This paper presents a joint resource allocation and network slicing framework for hybrid radio frequency (RF) and visible light communication (VLC) systems based on a proportional-fairness (PF) objective. The proposed approach formulates a convex optimization problem that jointly allocates bandwidth resources across multiple slices and access technologies to balance aggregate throughput and user fairness. A relaxed PF solution is first derived via projected gradient optimization, followed by two practical rounding strategies, a simple threshold-based method and a greedy assignment heuristic that produce integer allocations with low complexity. Simulation results for a 20 MHz hybrid RF/VLC system (10 MHz per band) demonstrate that the proposed PF-based allocation achieves aggregate sum-rates of approximately 450–500 Mbps with Jain’s fairness indices greater than 0.9, thus outperforming static and rounding baselines by 10–15% in throughput while maintaining high fairness. The analysis is further extended to asymmetric RF/VLC bandwidth conditions, demonstrating that the proposed PF-based slicing maintains high fairness while scaling throughput effectively. These results confirm that the PF formulation effectively captures the throughput fairness trade-off and provides near-optimal slicing performance under realistic indoor bandwidth and power constraints.

Unmanned aerial vehicles (UAVs)-assisted communication systems are considered as a promising technology in diverse verticals. This paper studies the deployment of UAVs in wireless sensor network (WSN) systems. Considering the energy-constrained nature of the wireless sensors , we have proposed a multi-UAV deployment algorithm that minimizes the maximum power transmitted among the sensor nodes (SN) for given minimum data collection rate, minimum data-transferring rate, maximum power and height constraints. The problem is divided into three subproblems in order to reduce the complexity involved in solving them as a single problem. The subproblems are UAV-SN association, 2D positioning of the UAVs and the altitude optimization of the UAVs. Each subproblem is optimized by fixing other parameters as constant. First, the UAV-SN association is addressed using a customized Gale–Shapley algorithm. Second, the 2D positions of the UAVs are optimized using a modified pattern search algorithm. Third, the altitudes of the UAVs are optimized through a customized inexact line search algorithm. Finally, we proposed a combined optimization algorithm that integrates the approaches of all three subproblems in the suitable hierarchy to provide an optimal or a near-optimal solution. In the combined optimization, the first and second subproblems are iteratively solved until the convergence. After that, the third subproblem is solved independently for each UAV. Moreover, the combined optimization gives the minimum number of UAVs required to serve all the SNs with the given rate and power constraints. The numerical simulation validates the efficacy of our proposed algorithms. The results indicate a significant performance gain compared to the benchmark methods in terms of the number of iterations for convergence, maximum transmission power requirement power and the minimum number of UAV requirements.

This paper proposes a deep joint source-channel coding (DJSCC) to minimize the age of information (AoI) for image transmission. A new content-based AoI metric called age of misclassified information (AoMI) is introduced to estimate the freshness of the information in an image classification system. AoMI is a critical metric in timely information delivery, measuring the age of the most recently received and correctly classified image at the receiver. The proposed system leverages a deep neural network at the transmitter to map image pixels directly to channel input symbols, eliminating the need for separate source and channel coding. At the receiver, the channel output is processed to perform image classification. To analyze the AoMI performance of the system, a stochastic hybrid systems (SHS) approach is employed. Closed-form expressions for the average AoMI (AAoMI) are derived, providing insights into the impact of system parameters on the AoMI. Simulation results demonstrate the effectiveness of the proposed DJSCC-based system in achieving lower AoMI compared to traditional separate source and channel coding schemes. The findings highlight the potential of deep learning techniques to maintain the freshness of the information in wireless communication systems. This work paves the way for the design of wireless communication systems that prioritize the freshness of delivered information – this is crucial in applications such as real-time monitoring, surveillance, and control systems.

Integration of simultaneous wireless information and power transfer (SWIPT) enabled non-orthogonal multiple access (NOMA) in an unmanned aerial vehicle (UAV) is a novel variant that benefits enhanced spectrum efficiency and energy efficiency. Despite these potential advantages, resource allocations and UAV trajectory optimizations pose major challenges to its realization. Thus, in this work, we optimize the UAV’s trajectory including its positioning, in up-link, and down-link NOMA-enabled UAV-assisted communication network while maximizing achievable rates at the ground users. To further enhance energy efficiency, the UAV is equipped with SWIPT to harvest energy from the received signals. The proposed solution utilizes the particle swarm optimization (PSO) tool to optimize the UAV’s position to maximize the minimum achievable rate while maximizing SWIPT-based energy harvesting. Simulation results demonstrate the improved minimum achievable rate of the proposed solution making the proposed communication model effective over conventional UAV communications.

This paper investigates the performance of dual-hop UAV-assisted communication system, employing a decode and forward relay architecture. The system utilizes Terahertz (THz) communication in the primary hop and Visible Light Communication (VLC) in the secondary hop. We conduct a thorough analysis by deriving closed-form expressions for end-to-end bit error rate (BER). Furthermore, a Monte Carlo approach will be employed to generate best fitting curves and validate the numerical expressions with simulation results. The outcomes of this work offer valuable insights into the feasibility and limitations of UAV-assisted THz-VLC systems.

Wildfires are a common and dangerous natural phenomenon that harms more than just the natural vegetation. There have been many methods proposed to detect the occurrence of wildfires using randomly placed sensor nodes, yet the optimization of the placement of sensor nodes has not been discussed in studies. This study presents a wireless sensor network (WSN) model supported by an unmanned aerial vehicle (UAV) that focuses on determining optimal locations for sensor placement, optimal determination of cluster heads (CHs), and UAV trajectory to achieve maximum efficiency. The system further introduces the use of time-splitting based simultaneous wireless information and power transfer (SWIPT) to harvest energy for the CHs so as to improve energy efficiency and expand the concept of zero-energy devices within the WSN for wildfire detection.

Simultaneous wireless information and power transfer (SWIPT) enabled wireless cooperative communication system is an emerging technology for future wireless communication applications. Furthermore, the Internet of Things (IoT) serves a diverse range of purposes, some of which are mission-critical and require constantly evolving real-time data. Thus, the information received at the destination must be updated timely manner to ensure its freshness. A performance metric named age of information (AoI) has been introduced to measure the freshness of received information. This study estimates the AoI of a SWIPT assisted decode and forward two-way relay assisted status update system in which two sources attempt to exchange status updates as quickly as possible to the destination. The relay system employs short packet communication to adhere to the latency and reliability requirements of the wireless communication system. We study the average Age of Information (AAoI) at the destination in the proposed relay network and derive approximations for the weighted sum AAoI under two different types of transmission scheduling policies at the relay: transmit without waiting (TWW) and wait until charged (WUC). Furthermore, the effects of transmission power, packet size, the distance between relay and sources and block-length on the weighted sum AAoI of the proposed SWIPT assisted short packet relay network are extensively investigated. The performance differences of the considered transmission policies are compared and insights are provided. Numerical simulations using the Monte Carlo method have been employed to validate derived analytical expressions.

