Search

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: 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: 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: 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 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: 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: 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: 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 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: 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]

Summary: Vehicular ad hoc networks (VANETs) are the ultimate solution for preventing road accidents, which result in the loss of precious human life worldwide. In this context, effective communication between the vehicular nodes is essential due to the varying network topology and high vehicular mobility inherent with VANETs. Cluster‐based routing is identified to be a significant approach for achieving efficient routing and improving communication proficiency in VANETs. In this paper, a beetle colony optimization algorithm–based clustering scheme (BCOACS) is proposed for generating optimized clusters for facilitating reliable data dissemination. This BCOACS algorithm includes two vital strategies such as beetle antenna search (BAS) and swarm intelligence for attaining inter‐cluster and intra‐cluster communications. In specific, BAS strategy that includes random search attributed toward gradient direction is used for intra‐cluster communication without using the complete amount of gradient information. On the other hand, a swarm intelligence strategy that encompasses a collective approach of self‐organized and decentralized agents is used for inter‐cluster communication with the view to minimize the load on each cluster head (CH) and to extend the clusters' lifetime. The simulation outcomes of the proposed BCOACS scheme confirmed improved performance in optimizing the number of constructed clusters independent of the increase in the network grid size, transmission range, and number of vehicular nodes in the network compared to the benchmarked approaches. The results also confirmed that the proposed BCOACS scheme achieved a maximized throughput of 13.42%, with reduced delay and protocol overhead of 18.96% and 19.45%, better than the benchmarked schemes used for investigation. [ABSTRACT FROM AUTHOR]

Summary: The unmanned aerial vehicle (UAV) coalition networks have been widely used in emergency mission scenarios. The introduction of the mobile edge computing (MEC) paradigm into multi‐coalition UAV networks further improves the mission processing performance of UAV coalitions. In this paper, we investigate the problem of minimizing total task processing delay of UAV members in MEC‐enabled coalition‐based UAV networks. First, we propose a hierarchical offloading model in which multiple UAV heads decide its position selection strategy and multiple UAV members decide its offloading strategy when offloading tasks to UAV heads. Considering data arrival from multiple UAV member nodes at each UAV head, the first come first served (FCFS) queuing model is introduced when the UAV head processes tasks from members. Second, the hierarchical offloading delay minimization problem is formulated as a multi‐leader multi‐follower Stackelberg game. The existence of a Stackelberg equilibrium (SE) is proved by showing that multi‐leader subgame and multi‐follower subgame are exact potential games (EPGs) with Nash equilibrium (NE). We design a best response‐based hierarchical iterative offloading algorithm to solve SE. Finally, the simulation results show that the performance of the proposed scheme is better than that of other benchmark methods and the proposed scheme can effectively reduce the total delay for all UAV members. [ABSTRACT FROM AUTHOR]

Summary: The non‐orthogonal multiple access (NOMA) wireless networks are a robust multi‐access mechanism that serves multiple clients accessing the same resource block simultaneously. The fifth‐generation wireless networks offer huge efficiency in spectrum utilization, which can be exploited to deploy NOMA for LOS communication of unmanned aerial vehicles (UAVs). Previous research has extensively analyzed various aspects of NOMA‐UAV communication systems, including user access fairness, coverage, maximizing system capacity, and total energy efficiency. However, only a few researchers have focused on maximizing the EE of NOMA‐UAV wireless networks with user quality of service (QoS) constraints. This paper proposes a fuzzy logic‐based crossover‐based coati optimization algorithm for maximizing the energy efficiency of NOMA‐UAV, along with user scheduling. The main objective of this model is to offer a solution to the joint energy efficiency and user QoS scheduling problem. The fuzzy decision‐making strategy optimizes the energy efficiency (EE) of NOMA‐UAV by selecting appropriate power and time resources. Additionally, the crossover‐based coati optimization algorithm transforms the subchannel allocation problem into a two‐sided matching procedure. The efficiency of the proposed algorithm is evaluated concerning overall residual energy, number of remaining nodes, and time consumption. The experimental outcomes demonstrate the capability of the proposed model in optimizing the energy efficiency of the NOMA‐UAV network by identifying the optimal resource set in terms of time and power while satisfying the clients' QoS. [ABSTRACT FROM AUTHOR]

