presented to validate the analytical expressions.

A Fog Computing-Based Device-Driven Mobility Management Scheme for 5G Networks.

The fog computing-based device-driven network is a promising solution for high data rates in modern cellular networks. It is a unique framework to reduce the generated-data, data management overheads, network scalability challenges, and help us to provide a pervasive computation environment for real-time network applications, where the mobile data is easily available and accessible to nearby fog servers. It explores a new dimension of the next generation network called fog networks. Fog networks is a complementary part of the cloud network environment. The proposed network architecture is a part of the newly emerged paradigm that extends the network computing infrastructure within the device-driven 5G communication system. This work explores a new design of the fog computing framework to support device-driven communication to achieve better Quality of Service (QoS) and Quality of Experience (QoE). In particular, we focus on, how potential is the fog computing orchestration framework? How it can be customized to the next generation of cellular communication systems? Next, we propose a mobility management procedure for fog networks, considering the static and dynamic mobile nodes. We compare our results with the legacy of cellular networks and observed that the proposed work has the least energy consumption, delay, latency, signaling cost as compared to LTE/LTE-A networks.

Intelligent UAV Deployment for a Disaster-Resilient Wireless Network.

Deployment of unmanned aerial vehicles (UAVs) as aerial base stations (ABSs) has been considered to be a feasible solution to provide network coverage in scenarios where the conventional terrestrial network is overloaded or inaccessible due to an emergency situation. This article studies the problem of optimal placement of the UAVs as ABSs to enable network connectivity for the users in such a scenario. The main contributions of this work include a less complex approach to optimally position the UAVs and to assign user equipment (UE) to each ABS, such that the total spectral efficiency (TSE) of the network is maximized, while maintaining a minimum QoS requirement for the UEs. The main advantage of the proposed approach is that it only requires the knowledge of UE and ABS locations and statistical channel state information. The optimal 2-dimensional (2D) positions of the ABSs and the UE assignments are found using K-means clustering and a stable marriage approach, considering the characteristics of the air-to-ground propagation channels, the impact of co-channel interference from other ABSs, and the energy constraints of the ABSs. Two approaches are proposed to find the optimal altitudes of the ABSs, using search space constrained exhaustive search and particle swarm optimization (PSO). The numerical results show that the PSO-based approach results in higher TSE compared to the exhaustive search-based approach in dense networks, consuming similar amount of energy for ABS movements. Both approaches lead up to approximately 8-fold energy savings compared to ABS placement using naive exhaustive search.

Hardware Impaired Self-Energized Bidirectional Sensor Networks over Complex Fading Channels.

Rapid emergence of wireless sensor networks (WSN) faces significant challenges due to limited battery life capacity of composing sensor nodes. It is substantial to construct efficient techniques to prolong the battery life of the connected sensors in order to derive their full potential in the future Internet of Things (IoT) paradigm. For that purpose, different energy harvesting (EH) schemes are relying on a wide array of sources. Following the same objective, in this work, we have observed a time-switching EH for half-duplex (HD) bidirectional WSN, which performed in-between relaying over Hoyt fading channels. For its comprehensive performance analysis, rapidly converging infinite-series expressions have been provided with focus on the outage probability (OP) and achievable throughput of the hardware-impaired system. Additionally, asymptotic behavior of these performance measures has also been provided. Further, an approach to the symbol-error probability (SEP) analysis is also presented in the context of the observed system. Finally, we consider the shadowing influence along the WSN propagation path. Performance analysis of observed EH system operating over Rician-shadowed fading channels has been carried out, with deriving exact corresponding infinite-series expressions for outage probability (OP) and achievable throughput of the system under the hardware impairment conditions. In addition, bidirectional relaying in a mixed fading environment has been considered.

A New Construction of High Performance LDPC Matrices for Mobile Networks.

Secure and reliable information flow is one of the main challenges in social IoT and mobile networks. Information flow and data integrity is still an open research problem. In this paper, we develop new methods of constructing systematic and regular Low-Density Parity-Check Matrices (LDPCM), inspired by the structure of the Sarrus method and geometric designs. Furthermore, these codes have cyclic structure and therefore, are less complex in computation and also require less memory in hardware implementation. Besides, an optimal method of post-processing for deleting girths four is presented. Numerical results show that the codes constructed by these methods perform well over the additive white Gaussian noise (AWGN) channel when decoded with the sum-product LDPC iterative algorithms. The proposed methods can be very efficient in terms of reducing memory consumption and improving the convergence speed of the decoder particularly in IoT and mobile networks.

Novel SWIPT Schemes for 5G Wireless Networks.

In this paper, we present a few novel simultaneous wireless information and power transfer (SWIPT) schemes that can be effectively used in various 5G wireless network implementations. First, we study the possibility of integrating distributed energy beamforming with the data rate fairness beamforming in a cooperative communication system with multiple cooperative relays and multiple destination users communicating simultaneously. We show that the system exploits significant performance gain using such a joint energy and data rate fairness beamforming scheme. Further, we propose an enhanced version of the SWIPT scheme, the energy-efficient modulation-based non-orthogonal multiple access (M-NOMA) SWIPT scheme, and observe its system efficiency in terms of more harvested energy. Finally, we consider an energy-harvesting SWIPT scheme where the channel response is estimated using the energy-harvesting signal as pilots superimposed on the information signal. For such a scheme, we compute the optimum transmit power ratio between the pilot and information signals under varying SNR conditions and improve the accuracy of the decoding process at the reception.

Determinants of under-five mortality in Sri Lanka: A multilevel analysis of 2016 Sri Lankan DHS data.

Under-five mortality (U5M) is considered a major public health issue directly impacts a country's development. This study analyzed the prognostic factors of U5M in Sri Lanka using data from the 2016 Demographic and Health Survey (DHS) of 8123 children. The study employed both a binary logistic regression model (BLRM) and a binary logistic random intercept multilevel model (BLRIMM) and compared the accuracy of each model's prediction percentage. The results showed that the BLRIMM had a higher correct prediction percentage (98.67%) compared to the BLRM (98.31%). The study found that children who were not breastfed (Odds Ratio (OR) = 116.74, 95% Confidence Interval (CI) = 62.97-216.41), were part of multiple births (OR = 3.73, 95% CI = 1.21-11.51), did not have a normal delivery (OR = 1.86, 95% CI = 1.11-3.12), were born to mothers who had experienced previous miscarriages or child loss (OR = 2.27, 95% CI = 1.26-4.11), and were born to mothers with a higher Body Mass Index (BMI) (OR = 1.05, 95% CI = 1.003-1.10) had higher odds of U5M. The odds of U5M were found to be lower among Buddhists (OR = 0.06, 95% CI = 0.01-0.50), Hindus (OR = 0.05, 95% CI = 0.01-0.46), and Roman Catholics (OR = 0.032, 95% CI = 0.003-0.307) compared to the "Other Religions" category in the dataset. The estimated covariance parameter of the random intercept (0.8231, p-value = 0.0405) indicated significant unobserved cluster-level variation in U5M. The study's results emphasize the importance of addressing religion related differences of U5M and improving maternal education regarding healthy lifestyle, proper food intake, the significance of breastfeeding, safe delivery methods, safety measures during pregnancy and childbirth in cases of multiple births, and proper child care after birth.