Internet of Things (IoT) is a rapidly growing network of interconnected devices that has the potential to revolutionize many industries and sectors. However, IoT devices are often vulnerable to security and reliability threats due to their limited resources and the challenging environments in which they are deployed. This study proposes a Secure and Reliable Cognitive Radio Network (SAR-CRN) architecture for the IoT applications. Leveraging cognitive radio capabilities, SAR-CRN enables efficient spectrum sharing between primary users and resource-limited IoT devices. We propose a two-step relay selection scheme that identifies the optimal relay node capable of correctly decoding the information and re-transmitting it with the highest secrecy rate. More-specifically, this scheme optimizes relay selection for enhanced security and reliability within the SAR-CRN framework. The performance of the proposed SARCRN system is evaluated using a variety of metrics, including the probability of correct decoding ability, and the average secrecy capacity (ASC) and secrecy outage probability (SOP) under both known and unknown channel state information (CSI) scenarios. The result analysis demonstrate that the proposed SAR-CRN system significantly outperforms conventional CRNs in terms of security and reliability, paving the way for secure and reliable communication in resource-constrained IoT environments.

One of the most challenging tasks in a disaster scenario is the detection and localization of victims with high accuracy and minimum delay, especially in out-of-coverage areas. In the event of a disaster that disrupts the cellular network infrastructure, emergency calls can be relayed to the core network via multi-hop D2D communications. In this paper, a localization system is proposed that uses radio measurements obtained through such D2D multi-hop assisted emergency calls to localize in-coverage and out-of-coverage devices. To address the uncertainty and gradual reception of data in real-time in this scenario, a dynamic constraint satisfaction-based Multi Victim Localization Algorithm(MVLA)is proposed. This algorithm locates multi-hop devices in a progressive propagation manner to provide fast and accurate updates on victim locations. Additionally, three modes of$\mathit{MVLA}$, namely$\mathit{MVLA}_{recent}$,$\mathit{MVLA}_{seq}$, and$\mathit{MVLA}_{all}$are proposed. Simulation results demonstrate that$\mathit{MVLA}_{all}$has a lower localization error compared to$\mathit{MVLA}_{recent}$and$\mathit{MVLA}_{seq}$. Moreover,$\mathit{MVLA}_{all}$, is compared with an existing particle filtering-based localization algorithm called RSSI Monte-Carlo Boxed Localization (RSSI-MCL) under an increasing number of emergency user devices and functional gNodeBs. Results show that$\mathit{MVLA}_{all}$significantly outperforms theRSSI-MCLmethod in terms of localization accuracy and computational delay.

This paper introduces an adaptive technique for grouping variable nodes in decoding non-binary LDPC codes that involve symbol flipping. The technique considers both the individual symbol reliability and majority-based voting when grouping variable nodes in each iteration. Groups are formed based on the cumulative density of the variable nodes, with the least reliable variable nodes given the highest priority. The decoding algorithm then proceeds to decode subsequent groups in order of decreasing priority. The results of numerical analysis demonstrate that this approach strikes a balance between computational complexity and bit error rate performance, making it suitable for various applications, such as data storage and mobile networks.

The advent of visible light communication (VLC) towards 5G and beyond (5GB) networks opened new doors to unveil the mysteries of unguided mediums such as ocean. The varying physicochemical properties of water introduces the underwater optical turbulence (UOT). The UOT of UVLC link is modelled as unified Gamma-Gamma (GG) distribution fading under moderate-to-strong turbulence channel conditions as well as the misalignment of transceivers following exponential fading are included and studied. This study also contains the effect of UOT which is characterized by multiple water layers within the Monte Carlo simulation framework. The end-to-end (E2E) performances of a Single-Input and Multi-Output (SIMO) underwater VLC (UVLC) system is in consideration of Intensity-Modulation/Direct-Detection (IM/DD) technique which is obtained to fulfill the current communication requirements in hostile aqueous channels. More specifically, the probability distribution function (PDF) and cumulative distribution function (CDF) are derived to obtain the E2E performance metrics of the SIMO-UVLC system in terms of Meijer-G function. Consequently, novel closed-form expressions for average bit-error-rate (ABER) and outage probability of the system are formulated. Finally, the numerical and simulation results are obtained based on the experimental data in mixed water layers of the oceanic environments, and analytically verified through the Monte Carlo simulation approach in harsh channel conditions.

Abstract Internet‐of‐things is an enabling technology in the fourth‐generation industrial revolution. The freshness of the data sent by a sensor node (SN) is an important parameter in the Internet‐of‐things, unlike the throughput in cellular communications. A relatively new performance metric named age of information (AoI) is used in this paper to quantify the freshness of the data. The SN, located in the transport infrastructure, harvests energy from radio frequency signals transmitted by the FD‐UAV. This is used to transmit real‐time sensor observations to the data sink via FD‐UAV. The SN generates an update after replenishing the battery and transmits it by using the harvested energy. A closed‐form expression for average AoI is derived as a function of time allocated for energy harvesting. The optimal time allocation for energy harvesting that maximizes the freshness of data update is identified. A deep learning technique namely long‐short term memory is used to predict the average AoI. Simulation results demonstrate the usefulness of the performance bounds in terms of the freshness of data updates.

This article focuses on the hidden benefits of harvesting the wasted energy from undesirable components of electric signals in electric power systems for powering the transceivers of Internet of Things (IoT) devices. These components, mainly harmonics and interharmonics, occupy the ultranarrowband power line communication spectrum (i.e., frequencies below 3 kHz). In this context, we introduce a mathematical formulation that allows us to quantify the number of transceivers of IoT devices that this kind of wasted energy can power. Based on a measurement campaign in a building facility, we show that the wasted energy can be modeled as a cyclostationary random process on weekdays and a stationary one on weekends, mimicking the energy consumption profile in a building facility. Numerical results also highlight achievable data rates obtained in the building facility if the wasted energy is reused. This analysis shows that this kind of harvested energy from wasted energy is suitable for powering numerous transceivers of IoT devices in practical scenarios.

Multicarrier-based frequency splitting simultaneous wireless information and power transmission (FS-SWIPT) signals are very prone to nonlinear effects due to the combination of high-power energy harvesting (EH) subcarriers with low-power data subcarriers. In this article, we study the impact of nonlinear effects in FS-SWIPT signals, as well as ways to minimize these effects on the data transmission performance. We start by analytically characterizing the impact of nonlinear devices on the signals, showing that the nonlinear effects on data subcarriers are exacerbated by a factor close to the ratio between the power spectral densities of EH and data terms. This suggests that conventional receivers, that treat nonlinear distortion as an additional noise term, can have very poor performance. Then, we present an iterative receiver that iteratively estimates and cancels nonlinear distortion, and is able to have a performance close to the linear case. Finally, we study the optimum performance of FS-SWIPT signals with strong nonlinear distortion levels, showing that, by using optimum receivers, the nonlinear distortion term can be used to improve the performance of FS-SWIPT, even outperforming the linear case.

