Search

Summary: With the continuous proliferation of sensing technology, it has become possible to utilize energy harvesting (EH)‐enabled sensor nodes for a variety of applications. However, conventional wireless sensor networks (WSNs), that is, those without EH‐enabled nodes, still have limited applicability due to their limited battery resources. Further, the utilization of EH‐enabled nodes in the network not only imposes a financial burden on the user but also limits its performance due to its dependence on environmental conditions. To address this concern, in this paper, we propose the EH‐enabled energy‐efficient routing (EHEER) technique for green communication in WSN. The predominant concern being addressed in this paper is the selection of cluster head (CH), which helps in gathering, aggregating and forwarding the data from the cluster‐based routing paradigm. We use the spotted hyena optimizer (SHO) algorithm for optimizing the fitness parameters for CH selection, namely, energy ratio, distance considerations, node density, load balancing and the network's average energy. We use EH‐enabled nodes in the network strategically so as to keep control over the costs incurred in the network. The simulation outcomes empirically prove the efficacy of the proposed work, as it effectively increases the network stability and operational period by a huge margin as compared to the existing techniques. [ABSTRACT FROM AUTHOR]

Summary: This paper investigates optimizing the collaborative energy power consumption between nodes with energy harvesting (EH) capability at the fusion center (FC) and multi‐antenna sensors using game theory. Using multi‐antennas at FC on sensor networks (SNs), we can benefit from the spatial diversity in receiving the data and using multi‐antenna sensors and energy to transfer the data and optimize the SN, respectively. Also, in this paper, the data transmission in the network is formulated by considering the limitations of storage resources of each sensor, minimum data receiving, minimum EH, and maximum collaboration among sensors. In this paper, some modes are suggested to minimize the collaborative energy among sensors for transmitting the data and energy among sensors in the collaboration of sensors to optimize the power control and allocation power policy. Suggestions have been studied based on the number of antennae to transmit, using the cooperative games in sharing the data and the energy and auction game in transmitting to FC. The simulation results of the proposed problem using MATLAB software show optimization in participation function, EH, allocation in cooperation time, and transferring to FC to improve the detection of the transmitted data based on the increasing number of antennas in FC. [ABSTRACT FROM AUTHOR]

Summary: This paper evaluates the performance of a spectral‐amplitude‐coding optical code division multiple access (SAC‐OCDMA) system over a free space optical (FSO) communication link under various weather conditions such as fog, snow, and rain. The system uses different code families, including modified quadrature congruence (MQC), random diagonal (RD), and diagonal eigenvalue unity (DEU), to address user codes and reduce the effects of multiple access interference (MAI). The system's bit error rate (BER) performance has been analyzed taking into account receiver noises and MAI, and calculates the required optical power for a BER value of 10−9 under different weather conditions. The results show that fog has the most significant impact on the system's performance, while rainy conditions require the lowest optical power. The performance of the system also declines with increasing transmission length and concurrent user count. Finally, the paper compares the performance of different code families under unfavorable weather conditions and concludes that DEU performs better than MQC and RD in bad weather. [ABSTRACT FROM AUTHOR]

Summary: In the era of big data, massive amounts of data hold great value. However, much data exists as isolated islands, and the maximum value of the data cannot be fully utilized. Federated learning allows each client to train local data and then share the training model parameters securely, which can address the isolated data island problem and exploit data value while ensuring data privacy and security. Accordingly, in order to securely complete the electric power load forecasting using existing data, this paper constructs a federated learning‐based privacy‐preserving scheme to support electricity load forecasting in edge computing scenarios. To address the problems of the data‐isolated islands and data privacy in electric power systems, this paper proposes a decentralized distributed solution based on the federated learning technique. Our scheme achieves electricity load forecasting for power systems through the federated learning‐based framework and uses edge computing architecture to improve real‐time data capability and reduce network latency. For the hierarchical scheduling structure in power systems, we divide the system into a cloud‐side‐device three‐layer architecture, which achieves structural coordination and balance, and each layer collects information according to the scheduling control tasks, promoting scheduling effectiveness. Finally, different privacy protection methods are used on the cloud‐edge and edge‐device sides to significantly enhance data security. Moreover, We have conducted extensive experimental simulations for our proposed scheme. The experimental results show that the relative error of electricity load forecasting is around 1.580%. Meanwhile, our scheme achieves high accuracy and low memory usage. The security analysis proves the feasibility and security of our scheme. [ABSTRACT FROM AUTHOR]

Summary Autonomy is becoming a prime requirement for satellite mission control operations. Data‐driven methods like Machine Learning models are playing a key role in bringing in autonomy. Health keeping data from satellite telemetry is a key ingredient in these data‐driven methods. In real‐world satellite operations, the health‐keeping telemetry data gradually drifts due to adverse space weather effects and wear and tear of electronic and mechanical components. The key question that arises is how to detect and quantify the data drift which is generally a gradual phenomenon. This paper discusses a novel statistical method for detecting data drift occurring in satellite telemetry. For the purpose of experimental work in this paper, an actual telemetry data set of the BUS CURRENT sensor which is part of the Electrical Power System of a Low Earth Orbit Satellite was considered. Data drift detection test was carried out using this sensor data using the developed novel statistical method and with Kolmogorov Smirnov test which is a probabilistic method. Both results are analysed and compared. Thereafter novel statical method was used to check its efficacy using a synthetic data set with induced drift. [ABSTRACT FROM AUTHOR]

Summary: This paper proposes a novel hybrid energy harvesting framework integrated with a graphene‐based supercapacitor to address the energy demands of 6G communication systems and smart grid networks. To ensure consistent power generation, the proposed framework combines diverse energy harvesting mechanisms, including acoustic, vibration, and radio frequency (RF) energy sources. These harvested energies are then efficiently managed and stored in a proposed graphene‐based supercapacitor compared with existing Li‐ion batteries, due to its high energy density and rapid charge‐discharge capabilities. Smart grids and 6G networks can utilize the energy that hybrid systems harvest. This paper examines the analysis of RF energy extracted from various antenna configurations. In the acoustic energy harvesting system, energy extraction has been achieved by subjecting it to acoustic pressure and impedance. Notably, the inclusion of acoustic impedance has resulted in a greater amount of harvested energy. The vibration energy harvesting analysis with angular frequencies under various force conditions is employed. The magnitude of force applied to the harvesting system significantly influences the efficiency of the harvested energy. The three‐dimensional structure and voltage levels of the graphene‐based supercapacitor have been examined for various electrodes. For maximizing the harvested hybrid energy, convex optimization is formulated due to its ability to efficiently navigate complex design spaces while ensuring reliable and globally optimal solutions. CVX tool in MATLAB is used for validation. The results improve the energy harvesting efficiency and enhance the power availability of all the harvesting sources. Furthermore, the compatibility of the proposed framework with existing network infrastructure highlights its potential for seamless integration into real‐world communication and energy distribution systems. [ABSTRACT FROM AUTHOR]

