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Underwater optical wireless communications (UOWCs) are promising and potential wireless carriers to envisage underwater phenomenal activities for various applications towards the futuristic 5G and beyond (5GB) wireless systems. The main challenges to deploy underwater applications are the physicochemical properties and strong turbulence channel conditions. In this regard, the end-to-end (E2E) performance analysis of a dual-hop mixed FSO/UVLC system under the intensity modulation/direct detection (IM/DD) technique in consideration of pulse amplitude modulation (PAM) scheme is investigated. Throughout this study, to tackle the issues of moderate-to-strong turbulence channel conditions, this work deploys the Gamma-Gamma (GG) distribution fading model and the links are designed by unifying plane wave models in the corresponding links, respectively. This investigation outperforms higher achievable data rate with minimal delay response and enhance network connectivity in real-time monitoring scenarios as compared with the traditional underwater wireless communication technologies. In more contrast, the probability distribution function (PDF), cumulative distribution function (CDF), and closed-form expression of the system are derived and presented in terms of Meijer-G function as well as Extended Generalized Bivariate Meijer-G Function (EGBMGF). The significant E2E performance metrics are obtained by employing the decode-and-forward (DF) relay protocol in hostile channel conditions. In aggregating this work, we combine the analytical expressions that present an efficient tool to depict the impact of channel parameters on the system. The simulation results are plausible of the system performance metrics as average BER (ABER) and outage probability $(P_{out})$ in the presence of pointing and without pointing error events. Finally, in this work, we use the Monte-Carlo approach for the best fitting curves and validate the numerical expression yields simulation results. [ABSTRACT FROM AUTHOR]

Security issue in underwater visible light communication (UVLC) arises mainly due to the scattering effect wherein numerous photons are statistically generated when a light beam strikes a water molecule. This paper considers an underwater communication scenario wherein a floating vehicle (FV) transmitter that is equipped with multiple light-emitting diodes (LEDs) communicates with the two legitimate near-end and far-end underwater vehicles (UVs) in presence of an eavesdropper. In particular, two non-orthogonal multiple access (NOMA) technology-based optimal LED selection (OLS) and suboptimal LED selection (SLS) schemes are proposed to select a LED that can transmit the information with the highest secrecy rate against active/passive eavesdropping attacks. Furthermore, the FVT transmits the information to both UVs with the selected LED only. Utilizing the successive interference cancellation (SIC) characteristic, this paper derives the closed-form secrecy outage probability expressions for both single-LED and multi-LED transmission strategies for both known and unknown CSI. The security performance of the proposed multi-LED NOMA-UVLC is compared with the conventional single-LED NOMA-UVLC under the effects of air bubbles for both fresh and salty water types. In addition, the validity of the numerical results is verified through Monte-carlo simulation analysis. [ABSTRACT FROM AUTHOR]

A multiple access (MA) soft-decision (SD) decoder based on the cost rankings of the channel output matrix, is proposed and applied in an optical wireless communication system in which permutation-based optical codes (POCs) are used. The proposed decoder determines the possible transmitted MA codewords by implementing the Hungarian and Murty’s algorithms to solve and rank the costs of all the possible codewords of the received signal. The performance of the proposed Hungarian-Murty (HM) decoder is evaluated in comparison with two decoders based on the Exhaustive Search (ES) technique, in terms of computational complexity and block error rate (BER). It is found that when POCs are employed, the proposed HM decoder achieves better BER performance with a low decoding complexity in comparison to the ES based decoders. [ABSTRACT FROM AUTHOR]

