Indoor Internet of Things (IoT) is considered as a crucial component of Industry 4.0, enabling devices and machine to communicate and share sensed data leading to increased efficiency, productivity, and automation. Increased energy efficiency is a significant focus within Industry 4.0, as it offers numerous benefits. To support this focus, we developed a hybrid switching mechanism to switch between energy harvesting techniques, ambient backscattering and Simultaneous Wireless Information and Power Transfer (SWIPT), which can be utilized within cooperative communications. To implement the proposed switching mechanism, we consider an indoor warehouse environment, where the moving sensor node transmits sensed data to the fixed relay located on the roof, which is then transmitted to an IoT gateway. The relay is equipped with the proposed switch to energize its communication capabilities while maintaining the expected quality of service at the IoT gateway. Simulation results illustrate the improved energy efficiency within the indoor communication setup while maintaining QoS at varying signal-to-noise (SNR) conditions.

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.

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.

Semantic communication, a multidisciplinary field, transforms communication technology by integrating semantic understanding and improving information flow efficiency. This study surveys various aspects of semantic communication to explore its multiple facets. This paper delves into the fundamental concepts of semantics in communication, emphasizing the importance of meaning extraction and interpretation. In this approach, The semantic problem focuses on the precision of conveying meaning, ensuring accurate information transmission while maintaining its original semantic relevance. This work presents an overview, and advancement to date, as well as identifies research issues and challenges in semantic communication. The paper, in principle, addresses the overview, technical issues, systems, and innovative technologies associated with semantic communication. The paper finally presents recommendations and future trends associated with this emerging future communication system. This provides a valuable reference and new avenues for future research in this direction.

Motivated by the timely need for fresh updates in time-critical applications, this paper investigates the AoI-driven UAV trajectory optimization for a two-way relay network. The non-linear simultaneous wireless information and power transfer (SWIPT) power-splitting (PS) technique is used to provide the energy required for UAV communication considering hardware impairments. Amalgamating derived outage probability, AoI expression is obtained to evaluate data timeliness and its performance trade-offs. Then, we optimize the trajectory of the UAV while minimizing the AoI performance within the given discretized time slot. The impact of the system parameters, that is, size of the status update, PS factor, outage probability, and UAV's position, on the AoI performance are extensively investigated. Motivated by the pressing demand for real-time updates in time-critical applications, this paper explores the optimization of UAV trajectories driven by the age of information (AoI) for a simultaneous wireless information and power transfer (SWIPT) enabled two-way relay network. AoI is introduced as a novel performance metric aimed at quantifying the data freshness at the receiver's end. The paper investigates trade-offs between AoI and conventional performance metrics, employing them to determine optimal parameters for the proposed UAV-assisted communication system.image

The complexity of successive interference cancellation at the receiver’s end is a challenging issue in conventional non-orthogonal multiple access assisted massive wireless networks. The computational complexity of decoding increases exponentially with the number of users. Further, under realistic channel conditions, a synchronous non-orthogonal multiple access scheme is impractical in the uplink device-to-device communications. In this paper, an asynchronous non-orthogonal multiple access-based cyclic triangular successive interference cancellation scheme is proposed for a massive device-to-device network. The proposed scheme reduces the decoding complexity, energy consumption, and bit error rate of a superimposed signal received in an outband device-to-device network. More specifically, the scheme follows three consecutive stages; optimization, decoding, and re- transmission. In the optimization stage, a dual Lagrangian objective function is defined to maximize the number of data symbols decoded at the receiver by determining an optimal interference cancellation triangle, under the co-channel interference and data rate constraints. In the decoding stage, the data in the optimal interference cancellation triangle is decoded using a conventional triangular successive interference cancellation technique. Next, the remaining users’ data are decoded in sequential iterations of the proposed scheme, using the retransmissions from such users. Utilizing the successive interference cancellation characteristics, the performance of the proposed device-to-device network is defined in terms of energy efficiency, bit error rate, computational complexity, and decoding delay metrics. Moreover, the performance of the proposed decoding scheme is compared with the conventional triangular successive interference cancellation decoding scheme to demonstrate the superiority of the proposed scheme.