Ultrareliable and low-latency communication (uRLLC) is a promising use case in the fifth generation and beyond systems for critical and delay-sensitive applications with aid of short-packet transmission. Nevertheless, multicarrier nonorthogonal multiple access (MCNOMA) is a promising technique to achieve spectral efficiency and massive connectivity, however, intercarrier interference (ICI) stands out to be a major downside. Recently, sparse vector coding (SVC) is proposed to fulfill the tradeoff between reliability and latency, thereby achieving the benchmarks of uRLLC. In this article, SVC-based downlink MCNOMA (SVC-MCNOMA) system is considered and first it is shown that SVC-MCNOMA is free from ICI due to the sparse nature of the information. Further, compressed sensing (CS)-based recovery at the receiver end helps in reducing the latency as well as enhances reliability. Moreover, to study the system performance, this article derives the closed-form outage expressions of the SVC-MCNOMA system over the Rician fading channel, and through Monte Carlo simulation, the analytical results are validated. The analyses demonstrate that SVC-MCNOMA outperforms conventional MCNOMA (C-MCNOMA), thereby achieving spectral efficacy, ultrareliability with low latency, and eradicates the effect of ICI.

Building upon the prevailing concept of edge computing (EC), a distributed EC market requires decentralized and verified transaction management to trade computing resources. Towards this goal, we study a blockchain-aided EC market wherein each data service operator (DSO) rents a group of edge computing nodes (ECNs) and leases the ECNs to the user terminals (UTs) to provide computation offloading services. A trustworthiness model is introduced to evaluate the quality of each network entity throughout the transactions. We develop a two-level trading mechanism over smart contract to enable the automatic and efficient transactions among the network entities and provide high quality services. First, we propose a smart contract based matching mechanism to establish the renting association between the DSOs and ECNs with the aim of maximizing the social welfare. Second, we propose a social welfare improved double auction (SWIDA) mechanism to build up the leasing association between the DSOs and UTs, and determine the pricing of the winners. We show that the proposed double auction mechanism can achieve individual rationality, balanced budget, truthfulness in expectation, and an improved social welfare than the benchmark mechanisms. Moreover, we put forth a trustworthiness driven Proof-of-Stake (PoS) consensus mechanism to enable verified transaction and fair allocation of block generation reward. Following the principle of PoS, we formulate the block generation as a coalitional game, wherein each stakeholder votes according to its trustworthiness and coinage, and shares the reward among the coalition according to the Shapley values. The simulation results show that the proposed PoS consensus mechanism can reduce the wealth inequality among the network entities compared with the conventional consensus mechanisms.

A dual-hop free space optics (FSO) and underwater visible light communication (UVLC) are a promising alternative signaling approach of next-generation wireless networking system. Nevertheless, the channel turbulence and the pointing errors are the bottlenecks in optical communication. In this regard, the performance of dual-hop mixed optical communication enabled a decode-and-forward (DF) relay protocol under consideration of strong turbulence and transceivers misalignment is proposed. In contrast, the both of the optical links are modeled by intensity modulation and direct detection (IM/DD) under consideration of pulsed amplitude modulation (PAM) scheme, and followed by Gamma-Gamma (GG) distribution model within the moderatestrong turbulence channel conditions. The Closed-form expressions in terms of probability density function (PDF) and cumulative density function (CDF) are analytically derived to obtain the outage probability and bit-error-rate (BER) performance matrices. Aggregating of the whole work, the extended generalized bivariate Meijer-G function (EGBMGF) is implemented and the results are simulated through the Monte-Carlo approach for validation of the simulated outcomes.

In this paper, a new network model for visible light communication (VLC) is proposed using delta-orthogonal multiple access (D-OMA) scheme and coordinated multi-point (CoMP) transmission. CoMP enables the coordination among the group of access points (APs) such that each user receives the signals from many access points and thereby achieves the diversity gain. Therefore, all the users experience good signal quality including the users in the boundary of the visible region. D-OMA allows the partial overlapping among the sub-bands of the non-orthogonal multiple access (NOMA) clusters to improve the massive access under allowable interference levels. A Closed form expression for the bit error rate (BER) of the proposed VLC network is derived. Also, optimal power allocation at the VLC transmitter is applied using Karush-Kuhn Tucker (KKT) conditions to maximize the user data rate. Numerical results demonstrate that the proposed CoMP-based D-OMA VLC network outperforms the existing NOMA scheme.

This article considers an unmanned aerial vehicles (UAVs) communication network, where UAV operate as an aerial mobile relay between a source and a destination of the network. To capture the “timeliness” of the received information at the destination node, a new performance metric named Age of Information (AoI) is considered. In addition, a short packet communication scheme maintains low latency in the proposed UAV wireless communication system. The finite block-length theory investigates the performances of the short packet communications scheme in the UAV-assisted wireless communications system. In this article, the Average AoI (AAoI) is estimated by applying the stochastic hybrid systems (SHSs) model. The SHS model comprises discrete states represents events that reset the AoI process and continuously dynamics that represent linearly growing age processes. Finally, a closed-form expression for the AAoI of the proposed UAV wireless communication system is derived and it can be used to estimate the optimal altitude, block length, and other parameters.

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.

In this paper, a novel system model for the non orthogonal multiple access (NOMA) based wireless network is proposed using physical layer network coding (PLNC) scheme. The outage performance of a two pairs hybrid NOMA-PLNC relay network is analyzed. Proposed network is designed with three time slots and half-duplex decode-and-forward (DF) relay. A closed form expression for the end-to-end outage probability of the proposed NOMA-PLNC relay network is derived. It is noted that the performance of the proposed hybrid NOMA-PLNC relay network is significantly improved when compare to the conventional orthogonal multiple access (OMA)-PLNC relay network. Finally, numerical results of the proposed relay network is validated using the simulated experimental results.

Age of Information (AoI) measures the freshness of data in mission critical Internet-of-Things (IoT) applications i.e., industrial internet, intelligent transportation systems etc. In this paper, a new system model is proposed to estimate the average AoI (AAoI) in an ultra-reliable low latency communication (URLLC) enabled wireless communication system with decode- and-forward relay scheme over the quasi-static Rayleigh block fading channels. Short packet communication scheme is used to meet both reliability and latency requirements of the proposed wireless network. By resorting finite block length information theory, queuing theory and stochastic processes, a closed-form expression for AAoI is obtained. Finally, the impact of the system parameters, such as update generation rate, block length and block length allocation factor on the AAoI are investigated. All results are validated by the numerical results.

Global pandemics such as Covid-19 have led to massive loss of human lives and strict lockdown measures worldwide. To return to a certain level of normalcy, community awareness on avoiding high population density areas is significantly important for infection prevention and control. With the availability of new telecommunication technologies, it is possible to provide highly informative population clustering data back to people using wireless aerial agents (WAAs) placed in a local area. Hence, a service architecture that allows users to access the localization of population clusters is proposed. Further, a convex hull-based clustering method, enhanced population clustering (E-PC), is proposed. This method refined the result of conventional clustering methods such as K-means and Gaussian mixture model (GMM). Moreover, the potential in E-PC to achieve the same or higher results compared to the original K-means and GMM, while consuming lesser data points, is demonstrated. On average, E-PC improved the cluster detection performance in both K-means and GMM by 18.93% under different environments such as remote, rural, suburban, and urban in terms of silhouette score. Further, E-PC allows a 15% data reduction which results in decreasing the computational cost and energy consumption of the WAAs.

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.

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.