Summary: There are numerous, interrelated, and multi‐dimensional aspects that influence a person's mental health, one of them being stress. Smart wearable technology having physiological and motion sensors has paved the way for real‐time data collection to deliver cutting‐edge information about the stress of individuals. It is now possible to build an Internet of Medical Things (IoMT) system that can recognise the user's stress, revealing the elements that cause stress. However, there are significant gaps in the existing system for stress recognition. To begin with, stress recognition is primarily studied for a specific set of people, such as occupational stress among office working persons or hospital staff during emergency duties, and so forth. Second, most past work on stress recognition has focused on extracting handcrafted traits, which necessitates human interaction and skill. To overcome above mentioned challenges, this work proposes a novel IoMT framework for continuous stress recognition for mental well‐being. This paper presents a hybrid deep learning (DL) approach for automatically retrieving features and classification into various stress states for the IoMT system to address these difficulties. The proposed expanded system gathers data from wearable physiological sensors and feeds it into a convolutional neural network–long short‐term memory (CNN‐LSTM), a hybrid DL classifier. The suggested approach has been tested on the wearable stress and affect detection (WESAD) dataset. It has a reported accuracy of 90.45%, which is higher than previously reported accuracies from existing machine learning (ML) and DL approaches. [ABSTRACT FROM AUTHOR]

Summary: This paper presents a near‐space communication system (NSCS) using advanced deployment strategies to gain high throughput. The airships are deployed according to the user's location, assuming robust backbone network characteristics such as signal path loss, fading factor, routing efficiency, and safety issues among bi‐connected airships. Due to the independent flying nature of airships, it is very attractive to deploy them as aerial base stations and construct airborne networks to provide service for on‐ground users. However, it is quite challenging to optimally deploy multiple airships for on‐demand coverage while maintaining the connectivity among airships. A balance between the network parameters, i.e., capacity and coverage area, should be maintained for optimal deployment of the airships. We have derived the maximum throughput of NSCS, including system parameters, as a multiobjective optimization problem subjected to efficient routing protocol and safety constraints. A decomposition‐based advanced multiobjective evolutionary algorithm (AMOEA/D) is adopted to solve the deployment optimization problem. The proposed algorithm is motivated by the non‐dominated solutions that maintain population diversity over the variable space. Two designed test problems, that is, the L‐shaped hotspot problem and nine hotspot problems, are also investigated. Numerical results show that the proposed method improves the system performance compared with benchmark external archive‐guided MOEA/D (EGA‐MOEA/D) and non‐dominated sorted genetic algorithms (NSGA‐II) by 10.46% and 3.84%, respectively. [ABSTRACT FROM AUTHOR]

Summary: Wireless sensor networks (WSNs) are frequently employed in the agriculture field to improve the quality and crop yield. The WSN might reduce the quality of the communication link because of the absorption, dispersion, and attenuation through the leaves of plants. Therefore, estimating the path loss due to signal attenuation before WSN deployment is crucial for the smooth operation of the network. In this research paper, three innovative path loss models are defined based on the MATLAB curve fitting tool: polynomial water cycle (PWC), exponential water cycle (EWC), and Gaussian water cycle (GWC) algorithm. Here, the path loss between the router node and the coordinator node is modeled on the basis of the received signal strength indicator (RSSI) and time of arrival (TOA) measurements in a sugarcane field. The correlation coefficient between the RSSI measurement and the distance must be increased to create a precise path loss model. This paper integrates the exponential, polynomial, and Gaussian functions with the water cycle algorithm (WCA) to evaluate the optimal coefficients that would lead to precise path loss models. The performance of the proposed models that determines the optimum linear fit between RSSI and distance is validated using the correction coefficient R2. The results show that the proposed path loss model is superior to existing path loss models. The correlation coefficient R2 of the proposed EWC model is 0.9993, whereas the existing PE‐PSO, LNSM, and PSO‐Exponential models yield 0.98, 0.87, and 0.93, respectively. Also, the proposed models attain the best mean absolute error (MAE) of 0.2187, 0.2951, and 0.3457 dBm for EWC, PWC, and GWC algorithms, respectively. [ABSTRACT FROM AUTHOR]

