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With the gradual improvement of the future wireless communication technology, the demand for high information capacity and reliable links in communication systems is also ever-increasing. Programmable topological plasmonic metasurfaces, consisting of artificially engineered structures with robust propagation pathways control, have emerged as a revolutionary technology for stable microwave and on-chip communication systems. Programmable topological plasmonic metasurfaces offer unprecedented flexibility and adaptability in managing multiple communication channels as the propagation paths can be easily reconfigured to meet specific communication requirements. Here, we have experimentally demonstrated the ability to dynamically manipulate electromagnetic waves along eight distinct topological pathways for a multichannel direct communication system. The simulation results of topological plasmonic metasurfaces with different coding schemes have showcased their excellent performance in multichannel wavefront control. Experimental results have consistently aligned with the simulation findings, validating the effectiveness of multichannel topological routes. Furthermore, an eight-channel direct communication system based on a programmable topological plasmonic metasurface is designed and implemented to transmit different information. The proposed multichannel communication system based on a programmable topological plasmonic metasurface opens up new possibilities for high-capacity, efficient, and adaptive communication systems, which hold great potential in transformative applications in areas such as 6G, Internet of Things, and beyond. [ABSTRACT FROM AUTHOR]

Metasurfaces, due to their outstanding ability to control electromagnetic waves, have great application prospects in the field of wireless communication. This paper provides a comprehensive review of research work based on metasurface in three aspects: wireless power transfer, wireless information transmission, and novel wireless transceiver architectures. In the domain of wireless power transfer, several focusing metasurfaces and systems with unique performance are presented along with a new formula for calculating wireless power transfer. Concerning wireless information transmission section, the direct digital information transmission based on metasurface and the information transmission based on space-time-coding digital metasurface are introduced. Lastly, a simplified wireless transceiver with metasurfaces was introduced. The paper concludes with a discussion on the future directions of metasurfaces in the wireless communication domain. [ABSTRACT FROM AUTHOR]

The deployment of fifth-generation mobile network (5G), beyond 5G and sixth-generation mobile network platforms encounters challenges of blockage, interference, and path loss in radio mobile environments. Metasurfaces provide a promising solution to address these limitations. In this paper, we present a methodology for developing ultrathin flexible metasurface-based frequency selective surfaces (FSSs). Our approach combines thermal evaporation for metallic thin films with a macroscopic metasurface mask (something analogous to screen-printing but using thermal evaporation instead of inks). As a proof of concept, we fabricate a sub-6 GHz metasurface-based FSS using gold deposition on a flexible polyethylene terephthalate substrate. Experimental results are validated through numerical full-wave simulations using COMSOL Multiphysics and equivalent-circuit model simulations. The metasurface operates within the primary frequency band utilized in 5G networks (3–5 GHz), indicating its potential applicability across a wide range of flexible, conformal, and wearable devices. The fabricated FSS can be installed on surfaces of any shape, such as flat or curved windows, as well as on walls or other external surfaces. This methodology offers practical solutions for wireless communications and enhancing signal transmission in diverse environments. [ABSTRACT FROM AUTHOR]

Conventionally, in engineering, the stopband of periodic structures, where propagating signals are unable to penetrate them, was of little interest to engineers. However, with the advent of topological physics, this has changed, and the stopband has moved into the center of attention. Here, we study the behavior of magnetoinductive waves in the stopband of a diatomic line. Surprisingly, here, we find that for lines hosting topological edge states, the signal power at frequencies in the stopband can be higher than anywhere in the passband. Further, they may also exceed both the signal power and Shannon capacity of a conventional monoatomic line, making them of interest for application in wireless communication. [ABSTRACT FROM AUTHOR]

Summary: In this manuscript, optimized wireless communication for 6G signals processing using memory‐augmented deep unfolding network (WC‐6G‐SP‐MADUN) is proposed. The aim of this work is to give a memory‐augmented deep unfolding network approach with a focus on belief propagation decoding of error correction codes and multiple‐input multiple‐output (MIMO) wireless systems. In contrast, compares and tabulates the performance of memory‐augmented deep unfolding methodologies with classic principled procedures, which could potentially enable 6G. Here, the wireless communication for 6G signal processing methods was used for a variety of receiver functions, including self‐interference cancelation, signal estimation and detection using memory‐augmented deep unfolding Network (MADUN), and advanced error correction by clouded leopard optimization algorithm (CLOA). Furthermore, outline the general framework of memory‐augmented deep unfolding method for any kind of signal processing application and talk about cutting edge research paths that will make it possible to build communication networks in the future. The proposed approach is implemented in MATLAB; the performance is analyzed with performance metrics such as reliability, complexity, SNR gain, convergence rate, hardware efficiency, and quantization bit width. The proposed approach attains higher SNR gain 17.96%, 24.75%, and 30.09%; lower complexity 17.92%, 23.41%, and 30.13%; and higher convergence 18.01%, 25.41%, and 31.39% when analyzed with existing techniques such as redefined wireless communication for 6G: signal processing meets deep learning and deep unfolding (RWC‐6G‐SP‐DU), lower complication deep unfolded neural network receiver for MIMO under probability data association detector (LC‐DUNN‐MIMO‐PDAD), and deep learning in physical layer communications: evolution with prospects on 5G and 6G networks (DL‐PLC‐6G), respectively. [ABSTRACT FROM AUTHOR]