Recently, the use of unmanned aerial vehicles (UAVs) as a relay node has been envisaged as an enabling technology in the upcoming wireless communication era. Thus, in this paper, we consider a full-duplex (FD) cooperative communication system with a source and a destination, where UAV serves as a mobile relay. Here, the transmission power cost is debited to energy harvested using simultaneous wireless information and power transfer (SWIPT) and self-interference energy harvesting (EH) via power-splitting (PS) protocol. In poor channel conditions, UAV uses a soft angular modulation scheme to perceive the soft information. In this proposed system, we present the outage probability over the Nakagami-m fading channels. A closed-form solution for the outage probability is derived. In addition, we formulate an optimization problem to minimize end-to-end outage probability subject of the UAV's power profile. The KKT conditions have been used to obtain a closed-form solution of the proposed optimization problem. Finally, numerical results are provided to evaluate the proposed system under various setups.

Simultaneous Wireless Information and Power Transfer (SWIPT) technique is introduced in Radio Frequency (RF) communication to carry both information and power in same medium. In this approach, the energy can be harvested while decoding the information carries in an RF wave. Recently, the same concept applied in Visible Light Communication (VLC) namely Simultaneous Light Wave Information and Power Transfer (SLIPT), which is highly recommended in an indoor applications to overcome the problem facing in RF communication. Thus, SLIPT is introduced to transmit the power through a Light Emitting Diode (LED) luminaries. In this work, we compare both SWIPT and SLIPT technologies and realize SLIPT technology archives increased performance in terms of the amount of harvested energy, outage probability and error rate performance.

This work examines the trajectory optimization of an unmanned aerial vehicle (UAV) for the purpose of data-gathering from a backscattering wireless sensor network. The sensors are assumed to be remotely powered by distributed power-beacons using wireless power transfer (WPT) technology. The energy signals are backscattered towards the UAV, carrying information about the sensors' observations. Under a strict deadline constraint, the number of time slots that can be used to gather data is limited and, thus, the sensors must carefully determine their activation time slots according to the UAV's position at given times. The UAV trajectory and sensor activation decisions are coupled and, thus, jointly determined by minimizing the mean-squared error of the reconstructed sensor observations at the UAV. The trajectory is constrained by the UAV's maximum flight speed and minimum altitude, and the sensors' transmissions suffer from altitude-dependent path loss. An iterative procedure is proposed where the UAV trajectory, elevation angle and sensor activation are updated in turn until convergence. Performance comparison is provided through numerical simulations.

Wireless mobile networks are widely used during large catastrophes such as earthquakes and floods where robust networking systems are indispensable to protect human lives. The objective of this paper is to present a self-adaptive emergency call protocol that allows keeping potential victims connected to the core network through the available functional stations, called gNBs in 5G, when a fraction of gNBs in a network area are fully destructed with no access to other gNBs or the core network due to the disaster. Nowadays, the density of mobile devices and progress in outband device to device (D2D) communication provide the framework for the extension of both mobile and network coverage. We propose a novel, 3GPP compatible and completely distributed protocol called M-HELP for emergency call service for 4G/5G enabled mobile networks. We assess M-HELP efficiency under various scenarios representing different degrees of network destruction and different emergency call conditions. The tests demonstrate the significant performance of M-HELP in terms of transmission success rate, energy management, latency and control traffic load.

Simultaneous wireless information and power transmission (SWIPT) is one of the popular technique used in radio frequency energy harvesting (EH). Frequency splitting based SWIPT (FS-SWIPT) is a novel SWIPT technique that can be adopted with frequency domain multiple access signal transmission protocol for the near field EH application in biomedical sensors. In this paper, we implement FS-SWIPT in orthogonal frequency division multiplexed (OFDM) signal, the OFDM signal has separate sub carriers for the data symbols and the energy carrying symbols. At the receiver, the energy and information symbols are based on their sub carriers by using FS-SWIPT technique. The amplification of high energy OFDM signal at transmitter by using a high power amplifier are susceptible to non linear distortion (NLD), which degrades the bit error rate (BER) performance. We analyze the impact of NLD on the BER performance of FS-SWIPT and validate the analytical results by using simulations.

This paper embodies the Fox's H-transform theory into a unifying modeling and analysis of HetNets. The proposed framework has the potential, due to the Fox's N-functions versatility, of significantly simplifying the cumbersome analysis and representation of cellular coverage, while subsuming those previously derived for all known simple and composite fading models. The paper reveals important insights into the practice of densification in conjunction with signal-to-noise plus interference (SINR) thresholds and path-loss models.

In this study, the authors present an energy‐efficient technique for the fog‐networks, where a node can communicate to other users using limited network infrastructure support. The authors' contribution is central to node mobility and lower energy consumption rates. They propose an energy‐efficient cellular communication model for fog‐networks. To establish the connection between the source and the destination node, the next generation involves node base station imports required information from nearby fog nodes and performs the network management with the help of data analytic units. A system‐level optimisation for the energy consumption model is also proposed, which supports a high degree of node mobility. They compared their results with 4G/LTE and observed that the proposed work provides the least energy consumption as compared to the legacy of the networks.

In this paper, we consider a hybrid terrestrial and underwater RF wireless cooperative communication system. We improve the energy awareness of the system by employing simultaneous wireless information and power transfer (SWIPT) technique. The impact of the system performance parameters, such as signal-noise-to-ratio, bit error rate, outage probability and throughput are extensively investigated. All theoretical results are validated by numerical results. Furthermore, the impact of the time allocation in time-switching protocol is investigated. Simulation results, which are based on theoretical analysis and underwater experimental data, verifies that SWIPT integrated proposed system improve the overall energy awareness while maintaining the system performance.

Smart metering infrastructure (SMI) is the core component of the smart grid (SG) which enables two-way communication between consumers and utility companies to control, monitor, and manage the energy consumption data. Despite their salient features, SMIs equipped with information and communication technology are associated with new threats due to their dependency on public communication networks. Therefore, the security of SMI communications raises the need for robust authentication and key agreement primitives that can satisfy the security requirements of the SG. Thus, in order to realize the aforementioned issues, this paper introduces a lightweight and secure authentication protocol, "LiSA", primarily to secure SMIs in SG setups. The protocol employs Elliptic Curve Cryptography at its core to provide various security features such as mutual authentication, anonymity, replay protection, session key security, and resistance against various attacks. Precisely, LiSA exploits the hardness of the Elliptic Curve Qu Vanstone (EVQV) certificate mechanism along with Elliptic Curve Diffie Hellman Problem (ECDHP) and Elliptic Curve Discrete Logarithm Problem (ECDLP). Additionally, LiSA is designed to provide the highest level of security relative to the existing schemes with least computational and communicational overheads. For instance, LiSA incurred barely 11.826 ms and 0.992 ms for executing different passes across the smart meter and the service providers. Further, it required a total of 544 bits for message transmission during each session.