Summary: This paper investigates the performance of novel multicarrier index keying‐aided non‐orthogonal multiple access (MCIK‐NOMA) system. Unlike the classical scheme, the proposed system sends the information through both index domain and constellation domain symbols thereby increases the spectral efficiency. The impact of channel state information (CSI) uncertainty on the system's performance is investigated. More specifically, the performance of MCIK‐NOMA under three different CSI conditions is analyzed: perfect CSI, MMSE‐based variable CSI, and fixed CSI uncertainty. This paper also discusses the optimum power difference needed for the successful separation of symbols at the SIC receiver by alternating the power ratio in the proposed system. The influence of selecting different active subcarriers and modulation techniques on the system's performance is studied in detail. The simulation results show that the proposed system achieves better BER and spectral efficiency and outperforms the existing systems. [ABSTRACT FROM AUTHOR]

Summary: Underwater acoustic channel is a challenging medium for communication due to the presence of significant multipath, high noise, frequency‐dependent propagation loss, and high and non‐uniform Doppler spread. Doppler shift is non‐negligible in underwater communication due to the low velocity of underwater signals. Synchronization and Doppler estimation are important requirements for achieving good performance in this channel. Synchronization algorithms that give good performance in radio communication do not work well in underwater communication. Hence, this area has received a lot of attention from researchers. This paper surveys important works in the area. The techniques proposed in the literature for frame synchronization, frequency and phase synchronization, and timing synchronization in single carrier communications are reviewed here. The synchronization techniques proposed for OFDM, MIMO OFDM, and spread spectrum communication are also surveyed. Doppler estimation methods proposed in the literature are also reviewed. It is found that most of the recent works in underwater acoustic communication focus on OFDM synchronization. Deep learning‐based methods proposed in the literature are also reviewed. Key open problems and areas that require future research attention in the field of synchronization and Doppler estimation in underwater communications are highlighted in this paper. The area needing most attention of underwater communication researchers was found to be MIMO OFDM due to the difficulty in synchronization in such systems while used in underwater communication. Reducing the computational complexity of the algorithms used is also important for future work. Schemes that work with Doppler due to relative velocity over 10 m/s also need to be developed. [ABSTRACT FROM AUTHOR]

Summary: With the popularization of 6G‐driven wireless access networks and the development of edge computing, the connection between piano performance and artificial intelligence algorithms is getting closer and closer. 6G was first used to solve large‐capacity, short‐latency communication problems, and research results in this field abound. However, in practical applications, the deployment of 6G high‐frequency network is a major problem faced by the industry. This paper mainly studies the artificial robust cluster piano demonstration platform from the perspective of the fusion of 6G and edge computing. We firstly consider that the edge computing is a technology in which artificial intelligence algorithms are transplanted to edge devices and chips. The vision of the 6G network is to realize ubiquitous wireless intelligence, which includes three dimensions: mobile ultra‐broadband, super Internet of Things, and artificial intelligence, and realizes the conversion of piano scores into digital signals. Artificial Robust Clustering is a comprehensive technique that incorporates many disciplines, including phonetics, artificial intelligence, computer science, and more. This paper analyzes the fusion technology of 6G and edge computing and studies the robust cluster intelligent piano demonstration platform. The mentioned technologies are combined together to make the designed efficient. [ABSTRACT FROM AUTHOR]