Summary: In the present scenario, wireless body area network (WBAN) use case has gone beyond medical monitoring (e.g., E‐Healthcare) and has become a vital part of our daily lives. WBANs, applied in E‐Healthcare systems, extract the physiological parameters through the implanted (in‐body) and/or wearable (on‐body) sensors applied to the human body and route them to the remote server in a systematized and well‐grounded manner. Thus, routing is the most primitive and non‐trivial task in WBANs for prompt and proper delivery of sensed data. The design of routing protocol is crucial for efficacious communication and high network performance. Therefore, the target of this paper is to present an all‐encompassing taxonomy of the state‐of‐the‐art routing protocols in WBANs. Firstly, this paper provides an insight into WBANs and their related projects. Next, WBAN routing challenges are explored, and after clustering these challenges based on their operating mechanism, the routing protocols are categorized into eight categories, which correspond to cluster‐ and tree‐based, cross‐layer‐based, fuzzy‐based, interference‐based, posture‐based, QoS‐based, SDN‐based, and temperature‐based routing protocols. Furthermore, comparison tables highlighting the goals, strengths, limitations, and novelty of each protocol, along with a qualitative comparison table of the routing protocols for each category based on their features are furnished. This exhaustive survey can serve as a starting point for WBAN researchers, as open research issues have been highlighted in the discussion section. [ABSTRACT FROM AUTHOR]

Summary: The Internet of Things (IoT) is a system that includes smart items with different sensors, advanced technologies, analytics, cloud servers, and other wireless devices that integrate and work together to create an intelligent environment that benefits end users. With its wide spectrum of applications, IoT is revolutionizing both the current and future generations of the Internet. IoT systems can be employed for broad‐ranging real applications, such as agriculture, the environment, cities, healthcare, and the industrial sector. In this paper, we briefly discuss the three‐tier architectural view of IoT, its different communication technologies, and the smart sensors. Moreover, we study various application areas of IoT such as the environmental domain, healthcare, agriculture, smart cities, and industrial, commercial, and general aspects. A critical analysis is shown for the existing schemes and techniques related to this work. Further, this paper addresses the basic context, tools and evaluation approaches, future scope, and the advantages and disadvantages of the aforestated IoT applications. A comprehensive analysis is provided for each domain along with its fundamental parameters like the quality of service (QoS), network longevity, scalability, energy efficiency, accuracy, and cost. Finally, this study highlights the technical challenges and open research problems existing in different IoT applications. [ABSTRACT FROM AUTHOR]

Summary: In this paper, a received signal strength indicator (RSSI)‐based weighted centroid localization (WCL) method for indoor corridor scenarios is developed and tested. The contribution of the proposed system is that, to scope the area of an unknown target position, the possible corridor area where the target node should be located is automatically selected, and only reference nodes deployed in such an area are applied for position estimation. Additionally, to improve the estimation precision, distance values converted from measured RSSIs and used for the WCL are also compensated to alleviate the RSSI variation problem caused by physical environments. Therefore, our methods can save a number of reference nodes to be used, while localization accuracy can also be achieved. Experiments in the corridor environment using a 2.4 GHz IEEE 802.15.4 wireless sensor network with four reference nodes deployed in the test field dimension of 22 m × 9.3 m have been performed. Experimental results demonstrate that the proposed method, which requires only two reference nodes, outperforms the original WCL method with four reference nodes by 53.053%, as indicated by average localization errors. The results also reveal that the proposed method provides error distances lower than the WCL method for all test target positions, while all estimated positions fall within the corridor areas by 100%. [ABSTRACT FROM AUTHOR]

Summary: This paper analyzes the performance of a cooperative nonorthogonal multiple access (NOMA) in an underlay cognitive radio network aided by an energy harvesting relay. A secondary source transmits signal for two users, where a near user acts as a relay for the far user. The far user applies the selection combining (SC) approach on the signals which were relayed by the near user and received via direct path from the secondary source. We analytically derive the outage probability (OP) of each user separately, the overall system OP, and the throughput of the system. The impact of the power allocation coefficient of NOMA and energy harvesting parameters on outage is indicated. Further, the performance of the network is investigated with imperfection in successive interference cancellation (SIC), maximal ratio combining (MRC) at relay, and Nakagami‐m fading. The results derived analytically are supported by simulation in MATLAB. [ABSTRACT FROM AUTHOR]

Summary: The orthogonal time frequency space (OTFS) transmission scheme was shown to outperform orthogonal frequency division multiplexing (OFDM) under the doubly dispersive channel. In this paper, the linear precoding is studied for multiple‐input and multiple‐out (MIMO) OTFS systems, in which a spatial‐Doppler domain singular value decomposition (SVD) precoding scheme is proposed. At the transmitter, the Doppler domain symbols from different spatial streams are precoded before projected onto multiple antennas for transmission. At the receiver, multipath components of the transmitted symbols in the delay‐Doppler grid are combined by using maximal ratio combining (MRC) strategy, so as to achieve the multipath diversity gain and increase the reception reliability. The achievable rate and complexity of the proposed scheme are analyzed, revealing that it can increase the achievable rate while reducing the detector complexity as well. The simulation results confirm that the SVD‐based precoding significantly enhances the error performance of the MIMO‐OTFS with MRC‐based detector. [ABSTRACT FROM AUTHOR]

Summary: This paper presents Relay node selection scheme and Deep sleep period for power management in Energy Harvesting Wireless Sensor Networks (RD‐EHWSN), a new energy‐saving scheme founded on asynchronous duty cycling. RD‐EHWSN reduces sensor node energy consumption and guarantees equilibrium energy use between sensor nodes in WSN with the energy harvesting capacity by adjusting these sensor nodes duty cycles more drastically and deeply by according to the estimated value of its residual energy on the basis of future‐presented harvested energy, and this is done through the use of a new proposed energy threshold policy. RD‐EHWSN also grips the benefit of transmitter initiated using the low power listening (LPL) technique with short preamble messages and uses a new relay node selection procedure to achieve the load balancing in WSN. We implemented RD‐EHWSN by using OMNeT++/MiXiM. For evaluation, we compared it with PS‐EHWSN, under multiple concurrent multihop traffic flows scenarios and scenarios in which nodes can harvest different energy harvesting rate. In all experiments, RD‐EHWSN significantly outperformed the PS‐EHWSN scheme; the results of simulation demonstrate that our scheme enhances the general yielding of WSN thru lessening the energy consumption and the mean latency, as well as raising the packet delivery ratio and the throughput. Moreover, RD‐EHWSN improves the WSN lifetime and ensures it operates in good condition in the case where the energy harvesting rate is lower by comparing it with the PS‐EHWSN scheme. [ABSTRACT FROM AUTHOR]

Summary: Opportunistic network (OppNet) belongs to the category of Mobile Ad‐hoc Networks (MANETs), a kind of Delay Tolerant Network (DTN), where the wireless nodes are completely mobile and the data transmission routes are dynamic. The major challenge in developing a routing model for such a network is the unpredictable nature of the movement of the nodes. In this paper, a spatiotemporal prediction model based on human mobility pattern is proposed using Bayesian posterior probability (BPPR) where several clusters are identified within the network and the day and time duration of nodes visiting those clusters are recorded. The Bayesian posterior probability is then used to determine the probability of the neighbor node visiting the destination's cluster. If the calculated probability for that node is higher than a specified threshold, the packet will be forwarded. A comparison of the results obtained on simulation is made with benchmark models—Epidemic, Prophet, HBPR, EDR, NexT, and EBC, to name a few, where it is found that on average the proposed model outperforms the other models in terms of delivery probability, hop count and number of messages dropped by around 23.89%, 24.8%, 24.4%, 37%, 11%, and 42% respectively, with varying number of nodes, TTL, message generation interval, and buffer size. Similar improvements have been observed in terms of the other two metrics. In terms of overhead ratio, the proposed model outperforms Epidemic, Prophet, HBPR, NexT, and EBC. However, as the number of nodes and TTL are varied, BPPR performs better than NexT by around 9% and 12%, respectively, in terms of average latency. [ABSTRACT FROM AUTHOR]