The Internet of Drones (IoD) is a multi-layered, control architecture to regulate and coordinate the navigation of Unmanned Aerial Vehicles (UAV) in a shared public airspace. UAVs have the potential to be employed in public space for pur- poses like surveillance, monitoring, package delivery, emergency services, etc. For proper operation, an efficient path planning among IoD is required so that they can adaptively decide their path for data dissemination. Most of the existing solutions for this problem have made unreasonable assumptions and do not offer scalability. The scheme proposed in the paper provides a network architecture for the scalable solution of UAVs in an urban environment addressing issues of path planning, safety, privacy, and network connectivity. The scheme has been tested using exhaustive simulation and results prove that the proposed scheme is efficient in terms of reducing the overall cost and delivery time with the increasing weight of payload in the drones.

With the advent of the Internet-of-Things (IoT), vehicular networks and cyber-physical systems, the need for real-time data processing and analysis has emerged as an essential pre-requite for customers' satisfaction. In this direction, Mobile Edge Computing (MEC) provides seamless services with reduced latency, enhanced mobility, and improved location awareness. Since MEC has evolved from Cloud Computing, it inherited numerous security and privacy issues from the latter. Further, decentralized architectures and diversified deployment environments used in MEC platforms also aggravate the problem; causing great concerns for the research fraternity. Thus, in this paper, we propose an efficient and lightweight mutual authentication protocol for MEC environments; based on Elliptic Curve Cryptography (ECC), one-way hash functions and concatenation operations. The designed protocol also leverages the advantages of discrete logarithm problems, computational Diffie- Hellman, random numbers and time-stamps to resist various attacks namely-impersonation attacks, replay attacks, man-in-the-middle attacks, etc. The paper also presents a comparative assessment of the proposed scheme relative to the current state-of-the-art schemes. The obtained results demonstrate that the proposed scheme incurs relatively less communication and computational overheads, and is appropriate to be adopted in resource constraint MEC environments.

This work presents a novel method to generate secret keys shared between a legitimate node pair (Alice and Bob) to safeguard the communication between them from an unauthorized node (Eve). To this end, we exploit the reciprocal carrier frequency offset (CFO) between the legitimate node pair to extract common randomness out of it to generate shared secret keys. The proposed key generation algorithm involves standard steps: the legitimate nodes exchange binary phase-shift keying (BPSK) signals to perform blind CFO estimation on the received signals, and do equi-probable quantization of the noisy CFO estimates followed by information reconciliation-to distil a shared secret key. Furthermore, guided by the Allan deviation curve, we distinguish between the two frequency-stability regimes-when the randomly time-varying CFO process i) has memory, ii) is memoryless; thereafter, we compute the key generation rate for both regimes. Simulation results show that the key disagreement rate decreases exponentially with increase in the signal to noise ratio of the link between Alice and Bob. Additionally, the decipher probability of Eve decreases as soon as either of the two links observed by the Eve becomes more degraded compared to the link between Alice and Bob.

In this paper, we analyze a M-ary quadrature amplitude modulation (M-QAM) scheme over twowave with diffuse power (TWDP) fading environment for multiple receive antennas based system. We consider a Selective decode-and-forward (DF) relayed system with multiple receive antennas at the relay and the destination node. Utilizing the moment generating function of TWDP fading distribution, we derive the closed form expression for the exact average symbol error rate (ASER) for MQAM scheme. Moreover, in order to get the better insight of the system, we also perform the asymptotic analysis for the considered system. Simulation results are presented for different scenarios and it is observed that analytical results show excellent agreement with the simulation results.

Non-orthogonal multiple Access (NOMA) is an effective 5G remedy that provides increase in networks spectral efficiency and access latency. In order to further upgrade the transmission reliability and achievable rate of NOMA, simultaneous usage of NOMA and cooperative relay transmission (CRS) emerges as an efficient approach. In this study, we present an approach for the performance analysis of NOMA based CRS over Hoyt fading channels. The exact expression for the average achievable rate is derived in the form of converging infinite-series sums of Maijer G functions in order to avoid usage of approximation based on the Gauss-Chebyshev method. Numerical results are provided and they demonstrate the validity of the presented analytical results using Hoyt fading channel.

With the rapid emergence of the Internet of Things (IoT) paradigm, the evolution of wireless senor networks (WSNs) is expected to witness a major blow. However, the accelerated upsurge of sensors in the future IoT networks will face significant challenges due to their limited battery life capacity. Thus, it is essential to devise efficient schemes to prolong the battery life of the connected sensors in order to derive their full potential in the future interconnected IoT networks. Towards this end, different energy harvesting (EH) techniques relying on wide array of sources namely solar, wind, thermal, coupled magnetic resonances and radio frequency have been proposed in the literature. Working in the similar direction, in this work, an EH system based on time-switching has been proposed for half-duplex bidirectional WSN with intermediate relay over a Hoyt fading channel. For its extensive performance analysis, exact closed-form expressions have been derived with respect to outage probability (OP) and achievable throughput of the system under the hardware impairment condition. Additionally, asymptotic analysis of high signal-to-noise-ratio (SNR) regime for these performance measures has also been provided. Further, an approach for the symbol-error-rate (SER) analysis is also presented in context of the observed system. In a nutshell, the work provides a detailed analysis of the effects of various parameters on the performances of energy harvesting applied in wireless sensor networks over a Hoyt fading channel.

Low altitude aerial base stations onboard unmanned aerial vehicles (UAVs) have recently gained a lot of attention to provide cellular coverage to mobile ground users. In this paper we evaluate the effect of carrier frequency offset (CFO) on the symbol error rate in the downlink of such systems, where a long-term evolution (LTE) compatible time-frequency grid based on generalized frequency division multiplexing (GFDM) is considered. The choice of GFDM as multi-carrier modulation scheme is motivated by its widely proposed application in fifth generation cellular systems and its backward compatibility with LTE. Simulation results are shown for "Better than the Nyquist (BTN)" pulse shaping filters in three different environments: Suburban, Urban and Urban High Rise. The use of BTN pulse shaping filters allows for higher robustness to CFO as compared to base line pulse shaping filer know as root-raised cosine filters for different environments conditions. Simulation results are presented considering realistic air-to-ground propagation conditions generated from the commercial Wireless InSite ray-tracing radio propagation software.

The unmanned aerial vehicles (UAVs) can serve for key applications in wireless communications. Cellular systems can be assisted by UAVs to provide ubiquitous coverage and additional capacity to overloaded base- stations. In this paper, we present the performance analysis of UAV assisted wireless communication system for ubiquitous coverage. In the considered system, the source and the destination terminals have single transmit and receive antennas, on the other hand the UAV node has multiple transmit and receive antennas. The closed form expression of the bit error rate (BER) performance for the considered system over generalized two-wave with diffused power (TWDP) fading is derived in particular. The performance analysis is done considering direct line of sight (LOS) and multi-path components between source-UAV- destination links. The results are analyzed for Rician and Rayleigh fading channel as a specific case of TWDP distribution. Moreover, in order to get the better insights of the system, we also perform the asymptotic analysis for the considered system. Simulation results are presented for different scenarios and it is observed that simulation results shows excellent agreement with the analytical results.