Summary: This paper investigates the performance of a dual‐hop mixed relay system with radio frequency (RF) and free‐space optics (FSO) communication under the effect of pointing error (PE) and atmospheric turbulence (AT). This paper considers a system where RF and FSO links are cascaded. The RF link is modeled by Nakagami‐m fading, and the FSO link is modeled as gamma–gamma (G‐G) fading channel. Both the channel models use orthogonal frequency division multiplexing (OFDM) with M‐ary quadrature amplitude modulation (QAM). The expressions for probability density function, cumulative distribution function, signal‐to‐noise ratio, and ergodic capacity are derived. The moment generating function (MGF) of fading and the bit error rate (BER) of the OFDM‐based M‐ary QAM scheme is derived in terms of Meijer's G‐function. It has been observed that, in fixed gain relay systems, the modulation scheme's BER is dominated by the SNR of the RF link. While in a variable gain relay system, the turbulence conditions of the FSO system affect the SNR and the BER of the modulation method. The feasibility of heterodyne detection and intensity modulation direct detection (IM/DD) is analyzed in terms of outage probability and ergodic capacity. The results can be used to choose the optimal modulation order and relay system for QAM‐OFDM‐based optical wireless systems. [ABSTRACT FROM AUTHOR]

Summary: In this paper, the massive multiple‐input multiple‐output fractional Fourier transform‐based orthogonal frequency division multiplexing (MIMO FrFT‐OFDM) system is investigated using the Long Range (LoRa) modulation technique. The conventional system relies on quadrature amplitude modulated (QAM) modulation technology; high‐power amplifiers are needed to transmit the QAM signal. The LoRa modulation technique produces long‐range and low power signals. The two‐wave with diffused power (TWDP) fading channel is used to examine the system's performance. The expression of the bit‐error rate (BER) of the proposed system is also represented in a unique closed form. The proposed system is applied to a state‐of‐the art hospital, one of the Internet of Things (IoT) applications. As the problem of heart stroke is common, it needs to be monitored every second. The electrocardiogram (ECG) data are used to evaluate how well the proposed system is working. Using the proposed model, the physicians get the patient's ECG data while moving in the hospital, getting it at a high data rate, at a low cost because of the extended battery life, a long range, and a low BER. The data considered are from the MIT‐BIH Arrhythmia Database. The result displays that the proposed model achieves a BER of 0.0005 at 10 dB of signal‐to‐noise ratio (SNR), and the conventional model achieves the same BER at 15 dB of SNR. The BER performance of the proposed system is improved by nearly 5 dB. [ABSTRACT FROM AUTHOR]

Summary: Two fundamental aspects of wireless communication, which make it challenging and interesting, are fading and interference. Multiple input multiple output (MIMO) and orthogonal frequency division multiplexing (OFDM) techniques when utilized together effectively combat fading and interference thereby achieving the requirement of high data rate and high performance. In this paper, a 2 × 1 MIMO‐OFDM baseband model of the physical layer according to IEEE 802.16.1 standard employing 256 subcarriers capable of transmitting 192 Mbps in a 21‐MHz bandwidth frequency selective fading channel is designed. All essential blocks of the communication system like channel coding, modulation, time synchronization, frequency synchronization, channel estimation, residual carrier frequency offset (CFO) estimation, and channel decoding are covered at the algorithm level. A two‐step time synchronization method is used in this work to avoid any ambiguity in frame detection. A long preamble, consisting of three short preambles, is designed to aid in time synchronization, frequency synchronization, and channel estimation. To evaluate the performance of the proposed design, simulations were carried out in MATLAB‐SIMULINK. [ABSTRACT FROM AUTHOR]