Summary Massive multiple‐input multiple‐output (MA‐MIMO) has been hailed as an auspicious technology for the future generation of wireless communications because it can considerably increase the capacity of the communication network. However, using the maximum likelihood (ML) direction‐of‐arrival (DOA) estimate method is severely constrained in actual systems because of the computationally expensive multi‐dimensional searching procedure. This paper proposes a novel approach to estimate DOA and channels by incorporating deep learning into the MA‐MIMO system. Here, a deep belief network (DBN) is used to learn both the spatial structures in the angle domain and the statistics of the wireless channel through both online and offline learning procedures. Also, a bald eagle search (BES) Optimization is used along with DBN to attain high precision through optimal training. The proposed model can estimate the channel based on the predicted DOA and the complex gain. According to numerical results, the suggested method performs significantly better than state‐of‐the‐art methods, particularly in tough conditions like low signal‐to‐noise ratio (SNR) and a finite number of snapshots. The proposed DBN‐BES technique accomplishes less root mean square error (RMSE) as 0.01 for SNR of 5 dB in elevation calculation and 0.02 for SNR of 5 dB in azimuth calculation. Also, the proposed algorithm greatly reduces computational complexity. [ABSTRACT FROM AUTHOR]

Triboelectric nanogenerators (TENGs) are effective in harvesting high‐entropy low‐frequency wave energy, yet traditional TENGs struggle to align with the meter‐scale wavelengths prevalent in marine environments, significantly impairing their wave energy conversion efficiency. Addressing this, the One Meter TENG (OM‐TENG) is introduced, a pioneering advancement in TENG design that extends the shell size to 1 m. This innovation features a novel lantern‐shaped stacked silicon‐manganese steel sheet configuration, optimizing internal space usage, and achieving a single‐cycle transfer charge of 60.82 µC and a friction layer area density of 1.76 cm−1. Furthermore, by integrating a segmented limiter device for rational control of different sliders, effective contact separation among numerous TENG units is realized. Comprehensive evaluations through theoretical analysis, multiphysics field numerical simulations, sensor data analytics, and comparative experimental measurements have unequivocally demonstrated OM‐TENG's superior capability in capturing meter‐scale wave energy under actual environmental conditions, alongside its remarkable anti‐capsize performance. Achieving peak outputs of 584 V and 444 µA, OM‐TENG can power 96 2 W LEDs and drive wireless communication modules, marking a significant step forward in the efficient utilization of wave energy and the design of large‐scale TENGs. [ABSTRACT FROM AUTHOR]

Summary Reconfigurable fractal antenna (RFA) design is always necessary for the continued development of wireless communication systems as the antenna is playing a vital part in device performance. The need for efficient radiators that are compact, low‐profile, inexpensive, and low weight has attracted scientists for their research works. As a result, numerous ideas were put forward by the researchers to attempt to resolve these problems by utilizing various kinds of fractal and reconfigurable antennas as well as their combinations. However, it is challenging to have a clear and transparent review of the various works with a large variety of solutions and their uniqueness. The advanced RFA design for wireless applications is reviewed in this study together with its most recent and pertinent counterparts. In Koch RFA, bandwidths enable selective bands spanning 1–6 GHz frequency range. Further, in band RFA design, the overall bandwidth ranges from 1.45 to 4.52 GHz (103%) with low gain; on the other hand, the crescent RFA achieves 5.67 dBi peak gain. Furthermore, in polarization RFA, the ARBWs are 17.61% (2.2–2.62 GHz) and 8.69% (2.91–3.18 GHz). The Hilbert RFA operates at 0.9 and 2.45 GHz with gains of 3.1 and 7 dBi, respectively. This article investigates a comprehensive review of the requirements for RFAs for wireless applications. Furthermore, a comparative study on different reconfigurability with switching techniques, fractal geometries, various RFA design approaches to enhance device performance, and their significance is discussed. Existing research challenges and future directions are also discussed as part of this article. [ABSTRACT FROM AUTHOR]

The 2D mesh topology-based Network-on-Chip (NoC) is a prevalent structure in System-on-Chip (SoC) designs, offering implementation and fabrication benefits. However, increased NoC scale leads to longer communication paths, more hops, and higher end-to-end latency and energy consumption. To mitigate these issues, Wireless NoC (WiNoC) integrates wireless communication, enhancing data rates, energy efficiency, and routing flexibility. Despite several mapping algorithms for NoCs, optimal techniques for hybrid WiNoCs are underexplored. This study proposes two novel application mapping methods for 2D mesh topology-based hybrid WiNoCs, using quadratic programming (QP) and simulated annealing (SA). Our goal is to minimize communication-related energy consumption. We evaluated these methods across various wireless router configurations, benchmarks, and custom application graphs. The QP-based method excels in smaller problems, while the SA-based approach yields optimal or near-optimal results for larger sizes within practical runtimes. [ABSTRACT FROM AUTHOR]