In this paper, the problem of content caching in 5G cellular networks relying on social-aware device-to-device communications (DTD) is investigated. Our focus is on how to efficiently select important users (IUs) and how to allocate content files to the storage of these selected IUs to form a distributed caching system. We aim at proposing a novel approach for minimizing the downloading latency and maximizing the social welfare simultaneously. In particular, we first model the problem of maximizing the social welfare as a many-to-one matching game based on the social property of mobile users. We study this game by exploiting users' social properties to generate the utility functions of the two-side players, i.e., content providers (CPs) and IUs. Then we model the problem of minimizing the downloading latency as a many-to-many matching problem. For solving these games, we design a many-to-one IU selection (MOIS) matching algorithm and a many-to-many file allocation (MMFA) matching algorithm, respectively. Simulation and analytical results show that the proposed mechanisms are stable, and are capable of offering a better performance than other benchmarks in terms of social welfare and network downloading latency.

The hybrid wireless and power line communication (HWPLC) networks address the problem that mobile wireless sensors and power line communication (PLC) sensors cannot communicate with each other within an Internet of Things (IoT) network. In this paper, we design a relay equipped with a dual wireless and PLC interface, which connects both the PLC and wireless sensors into an IoT network. Furthermore, the dual-interface relay forwards messages by adaptively selecting a interface according to the channel state. A general mathematical probability model of the dual-interface relaying system is presented. The probability density function of the output signal-to-noise ratio (SNR) is developed, which is based on explicit closed-form expressions derived from the statistics character of the PLC and wireless channel. Furthermore, the average capacity, bit-error rate (BER) expressions, and the outage probability formulas are derived. Numerical results show that the HPLWC relaying system with the dual-interface can significantly improve the performance of capacity, BER, and outage probability by adaptively selecting the interface with the optimal received SNR.

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.

Evidence indicates that demands from mobile users (MU) on popular cloud content, e.g., video clips, account for a dramatic increase in data traffic over cellular networks. The repetitive downloading of hot content from cloud servers will inevitably bring a vast quantity of redundant data transmissions to networks. A strategy of distributively pre-storing popular cloud content in the memories of small-cell base stations (SBS), namely, small-cell caching, is an efficient technology for reducing the communication latency whilst mitigating the redundant data streaming substantially. In this paper, we establish a commercialized small-cell caching system consisting of a network service provider (NSP), several video providers (VP), and randomly distributed MUs. We conceive this system in the context of 5G cellular networks, where the SBSs are ultra-densely deployed with the intensity much higher than that of the MUs. In such a system, the NSP, in charge of the SBSs, wishes to lease these SBSs to the VPs for the purpose of making profits, whilst the VPs, after pushing popular videos into the rented SBSs, can provide faster local video transmissions to the MUs, thereby gaining more profits. Specifically, we first model the MUs and SBSs as two independent Poisson point processes, and develop, via stochastic geometry theory, the probability of the specific event that an MU obtains the video of its choice directly from the memory of an SBS. Then, with the help of the probability derived, we formulate the profits of both the NSP and the VPs. Next, we solve the profit maximization problem based on the framework of contract theory, where the NSP acts as a monopolist setting up the optimal contract according to the statistical information of the VPs. Incentive mechanisms are also designed to motivate each VP to choose a proper resource-price item offered by the NSP. Numerical results validate the effectiveness of our proposed contract framework for the commercial caching system.

In this paper, we propose a task scheduling strategy for an Internet of Things (IoT) node powered by renewable energy (RE). The node is assumed to have a rechargeable battery and an RE harvester. Moreover, the node is requested to perform M tasks over a planning period of N ≥ M time slots. Each task is assigned a priority rating and a reward. With these considerations we develop a mathematical framework to optimize the utility of the node, defined as the sum of rewards over the specified planning horizon. Using the proposed framework, we derive a genie-aided strategy, which serves as a performance benchmark for online algorithms. We then propose an online task scheduling strategy, which uses existing forecasting methods to estimate future RE production. We finally evaluate the performance of the proposed strategy and its robustness to forecasting errors through extensive simulations. The impact of system parameters such as battery size and RE harvesting capacity are also examined numerically.

In this paper, we analyze the error rate performance of selective decode-and-forward (DF) based multiple relayed cooperative system for M-QAM (Quadrature Amplitude Modulation) signalling. The analysis is performed for selective DF based cooperative relaying with single as well as multiple relayed system. In particular, an alternate representation of Q-function is used to derive the closed-form expression of asymptotic symbol error rate probability (ASEP) over Rayleigh faded channels with high SNR approximation. Further, the analytical results are corroborated by Monte Carlo simulations for M-QAM MRC cooperative system.

Non-orthogonal multiple access (NOMA) has been acknowledged as an emerging technique for multiple access techniques in fifth generation (5G) wireless network. It offers progressive and attractive features such as low latency, ultra- dense coverage, high fairness and new waveform design as compared to the previous schemes. In this paper, recent advances and future research challenges of NOMA is mainly considered. We start by summarizing the existing works with emphasis on recent literature in resource allocation, performance analysis, principal features related to NOMA, and various types of NOMA techniques are discussed. We offer comparative features on demonstrating how NOMA impacts device to device (D2D) communications, cognitive radio networks, massive multiple input multiple output (MIMO), radio frequency (RF) energy harvesting, and other emerging technologies in 5G. Finally, we present the future research challenges and recommendations in order to mitigate the existing issues and advance this unique feature in 5G.

As a promising wireless network virtualization technology, virtualized base station (BS) has been proposed to tackle the problem of low-efficient utilization of BS's computing resources, e.g., baseband processing units (BPU). In this paper, we design a novel scheme to achieve the efficient BPU allocation based on a contract-theoretic approach. To achieve this, we consider the BPUs as a kind of trading resources. We establish a monopoly market, where the infrastructure provider (InP) is the monopolist owning all the BPUs, and multiple mobile network operators (MNOs) intend to rent BPUs from the InP for processing their baseband signals. In such a market, the InP offers a set of quantity-price contract items to the MNOs based on statistical information of their types, and at the same time, the MNOs are stimulated to accept the offers for the purpose of making profit. We propose the optimal contract design to maximize the InP's profit, as well as develop an incentive mechanism to guarantee each MNO choosing a proper contract item. Numerical results validate the effectiveness of our incentive mechanism for BPU resource allocation.

In this paper, we propose a new methodology for soft forwarding which is based on a novel technique known as soft angular modulation (SAM). This is effective even under poor source-relay link conditions. The new treatment presented here allows a more flexible system design. This makes soft forwarding, which is not practical with current infrastructure, a feasible approach. In this work, we convert soft information from the soft domain into the angular domain. We then forward unity amplitude symbols using wireless fading channels. Due to the analogue nature of the probabilistic content (or soft information), the soft information relaying (SIR) scheme is not treated as a practically feasible relay protocol. We offer a remedy to this by forwarding unity amplitude symbols from the relay. Using the expression of soft noise variance, we deduct an approximate log likelihood ratio (LLR) expression for a parallel relay network employing SAM scheme. It is shown that the derived BER of SAM and numerical BER are closely aligned. The proposed scheme yields improved BER performance as compared to other conventional schemes.