Summary: Wireless sensor networks are an indispensable part of the present industrial and environmental scenario, with the everlasting challenges to increase network lifetime and reduce energy consumption. This paper presents an energy‐efficient adaptive clustering (EEAC) model, which is built upon the existing Low Energy Adaptive Clustering Hierarchy (LEACH) protocol with mobile sink and rendezvous nodes. The nodes are energy aware and participate in cluster head selection only if their current energy is higher than the average energy for the round. The idle nodes in the rendezvous region, which do not act as rendezvous nodes undergo clustering within themselves for the efficient routing of data. The EEAC inspires local clustering successfully conserves the energy of continuous long‐range transmission and enhances network lifetime. The proposed scheme proves to be remarkably better than the previous schemes, especially in large network cross‐sections. It improves alive nodes' performance for around 50% more rounds than the optimizing‐LEACH and the remaining energy curves improve around 500 rounds for 250 mx250 m network. For 350 mx350 m and 450 mx450 m networks, the results improved much in EEAC. In addition, the improvement in stability period is 450%, 578%, and 198% for the network cross‐section 150 mx150 m, 200 mx200m, and 250 mx250 m, respectively. [ABSTRACT FROM AUTHOR]

Summary: Unmanned aerial vehicle (UAV) path planning can be treated as a nondeterministic polynomial (NP) hard concern or an optimization problem. The conventional approaches are unable to effectively handle these issues due to discontinuity, non‐linearity, multi‐modality, and inseparability. On the other hand, meta‐heuristic algorithms are effective at tackling these issues because they are simple, adaptable, and derivation free. To enhance the performance in a variety of challenging circumstances, this paper proposes a novel Q‐learning‐based multi‐objective sheep flock optimizer with a Cauchy operator (Q‐MOSFO‐CA) to solve the constrained UAV path planning issues. The multi‐objective functions considered here are costs and constraints (threat, terrain, turning, climbing, and gliding constraints) to determine the feasible and optimal path. To avoid the probability of falling into the local optimum and to address the shortcoming of unbalanced convergence and also to maintain the exploitation and exploration capability, the Cauchy operator (CA) is integrated with the sheep flock optimization (SFO) algorithm. The Q‐learning model is introduced to balance both the global and local searches. Here, the exploration model performs the global search whereas the exploitation model performs the local search to attain an optimal solution. In the simulation scenario, the statistical analysis is conducted under two scenarios, and some essential measures such as the number of iterations at convergence (NIC), evaluation time (ET), energy consumption, and convergence analysis are determined. The proposed method obtains NIC of 1305 and 1436, ET of 12.8 and 15.2 s, and energy consumption of 20,600 and 21,465 J for both Scenarios 1 and 2, respectively. [ABSTRACT FROM AUTHOR]

Summary: The next‐generation networks are expected to support diverse latency‐sensitive services, that is, auto‐driving, telemedicine, and so on. Deploying these services in current hardware‐based networks faces significant challenges. The emergence of network function virtualization (NFV) and software defined network (SDN) makes network deployment flexible and agile. In order to meet the strict latency constraints, joint VNF deployment and resource allocation problems are needed. In this paper, we consider the resource‐delay interpendency and formulate the joint VNF deployment and resource allocation problems as linear programming (LP) problems. Discrete spider monkey optimization (DSMO) algorithm is proposed to solve this problem, which imitates spider monkeys' fission and fusion social behavior during foraging. The two‐phase decision update mechanism greatly increases the diversity of the spider monkey decision population and promotes the algorithm to perform a global search of the solution space. Evaluation results show that the proposed solutions achieve superior performance in terms of latency, CPU utilization and service acceptance rate. [ABSTRACT FROM AUTHOR]