Summary: Fractal antenna arrays are usually used to tune multiband frequencies. However, these types of iteratively constructed antennas are associated with undesirable high sidelobe levels and low directivities. In this paper, an optimization procedure based on the genetic algorithm is used to find the optimal weights of the array elements such that the corresponding array patterns have low sidelobe levels and good directivity. Moreover, the fractal nature in the proposed arrays is maintained regardless of the optimized weights. Thus, the proposed fractal‐shaped array maintains its capability in performing multiband frequency operation. These good radiation features make the proposed fractal‐shaped array more appropriate for the current and future wireless communication applications. Simulation results confirm the superiority of the presented linear and planar fractal‐shaped array structures with compared to the conventional fractal cantor linear array and the standard Sierpinski carpet planar array. For the proposed fractal cantor linear array, the sidelobe level has been reduced to more than −20 dB at different operating frequencies, and the directivity has been improved by more than 8 dB, while the modified Sierpinski carpet planar array has achieved −30 dB depressions in the sidelobe level and 6 dB improvement in the directivity. [ABSTRACT FROM AUTHOR]

Summary: It has been confirmed that the aerial intelligent reflecting surface (AIRS) can dramatically improve the coverage and quality of service of wireless communication systems. This paper proposes to exploit an AIRS to enhance the physical layer security (PLS) of wireless communication systems. In particular, the AIRS flies at convenient positions for enhancing legitimate channel gain and reducing eavesdropping channel gain. Moreover, the worst‐case security is determined where the legitimate user is affected by hardware impairments (HIs) while the eavesdropper hardware is ideal (ID). The analytical expression of secrecy outage probability (SOP) of the considered systems (referred to as the AIRS‐HI systems) is derived over realistic Nakagami‐ m channels recommended for application in the fifth and beyond generations (5G & B5G). To clarify the behaviors of the considered systems, the asymptotic expressions of signal‐to‐distortion‐plus‐noise ratio (SDNR) at the legitimate user, signal‐to‐noise ratio (SNR) at the eavesdropper, and SOP are also provided. Monte‐Carlo simulations are employed to confirm the accuracy of the derived theorem. Numerical results confirm that the SOP of the AIRS‐HI systems is dramatically higher than the SOP of the AIRS‐ID systems. In other words, a strong effect of HIs on the SOP of the AIRS‐HI systems is clearly indicated. Consequently, utilizing the high transmit power is not an effective solution to improve the secrecy performance of the AIRS‐HI systems. In contrast, it is essential to employ an appropriate transmit power tailored to the specific system parameters. Furthermore, the considerable advantages of incorporating AIRS are demonstrated through a comparison between the SOPs of AIRS‐HI systems and HI systems lacking AIRS. Additionally, a comprehensive examination of AIRS‐HI system behaviors is conducted by varying various system parameters, including the predefined secrecy rate, HI level, the number of reflecting elements (REs) in AIRS, WiFi network frequency, AIRS altitude, bandwidth, and channel fading order. These observations lead to the identification of numerous recommended solutions for enhancing the SOP performance of the considered AIRS‐HI systems. [ABSTRACT FROM AUTHOR]

Summary: IoT‐assisted WSN contains various nodes, which are placed on a huge scale that increases complications. Thus, the challenges and issues of these networks fluctuate as compared to WSNs. Hence, sensor nodes are imperative unit that runs on less energy resources. Hence, devising a robust and energy‐effective protocol for increasing network lifetime is a complex task. This paper devises a novel hybrid optimization‐driven approach for selecting cluster head (CH) in IoT‐assisted WSNs. Initially, the simulation of IoT nodes is done by configuration. Thereafter, the Cluster Head selection is done using a newly devised optimization technique, namely the Taylor‐Political optimizer (Taylor‐PO). Thus, fitness is newly developed by adapting certain attributes like energy, delay, inter and intra‐cluster distance, Link Lifetime (LLT), predicted energy, and delay. Here, the multipath routing is accomplished using Tunicate Swarm gray wolf optimization (TSGWO). Thus, the proposed Taylor‐PO is offered for effective Cluster Head selection along with multipath routing using TSGWO. The proposed Taylor‐PO offered improved performance with smallest delay of 0.006 sec, highest energy of 2.368 J, highest throughput of 494.043 kbps. [ABSTRACT FROM AUTHOR]

Summary: Communicating large amounts of data requires an encryption solution that ensures fast and secure data transfer. Unfortunately, it faced privacy and security issues, resulting in higher power consumption, data scarcity, energy, diversity, data reliability, low security, and packet loss in the communication process. The goal of this research is to ensure data transfer while conserving energy and protecting data transmission in WSNs. Therefore, this paper proposes a multipath routing protocol using the HGSPSO algorithm, which is a combination of hybrid gravitational search algorithm (HGSA) and particle swarm optimization (PSO), to securely transmit data from one node to another node under public and private key cryptography. The PSO approach is utilized to resolve the energy hole problem by selecting the cluster head in the sink coverage area. The RSA can be employed for data encryption, data decryption, key generation, and sharing. The metrics like acceleration constants and inertial weights are used for the HGSPSO algorithm. The result of this implementation demonstrated that the scheme had a low energy consumption of 36%, a maximum packet delivery ratio (PDR) of 96%, a higher throughput rate of 88%, and a low packet loss of 39%. [ABSTRACT FROM AUTHOR]

Summary: Unmanned aerial vehicles (UAVs) can serve as aerial mobile edge computing (MEC) servers to provide computing services to Internet of Things smart devices (ISDs) with insufficient computing capacity on the ground. However, how to provide energy‐efficient computing services by designing appropriate resource optimization strategy is still a challenge issue in UAV‐enabled MEC networks. To this end, this paper proposes a computation efficiency (CE)‐oriented partial offloading framework for UAV‐enabled MEC networks, where the ISDs' computation bits and energy consumption are taken into account simultaneously. Specifically, we firstly divide the ISDs into multiple clusters and determine the deployment of UAVs by k‐means method. Meanwhile, ISDs occupying the same subchannel in the same cluster can offload data through non‐orthogonal multiple access (NOMA) technology. Then, the problem of maximizing the CE of the system is formulated by optimizing subchannel allocation, transmit power and computation resources of ISDs. To solve it, we propose a staged optimization approach by using matching theory, Dinkelbach and sequential convex programming (SCP) methods. Numerical results demonstrate the proposed scheme can achieve higher CE compared with other baseline schemes. [ABSTRACT FROM AUTHOR]

Summary: The millimeter‐wave (mmW) band has been chosen to obtain multi‐gigabit per second in the fifth generation (5G) communication and beyond. The knowledge of this frequency band is still the focus of research today. After UTI announced its choice of mmW for 5G communication, massive studies were carried out on this band. Among these studies, many optimization methods were proposed to reduce the impact of degradation sources. In this paper, we propose a new method to optimize the system error vector magnitude (EVM) of complex systems with many different calibration sources. A difference of 0.1% is observed between our optimization method and old methods. This small improvement of the EVM system can push the 3GPP system EVM (EVM at the receiver) limits by a few centimeters, which is not negligible in a high‐frequency transmission. Moreover, we have also proposed a new method to compute the throughput that takes into account the TX and RX directional antenna heights. The measurement campaigns and simulation results have shown an improvement from 0% to 6% of throughput. The results depend on indoor environment study and different obstacles in NLOS (non‐line of sight) conditions. [ABSTRACT FROM AUTHOR]

