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Vehicle-to-everything (V2X) communication is essential in 5G and upcoming networks as it enables seamless interaction between vehicles and infrastructure, ensuring the reliable transmission of critical and time-sensitive data. Challenges like unstable communication in highly mobile vehicular networks, limited channel state information, high transmission overhead, and significant communication costs hinder vehicle-to-vehicle (V2V) communication. To tackle these issues, a unified approach utilizing distributed deep reinforcement learning is proposed to enhance the overall network performance while meeting the quality of service (QoS), latency, and rate requirements. Recognizing the complexity of this NP-hard, non-convex problem, a machine learning framework based on the Markov decision process (MDP) is adopted for a robust strategy. This framework facilitates the formulation of a reward function and the selection of optimal actions with certainty. Furthermore, a spectrum-based allocation framework employing multi-agent deep reinforcement learning (MADRL) is confidently introduced. The deep deterministic policy gradient (DDPG) within this framework enables the exchange of historical data globally during the primary learning phase, effectively removing the need for signal interaction and manual intervention in optimizing system efficiency. The data transmission policy follows an augmented online policy scheme, known as the proximal online policy scheme (POPS), which confidently reduces the computational complexity during the learning process. The complexity is marginally adjusted using the clipping substitute technique with assurance in the learning phase. Simulation results validate that the proposed method outperforms existing decentralized systems in achieving a higher average data transmission rate and ensuring quality of service (QoS) satisfaction confidently. [ABSTRACT FROM AUTHOR]

Vehicular ad hoc networks (VANET) are revolutionizing intelligent transportation systems (ITS), and as a result, research on their security is becoming increasingly important. As the primary security concern for VANET, authentication security is still quite difficult to achieve. Consequently, the prior knowledge of VANET is covered in this survey before outlining the primary security concerns. To set itself apart from previous surveys, this study suggests security properties and challenges among VANET. Next, the essential and significant features of a secure VANET system, such as confidentiality and integrity of data, and the availability of network systems have been reported, the authenticity of nodes and messages, and the refusal to deny data once it has been transmitted is detailed. Later, it outlined the requirement of the ITS which makes the survey unique. More importantly, the report on the most recent developments in VANET concentrates on the authentication schemes that have been proposed recently. The security features and authentication resistance against attacks, along with the overhead and efficiency of these schemes, are thoroughly examined and contrasted. A detailed analysis of V2V, V2I, and V2X authentication is been reported. Various cryptographic schemes have been discussed along with some advanced techniques such as Blockchain and hybrid schemes. An overview of the integration of 5G/6G networks is documented. Applications of VANET have been discussed in detail along with some open challenges in VANET. In summary, this work reviews a few lessons learned and explores different possibilities for future research. [ABSTRACT FROM AUTHOR]

An antenna array having a size of 45 40 cm2 (5.7 5 2) and consisting of four pairs of printed U-shaped dipoles positioned above a metal reflector, for 5G Sub-6 GHz base station applications, is designed and tested. The array consists of eight excitation ports, one port for each dipole. Four parasitic square patches are etched on the bottom side of the dipole arms for producing radiations in 2.2 GHz and 3.8 GHz bands. The size of the reflector and height of the dipoles are optimized in order to enhance antenna gain up to 11.5 dB at 2.2 GHz and 14.5 dB at 3.8 GHz. Beam steering up to 20 is achieved, using phase shifted simultaneous excitation of different ports. The proposed antenna array not only fulfills 5G base station requirements but is also simple and compact as it only requires eight ports to achieve dual-band, high-gain and beam steering operation in a single design. It also offers a unique feature of dual-sector coverage per panel, which results in an increased coverage capacity of the base station without increasing the system resources. [ABSTRACT FROM AUTHOR]

This paper proposes a novel decentralized federated reinforcement learning (DFRL) framework that integrates deep reinforcement learning (DRL) with decentralized federated learning (DFL). The DFRL framework boosts efficient virtual instance scaling in Mobile Edge Computing (MEC) environments for 5G core network automation. It enables multiple MECs to collaboratively optimize resource allocation without centralized data sharing. In this framework, DRL agents in each MEC make local scaling decisions and exchange model parameters with other MECs, rather than sharing raw data. To enhance robustness against malicious server attacks, we employ a committee mechanism that monitors the DFL process and ensures reliable aggregation of local gradients. Extensive simulations were conducted to evaluate the proposed framework, demonstrating its ability to maintain cost-effective resource usage while significantly reducing blocking rates across diverse traffic conditions. Furthermore, the framework demonstrated strong resilience against adversarial MEC nodes, ensuring reliable operation and efficient resource management. These results validate the framework's effectiveness in adaptive and efficient resource management, particularly in dynamic and varied network scenarios. [ABSTRACT FROM AUTHOR]