Network coding (NC) holds great significance in the upcoming 5G paradigm because of the potential improvements it offers in terms of network throughput, energy efficiency and data security. However, the evidence for these potential advantages comes mainly from within a theoretical framework or is based on simulations; there is a paucity of empirical evidence. Secondly, few works have evaluated NC in terms of its impacts on both throughput and bit error rate (BER) simultaneously. The work outlined in this paper addresses both of the aforementioned issues. We implement both the NC and non-NC schemes for a communication system in the context of n-source multiple-input single- output (MISO) topologies on software-defined radios (SDRs). The performances of the two schemes have been compared in terms of BER, throughput and goodput or useful throughput. Our results show that the goodput improvement in NC when compared to non-NC is more pronounced at higher transmitter (TX) gains and that below a certain TX gain threshold, non-NC should be preferred over NC.

Mobile TV receivers operate with a weaker link budget in the Digital Video Broadcast (DVB) network compared to the fixed rooftop mounted antenna receivers. Nevertheless, the cellular radio interface is an attractive alternative for broadcast services given its reliability. In this work, we use Long Term Evolution (LTE)'s evolved Multimedia Broadcast Multicast Service (eMBMS) to multicast overhead parity packets among the multicast groups of mobile TV receivers (e.g. smartphones suffering from DVB packet erasures). The proposed multicast scheme recovers erased packets at each smartphone by Systematic RaptorQ Code (SRQC) decoding the directly received DVB transmission along with the overhead packets transmitted via eMBMS multicast. We analyze the load generated in the Cellular Radio Access Network due to this erasure-recovery multicast scheme and compare the gains of such a service over the LTE unicast retransmissions of the missing DVB packets.

This paper investigates the outage probability of the achievable secrecy rate in the presence of multiple eavesdroppers that employ energy harvesting (EH) and information decoding (ID). We derive the theoretical outage probability of the achievable secrecy rate between the legitimate transmitter and receiver pair when both the main channel and wiretap channel experience Rician fading. This work also considers both ideal and imperfect channel state information as well as different EH architectures (i.e. separated and integrated receiver architecture) in the secrecy analysis. Furthermore, the use of transmit antenna selection (TAS) for enhancing message confidentiality is also studied. Numerical and simulation results are provided to validate our analysis.

To cope with the data surge problem and to enhance the coverage of existing cellular systems, heterogeneous networks (HetNets) are deployed in hierarchical manner, comprising of macrocells and overlaid femtocells. A novel interference mitigation technique of Reverse Frequency Allocation (RFA) scheme is introduced, which provides intercell orthogonality by dividing the cell into spatial regions and optimally allocating the frequency resources. RFA enhances the data rates of downlink femto users by eliminating the cross-tier interference from macro base station (MBS). In this paper, we extend the multiple region RFA scheme in multi-cellular network to further mitigate the impact of interference in the adjacent cells. In addition, we also develop a hybrid RFA scheme that merges the benefits of different RFA schemes in terms of large bandwidth and limited interference to achieve higher data rates. Simulation results show that the modified RFA (M-RFA) schemes exhibit superior performance as compared to the conventional RFA schemes in terms of user-fairness and improved sum capacity. For the evaluation of system performance, several metrics such as outage probability, sum rates and outage capacity have been analyzed for satisfying the constraint of minimum capacity requirement of cell edge users.

Non-orthogonal multiple access (NOMA) is considered as a promising candidate for fifth generation (5G) wireless networks. Although, NOMA promises large data rates, however, it also offers significant interference especially when the number of users is large. Therefore, in this paper, we propose a low complexity orthogonal frequency division multiple access (OFDMA)-based NOMA system, which uses the concept of successive bandwidth division (SBD) that not only reduces the complexity of the receiver, but also enhances the overall signal-to-interference plus noise ratio (SINR) of the uplink NOMA by supporting 2N users with just N base station (BS) antennas. Power allocation is being performed in SBD-NOMA to maximize the sum rate using a divide-and-allocate approach such that all users are allocated with an optimal transmission power. Simulations results are provided to access and compare the performance of the proposed scheme with other contemporary approaches.

In this paper, we present the network coverage issues for both Femto Users (FUs) and Macro Users (MUs) located at cell edges. The cognitive-femtocell networks functioning under the vicinity of a macrocell frontier where the parameters such as pathloss, shadowing, Rayleigh fading have considered into the system model. The users, located at network border are positioned far apart from the Macro Base Station (MBS)-treated as the underprivileged users. They are to be facilitated by the femto cell base stations to provide uninterrupted QoS. We present an overall outage probability of Single Input single Output (SISO) users and Single Input Multiple Output (SIMO) users, respectively, by taking several circumstantial components such as such as probability density function (PDF), location gap between base stations (BSs) and users, intra-tier interference and inter-tier interference into account. Further, evaluation has been extended by considering network throughput as the efficiency measures based on the sub-carrier and the power allotment in the dual tier network.

This paper presents a novel approach to cooperative non orthogonal multiple access (NOMA) using distributed space time block coding (STEG) known as STEG-NOMA. In conventional NOMA, the strong users detect the messages of weak users through successive interference cancellation (SIG). In cooperative NOMA, these copies are then forwarded by strong users to weak users at the expense of extra time slots. However, the proposed scheme exploits this feature of cooperation using STEGs to enable cooperation among the users. The STEGNOMA renders less complexity as lesser number of SIGs are performed at each user. To this end, we derive the outage probability of the STEG-NOMA scheme which involves finding the distribution of signal-to-interference ratio at the receiving terminals. The numerical results show that STEG-NOMA outperforms conventional NOMA and conventional cooperative NOMA in terms of outage probability and average sum rate.

Next generation of mobile communication systems must support astounding data traffic increases, higher data rates and lower latency, among other requirements. All these requirements should be met while assuring energy efficiency for mobile devices and base stations. Most likely, the future 5G systems will include massive MIMO (Multiple Input Multiple Output) schemes with dozen or hundreds of antennas enabling beamforming while operating in the millimeter wave spectrum. As soon as the millimetric wave propagation difficulties are overcome, the full potential of massive MIMO structures can be tapped. This paper presents a transmission system with bi-dimensional antenna arrays, based on a double layer structure combining beamforming with a multi-branch power amplification that achieves simultaneously power efficiency in amplification of multilevel constellations without penalties on system performance when compared with common schemes using only beamforming.

Simultaneous Information and Power Transfer (SWIPT) for wireless communication systems presents a new paradigm, allowing wireless nodes to recharge their rechargeable batteries from RF signals (instead of fixed line or traditional energy sources) while decoding information. In this approach, the energy is harvested from ambient electromagnetic sources available within the communication system or from sources that directionally transmit RF energy. This work presents an overview, and advancement to date, as well as identifies research issues and challenges in SWIPT and RF Wireless Power Transfer (WPT) assisted technologies. The paper, in principal, addresses innovative 5G communications and Internet of Things (IoT) technologies associated with SWIPT/WPT. The paper finally presents recommendations and future trends associated with this emerging future electricity technique. This provides a valuable reference and new avenues for the future research in this direction.