Summary: Flying ad hoc networks (FANETs) are a class of highly dynamic mobile ad hoc networks in which flying UAVs coordinate among themselves for delivering the data to the applications. Data routing in FANETs has been a challenge due to the inherent mobile and unpredictable movement of UAV nodes. This paper proposes a quality of service‐aware routing protocol (QARP) for FANETs which incorporates hybrid nature‐inspired heuristics to identify optimized routes to the destination UAVs. The routing mechanism operates in two phases. In the first phase, the neighbour discovery initializes the adapted firefly algorithm to identify nodes with least packet delivery delay to the destination. In the second phase, the Gaussian quantum‐behaved particle swarm optimization meta‐heuristic algorithm is utilized to identify the most optimal nodes to create a route for data delivery to destination. The proposed protocol has been tested to perform better in terms of delay, routing overhead, throughput and packet delivery ratio in comparison to MA‐DP‐AODV, MDA‐AODV and MDRMA routing protocols. [ABSTRACT FROM AUTHOR]

Summary: This paper presents the performance of maximum ratio combining (MRC) diversity receiver over shadowed Beaulieu‐Xie (SBX) fading model. The SBX model is used to characterise wireless communication environments that include multiple numbers of line‐of‐sight (LOS) and non‐line‐of‐sight (NLOS) signals. The probability density function (PDF) of the MRC scheme over the SBX channel has been derived. The PDF‐based approach has been used to calculate the outage performance and average bit error rate of several modulation schemes for coherent and non‐coherent signals. It has also been shown how the diversity orders and the fading channel's parameters affect the system's performance. To authenticate the evaluated expressions, Monte‐Carlo simulation results are used for validation. The SBX model is used to characterise wireless communication environments that include multiple numbers of LOS and NLOS signals. [ABSTRACT FROM AUTHOR]

Summary: Non‐orthogonal multiple access (NOMA) has proven to be a very effective multiple access scheme to be employed in visible light communication (VLC) systems. NOMA scheme is capable of enhancing the spectral efficiency, sum rate performance, and various other performance parameters in VLC systems as compared to traditional orthogonal multiple access schemes. However, it is not practical to apply the concept of NOMA to all the users jointly. Therefore, the concept of user pairing has been introduced in literature to implement NOMA effectively so as to reduce the decoding order of successive interference cancellation (SIC) mechanism and complexity. In this paper, we have proposed a user pairing scheme based on clustering for downlink 3D NOMA‐based VLC systems. In this user pairing scheme, clustering is performed prior user pairing. The number of clusters are selected using K‐means algorithm and Elbow method, and the user allocation in a particular cluster is validated using artificial bee colony (ABC) optimization. In order to achieve high throughput, inter‐cluster user pairing is performed by forming pairs of two or three users with maximum channel gain difference in between them. The simulation results show that, for given values of signal‐to‐noise ratio (SNR), the proposed user pairing scheme offers higher average user data rates (AUDRs) as compared to the existing user pairing schemes for downlink NOMA‐based VLC systems. The energy efficiency (EE) and the bit error rate (BER) performance of the proposed user pairing scheme have also been studied. [ABSTRACT FROM AUTHOR]

Summary In this growing world, the field of communication is developing quickly. The research community's attention is shifting to the design of networks beyond fifth generation (5G) and the sixth generation (6G) due to the rapid spread of the 5G mobile networks. Due to that, there will be a lot of traffic in the area, which will interfere with the channels and maybe produce noise. Nonorthogonal multiple access (NOMA) contributes to streamlined communication and a decrease in the possibility of interference. The communication will be encoded and decoded from transmitter to receiver utilizing the superposition coding (SC) and successive interference cancelation (SIC) approaches, ensuring the message's secrecy. This paper considers a simultaneous wireless information and power transfer (SWIPT)‐based cooperative NOMA system, where the nearby user to the source node acts as a relay to assist the far user. To further enhance the system performance, an improved golden search optimization (IGSO) is used to determine the best power allocation and power splitting coefficients by decreasing the outage probability. The existing models are compared with the proposed model in the results section regarding outage probability and throughput, where the proposed model outperformed all other existing models. [ABSTRACT FROM AUTHOR]

Summary Underwater wireless sensor network (UWSN) connects the real world to the hidden resources available deep into the sea using sensor nodes deployed sparsely and are interconnected to gather information for any movement/change in the ocean. The computed information on nodes obtained from concurrently running UWSN's applications will be meaningful, only if the location of this change will be identified. Nevertheless, it is always difficult to obtain the exact location coordinates of any misadventure like tectonic plate's movement but using localization algorithms in UWSN helps to obtain the coordinates. Since localization algorithms for terrestrial networks are not feasible for UWSN because of environmental challenges. Moreover, GPS systems do not work after 15 m of depth and the radio frequency gets suppressed. So, the requirement arises to analyze existing localization approaches in the deep sea where acoustic signals are used for communication and data transfer. In this paper, along with describing the UWSN's applications and challenges, the underwater localization schemes are reviewed to present, summarize, and mention the scope of improvement. Further, classification into range‐based and range‐free categories of these schemes is depicted with implementation in the NS2.30 simulation environment of some of the recent techniques to showcase the reasons for better performance. [ABSTRACT FROM AUTHOR]

Summary The underwater acoustic sensor network is a fundamental source for ocean exploration. The potential applications of underwater acoustic sensor network (UASN) include seismic imaging, disaster prevention, mine reconnaissance, pollution monitoring, exploration of natural resources, and military surveillance. To acquire accurate results, implementing all applications of underwater sensor networks requires an adequate network connection and communication technology. The precise placement of underwater sensor nodes needs to be identified in order to achieve effective communication. To accomplish the requirement, the paper presents an efficient localization algorithm to compensate the stratification effect based on an improved underwater salp swarm optimization technique (LAS‐IUSSOT). To compute the location of sensor nodes with high accuracy, the nodes are initially randomly deployed in three‐dimensional underwater acoustic sensor network (3D‐UASN). After that, the hybridization of centroid‐based localization and the ray theory technique is used, and then, the degree of coplanarity is analyzed among the underwater sensor nodes. Then, the computation of the location of unknown nodes is performed using improved underwater salp swarm optimization technique (IUSSOT) to obtain the optimized location and compensate the impact of the stratification. The comparison of the simulation results of the existing algorithm and the proposed algorithm is performed. The LAS‐IUSSOT achieves 40.46% and 28.00% accuracy in terms of localization of underwater sensor nodes for both the sparse and dense regions in 3D‐UASN. The LAS‐IUSSOT achieves 49.39% and 62.57% accuracy in terms of ranging of underwater sensor nodes for both the sparse and dense regions in 3D‐UASN. Simulation results illustrate that the proposed algorithm outperforms the existing algorithm in terms of localization and ranging accuracy in both sparse and dense regions in 3D‐UASN, root mean square error (RMSE), normalized localization error (NLE), computation time, and convergence rate. [ABSTRACT FROM AUTHOR]

