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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. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicles (UAV) assisted edge computing has risen as an assuring technique to accommodate ubiquitous edge computation for resource‐limited devices. Thus, this paper proposes an approach to maximize the latency fairness in a UAV‐assisted multi‐access edge computing (MEC) system. To maximize latency fairness, the authors focus on minimizing the maximum latency experienced among the users. In here, multiple ground users (GUs) offload their tasks to MEC UAV in the absence or unavailability of ground servers due to a disaster or heavy traffic where an iterative algorithm is proposed to minimize the maximum latency among the users subject to minimum control link rate and total power constraints. Sequentially, the UAVs' 3D location, offloading ratio, GUs' transmit power and GUs' computational capacity are optimized. The location of the UAV is optimized by using the novel approach, guided pattern search algorithm while the altitude of the UAV is optimized by analyzing the elevation angle dependant behaviour of the channel gain. A simple approach is utilized for optimizing the offloading ratio of the users by considering the problem as minimizing the point‐wise maximum of two convex functions while the bisection method is used to optimize the power allocation. Numerical simulation results illustrate that the proposed approach outperforms other baseline approaches in convergence, minimizing the maximum latency and maximizing and maintaining the fairness among the GUs. Furthermore, it is proved that the guided pattern search algorithm converges at least 3.5 times better while the proposed combined optimization gives 400% fairness gain, in comparison with the baseline approach. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Abstract: This paper investigates a new spectrum‐sharing strategy using non‐orthogonal multiple access (NOMA), a technique that is expected to lead toward the fifth generation of wireless networks. The proposed scheme, namely, successive bandwidth division (SBD), NOMA, is a hybrid approach exploiting the characteristics of both the conventional NOMA system and the orthogonal multiple access (OMA) system. Power allocation is being performed in successive bandwidth division NOMA to maximize the sum rate using a divide‐and‐allocate approach such that all users are allocated with optimal transmission power. Under Rayleigh fading, the probability density function (PDF) of the received signal‐to‐interference‐plus‐noise ratio (SINR) is derived, and closed‐form expressions for the outage probability are presented when channel state information (CSI) is available at the base station. The performance evaluation is carried out in terms of receiver complexity, average sum rate, and outage probability. Simulations results are provided to access and compare the performance of the proposed scheme with other contemporary approaches. [ABSTRACT FROM AUTHOR]

In this paper, we initially dealt with the issue of spectrum allocation among macro (or "licensed") and femto (or "unlicensed") users in an orthogonal frequency division multiple access femtocell network of noncooperative game theoretic frequency reuse approach. We formulate the difficulty based on spectrum bidding. Here, individual secondary users (SUs) create an auction for the amount of bandwidth and every primary user can share the frequency band among SUs by itself according to the intelligence from SUs without lowering its own performance. Here, we consider that the bidding is a noncooperative game and one of its solutions is a Nash equilibrium. The femto base stations are grouped into different cluster for mitigating the undesired interference among them. The game theoretical method deals with the intercluster frequency clashes. We exemplified a link between utility function and the number of players by noncooperative game theoretic approach to guide the spectrum sharing decision at the cell edges. The convergence of the development mechanism is rigorously scrutinized and extensive numerical outcomes are presented to illustrate their potential merits. Frequency Reuse in OFDMA Using Game Theory In this paper, we present the issue of spectrum allocation among macro (or "licensed") and femto (or "unlicensed") users in an orthogonal frequency division multiple access (OFDMA) femtocell network of non‐cooperative game theoretic frequency reuse approach. The cross‐layer interference between the macro cell and femto cells is significantly mitigated with the aid of femtocell resource allocation. The convergence of the development mechanism is rigorously scrutinized and extensive numerical outcomes are presented. [ABSTRACT FROM AUTHOR]