A good understanding of the behavior of the atmosphere is a key factor in radio wave propagation and link's design. This study investigated the influence of refractivity gradient, effective earth radius factor (k-factor) and geo-climatic factor (K-factor) on radio communication over the cities of Kaduna, Katsina and Sokoto, in Northwestern parts of Nigeria. Forty-one year's secondary data (1980–2020) of temperature, pressure and humidity at the surface 12, 100 and 250 m above ground level retrieved from European Centre for Medium-Range Weather Forecasts (ECMRWF) ERA-5 reanalysis were used for the study. The three secondary radio-climatic parameters under investigation were computed and analyzed using latest ITU-R (Rec.P.453-14 (08/2019)) Models. It was observed that secondary radio-climatic variables exhibit seasonal type dependence. The research also reveals that the secondary radio-climatic variables depend on location, with all the study locations having different values. The highest value of refractivity gradient obtained is about −75.06 (N-units / km) in the month of February in Sokoto while the least of about −162.65 (N-units/km) was recorded in Kaduna in September. The value of the refractivity gradient is higher during the dry season compared to the wet season months with Sokoto recording the highest values for more than half of the months, followed by Katsina. Kaduna recorded highest number of lowest values of refractivity gradient. For the geoclimatic factor, it was revealed that Kaduna has an average maximum geoclimatic factor of 14.0000E-5 in September and an average minimum of 9.6677E-05 in February. Furthermore, the obtained values of k factor values for the study areas are higher than the standard value of, 4 3 (1.33). The k-factor in Kaduna ranges from 1.69 to 2.16 with mean value of 1.85 for dry season while for the wet season it ranges from 2.66 to 4.12 with a mean value of 3.74; the overall mean value for Kaduna is 2.80. In Katsina, it ranges from 1.66 to 2.20 with mean value of 1.81 for dry season while for the wet season it ranges from 1.95 to 4.00 with a mean value of 3.27; the overall mean value is 2.54. In Sokoto it ranges from 1.60 to 2.30 with mean value of 1.78 for dry season while for the wet season it ranges from 1.72 to 3.45 with a mean value of 2.59; the overall mean value is 2.19. The interpretation of this is that, radio signal propagation in the Northwest region of Nigeria is super-refractive. The overall findings of this research are essential for estimating location-dependent fade margins, which are useful for the design of wireless communication links for the region. [ABSTRACT FROM AUTHOR]

Vectorial structured beam, which possesses diverse inhomogeneous spatial field distributions, has been developed into an advanced technology for particle trapping, optical communication, and quantum information. However, most of the related studies are based on static devices that can only generate structured light with fixed field distributions. To break through this restriction, the study proposes and experimentally demonstrates a reflection‐type spin‐independent programmable metasurface (SIPM) that can generate arbitrary vector vortex beams (VVBs) dynamically in microwave frequencies. By controlling the working states of loaded positive‐intrinsic‐negative (PIN) diodes, the metasurface can realize real‐time and spin‐independent manipulations of amplitude and phase of the reflected waves. Therefore, any desired VVBs can be achieved by dynamically controlling the superimposition of left‐ and right‐handed reflected circularly polarized vortexes. The proposed SIPM exhibits powerful abilities in modulating the vectorial structured beams in the microwave band, and may bring potential technological innovations for the future spintronics, imaging display, optical computing, and wireless communications. [ABSTRACT FROM AUTHOR]

In order to optimize the spectrum allocation strategy of existing wireless communication networks and improve information transmission efficiency and data transmission security, this study uses the independent correlation characteristics of chaotic time series to simulate the collection and control strategy of bees, and proposes an artificial bee colony algorithm based on uniform mapping and collaborative collection control. Furthermore, it proposes an artificial bee colony algorithm based on uniform mapping and collaborative collection and control. The method begins by establishing a composite system of uniformly distributed Chebyshev maps. In the neighborhood intervals where the nectar sources are firmly connected and relatively independent, the algorithm then conducts a chaotic traversal search. The research results demonstrated the great performance of the suggested algorithm in each test function as well as the positive effects of the optimization search. The network throughput rate was over 300 kbps, the quantity of security service eavesdropping was below 0.1, and the spectrum utilization rate of the algorithm-based allocation method could be enhanced to 0.8 at the most. Overall, the performance of the proposed algorithm outperformed the comparison algorithm, with high optimization accuracy and a significant amount of optimization. This is favorable for the efficient use of spectrum resources and the secure transmission of communication data, and it encourages the development of spectrum allocation technology in wireless communication networks. [ABSTRACT FROM AUTHOR]