Summary Effective, reliable, and rapid spectrum sensing in concordance with maximum throughput efficiency is necessary at the cognitive radio network to maximize the network's utilization. An adaptive coalition using Kullback–Leibler divergence (KLD)‐based cooperative spectrum sensing scheme (KLDCSS) with a nominal sensing time to optimize the spectral efficiency is presented in this paper. In a coalition‐based spectrum sensing scheme, cooperating secondary users (SUs) are allocated to different coalitions to sense different Primary User (PU) channels. The same cognitive users allocated to sense the primary user channels are allotted to detect in different sensing phases. In the proposed sensing scheme, the cooperating SUs are adaptively allocated to different coalitions to maximize the throughput efficiency. Collaborating cognitive users with a standard signal‐to‐noise ratio and distinct energy levels that are characterized by the localized probabilities of detection and false alarm is considered. An adaptive coalition and user allocation algorithm are proposed to optimize the average opportunistic throughput and diminish the sensing overhead. The expression for throughput efficiency in terms of average throughput and sensing accuracy is derived. In this scheme, the SU computes the log‐likelihood ratio (LLR) from the acquired sample and forwards the same to the fusion center. The fusion center then accumulates the LLR values computed by the SU to estimate the likelihood of spectrum availability. Simulation results highlighting the competitive edge of the proposed scheme, with higher throughput efficiency over various numbers of SUs, coalitions, and signal‐to‐noise ratios, are presented. [ABSTRACT FROM AUTHOR]

Summary Multiple input multiple output (MIMO) constitutes a wireless approach that employs several senders and receivers in order to send numerous data at once. Due to the rapid increase of cellular mobile device usage and the limitation of computing power, antenna selection (AS) has attracted more and more attention recently. AS can keep a balance between communication performance and computational complexity. In this paper, a novel deep learning (DL)‐based AS for MIMO software defined radio (SDR) system is proposed. The main objective of this work is to select the optimal antennas in MIMO systems to balance the efficiency of communication and maximize the secrecy capacity in massive MIMOME channels. First, we set up a DL‐based AS‐aided MIMO SDR environment that ensures intelligent decisions for AS. Accordingly, the hybrid loss function induced in bidirectional long short term memory (HLFI‐Bi‐LSTM) model is proposed to build the decision server, in which it takes some estimated features as input. The features such as channel state information, received signal strength indicator (RSSI), signal‐to‐noise ratio (SNR), and antenna gain are considered accordingly as the input to HLFI‐Bi‐LSTM. The HLFI‐Bi‐LSTM model is the extended version of Bi‐LSTM, which is improved by inducing the hybrid loss function, which is the combination of two functions namely, combo loss and inverse mean square error. The proposed HLFI‐Bi‐LSTM attained the greater accuracy value of 0.968 at 80% for optimal selection of the antenna. [ABSTRACT FROM AUTHOR]

Summary This paper presents a compact (20 × 20 × 1.59 mm3), (0.34λg × 0.34λg × 0.01λg at 2.4 GHz) triple band monopole antenna for Internet of Things (IoT) applications. The geometry of the antenna consists of (i) U‐shape monopole with feed line, (ii) stubs, and (iii) modified ground to achieve three independent operating bands ranging from (i) 2.4–2.48 GHz for industrial, scientific, and medical (ISM)/3G; (ii) 3.4–3.6 GHz for 4G/5G; and (iii) 5.725–5.825 GHz for 5.8G Wi‐Fi/extended 5G. Various parameters, input impedance, and current distribution of the proposed structure are carried out to investigate the effects of stub, ground plane and analyze the radiation. The measured result covers the three individual bands in range of 2.38–2.48 GHz, 3.41–3.61 GHz, and 5.76–6.04 GHz, respectively, and exhibits stable omnidirectional radiation patterns, acceptable antenna gain, and efficiency in the operating bands. The experimental result of the fabricated antenna closely matches with the simulated result. Therefore, satisfactory result ensures its ability to work for 3G/4G/5G/extended 5G IoT portable applications. [ABSTRACT FROM AUTHOR]

Summary The solution of resource allocation is based on NOMA and OMA structures that are suboptimal to satisfy the demanding QoS and higher data rate requirements compared to EE requirements in 5G cellular networks. In this work, the resource allocation problem in the hybrid MC‐NOMA system is solved. The system achieves the trade‐off between spectral and energy efficiency (EE) with the lowest rate of user requirements. The system's resource allocation, including power allocation, is considered the crucial factor and is identified as a single‐objective problem. The suggested work focuses on user pairing and allocation on paired users following processing. The user grouping is designed to connect near‐ and far‐users with high C3 to increase the fairness of NOMA. As a result, this work considers multiple goals, such as C3 maximization, spectrum efficiency, and energy efficiency. This paper aims to present a novel hybrid optimization model with the combination of coati and bald eagle optimization algorithms, to solve the defined optimization problem. The experimental results show that the suggested system outperforms the conventional algorithms by evaluating different performance measures such as channel correlation, spectrum efficiency, energy efficiency, and power allocation. [ABSTRACT FROM AUTHOR]

Summary The main goal of this strategy is to detect the occurrence of wild animals in farmsteads and human habitats using an improved deep learning in order to avoid loss of life and damage to agricultural crops. This paper formulates a technique for recognizing wild animals in an Internet of Things (IoT) environment utilizing deep batch normalized exponential linear unit AlexNet (DbneAlexnet) and the Gazelle Hunting Optimization Algorithm (GHOA). The IoT‐Multimedia Sensor Networks (WMSN) network is first simulated, with the IoT nodes capturing the images needed for wild animal identification. The suggested GHOA is used for routing, which sends the captured images to the base station (BS). The input wild animal image is transmitted to image preprocessing at the BS, where it is processed using the Weiner filter (WF) to remove undesirable noise from the image. The denoised output is sent into salient map extraction, which extracts salient map to determine the regions that are conspicuous or noticeable at every place in the field of vision and guides the selection of attended location. Finally, the saliency map is forwarded to DbneAlexnet for detecting the wild animals, where the DbneAlexnet is trained using proposed GHOA. The suggested GHOA algorithm is created by combining the Gazelle Optimization Algorithm (GOA) and the deer hunting optimization algorithm (DHOA). Furthermore, detection is appraised by precision, recall, and f1‐score, which provide values of 90.2%, 89.1%, and 89.6%, respectively. [ABSTRACT FROM AUTHOR]

Summary The rapid growth in wireless communication technology and the proliferation of multimedia applications, specifically Voice over Wireless Fidelity (VoWiFi), necessitate the exploration of innovative techniques for improving network performance and quality‐of‐service (QoS). This research paper presents an innovative approach to enhance VoWiFi cell capacity using aggregate medium access control protocol data unit (A‐MPDU) frame aggregation for variable bit rate (VBR) traffic. In this research article, we investigated the effect that the retransmission of voice packets has on the cell capacity of a wireless local area network (WLAN) standard that provides VoWiFi service while taking into account the A‐MPDU approach. When taking into consideration the constant bit rate (CBR) and VBR traffics, we compared the results obtained using WiFi 6 (i.e., IEEE 802.11ax) with older WLAN standards such as IEEE 802.11b/g/n/ac. [ABSTRACT FROM AUTHOR]