In this paper, a resource allocation and data gathering scenario of an unmanned aerial vehicle (UAV) assisted wireless powered sensor network is investigated, in which the sensor nodes (SNs) are remotely powered by power beacons (PBs) via radio-frequency wireless power transmission (RF-WPT). A time-block structure with two phases is proposed to accommodate operations in the proposed system. During Phase-I, SNs harvest energy from PBs and periodically send its sensed data to the selected cluster heads (CHs). In Phase-II, an UAV collects the data from CHs to be delivered to the data sink for further processing avoiding the need for long range transmission and multi hop communication to the data sink. Then, a closed-form expression for outage probability of the proposed system over Rayleigh and Rician fading channels is derived. Next, outage probability minimization problem is formulated to obtain optimal time allocation for RF-WPT energy harvesting to improve the system performance. Due to the complexity of the problem, Lagrangian duality method is used to develop an asymptotic optimal solution with less execution complexity avoiding complex brute force/ exhaustive search approach. Furthermore, a heuristic method is presented to further lower the computation complexity. Simulation results reveal the superiority of the proposed methods compare to brute force/ exhaustive search approach via analysis, comparison and insights of the system performance results. Finally, the performance superiority of the proposed system is demonstrated with compare to identified baseline WSNs. [ABSTRACT FROM AUTHOR]

In this paper, we develop an innovative approach to quantitatively characterize the performance of ultra-dense wireless networks in a plethora of propagation environments. The proposed framework has the potential of simplifying the cumbersome procedure of analyzing the coverage probability and allowing the unification of single- and multi-antenna networks through compact analytical representations. By harnessing this key feature, we develop a novel statistical machinery to study the scaling laws of wireless networks densification considering general channel power distributions including small-scale fading and shadowing as well as associated beamforming and array gains due to the use of multiple antenna. We further formulate the relationship between network density, antenna height, antenna array seize and carrier frequency showing how the coverage probability can be maintained with ultra-densification. From a system design perspective, we show that, if multiple antenna base stations are deployed at higher frequencies, monotonically increasing the coverage probability by means of ultra-densification is possible, and this without lowering the antenna height. Simulation results substantiate performance trends leveraging network densification and antenna deployment and configuration against path loss models and signal-to-noise plus interference thresholds. [ABSTRACT FROM AUTHOR]

With the advancements in real-time applications, age of information (AoI) emerges to describe the freshness of data. Here, we investigate AoI performance metric in simultaneous wireless information and power transfer (SWIPT) enabled cooperative wireless communication system. We use two SWIPT protocols: time-switching (TS) and power- splitting (PS) at the relay node and compute the AoI performance. SWIPT has a great potential to energize energy constrained communication nodes in wireless sensor networks (WSNs) and Internet of Things (IoT) applications while maintaining a high degree of Quality-of-Service (QoS). Finally, we discuss the possible future directions in terms of 5G and beyond (5GB) to realize the integration of SWIPT with the enhancement of industrial IoT together with ultra-reliable low latency communication (URLLC) for future 3GPP releases. [ABSTRACT FROM AUTHOR]

This paper presents efficient interference-mitigation techniques, such as fractional frequency reuse (FFR) and soft frequency reuse (SFR) schemes, in multicell orthogonal frequency division multiple access networks under the composite multipath fading environment, where Rayleigh fading is superimposed over log-normal shadowing. We begin by outlining the obtained explicit expressions of area spectral efficiency in down-link transmission for both FFR and SFR schemes. The theoretical result are shown to be very accurate with their simulated counterparts using Monte Carlo simulations. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicles (UAVs) have recently been envisaged as an enabling technology of 5G. UAVs act as an intermediate relay node to facilitate uninterrupted, high quality communication between information sources and their destination. However, UAV energy management has been a major issue of consideration due to limited power supply, affecting flight duration. Thus, we introduce in this paper a unified energy management framework by resorting to wireless power transfer (WPT), simultaneous wireless information and power transfer (SWIPT) and self-interference (SI) energy harvesting (EH) schemes, in cooperative relay communications. In our new technique, UAVs are deployed as relays equipped with a decode and forward protocol and EH capability operating in a full-duplex (FD) mode. The UAV assists information transmission between a terrestrial base station and a user. The UAV's transmission capability is powered exclusively by the energy harvested from WPT, radio frequency signal transmitted from the source via time-switching SWIPT protocol and SI exploitation. We improve the overall system throughput by the use of FD based UAV-assisted cooperative system. In this proposed system, we formulate two optimization problems to minimize end-to-end outage probability, subject to UAV's power profile and trajectory for a DF relay scheme, respectively. The KKT conditions have been used to obtain closed-form solutions for the two formulated problems. Numerical simulation results validate all the theoretical results. We demonstrate that the performance of our proposed unified EH scheme outperforms that of existing techniques in the literature. [ABSTRACT FROM AUTHOR]