Stretchable electronics have experienced remarkable progress, especially in sensors and wireless communication systems, attributed to their ability to conformably contact with rough or uneven surfaces. However, the development of complex, multifunctional, and high‐precision stretchable electronics faces substantial challenges, including instability at rigid‐soft interfaces and incompatibility with traditional high‐precision patterning technologies. Metallized electrospun nanofibers emerge as a promising conductive filler, offering exceptional stretchability, electrical conductivity, transparency, and compatibility with existing patterning technologies. Here, this review focuses on the fundamental properties, preparation processes, patterning technologies, and application scenarios of conductive stretchable composites based on metallized nanofibers. Initially, it introduces the fabrication processes of metallized electrospun nanofibers and their advantages over alternative materials. It then highlights recent progress in patterning technologies, including collector collection, vapor deposition with masks, and lithography, emphasizing their role in enhancing precision and integration. Furthermore, the review shows the broad applicability and potential influence of metallized electrospun nanofibers in various fields through their use in sensors, wireless systems, semiconductor devices, and intelligent healthcare solutions. Ultimately, this review seeks to spark further innovation and address the prevailing challenges in stretchable electronics, paving the way for future breakthroughs in this dynamic field. [ABSTRACT FROM AUTHOR]

Wireless Powered Communication Networks (WPCNs) represent a transformative approach to address the energy demands of mobile and Internet of Things (IoT) devices. By integrating Nonorthogonal Multiple Access (NOMA) and Intelligent Reflecting Surfaces (IRS), we can significantly enhance system performance, extend coverage, and elevate the sum rate. NOMA efficiently utilizes the entire bandwidth by employing a power allocation strategy, whereas IRS, serving as an alternative to traditional relay amplification, further bolsters the sum rate. Despite these advancements, optimizing the sum rate introduces a nonconvex optimization challenge, primarily owing to the signal‐to‐interference‐plus‐noise ratio (SINR) complexities introduced by NOMA's Successive Interference Cancellation (SIC). Traditional convex optimization solvers, such as the CVX, struggle to address nonconvexity directly. Consequently, they were unable to produce the desired outcome. Moreover, the combination of multiple technologies to improve the sum rate complicates the optimization framework, necessitating a multitude of constraints that not only heightens the mathematical complexity but also induces errors through the requisite approximations for convexity conversion. To circumvent these hurdles, we advocate the application of a minimum constrained nonlinear multivariable function (Fmincon). This approach enables us to tackle the nonconvex problem head‐on, maintaining consistent simulation parameters while limiting constraints to two pivotal factors: joint optimization of the transmit power ( PT$$ {P}_T $$) and transmit time ( Tx$$ {T}_x $$). This strategic simplification mitigates complexity and minimizes errors. Our numerical analyses confirmed the efficacy of the proposed model and optimization technique. By co‐optimizing the transmission power and time, we achieved a notable sum rate. Comparative evaluations with extant models underscored the superior performance of our proposed framework, marking a significant stride in WPCN advancement. [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: Devices in close proximity can directly communicate with each other through device‐to‐device (D2D) communication, bypassing the need for base stations. To minimize the delay for D2D active clients, we use a sequential approach to reuse cellular‐type resources. Unlike conventional methods that focus solely on uplink or downlink resource distribution, our study introduces a novel optimization technique to maximize network throughput. Our proposal incorporates a hybrid approach that combines both downlink and uplink techniques for resource allocation. We utilize random forest and game theory algorithms to ensure smooth D2D communication while reducing interference between cellular and D2D pairings. Our hybrid structure effectively addresses challenges arising from intra‐ and inter‐cell interferences resulting from spectrum reusability and deployment. This approach also improves power control and quality of service. Traditionally, NP‐hard optimization solutions are proposed for mixed‐integer nonlinear problems. In our study, the critical stages include channel assignment and energy allocation. The objective problem in resource allocation considers parameters such as the transmission power of D2D active clients, cellular users, connection distance, base stations, and quality of service constraints. Our proposed hybrid method aims to enhance overall spectrum efficiency and network throughput. Simulated results demonstrate the superiority of our modified hybrid technique compared to existing joint resource allocation methods. This comprehensive approach represents a significant advancement in addressing the complexities associated with D2D communication, offering improved efficiency and performance in contemporary network environments. [ABSTRACT FROM AUTHOR]

This paper employs the Sine Cosine Algorithm, a recent meta-heuristic method, to enhance the radiation properties of concentric elliptical antenna arrays in far-field applications, such as smart grid wireless communication and the Internet of Things. It focuses on minimizing the Sidelobe Level, a key parameter in antenna radiation, to mitigate unwanted signals and interference. The proposed method, known for its global optimization effectiveness, tackles the challenge of designing sparse multiple concentric elliptical arrays. By using the Sine Cosine Algorithm, the inter-element spacing and optimal determination of amplitude coefficients are achieved, resulting in a radiation pattern with reduced sidelobe level. To showcase the adaptability and superior performance of our proposed algorithm, we systematically evaluated its effectiveness across four distinct sets of concentric elliptical antenna arrays. These arrays comprise varying numbers of elements: (6, 12, 18 elements, 6, 12, 18, 24 elements, 6, 12, 18, 24, 30 elements and 6, 12, 18, 24, 30, 36 elements) with and without a central element. Using the sine cosine algorithm, we synthesize arrays and compare their sidelobe level and First Null Beam Width values with those from recent methods. Our findings consistently shows that the proposed algorithm consistently outperforms alternatives, yielding significantly lower sidelobe level values in all comparisons. [ABSTRACT FROM AUTHOR]