Summary In the case of future access networks, such as 6G‐based applications, the free‐space optical communication (FSO) technology is an efficient solution. FSO in 6G is extremely popular because of its unique properties, which include ease of installation, high bandwidth, high security, license‐free long range, and interference resistance. However, environmental disturbances have a negative impact on the FSO system's functioning. Because of these atmospheric turbulences, the optical information gets restricted, which in turn reduces the link reliability, power density, and distance. This paper proposes a hybrid FSO strategy for improving system efficiency to address these problems. Signal creation is fundamental to every successful communication system. The FSO system consists of three components: the transmitter, the channel medium, and the receiver. The transmitter section includes a continuous wave laser, a Mach–Zehnder modulator, a nonreturn to zero transpose Walsh code generator, and a nonreturn to zero pulse generator. Wavelength division multiplexing‐optical code division multiple access‐spectrum slicing (WDM‐OCDMA‐SS) is used to facilitate efficient data transfer after signals have been generated by alternate mark inversion (AMI). In order to boost a weak signal, fused Raman erbium amplifiers (Fuse‐RE) are used. Q factor and log bit error rate (BER) are used to assess the performance of the suggested approach. The proposed model has obtained a log BER of −15.3291 for clear air and a Q factor of 8.2922, whereas the performances are implemented using Python. The proposed approach achieves better performance when compared to the existing methodologies. [ABSTRACT FROM AUTHOR]

Summary Optical millimeter‐wave generation is a predominant approach for the generation of high‐quality carrier signals for future wireless transmissions. This paper proposes an optical frequency 12‐tupling millimeter‐wave generation scheme using three cascaded‐MZMs assisted by polarization multiplexing for carrier suppression. A three‐stage MZM architecture produces the desired sixth‐order sidebands along with the undesired carrier signal. The proper adjustment of polarization direction and angle of polarization rotation lead to the effective suppression of the undesired optical carrier signal. A comprehensive mathematical analysis has been accomplished to evaluate the system's performance, and the obtained results are also validated through simulation findings. The derived results demonstrate that the proposed system is capable of operating over a broad modulation index range extending from 1.5 to 4.5, thereby relaxing the stringent requirements for a constant modulation index. The proposed system generates high‐purity mm‐wave signals with an OSSR of 62.06 dB and an RFSSR of 54.79 dB at a modulation index of 2.6. Moreover, it is also validated that even if the system parameters like modulation index, polarizer rotation angle, and phase difference among RF driving signals deviate from their ideal values to a certain degree, the system performance remains acceptable. The involvement of polarization technique, omission of wavelength‐dependent devices, and a large modulation index operating range make this methodology readily appealing for implementation in radio‐over‐fiber transmissions. [ABSTRACT FROM AUTHOR]

Summary Mobile Ad Hoc Network (MANETs) are indeed autonomous, fast‐deployable wireless networks that are ideal for communications in areas with limited radio infrastructure, outdoor events, military operations, and disaster relief. But the primary problem is with routing because of the nodes' mobility. This paper proposes a cluster‐based routing under energy prediction via deep learning techniques. Here, proposes a new model termed as Concatenation of Convolutional with Max‐Avg Pooling layer in Deep Convolutional Neural Network (CCMAP‐DCNN) for energy prediction, in which additional layers are inserted into the extant DCNN structure to ensure the effectiveness of energy prediction. As a result, clusters are created by grouping the nodes together. Constraints like energy, trust, distance, and latency are taken into account while choosing the cluster leader. For cluster head selection and optimal routing, proposes a new hybrid Namib Beetle Upgraded Jellyfish Search Optimization (NBUJSO) algorithm that utilizes the NBO strategy to the JSO algorithm making the selection process more optimal. The best route is then chosen by the optimum routing method, which takes into account variables like network quality and mobility to send data packets from source to destination as efficiently as possible. Finally, the data aggregation process is followed for eliminating the redundant transmission. [ABSTRACT FROM AUTHOR]

Summary A unique MIMO antenna with circular polarization characteristics that works similarly for skin, brain and heart phantoms has been proposed in this paper. The twin rectangular X‐shaped slot that serves as the basic structure of the proposed antenna is entirely planar and low‐profile but has a defective ground plane. For three different phantoms, the proposed antenna resonates at 2.4–2.45 GHz ISM band. With a dimension of 15.5×9×1.27mm3$$ 15.5\times 9\times 1.27\ {\mathrm{mm}}^3 $$, the antenna exhibits compactness. Rogers RT/duroid 6010 substrate material has been used to fabricate the antenna in order to validate the designed antenna structure. Utilizing the high dielectric material for both substrate and superstrate, both skin‐mimicking gel and minced hog meat were employed in the experiment setup at 2.45 GHz ISM band. At ISM band, −28.3 dBi has been observed has realized peak gain. The obtained fractional bandwidth (FBW) and Axial Ratio Bandwidth (ARBW) values are 30.67% and 45%, respectively. Also, the maximum specific absorption rate (SAR) values are found to be in the acceptable limit regulated by IEEE. [ABSTRACT FROM AUTHOR]

Summary An evaluation of various transmit precoding schemes is proposed in this thesis on basis of spectral efficiency (SE) of massive MIMO (m‐MIMO) system in 2 GHz spectrum. The present generation of wireless networks must be rethought due to the rapidly rising user base, huge volume data transfer, wide coverage requirement, and exponential rise in data rate. 5G mobile network includes a multi‐fold increase in network capacity, energy conservation, decreased latency, higher coverage probability, and a seamless connection. m‐MIMO has provided good solution for enhancing the data rate with the coverage, overcoming the effects of multipath fading and has also increased diversity of the system. Massiveness of MIMO system along with 5G network is the key technology to address the issue of SE, throughput, improvement of QoS (quality of service), coverage probability, power delay profile, diversity simulation, energy efficiency, and improvement in bit error rate. Parameters such as SE, throughput, and coverage probability are important for any communication system, and their improvement can increase overall capacity of cellular network system and could meet the requirement of upcoming demand for mobile network. The research paper is focused on performance analysis of m‐MIMO with reference to the SE of various transmit precoding schemes. Simulation results show that SE provided by M‐MMSE (multi‐cell minimum mean‐squared error) technique of precoding ranks highest for the same number of antennas and pilot reuse factor as compared to other schemes. [ABSTRACT FROM AUTHOR]

Summary: The paper discusses about the design and analysis of a unique circular printed antenna with quatrefoil‐shaped slots and meta‐surface for body centric communications. The antenna design is progressed with a slots in quatrefoil shape carved on the patch placed on Taconic_LX substrate whose thickness is 1 mm. The footprint of the antenna is 32 × 24 × 1 mm3. The antenna's bandwidth is improved using defected ground. The proposed design operates from 2 to 14 GHz of the ultra‐wideband (UWB) spectrum, thus providing 143% bandwidth. The antenna exhibits good gain values of 2.5 and 6 dB at 2.45 and 5.8 GHz, respectively, with efficiency of 81% and 91%. At 2.45 GHz, the design proposed functions in on‐body mode, and at 5.8 GHz, it functions in off‐body mode. Specific absorption rate (SAR) analysis was carried out whose results are within the safety range of health measures. Bending analysis was also done to enhance the antenna's applicability. Path loss, fidelity, and group delay analysis are done. The simulated results were validated by fabricating and testing the prototype. On‐body testing of the fabricated antenna was also done at various body locations. The measured results were found to be in good agreement with the simulated results. [ABSTRACT FROM AUTHOR]