Due to the rapid growth of IoT and other connected devices, developing battery-less and/or self-sustainable devices to enable green communication is crucial. This letter presents a practical simultaneous wireless information and power transfer (SWIPT) scheme based on an $M$ -ary quadrature-amplitude modulation (QAM) modulation based technique (${MS} $). The proposed scheme employs hybrid constellation shaping system (HCS) to improve the spectral efficiency. We compare ${MS} $ with the traditional power splitting scheme based SWIPT (${PS} $) technique. We demonstrate that our proposed scheme outperforms ${PS} $ in terms of the error rate performance. ${MS} $ scheme is mainly focused on improving the reliability of low powered IoT sensors and it offers better achievable information rate at operating SNR region as compared to that of ${PS} $. Those improvements come at the expense of a slight reduction in the maximum achievable spectral efficiency. [ABSTRACT FROM AUTHOR]

Mobile edge computing (MEC) reduces the computational distance between the source and the servers by fortifying near-user site evaluations of data for expedited communications, using caching. Caching provides ephemeral storage of data on designated servers for low-latency transmissions. However, with the network following a hierarchical layout, even the near-user site evaluations can be impacted by the overheads associated with maintaining a perpetual connection and other factors (e.g., those relating to the reliability of the underpinning network). Prior solutions study reliability as a factor of throughput, delays, jitters, or delivery ratio. However, with modern networks supporting high data rates, a current research trend is in ultrareliability. The latter is defined in terms of availability, connectivity, and survivability. Thus, in this paper, we focus on the ultrareliable communication in MEC. Specifically, in our setting, we use drones as on-demand nodes for efficient caching. While some existing solutions use cache-enabled drones, they generally focus only on the positioning problem rather than factors relating to ultrareliable communications. We present a novel neural-blockchain-based drone-caching approach, designed to ensure ultrareliability and provide a flat architecture (via blockchain). This neural-model fortifies an efficient transport mechanism, since blockchain maintains high reliability amongst the peers involved in the communications. The findings from the evaluation demonstrate that the proposed approach scores well in the following metrics: the probability of connectivity reaches 0.99; energy consumption is decreased by 60.34%; the maximum failure rate is affected by 13.0%; survivability is greater than 0.90; reliability reaches 1.0 even for a large set of users. [ABSTRACT FROM AUTHOR]

The ever-increasing demands of vehicular networks pose significant challenges such as availability, computation complexity, security, trust, authentication, etc. This becomes even more complicated for high-speed moving vehicles. As a result, increasing the capacity of these networks has been attracting considerable awareness. In this regard, the next generation of cellular networks, 5G, is expected to be a promising solution enabling high data rates, capacity, and quality of service as well as low latency communications. However, 5G networks still face challenges in providing ubiquitous and reliable connections among high-speed vehicles. Thus, to overcome the gaps in the existing solutions, we propose a software defined network (SDN)-based consolidated framework providing end-to-end security and privacy in 5G enabled vehicular networks. The framework simplifies network management through SDN, while achieving optimized network communications. It operates in two phases: first, an elliptic curve cryptographic based authentication protocol is proposed to mutually authenticate the cluster heads and certificate authority in SDN-based vehicular setups, and, second, an intrusion detection module supported by tensor based dimensionality reduction is designed to reduce the computational complexity and identify the potential intrusions in the network. In order to assess the performance of the proposed framework, an extensive evaluation is performed on three simulators; NS3, SUMO, and SPAN. To harness the potential benefits of the proposed model, the first module, is evaluated on the basis of security features, whereas the second module is evaluated, and compared with the existing state-of-the-art models, on the basis of detection rate, false positive rate, accuracy, detection time, and communication overhead. The simulation results indicate the superiority of the proposed framework as compared to the existing models. [ABSTRACT FROM AUTHOR]