Summary The future wireless communication networks (beyond 5G) are intended to provide seamless connectivity, higher data rates, and lower latency. The intelligent reflecting surface (IRS) promises extended network coverage. The non‐orthogonal multiple access (NOMA) technique provides higher spectral efficiency and supports a larger number of users. In general, the cell‐edge users far from the base station are affected by severe fading, which may result in an outage. To overcome this issue, we propose an IRS‐aided device‐to‐device (D2D)‐enabled two cells coordinated NOMA system in which a common cell‐edge user acts as D2D receiver. The cell‐edge user receives the signals from near users, IRSs, and both base stations to achieve better diversity. We analyze the outage probability of cell‐edge user, while all the fading channels are assumed Nakagami‐ m$$ m $$ and obtain a closed‐form expression at higher signal‐to‐noise ratios. We develop an algorithm to find the ergodic capacity of the cell‐edge user. We validate the mathematical expressions with simulation results and see a substantial improvement in outage performance over the existing systems. [ABSTRACT FROM AUTHOR]

Summary The increasing prevalence of MIMO technology in wireless communication networks is attributed to its ability to augment system capacity and dependability. Consequently, there is a notable enthusiasm for the advancement and implementation of S‐band applications. Nevertheless, the mutual coupling between numerous antennas presents a crucial obstacle to MIMO system performance. This paper presents a novel technique that utilizes a defective ground structure with parasitic components to increase antenna isolation and gain. Additionally, an L‐shaped slot is incorporated into the patch element to enhance the antennas impedance bandwidth. Antennas are intentionally placed in a perpendicular arrangement to minimize the impact of the coupling effects. The antenna exhibits an impedance bandwidth in the frequency range of 2.62–2.79 GHz. Furthermore, the utilization of a four‐element MIMO antenna setup with a defective ground structure yields outstanding isolation properties, with values notably lower than −25 dB. To achieve an optimal MIMO performance, we assessed various diversity parameters, including diversity gain, channel capacity loss, total active reflection coefficient, and envelope correlation coefficient. The parameter values were within acceptable limits (ECC < 0.04, DG = 10 dB, TARC < 0 dB, and CCL < 0.1 bits/s/Hz). This research paper therefore offers essential insights into the design and optimization of MIMO antennas specifically for 2.7 GHz applications. [ABSTRACT FROM AUTHOR]

Summary Radio frequency (RF) energy harvesting (EH) for wireless networks provides a green and sustainable solution and offers an energy‐efficient system. It is most crucial for fulfilling the power requirement of the rising number of low‐powered wireless devices and achieving sustainable development goals (SDG). It ensures the longevity of devices in the network even at inaccessible remote locations. Such RF‐EH‐based mechanisms are utilized in simultaneous wireless information and power transfer (SWIPT) systems. Most of the prevailing studies have analyzed the SWIPT system over conventional fading channels. However, due to the higher rate requirements, the current paradigm shift in frequency usage shifts towards the GHz band, which also offers better EH efficiency. Hence, SWIPT system analysis over the channel that is suitable for mm‐wave signal propagation is dealt with in this study. This study evaluates SWIPT performance over fluctuating two‐ray (FTR) fading channel that is crucial since it provides the best fit for characterizing GHz signal and also provides a generalized framework for most of the conventional fading channels. This study presents new analytical results assuming time switch relaying (TSR) protocol with (i) amplify and forward (AF) and (ii) decode and forward (DF) relaying. The results are also analyzed for H branches maximal ratio combining (MRC) diversity technique and evaluated the diversity gain for both AF and DF relays. The effectiveness of the system is measured in terms of system outage probability (SOP) to envisage the reliability of SWIPT based system. This work presents the simulation and modeling of such system and its obtained results are validated by Monte Carlo simulations for their accuracy. [ABSTRACT FROM AUTHOR]

This paper presents an innovative deep-learning model for Automatic Modulation Classification (AMC) in wireless communication systems. The proposed architecture integrates Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) networks, augmented by a Gaussian noise layer to mitigate overfitting. The integration of both networks seeks to enhance classification accuracy and performance by leveraging the unique capabilities of CNNs and LSTMs in capturing spatial and temporal features, respectively. The model is expected to distinguish between eight digital and two analog modulation modes. Experimental evaluation on the RadioML2016.10b dataset demonstrates a peak recognition accuracy of 93.2% at 18 dB SNR. Comparative analyses validate the superior performance of the proposed architecture. The Gaussian noise layer contributes significantly to a 3% performance improvement at 18 dB SNR. The model achieves recognition accuracy exceeding 96% for most modulation modes, highlighting its robustness. Finally, computational complexity analysis underscores the efficiency of the proposed architecture, reinforcing its practical viability. [ABSTRACT FROM AUTHOR]