The exponential growth of Internet-of-Things (IoT) applications in next-generation communications has led to increasingly connected devices in the communication infrastructures. These connected devices are responsible to generate and exchange information within different entities of the communication setup to support decision taking processes in IoT applications. Emergence of diverse IoT applications (i.e., intelligent transportation systems, smart environmental applications, Tactile Internet applications, etc.) required the information freshness at the edge users to be increased much as possible. Thus, it is essential to maintain freshness of the information received since outdated information can jeopardize reliability of the system output given rise to safety risks. Data freshness at the destination is a quite difficult objective to achieve in wireless communication. It is also noteworthy that data freshness is different and goes beyond the latency. As a contribution in this direction, this book chapter defines the basic building block of the new performance metric named age of information. It begins with an introduction to AoI, and then it is shown the way AoI can be modeled for simultaneous wireless information and power transfer (SWIPT)-enabled cooperative communication network considering hardware impairments. Next, we investigate the relationship of AoI with other traditional performance metrics such as outage probability and throughput. Then, we optimize resource allocation of the SWIPT-enabled communication setup to improve AoI performance adhering to the quality-of-service (QoS) requirements. Finally, important future directions of AoI toward beyond 5G are provided along with conclusion remarks.

The 5G cellular network provides a sufficient data rate to support the ever growing number of devices that will be connected to the Internet. To enable Internet of Things (IoT) applications in remote locations, it is very crucial to increase the coverage of the cellular networks. This article proposes a wireless communication system that exploits a full-duplex enabled unmanned aerial vehicle (FD-UAV) integrated into a communication network as a mobile relay to expand network coverage. With the deployment of IoT devices, a large volume of data is introduced into the network, causing a delay in data delivery due to scarcity of resources. Real-time information updates play an important role in modern IoT applications including connected vehicles in intelligent transportation systems, digital healthcare, real-time tracking, and so on. Decision making based on the latest fresh information is critically important for these applications. We quantify the freshness of data in IoT applications using a new performance metric, the age of information (AoI). This work proposes a new mathematical model to estimate the average AoI (AAoI) in the FD-UAV assisted cooperative wireless communication system. Here, sensors located in a transport infrastructure harvest energy from radio frequency (RF) signals transmitted by the FD-UAV via a wireless power transmission RF energy harvesting (EH) technique. Then sensors consume this energy to transmit their sensed real-time observations to the access point with the aid of FD-UAV. A closed-form expression for the AAoI is derived as a function of time allocated for energy harvesting. The optimal time allocation for EH that minimizes the AAoI is identified together with the effect of self-interference experienced by the UAV.

Recently, underwater visible light communication (UVLC) has become a potential wireless carrier candidate in the acrimonious mingled ocean straits. The combined strait of the North and Baltic ocean is a harsh and strongly turbid aqueous zone that contributes signal fading at a large scale. Due to this, we are proposing a UVLC system within the Baltic–North ocean mingled water under strong turbulence channel conditions. In this study, the Gamma–Gamma distribution is used to model UVLC link under an OOK modulation scheme. Subsequently, the reason for the unavailability of the latest North–Baltic oceanographic data within this bayou, we investigate the BER and outage probability performance of the proposed system within the mingled strait for the whole year during 1996s. Throughout, this work, the performance is obtained individually in both of the oceans and then compared with the heterogeneous state. It is noteworthy that the analytical work has been considered of the following distinct physio-chemical properties and the data provided for each ocean. Additionally, the simulation results are verified the analytical work of the proposed system model.

Unmanned aerial vehicles (UAVs) is a promising technology for the next-generation communication systems. In this article, a fixed-wing UAV is considered to enhance the connectivity for far-users at the coverage region of an overcrowded base station (BS). In particular, a three dimensions (3D) UAV trajectory is optimized to improve the overall energy efficiency of the communication system by considering the system throughput and the UAV’s energy consumption for a given finite time horizon. The solutions for the proposed optimization problem are derived by applying Lagrangian optimization and using an algorithm based on successive convex iteration techniques. Numerical results demonstrate that by optimizing the UAV’s trajectory in the 3D space, the proposed system design achieves significantly higher energy efficiency with the gain reaching up to $20\,\,bitsJ^{-1}$ compared to the $14\,\,bitsJ^{-1}$ maximum gain achieved by the 2D space trajectory. Further, results reveal that the proposed algorithm converge earlier in 3D space trajectory compare to the 2D space trajectory.