This paper investigates a new methodology for soft information forwarding (SIF) based on a novel technique known as soft angular modulation (SAM). In this new relay scheme, the soft symbols are embedded into phases at the relay. This is more advantageous as we refrain to forward real values (under bandwidth constraints) via wireless channels. This makes the proposed scheme practically feasible. The proposed system provides a means of using distributed low-density parity- check (LDPC) coding in conjunction with a new soft encoding scheme (puncturing), which is useful even under indigent source-relay link conditions. This also precludes the amplitudes of generated symbols descent to zero, as happens with most of the existing soft forwarding methods. Ordinarily, such schemes suffer from error propagation to the destination when the signal-to-noise ratio (SNR) of the source-relay link is low; however, our system avoids this problem by regenerating soft versions of the source symbols at the relay. Furthermore, we also propose a computationally efficient formula for log-likelihood ratio (LLR) at the destination. Simulation results demonstrate that the proposed scheme can maintain very good performance under poor source relay SNR conditions.

In this work, we propose a new technique of spatially-coupled low-density parity-check coding within a threshold-based lossy forwarding protocol for a multiple access relaying system. Here, block Rayleigh fading is assumed for all transmission links and error-free decoding at the relay is not required. Two schemes are presented in which the relay computes log-likelihood ratios (LLRs) of the network-coded symbols (from the sources) based on the received signals. By comparing the LLRs to a preset threshold, the relay decides to forward hard decisions when the network-coded symbol reliability is higher than the preset threshold. Otherwise, the relay decides to stay silent (first scheme) or to forward the LLRs to the destination (second scheme). Finally, we modify the LLR combining at the destination, based on an expression for the uncoded bit-error probability which is tailored to the proposed schemes. Simulation results demonstrate that the proposed relay protocol yields an improved bit-error rate performance compared to competitive schemes proposed in the literature.

Massive MIMO (multiple-input multiple-output) has been identified as a key technology for next generation cellular systems. This paper considers a multi-cellular system with large antenna arrays at the base station (BS) and single antenna user terminals (UTs), operating in a time division duplex (TDD) mode, under a composite fading- shadowing environment. In the uplink transmission, the pilot contamination occurs as the UTs transmit pilots to their respective BSs, and the serving BS estimates the channel state information using a minimum mean squared error estimation. This channel information is further used to design beamforming (BF) and regularized zero-forcing (RZF) precoders for downlink (DL) transmission. We analyze the ergodic rates for DL transmission using different precoding schemes and varying shadowing intensity. It has been observed that shadowing does not average out as we increase the number of antennas as opposed to multi-path fading, and the severity of shadowing badly affects the performance of massive MIMO systems.

This paper proposes a new technique of spatially-coupled low-density parity-check (SC-LDPC) code-based soft information relaying scheme for a two-way relay system. We introduce an optimized SC-LDPC codes in relay channels. A more precise model is proposed to characterize the soft noise on the soft symbols, using a pre-calculated look-up table at the destination. This requires less signalling overhead compared to existing soft noise modelling techniques. We also introduce a variance correction factor to provide a rectification to the equivalent total noise variance at the destination. Finally, we modify the LLR former at the destination which is tailored to the proposed soft information relaying technique. Simulation results demonstrate that the proposed relay protocol yields an improved BER performance compared to competitive schemes proposed in the literature.

This paper proposes a new power efficient multilevel threshold based soft quantization (MLT- SQ+PA) scheme for a multiple access relay system (MARS). In the proposed MLTSQ+ PA protocol, the relay computes the reliabilities, expressed as log-likelihood ratios (LLRs), of the received signals from the two sources. We provide an analytical closed form expression for the optimized power allocation factor at the relay. The relay evaluates the LLRs of the network-coded packet, quantizes and scales these using the optimum power allocation factor, forwarding the resulting "quantized soft symbols" to the destination. Compared to competing schemes, the performance of our system is superior in terms of BER when the same amount of channel state information (CSI) is exploited.

Low-density lattice codes (LDLCs) are known for their high decoding efficiency and near-capacity performance on point-to-point Gaussian channels. In this paper, we present a distributed LDLC-based cooperative relaying scheme for the multiple-access relay channel (MARC). The relay node decodes LDLC-coded packets from two sources and forwards a network-coded combination to the destination. At the destination, a joint iterative decoding structure is designed to exploit the diversity gain as well as coding gain. For the LDLC-based network coding operation at the relay, we consider two alternative methods which offer a tradeoff between implementation complexity and performance, called superposition LDLC (S-LDLC) and modulo-addition LDLC (MA-LDLC). Soft symbol relaying is considered as an alternative to hard decision relaying which is capable of reducing the effect of error propagation at the relay. Simulation results show that the proposed scheme can provide greater diversity gain and up to 6.2 dB coding gain when compared with noncooperative LDLC coding and uncoded network-coded transmission. The proposed scheme also achieves 2.5 dB gain over network-turbo-coded cooperation, for the same code rate and overall transmitted power. Also, soft symbol relaying is shown to provide approximately 2 dB gain over hard decision relaying when the source-relay link suffers from deep fading.

This paper proposes the novel technique of multilevel threshold based soft quantization (MLT-SQ) for a multiple access relay system (MARS). The scheme is suitable for systems using binary phase-shift keying (BPSK) and network coding at the relay. In the proposed MLT-SQ protocol, the relay evaluates the reliabilities, expressed as log-likelihood ratios (LLRs), of the received signals from the two sources. It then computes the LLRs of the network-coded packet and quantizes these using a set of optimized multilevel thresholds, forwarding the resulting “quantized soft symbols” to the destination. We provide the derivation for the bit error rate (BER) at the destination, based on which we optimize the multilevel thresholds to minimize the BER. Compared to competing schemes, the performance of our system is superior in terms of BER when the same amount of channel state information (CSI) is exploited.

This paper investigates a low-density parity-check (LDPC) coded soft-decode-and-forward (SDF) relaying protocol for a two way relay channel (TWRC). In this SDF protocol, the relay evaluates the reliabilities, expressed as log-likelihood ratios (LLRs), of the received signals from the two sources. The relay then forwards a network-coded combination of the parity symbols of both sources, but in the “soft” domain to avoid error propagation from the relay. We introduce a model for the effective noise experienced by the soft network coded symbols, constituting the new parameters of soft scalar and soft error; this model is then used to compute the log-likelihood ratios (LLRs) at the destination. To facilitate this latter computation, we have derived an analytical expression for soft error variance, as well as a simplified expression based on a common assumption on the statistical behavior of the LLRs. This enables low-complexity computation and tracking of the soft error variance on-the-fly. The proposed system outperforms standard competing schemes reported in the literature in terms of error rate performance over Rayleigh fading links.

This paper investigates soft information relaying (SIR) for low-density parity-check (LDPC) coded transmission in wireless networks. We introduce a new scheme for soft parity symbol generation at the relay, which features two key strategies: a two-step soft parity generation process, and a prescaling technique. The two-step soft parity generation procedure is designed to allow efficient relay processing, while yielding an overall (i.e., destination) parity-check matrix structure with desirable properties. The pre-scaling method prevents the amplitudes of generated soft symbols successively converging to zero, as happens with some existing soft forwarding methods. Finally, we propose an appropriate LLR former at the destination which is tailored to the proposed soft parity generation technique. Simulation results demonstrate that the proposed relay protocol yields an improved BER performance compared to competitive schemes proposed in the literature.