As a promising technology to achieve the permanent operation of battery-powered wireless sensor devices, wireless rechargeable sensor networks (WRSNs) by radio-frequency radiation have attracted considerable attention in recent years. Determining how to save the deployment cost of WRSNs has been a hot topic. Previous scholars have mainly studied the cost of deploying chargers, thus ignoring the impact of sensor deployment on the network. Therefore, we consider the new problem of joint deployment of sensors and chargers on a two-dimensional plane, i.e., deploying the minimum number of sensors and chargers used to monitor points of interest (PoIs). Considering the interaction of deployed sensors and chargers, we divide the problem into two stages, P1 and P2. P1 addresses the sensor deployment, while P2 addresses the deployment of chargers. Both P1 and P2 have proved to be NP-hard. Meanwhile, we notice that the aggregation effect of sensors can effectively reduce the number of chargers deployed; therefore, we propose a greedy heuristic approximate solution for deploying sensors by using the aggregation effect (GHDSAE). Then, a greedy heuristic (GH) solution and a particle swarm optimization (PSO) solution are proposed for P2. The time complexity of these solutions is analyzed. Finally, extensive simulation results show that the PSO solution can always reduce the number of chargers deployed based on the GHDSAE solution sensor deployment approach. Therefore, it is more cost-effective to jointly deploy sensors and chargers by using the GHDSAE solution and the PSO solution. [ABSTRACT FROM AUTHOR]

The exploiting of hybrid beamforming (HBF) in massive multiple-input multiple-output (MIMO) systems can enhance the system's sum rate while reducing power consumption and hardware costs. However, designing an effective hybrid beamformer is challenging, and interference between multiple users can negatively impact system performance. In this paper, we develop a scheme called Subset Optimization Algorithm-Hybrid Beamforming (SOA-HBF) that is based on the subset optimization algorithm (SOA), which effectively reduces inter-user interference by dividing the users set into subsets while optimizing the hybrid beamformer to maximize system capacity. To validate the proposed scheme, we constructed a system model that incorporates an intelligent reflecting surface (IRS) to address obstacles between the base station (BS) and the users set, enabling efficient wireless communication. Simulation results indicate that the proposed scheme outperforms the baseline by approximately 8.1% to 59.1% under identical system settings. Furthermore, the proposed scheme was applied to a classical BS–users set link without obstacles; the results show its effectiveness in both mmWave massive MIMO and IRS-assisted fully connected hybrid beamforming systems. [ABSTRACT FROM AUTHOR]

Next-generation communication systems demand the integration of sensing, communication, and power transfer (PT) capabilities, requiring high spectral efficiency, energy efficiency, and low cost while also necessitating robustness in high-speed scenarios. Integrated sensing and communication systems (ISACSs) exhibit the ability to simultaneously perform communication and sensing tasks using a single RF signal, while simultaneous wireless information and power transfer (SWIPT) systems can handle simultaneous information and energy transmission, and orthogonal time frequency space (OTFS) signals are adept at handling high Doppler scenarios. Combining the advantages of these three technologies, a novel cyclic prefix (CP) OTFS-based integrated simultaneous wireless sensing, communication, and power transfer system (ISWSCPTS) framework is proposed in this work. Within the ISWSCPTS, the CP-OTFS matched filter (MF)-based target detection and parameter estimation (MF-TDaPE) algorithm is proposed to endow the system with sensing capabilities. To enhance the system's sensing capability, a waveform design algorithm based on CP-OTFS ambiguity function shaping (AFS) is proposed, which is solved by an iterative method. Furthermore, to maximize the system's sensing performance under communication and PT quality of service (QoS) constraints, a semidefinite relaxation (SDR) beamforming design (SDR-BD) algorithm is proposed, which is solved using through the SDR technique. The simulation results demonstrate that the ISWSCPTS exhibits stronger parameter estimation performance in high-speed scenarios compared to orthogonal frequency division multiplexing (OFDM), the waveform designed by CP-OTFS AFS demonstrates superior interference resilience, and the beamforming designed by SDR-BD strikes a balance in the overall performance of the ISWSCPTS. [ABSTRACT FROM AUTHOR]

Emerging millimeter‐wave wireless communication systems require high‐performance radio frequency switches to support advanced functionality such as frequency agility, circuit reconfigurability, and beamforming. Ferroelectric (FE)‐gated AlGaN/GaN high‐electron‐mobility transistors (HEMTs) (FeHEMTs) are developed and demonstrated as a technology option for this important role. AlGaN/GaN HEMT heterostructures grown by metal‐organic chemical vapor deposition are augmented with a FE gate stack comprising atomic layer deposition‐grown HfZrO2. In addition, highly doped regrown source and drain Ohmic contacts are integrated into an improved fabrication process flow. This improved process leads to contact resistances of 0.105 Ω mm and a reduction in switch on‐resistance as compared to prior reports, as well as drain current densities of 1 A mm−1 and measured ft = 54 GHz for gate lengths of 0.1 μm. The improved contact and gate length scaling makes FeHEMTs a promising candidate for mm‐wave switch applications achieving a reported switch figure of merit of fCO = 1.55 THz. [ABSTRACT FROM AUTHOR]