Summary: This paper proposes a high‐selective crossover with a third‐order filtering characteristic, high passband isolation, and multiple controllable transmission zeros based on a coupled topology using single‐ and dual‐mode resonators. By virtue of the odd‐ and even‐mode feature of the stub‐loaded dual‐mode ring resonator, not only can the two resonant modes for different passbands be relatively independently controlled, but also better isolation can be achieved. With a single‐mode resonator and stub‐loaded dual‐mode resonant coupling topology, the resultant crossover can perform third‐order filtering performance in two distinct passbands/channels and generate several transmission zeros outside the desired bands to improve the isolation between the passbands. Experimental results demonstrate that, compared with conventional works, the filtering order of the proposed crossover is promoted and its passband isolation can be significantly improved by about 8 dB. The proposed work may facilitate its widespread applications in high‐performance multichannel integrated microwave systems for avoiding interference between multiple intersecting signal paths. [ABSTRACT FROM AUTHOR]

Summary: The demand for the Internet of Things (IoT) has significantly increased in the current scenario; specific sectors that require IoT include industrial automation, home control, health care applications, military and surveillance applications, habitat monitoring, and nanoscopic sensor applications. The use of optimal wireless sensor networks (WSNs) in transmission techniques has resulted in their involvement. A WSN is made up of thousands of randomly distributed sensor nodes that sense and transmit environmental data such as temperature, pressure, humidity, light, and sound. One of the most important requirements when using these sensor nodes is energy. As a result, it has become a major area of research in recent years; additionally, several design techniques and protocols have been presented in the last decade, particularly for IoT‐based applications. As a result, the systemization of an energy‐optimized WSN in dynamic functional conditions with automatic self‐configuration of sensor nodes is a critical goal. This paper proposed an opportunistic energy‐efficient dynamic self‐configuration routing (OEDSR) algorithm for IoT‐based applications. Initially, the optimal route to the base station (BS) is calculated by using the residual energy and mobility factor of the sensor nodes obtained through a routing tree model based on graph theory. To reduce the number of connections, an optimal path is determined based on dynamic cluster generation through a hierarchical tree architecture. Finally, the network‐related parameters, such as throughput, delay and packet delivery ratio (PDR), are compared with the peer existing routing protocols to depict the efficiency of the OEDSR protocol. [ABSTRACT FROM AUTHOR]

Summary: In this paper, we propose a reactive defragmentation with minimum spectrum route (RDMSR) for the problem of route, spectrum, and modulation‐format allocation (RSMA) in mixed grid optical network. In mixed grid network, spectrum redundancy and its assignment problem increase due to the spectrum continuity and contiguity constrains. In the proposed RDMSR strategy, process of defragmentation initiates after the termination of the existing connections. In addition, the route that needs minimum spectrum is given priority over the other available routes. The performance of the proposed strategy is compared with the two existing strategies: shortest path first (SPF) and mixed grid aware dynamic resources allocation (MDRA). Simulations are performed on NSFNET and ARPANET topologies. The existing and proposed strategies are evaluated on the metrics of bandwidth blocking probability (BBP), network capacity (NC), and average hops (AH) at three different combinations of the network traffic. Results show the proposed strategy outperforms than the other existing state of art strategies. [ABSTRACT FROM AUTHOR]

Summary: This paper proposes an IoT‐enabled soil monitoring system using wireless sensor network for automatic irrigation in agricultural applications, especially for lemongrass plants, where an automated control system is required for irrigation applications. This can solve the problem of the water crisis, which is faced by the farmers during the cultivation of the crop in the field. This controls the water supply in the irrigation process using an IoT communication system. A system architecture for soil monitoring and controlling irrigation using IoT technique is designed where the different sensors and actuators like humidity, soil moisture, temperature, pump, and so forth are connected with a node microcontrol unit and message queuing telemetry transport (MQTT) protocol for enhancing communication capabilities. This wireless sensor network gives feedback to the system. This provides automation by the on/off pump system during drip irrigation. The sensor data are displayed on a PC or mobile phone through wireless communication and an IoT cloud platform. An experimental testing setup is developed and the experimental performance of a soil monitoring system using IoT technique for automatic drip irrigation has been carried out and soil moisture data are also stored in a cloud server for analytics. The performance shows that the MQTT protocol sends data within 48 s to the IoT cloud so that the data can be acquired in a faster manner. This shows that this kind of soil monitoring system is suitable for automatic drip irrigation, which enhances the farming process and overcomes the water crises in the agricultural system by reducing the wastage of water. [ABSTRACT FROM AUTHOR]