Visible light communication (VLC) has become recently attracted a renewed communication trade in underwater environment. However, the deployment of underwater applications and oceanographic data collection is more challenging than a terrestrial basis communication. In this regard, a more sophisticated communication system needs to deploy in harsh aqueous medium. Afterward, collected data transmits with the inland base station for further analysis. The necessity of real-time data streaming for military and scientific purposes a dual-hop hybrid cooperative communication is needed. Throughout this research, a dual-hop hybrid RF and underwater visible light (UVLC) relayed communication system developed under consideration of strong turbulence channel conditions along with miss-alignment of transceivers. Moreover, RF link is modeled by nakagami-m fading distribution, while the UVLC link is modeled by Gamma-Gamma distribution for strong turbulence channel conditions. Furthermore, an amplify-and-forward (AF) and decode-and-forward (DF) protocols were considered to assist information transmission with underwater-based destination. The simulation results are used to analyze RF-UVLC link combination and bit error rate (BER) performance through both AF and DF signal protocols in different waters along with the large- and small-scale factors in highly turbid water mediums and pointing errors of the propagated light beam. We used to Monte Carlo approach for the best fitting curves to yield simulation results.

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.

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.

Unmanned aerial vehicles (UAVs) play a major role in advancements of Internet of Things (IoT) applications for smart cities in next-generation communication networks. The emergence of diverse IoT applications (i.e. intelligent transportation systems, smart environmental applications, etc.) required reliable quality of service (QoS) of edge users to be increased as much as possible. Therefore, UAV-assisted communication is being increasingly used as a potential technique to enable robust and reliable communication between base stations and the edge users. As a contribution in this direction, a self-energized UAV-based cache-assisted communication network is investigated, in which a source node communicates with a group of edge users with the aid of a UAV. In order to prolong the UAV's serving time, the UAV is equipped with cache memory and energy-harvesting capability. We use power-splitting simultaneous wireless information and power transfer (PS-SWIPT) technique to power up the UAV's communication capabilities. Then, the effects of caching, energy harvesting, source transmission power, operational time, and the UAV's trajectory on the system performance are analyzed in terms of the achievable information rate at the edge users. In particular, two optimization problems are formulated to maximize the achievable throughput at the users and the trajectory of the UAVs, which guarantee a maximum information rate at the edge users while maintaining the QoS requirement. Finally, numerical simulation results are provided to validate the theoretical analysis provided in this chapter.

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.

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.

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.

Radio frequency energy harvesting (RF-EH) offers an unorthodox solution to the painstaking energy constraint drawback in wireless sensor networks (WSNs). In this paper, a data-gathering scenario from a UAV assisted WSN that consists of multiple sensor nodes (SNs) and power beacons (PBs) is considered. All the SNs are remotely powered by the PBs via wireless power transfer (WPT). In the first phase, a cluster-head (CH) is selected from the powered-up SNs and each SN periodically sends its observations to the CH. In the second phase, UAV powers the CH and collects the aggregated sensor observations from the CH. Under the assumption of Rayleigh and Rician fading channels, the outage probability at the UAV is derived and identified the time ratio of the proposed time-block structure that minimizes the outage probability. Furthermore, an effective algorithm is proposed to generate a solution for the process of CH selection. Finally, the achievable outage probability, throughput and the service range of the UAV are demonstrated for a given random setup of WSN through the theoretical and simulation results obtained.

In this paper, we propose a unified energy harvesting scheme using wireless power transfer (WPT), simultaneous wireless information and power transfer (SWIPT) and loop-back self-interference energy harvesting (SI-EH) enabled full-duplex (FD) cooperative communication system for unmanned aerial vehicles (UAVs). In contrast to traditional UAV assisted cooperative networks, here the UAV relies on alternative energy sources rather than pre-charged battery. Furthermore, the optimal time allocation for WPT and SWIPT scheme is obtained theoretically. Considering a delay-limited transmission mode, we derive an approximate close-form expression for the outage probability and the average throughput of the proposed system.

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.