Summary: This paper considers a dual‐hop cooperative relay‐based communication with uplink (UL) and downlink (DL) non‐orthogonal multiple access (NOMA), where communication between sources to destinations takes place parallelly in the same frequency band over a Rayleigh fading channels. The energy harvesting (EH)‐based full‐duplex (FD) relay helps in forwarding the message from the source node to the destination node via superposition coding, thus calling it a multiple sources full‐duplex energy‐harvesting cooperative relay NOMA (MS‐FD‐EH‐CR‐NOMA) system. Early works focus on EH from one source node or a dedicated power station. In this article, the communication between sources and destinations occurs in two slots where first slot deals with energy harvesting while in second slot information transmission occurs. We studied the effect of imperfect successive interference cancellation (ipSIC) and residual self‐interference (RSI) in decoding the message at the relay and the destinations. We derived the closed‐form expressions for the outage probability of each pair and the system outage probability of the MS‐FD‐EH‐CR‐NOMA system. Next, we derive the closed‐form expressions of ergodic capacity under Rayleigh distributed fading channels. Further, numerical results are validated by its simulation results using Monte Carlo simulations in MATLAB. The results obtained through this work are a good step towards designing multiple source–destination communication using NOMA and EH relay. [ABSTRACT FROM AUTHOR]

Summary: The lack of interoperability between blockchains is a primary barrier to adopting the technology. Blockchains suffer from vendor lock‐ins as users cannot easily move their assets between blockchains. To resolve this issue, we propose a cross‐chain decentralized asset transfer protocol for blockchains without involving any intermediaries. Cross‐chain transactions can be efficiently executed using our proposed protocol without including any centralized third party. Most of the existing asset transfer solutions neglect the transaction finality guarantees; however, the protocol presented in this paper keeps track of transaction finality, providing transaction irreversibility guarantees and preventing assets from being lost in the transfer process. The reference implementation for the proposed protocol consists of smart contracts and a Web API for carrying out the cross‐chain transfer of assets. The proposed protocol is experimentally validated for the transfer of assets between Ethereum and Binance testnets. The performance testing shows that the cost of the proposed protocol is acceptable. [ABSTRACT FROM AUTHOR]

Summary: This paper introduces an innovative four‐element Ultra‐wideband (UWB) MIMO structure featuring an integrated global system for mobile (GSM) antenna with the ability to achieve dual and triple band‐notch capabilities. The antenna's distinctiveness is achieved through the utilization of four directional meandered line shaping decoupling structures (MLSDS), an orthogonal arrangement, and multi‐slot techniques. The incorporation of orthogonal separation alongside four directional MLSDS significantly reduces the mutual interference between radiating elements. By placing MLSDS on both sides of the substrate, effective coverage of the GSM band is achieved. The development of the MIMO structure unfolds through four distinct phases. The initial stage lacks MLSDS, while the second stage incorporates MLSDS. The third and fourth stages respectively introduce MLSDS with dual and triple notch characteristics. The presence of MLSDS enhances the antenna's impedance bandwidth (IBW). The intended notches are tailored to address interference from bands like Band n41, WLAN, and X‐band. Furthermore, the proposed antenna has undergone simulation, measurement, and comparative analysis with existing models, focusing on diversity performance metrics. The results reveal its exceptional diversity performance, positioning it as a potential choice for creating a portable UWB‐MIMO system. [ABSTRACT FROM AUTHOR]

Summary: Content interest forwarding is a prominent research area in Information Centric Network (ICN). An efficient forwarding strategy can significantly improve data retrieval latency, origin server load, network congestion, and overhead. The state‐of‐the‐art work is either driven by flooding approach trying to minimize the adverse effect of Interest flooding or path‐driven approach trying to minimize the additional cost of maintaining routing information. These approaches are less efficient due to storm issues and excessive overhead. Proposed protocol aims to forward interest to the nearest cache without worrying about FIB construction and with significant improvement in latency and overhead. This paper presents the feasibility of integrating reinforcement learning based Q‐learning strategy for forwarding in ICN. By revising Q‐learning to address the inherent challenges, we introduce Q‐learning based interest packets and data packets forwarding mechanisms, namely, IPQ‐learning and DPQ‐learning. It aims to gain self‐learning through historical events and selects best next node to forward interest. Each node in the network acts as an agent with aim of forwarding packet to best next hop according to the Q value such that content can be fetched within fastest possible route and every action returns to be a learning process, which improves the accuracy of the Q value. The performance investigation of protocol in ndnSIM‐2.0 shows the improvement in a range of 10%–35% for metrics such as data retrieval delay, server hit rate, network overhead, network throughput, and network load. Outcomes are compared by integrating proposed protocol with state‐of‐the‐art caching protocols and also against recent forwarding mechanisms. [ABSTRACT FROM AUTHOR]

Summary: In this paper, for the first time, the capability of a compact low‐cost wideband omnidirectional circularly polarized (CP) antenna to suppress multipath fading characteristics in a typical indoor propagation channel for 2.4 GHz applications is investigated. A ray tracing method based on the geometrical optics and uniform theory of diffraction is applied to analyze an indoor propagation channel using the measured radiation patterns of the proposed antenna. The design uses a conventional monopole antenna with a circular ground plane to generate a vertically polarized electric field. Sequentially flag‐shaped stubs are then added to the ground plane to produce horizontally polarized electric field and to improve the impedance bandwidth of the proposed antenna. The antenna is designed for 2.4 GHz WLAN application with 10 dB impedance bandwidth of 25.5% and 3 dB axial ratio (AR) bandwidth of 24.5%. The polarization can be readily changed between the left‐hand circular polarization (LHCP) and right‐hand circular polarization (RHCP) by altering the direction of the coaxial probe (monopole) or varying the orientation of the printed bended stubs. Both the LHCP and RHCP prototypes of the proposed antenna are designed, fabricated, and tested, and the similar results are obtained. [ABSTRACT FROM AUTHOR]

Summary: Energy internet permits the power to stream lithely for broadcast and it aids in transporting energy to each user using electric vehicles (EVs). The energy that EVs utilize is generated using certain sources. Still, considering poor weather, the power station averts the production of energy and needs to acquire power transmitted to another location. One resolution is to set stations that aid to save surfeit energies and minimize energy loss during transportation. This paper devises a new model for choosing charging stations to charge EVs. Energy is transferred from the energy source to the charge station via bus station through optimal path using Battle Royale Jaya Optimization (BRJO) routing with fitness attributes like distance to select the shortest path and energy. The prediction of energy is done with a deep recurrent neural network (DRNN) and the charge is distributed optimally to EVs by employing a proposed Competitive Swarm‐Battle Royale Jaya Optimization (CSBRJO) by utilizing multi‐parameters, like priority, distance, predicted energy, waiting time, and EV count needed for charging. The CSBRJO outperformed with the smallest distance of 6.935 km, energy consumption of 1.676 J, path length of 5.05 m, and waiting time of 4.645 sec. [ABSTRACT FROM AUTHOR]