Summary: An unmanned aerial vehicle (UAV)‐assisted communication is a promising technique for enabling ground users in a non‐functional area (NFA) or disaster area to communicate. All the base stations in the disaster area may be partially or fully damaged due to the natural calamity. Device‐to‐device (D2D) communication can be a viable solution for immediate connection between users in an NFA. We propose a UAV‐assisted multi‐hop D2D communication following a hybrid power‐time switching (PTS) in this paper. Moreover, a D2D user of a cluster can communicate with another D2D user in a different cluster through UAVs. However, D2D users can harvest energy from their respective ad hoc energy stations and forward the information to the nearby D2D user following a hybrid PTS‐based strategy. We propose a time frame for the same and show a node‐based energy harvesting strategy. The expressions of outage probability, throughput, end‐to‐end energy consumption, and energy efficiency are developed for the Rician and Nakagami‐m faded channel. The impact of several network parameters such as energy harvesting factor, energy harvesting efficiency, and fading parameter on the network performance is also indicated. [ABSTRACT FROM AUTHOR]

Summary: Developing a reliable and robust underwater acoustic communication system is a difficult task due to the complicated nature of the underwater channel, non‐stationary noise, and several other factors. Indeed, channel estimation or equalization presents numerous challenges in this non‐stationary, highly Doppler, multipath environment; as a result, traditional equalizers and PLL‐based methods have limited performance. Generally, communication over such time‐varying channels is accomplished via packets that contain a prefix/preamble signal for training, a payload containing the actual data, and a silent period for proper alignment. The prefix signal must be designed properly because it is used to estimate the channel and determine the start of the packet. In this paper, we propose a new prefix signal based on the hyperbolic chirp signal, which has Doppler invariance properties. These properties enable the extraction of the entire packet even under severe multipath and Doppler. Our new proposed prefix signal can accurately and efficiently characterize an underwater channel by estimating the multipath delay, amplitude, and Doppler scales. Our new method has been validated through extensive simulations using various channel models for its robustness and effectiveness under various conditions. It has also been tested on a real‐world channel. [ABSTRACT FROM AUTHOR]

Summary: A novel scheme for designing polar codes with specific decoding schemes in the additive white Gaussian noise channel is presented in this paper. The code construction strategy is built on the genetic algorithm (GA) where successive evolution of populations (or group of information sets) leads toward fittest candidate to attain finest error‐rates. In this work, it is shown that better error‐rates can be attained by both successive cancelation list decoding using GA with no cyclic redundancy check (CRC) and belief propagation decoding using GA with no CRC and no list, compared to existing polar decoding schemes. Our proposed polar code design scheme using GA has the ability to attain a target block error rates with the least possible SNR and using no additional CRC by exploiting least belief propagation iterations or lesser successive cancelation list list size with no self‐alterations in the decoding algorithm. [ABSTRACT FROM AUTHOR]

Summary: With the promotion and application of IPv6 in the world, there is a growing demand for IPv6 alias resolution. How to resolve IPv6 alias efficiently and accurately becomes an urgent problem to be solved. After analyzing the features of IPv6 addresses, this paper proposes a large‐scale adaptive IPv6 alias resolution method based on fingerprint information by combining Too‐Big Trick, UAv6, APD, and other alias resolution algorithms. It sends ICMPv6 probe packets to different types of IPv6 addresses to get the fingerprint information of target hosts. After filtering the classified addresses, our proposed alias resolution method is adaptively selected to resolve alias addresses. In the experiment, we use multi‐thread method to resolve the aliases of large‐scale IPv6 addresses, which greatly improves the efficiency of detection. Meanwhile, we use IPv6 datasets collected from the organizations RIPE and CAIDA. By comparing with Speedtrap and Too‐Big Trick, we confirm the accuracy of this method and obtain more alias pairs. [ABSTRACT FROM AUTHOR]