Next‐generation "Beyond 5G (B5G)/6G" wireless network systems have been researched and developed for meeting the rapid growth of mobile traffic. A high‐yield fabrication process of InP‐based transistors and tera‐hertz monolithic integrated circuits with 300 GHz operation is reported, which is a candidate frequency for "Beyond 5G/6G" network systems. The main focus is on a high‐yield and reproductive fabrication process of InP‐based high electron mobility transistors (HEMTs) while revisiting previous studies. The DC and radio frequency characteristics of fabricated InP‐HEMTs from the viewpoint of integrating circuits are described. Then, high‐frequency performances of ft = 280 GHz and fmax = 860 GHz in the bias conditions of Vgs/Vds = 0.2/1.1 V with good uniformity are obtained. Finally, InP‐based 300 GHz‐band mixer and power amplifiers are introduced, to which a backside process is also applied for ensuring their stability and enhancing output power. [ABSTRACT FROM AUTHOR]

This letter presents experimental angularly resolved measurements and a model framework for characterizing continuous wideband reflection coefficients at sub‐terahertz frequencies between 92 and 110 GHz. Surfaces that appear "smooth" but with internal features comparable to the wavelength have shown to cause frequency selective scattering. An nth‐degree polynomial regression model is employed to quantify non‐linear multi‐path scattering that cannot be described by a best‐fit line, with least‐squares regression applied to find the best‐fitting polynomial and hence the coefficients. The obtained coefficients are then validated against the delay domain statistics of the propagation channel, demonstrating the proposed model's good agreement with measurements and its efficiency in reproducing angle‐dependent reflection coefficients for use in ray‐tracing tools. [ABSTRACT FROM AUTHOR]

Precoding is a critical signal processing technique used in wireless communication systems to enhance transmission performance. This paper initially provides a brief overview of various conventional precoding algorithms. The exploration includes various nonlinear precoding algorithms which outperform linear techniques in high signal-to-noise ratio (SNR) scenarios. Moreover, the paper delves into practical considerations and provides insights into selecting the most suitable technique for specific communication scenarios. The deep learning-based hybrid precoder is designed using the MDL-AltMin algorithm and simulated results show a spectral efficiency of (SE) 40.96 dB compared with different precoding algorithms. The precoder model is modified with a Hybrid Precoding Net algorithm with a spectral efficiency of 21.07 dB for high values of SNR such as −30 and again compared with deep learning precoders. The HPNet model is proposed with a spectral efficiency of 23.04 dB with and without CSI (Channel State Information) at the transmitter. Furthermore, the HPNet model is compared with optimal digital precoders. [ABSTRACT FROM AUTHOR]

The popularity of wireless communication technology and smart devices make emerging tasks tend to be computationally intensive. Unfortunately, mobile devices are often computationally resource-constrained. Mobile edge computing is proposed to offer computing power for these resource-limited devices to solve the computing requirement of their tasks. The unmanned aerial vehicle (UAV) enabled edge networks are flexible and low-cost, so they are considered to provide more flexible computing service for mobile devices. However, UAV-enabled edge networks are limited by the weak wireless propagation environment. To this end, we introduce intelligent reflecting surface (IRS) into the UAV-enabled edge networks in which IRS is used to construct a stronger link between the mobile devices and the UAV for task offloading. We formulate the IRS-aided offloading problem as an optimization problem to optimize the overall delay by jointly optimizing UAV movement, offloading decision, IRS configuration, and UAV's computation resource. To solve the problem more efficiently, we use the deep reinforcement learning (DRL) model to explore the intelligent action that can minimize the task processing time. Our simulation demonstrates the DRL scheme is more effective compared with the benchmarks. [ABSTRACT FROM AUTHOR]

In this paper, we compute the throughput of wireless communications using Reconfigurable Intelligent Surfaces (RIS) when the source harvests energy using a solar panel. Harvesting duration is also optimized to enhance the performance of wireless communications when RIS is used. We derive the statistics of the Signal to Noise Ratio (SNR). We show that the SNR is the product of a Gaussian and a chisquare random variables (r.v.). We consider solar energy harvesting for Rayleigh channels. [ABSTRACT FROM AUTHOR]