Summary: In this paper, the throughput and outage performance for an unmanned aerial vehicle (UAV)‐assisted non‐orthogonal multiple access (NOMA)‐based hybrid cognitive radio (CR) network are examined under m‐Nakagami fading channel. To be more specific, a secondary source transmitter (SUT) broadcasts a NOMA‐enabled mixed signal to secondary destinations via UAV relay, which operates in full‐duplex (FD) mode and employs decode‐and‐forward protocol. In our approach, an energy harvesting (EH) circuit is employed at both SUT and UAV to harvest energy from the PU radio frequency (RF) signals. These secondary transmitters are also incorporated with energy detector (ED) circuit as well, which detects the activity of the primary user (PU). The status of PU to be busy or idle is confirmed on the basis of the energy detector's results. In turn, this drives SUT and UAV to switch between underlay and overlay protocols in an adaptive manner to increase spectrum efficiency (SE). The closed form mathematical expressions of the secondary outage probability for NOMA‐based UAV equipped CR networks under imperfect successive interference cancellation (i‐SIC) conditions have been evaluated. The administration of the power allocation policy at the SUT and UAV is assessed while maintaining the PU quality of service (QoS). Finally, MATLAB simulation testbed has been used to verify all the analytical closed form expressions. [ABSTRACT FROM AUTHOR]

Summary: This paper presents a wideband millimeter wave (mmWave) channel model for aerial reconfigurable intelligent surface (ARIS) communications, in which the reconfigurable intelligent surface (RIS) is attached to an unmanned aerial vehicle (UAV) to enable intelligent signal reflections in the air. The model is established according to standard 3GPP channel models and considers important propagation factors, for example, large‐scale fading, small‐scale fading, and radiation pattern of reflection units (RUs). In addition, the model assumes three‐dimensional (3D) rotations of RIS and can capture its effects on channel characteristics. Based on the model, we propose a design method for RIS reflection phases. Statistics including channel amplitude, spatial, temporal, and frequency correlation functions (CFs), and space‐Doppler power spectral density (SD‐PSD) are obtained. The impacts of RU number, UAV height and speed, and RIS rotation on channel statistics are investigated. Results suggest that the designed reflection phases can effectively mitigate multipath fading and Doppler effect. Compared to the yaw angle of the UAV platform, channel characteristics are more sensitive to the roll and pitch angles. [ABSTRACT FROM AUTHOR]

Summary: The Internet of Things (IoT) has provided us with various applications that need processing in real‐time. Fog computing has arisen as a highly effective computing paradigm that provides services closer to the IoT devices and hence fulfills the need for rapid response time and delay requirements of IoT applications. However, the heterogeneity of IoT tasks and the limited resources of fog nodes pose considerable challenges to task scheduling. Therefore, the effective utilization of fog resources is highly significant and necessitates an optimal and intelligent approach to task scheduling. This paper presents the "deadline‐cost aware task scheduling" (DCaTS) algorithm, which is designed for fog‐based IoT applications. The primary objective of this algorithm is to minimize the monetary cost while taking into account the deadline requirements and priority of tasks. The efficacy of DCaTS is assessed by analyzing various parameters, including completion time, monetary cost, response time, and waiting time. The experimental results show that in comparison with traditional policies, the proposed algorithm shows superiority in all the parameters. The proposed algorithm reduces the monetary cost up to 11.07% compared with the second best result. The results also indicate that DCaTS achieves a reduction of 10.05% in completion time, 10% in response time, and 10.12% in waiting time compared with the second best result. [ABSTRACT FROM AUTHOR]

Summary: Wireless sensor networks (WSNs) are used to monitor the real‐time parameters of remote/restricted access areas of automation industries which are tightly sealed. In such scenarios, the main challenge is signal transmission in sealed environments. An omnidirectional radiation pattern is preferred as a control link for receiving packets or periodic updates from its neighbouring nodes. However, the gain and directivity of omnidirectional antenna should be sufficient enough to transfer the data to the collecting node. This paper proposes a high‐gain horizontally polarised omnidirectional radiation pattern planar antenna resonating at the 2.45 GHz. The developed microstrip planar antenna offers a very simple and compact structure printed on either side of FR4 epoxy substrate (ε = 4.4) suitable for WSN nodes. A printed dipole director is arranged orthogonally and offers horizontal polarisation. A pair of parasitic elements is placed parallel to dipole radiators to improve the total gain of the antenna. A parallel pair of parasitic elements is placed on an inclination of 45° in antenna design plane for uniform distribution of surface current to achieve the omnidirectional antenna. The symmetrical structure of the radiating element on either side of the substrate avoids the design of the traditional balun structure to reduce the complexity of feeding network. The developed antenna is simulated, fabricated, measured and tested using WSN. The measured radiation (directivity = 3.9 dBi) is maximum at Ⴔ = 0° and Ⴔ = 90°. The frequency response of the antenna indicates a −10 dB fractional bandwidth of 380 MHz (2.24 GHz–2.62 GHz). The measured far‐field response shows a stable average gain of 3.9 dBi over the ISM band. The real‐time received signal strength indicator (RSSI) of the antenna installed in the sensor node observed a success rate of 79.46% with a transmission error of 10%. The observed response of an antenna makes it well‐suitable for WSN in industrial automation. [ABSTRACT FROM AUTHOR]

Summary This study presents a novel method for reducing return loss and achieving lower side lobe levels in small planar antenna arrays (PAAs). Quantum particle swarm optimisation (QPSO) findings are utilised for antenna design modelling and performance assessment utilising the MATLAB‐based moment's code approach and MATLAB‐HFSS interface. The mutual coupling between antenna components is considered and computed using the method of moments (MoM). Changing the array elements' length and spacing will accomplish the abovementioned objectives. The Matlab‐based moments code calculates the antenna components' length and spacing, and the antennas' length and spacing are used to produce the radiation pattern via the Matlab‐HFSS interface. Four examples of small PAA designs are given to illustrate how well the applied methodology works. The method discussed in this paper is generic and can be employed in the future for different sizes of the array elements and the different antenna array structure designs. [ABSTRACT FROM AUTHOR]

Summary: In this paper, we study the task offloading optimization problem in satellite edge computing environments to reduce the whole communication latency and energy consumption so as to enhance the offloading success rate. A three‐tier machine learning framework consisting of collaborative edge devices, edge data centers, and cloud data centers has been proposed to ensure an efficient task execution. To accomplish this goal, we also propose a Q‐learning‐based reinforcement learning offloading strategy in which both the time‐sensitive constraints and data requirements of the computation‐intensive tasks are taken into account. It enables various types of tasks to select the most suitable satellite nodes for the computing deployment. Simulation results show that our algorithm outperforms other baseline algorithms in terms of latency, energy consumption, and successful execution efficiency. [ABSTRACT FROM AUTHOR]

Summary: The cloud computing systems, such as the Internet of Things (IoT), are usually introduced with a three‐layer architecture (IoT‐Fog‐Cloud) for the task offloading that is a solution to compensate for resource constraints in these systems. Offloading at the right location is the most significant challenge in this field. It is more appropriate to offload tasks to fog than to cloud based on power and performance metrics, but its resources are more limited than the resources of the cloud. This paper tries to optimize these factors in the fog by specifying the number of usable servers in the fog. For this purpose, we model a fog computing system using the queueing theory. Furthermore, binary search and reinforcement learning algorithms are proposed to determine the minimum number of servers with the lowest power consumption. We evaluate the cost of the fog in different scenarios. By solving the model, we find that the proposed dispatching policy is very flexible and outperformed the known policies by up to 31% and in no case is it worse than either of them, and the overall offloading cost increases when fog rejects tasks with a high probability. Our offloading method is more effective than running all fog servers simultaneously, based on simulation results. It is evident from the similarities between the simulation results and those derived from the analytical method that the model and results are valid. [ABSTRACT FROM AUTHOR]