Summary: A miniaturized frequency‐selective surface (FSS) for radio frequency (RF) filtering applications is reported in this paper. The proposed FSS is designed to operate with band stop property at 1.57 GHz. The FSS element is developed using highly convoluted lines running on either side of the substrate interconnected using via lines. This specific arrangement increases the electrical length of the resonator without increasing the physical size. Furthermore, the stability towards polarization variation and independence to different angles of incidence are other major concerns in the design of FSS. The FSS unit cell has rotational symmetry thereby providing polarization‐independent operation. The angular independence is tested for various incidence angles, and the results are presented. The performance of the FSS is validated in real time, and the results are presented. The maximum realized transmission loss is 27 dB at 1.57 GHz, and the attenuation bandwidth with reference 10 dB shielding level is estimated to be 400 MHz centered around 1.57 GHz. The convolution technique along with shorting vias has offered this extreme miniaturization ranging from 7% to 95.7% with reference to most of the FSS reported for L‐band services such as radio, telecommunications, military, and aircraft surveillance. [ABSTRACT FROM AUTHOR]

Summary: Small cell networks can fulfill the increasing demandfor the high data rate of wireless applications. Energy efficiency is an important design parameter of the ultra dense small cell network (UDSCN). The sleeping strategy of small base stations (s‐BSs) is used to enhance the network's energy efficiency. An efficient sleeping strategy of s‐BSs is required while preserving users' quality of service (QoS). The idle s‐BSs can be switched to sleep mode. This paper proposes a blockchain‐enabled solution for the sleeping strategy of s‐BSs. Here, a blockchain‐enabled small cell network is created between the s‐BSs. The network is decentralized, which eliminates the workload of the macro base station (MBS). The proposed network architecture is enabled as a decentralized network through blockchain. The blockchain provides distributed control over the s‐BS operations through a smart contract. Here, smart contracts act as distributed self organizing network features to handle self‐transactions among small cells for switching off s‐BSs in the network. All the software logic required to perform s‐BS operations is written in a smart contract using Ethereum. The proposed solution improves energy efficiency and enables the ultra dense small cell network to be decentralized. [ABSTRACT FROM AUTHOR]

Summary: Clustering is an indispensable strategy that helps towards the extension of lifetime of each sensor nodes with energy stability in wireless sensor networks (WSNs). This clustering process aids in sustaining energy efficiency and extended network lifetime in sensitive and critical real‐life applications that include landslide monitoring and military applications. The dynamic characteristics of WSNs and several cluster configurations introduce challenge in the process of searching an ideal network structure, a herculean challenge. In this paper, Hybrid Chameleon Search and Remora Optimization Algorithm‐based Dynamic Clustering Method (HCSROA) is proposed for dynamic optimization of wireless sensor node clusters. It utilized the global searching process of Chameleon Search Algorithm for selecting potential cluster head (CH) selection with balanced trade‐off between intensification and extensification. It determines an ideal dynamic network structure based on factors that include quantity of nodes in the neighborhood, distance to sink, predictable energy utilization rate, and residual energy into account during the formulation of fitness function. It specifically achieved sink node mobility through the integration of the local searching capability of Improved Remora Optimization Algorithm for determining the optimal points of deployment over which the packets can be forwarded from the CH of the cluster to the sink node. This proposed HCSROA scheme compared in contrast to standard methods is identified to greatly prolong network lifetime by 29.21% and maintain energy stability by 25.64% in contrast to baseline protocols taken for investigation. [ABSTRACT FROM AUTHOR]