With the continuous maturity and adoption of mobile devices enabled by wireless communication technology, people are more apt to record their sport exercise data or healthcare data through various lightweight and smart devices, e.g., mobile phones and smart watches. Meanwhile, massive sport data or healthcare data keep being produced with time, which forms a main source of big healthcare data. Deep mining and analysis of such healthcare data are of positive significance for accurately recognizing the real-time health condition of mobile users and further recommend appropriate sport items to them. However, traditional centralized healthcare data mining and recommendation approaches require mobile users to transmit their health data collected by mobile devices to a remote cloud platform, which often involves heavy data transmissions from mobile devices to cloud platform. As a consequence, the transmission cost is high and the time delay is long. Moreover, long-distance data transmissions are prone to disclose user privacy. Considering these limitations, we bring forth a novel time-efficient and privacy-preserving healthcare data integration and mining approach for sport item recommendation, based on edge-cloud collaboration mechanism. At last, we design a group of simulation experiments to validate the effectiveness and efficiency of our approach. Experimental comparisons indicate a good balance between different evaluation metrics. [ABSTRACT FROM AUTHOR]

Electromagnetic fields unintentionally radiated from power-line communications used in factories interfere with wireless communications. It is important to distinguish the mechanism of this undesired and unintentional radiation from that of wired communication as it affects wireless communications. In particular, unintentional radiated emissions should be reduced in order to construct a stable wired/wireless communication network. This paper focuses on power-line communication as it is used in a factory. The power distribution network in the factory consists of multiple cables bundled together. The effects of cables other than the power cable that applies the communication signal to the radiated electromagnetic field are investigated. Some of the signal power reaching the reciever is converted into common-mode current by an imbalance mismatch. The common-mode current is one of the main causes of unwanted electromagnetic radiation. To predict this conversion, an imbalance difference model is created to account for multi-conductor transmission lines such as those in the power distribution network of the factory. The proposed model can calculate the amount of common-mode excitation associated with changes in the load condition of the power lines. To verify the proposed method, the authors measured the change in common-mode current due to the difference in pairs of power lines to which the signal is applied. The calculation using the proposed model could estimate the amount of reduction in common-mode current to within an error of 1 dB. [ABSTRACT FROM AUTHOR]

Nowadays, Optical Wireless Communications provide high data rates and minimal delay, making them ideal for real-time video and image applications in the Internet of Underwater Things (IoUT). However, Line-of-Sight (LOS) communication may not always be feasible due to misalignment, obstacles, or the random orientation of transceivers, especially for underwater sensor nodes or mobile users, to mitigate this challenge, a non-LOS (NLOS) link configuration is established. This paper conducts a feasibility study of communication links using a link budget approach to determine the feasible NLOS communication range for two types of transmitters: light emitting diode photo source (LED-PS) and laser diode photo source (LD-PS), at two wavelengths. A more realistic power link budget is developed. This paper examines the effects of underwater channel scattering and absorption, LED and LD-PS-based transmitters, and SiPM-PD-based receivers. In addition, it investigates how underwater environments, transmitter, and receiver parameters impact the communication link range. The effect of different water types on communication range was analyzed. Various transmitter parameters such as beam divergence angle and optical power, as well as receiver parameters such as incident angle and PD active area, were explored. The impact of different Lambertian order values was also assessed. The contribution of this paper is knowing the value of the received power used to determine the communication distance, this power is compared to the required receiver sensitivity, and the resulting link margin is used to determine the feasibility of the communication link. [ABSTRACT FROM AUTHOR]

Underwater Wireless Optical Communication (UWOC) offers a promising alternative to acoustic transmission methods, boasting reduced latency, increased data rates and smaller device sizes, with a focus on leveraging the underwater channel's optical spectra diversity for high-speed data services. Underwater signal propagation encounters absorption, turbulence and scattering, causing misalignment between optical transmitter and receiver due to turbulent water waves, degrading performance. In Point-to-Point UWOC, changes in beam divergence angle at the transmitting node disrupt links between underwater sensor nodes and maximize sensor battery usage. Therefore, this research work introduces the Efficient Deep Spiking Convolutional Neural Network with Graph Attention Layer (EDSCNN-GAL) that serves as a misalignment-robust blind receiver, utilizing convolutional layers, spatial-pooling layers and graph attention layers to extract and process features from received optical signals. Additionally, Multi scale Deep CapsNet (MD CapsNet) optimizes transmission power and beam divergence angle to sustain connections and minimize battery usage in underwater sensors. Enhanced walrus optimization is employed to efficiently optimize MD CapsNet parameters. The introduced model's efficacy is demonstrated through a comparison with state-of-the-art models, achieving better, throughput superior instantaneous signal to noise ratio (24 dB), lower misalignment probability (4%) and less transmission power (6.4 mW). [ABSTRACT FROM AUTHOR]

Wireless power transfer (WPT) refers to promising technology that allows energy transfer between devices without wires or cables. Although wireless power transfer systems have come a long way, they still have a long way to go before they become truly viable. An approach that has been offered to address these issues is the implementation of fractional‐order elements in WPT systems. Fractional‐order wireless power transfer systems have emerged as a promising solution to address some challenges in classical approaches. This review aims to provide a valuable resource for researchers and engineers interested in designing and optimizing WPT systems using fractional methods by summarizing the current knowledge on fractional‐based approaches in WPT. Furthermore, this article sheds light on the benefits, challenges, and prospects of integrating fractional elements into WPT strategies. [ABSTRACT FROM AUTHOR]