This study presents an advanced framework integrating LLAMA_V2, a large language model, into Open Radio Access Network (O-RAN) systems. The focus is on efficient network slicing for various services. Sensors in IoT devices generate continuous data streams, enabling resource allocation through O-RAN's dynamic slicing and LLAMA_V2's optimization. LLAMA_V2 was selected for its superior ability to capture complex network dynamics, surpassing traditional AI/ML models. The proposed method combines sophisticated mathematical models with optimization and interfacing techniques to address challenges in resource allocation and slicing. LLAMA_V2 enhances decision making by offering explanations for policy decisions within the O-RAN framework and forecasting future network conditions using a lightweight LSTM model. It outperforms baseline models in key metrics such as latency reduction, throughput improvement, and packet loss mitigation, making it a significant solution for 5G network applications in advanced industries. [ABSTRACT FROM AUTHOR]

This paper discusses a new symbol modulation scheme known as polarized amplitude and phase shift keying, (Pol$Pol$‐APSK) modulation with four rings in its basic form. The new scheme maps power‐polarized symbol pairs on its constellation in order to increase the number of data symbols. Pol$Pol$‐APSK exploits a symbol mapper based on a conjugate power splitting algorithm. Product modulation is applied, where a voltage signal of a specified amplitude and phase is multiplied by another current signal of a specified amplitude and phase, thus forming polymorphic signals in the product constellation. At the receiver, an isolated detection is performed, where the voltage signal is detected independently of the received current signal. A selection combining scheme is then used. The results depict unity peak‐to‐average power ratio and low average symbol energy, which is desirable for Green communications in 5G networks. It presents lower bit error rates when compared with the state‐of‐the art M$M$‐ary quadrature amplitude modulation, with a signal‐to‐noise ratio gap of at least 10[dB]$10\; [\text{dB}]$. The proposed analytical framework closely matches the simulations for bit error rates under M=16,32,64Pol-APSK$M=16,32,64 \ Pol\text{-APSK}$. [ABSTRACT FROM AUTHOR]

In order to meet the growing demands and extend network coverage for high‐speed railway (HSR) system, the dense deployment of a large number of small cells (SCs) is considered for 5G networks. However, the deployment of dense SCs and the high speed of trains result in challenging problems such as interference, frequent handovers (HOs), increased HO failure rate, and consequently the deteriorated overall quality of service (QoS). In order to address the challenges in handover, an improved handover decision strategy is proposed based on Support Vector Machine (SVM). The HO decision making is considered as a classification problem taking into account available states that they may have in the HSR network. From the simulation results, it is observed that the proposed scheme is capable of decreasing the number of HO, HO failure rate and enhancing the network performance remarkably. [ABSTRACT FROM AUTHOR]

In the realm of intelligent healthcare, there is a growing ambition to reshape medical services through the integration of artificial intelligence (AI). However, conventional machine learning faces inherent challenges such as privacy issues, delayed updates, and protracted training times, particularly due to the hesitance of medical institutions to directly share sensitive data, with possible noises. In response to these concerns, a Quantum-Assisted Federated Intelligent Diagnosis Algorithm (β -QuAFIDA) is proposed, applied into real medical data. Leveraging the capabilities of the 5G mobile network, this approach works the connection between Internet of Medical Things (IoMT) devices through the 5G, synchronizing training and updating the server model without disrupting their real-world applications. In our quest to safeguard patient data and enhance training efficiency, our study employs an innovative heuristic approach marked by a nested loop structure. Specifically, the inner loop is dedicated to training the beta-variational quantum eigensolver (β -VQE) to approximate the expectation values of the proposed algorithm; the outer loop trains the β -QuAFIDA to reduce the relative entropy towards the target. This approach involves a balance between privacy considerations and the urgency of training. Results demonstrate that representations with low-rank attained through β -QuAFIDA offer an effective approach for acquiring low-rank states. This research signifies a step forward in the synergy between AI and 5G technologies, presenting a novel avenue for the advancement of intelligent healthcare. [ABSTRACT FROM AUTHOR]

The diversification of network applications has become more comprehensive with the development of 5G mobile networks and Internet of things (IoT). Traditional intrusion detection system using rule-based anomaly technology is obviously insufficient for the changing network environment. Integrating the deep learning (DL) model can help intrusion detection system discover newly or unknown hacker's behavior. However, the quality of training dataset for DL is usually critical. If the dataset has not enough amount for training or is imbalanced for some kinds of attack categories, these situations may influence the detection accuracy. This paper aims to enhance the usage of dataset by dynamically adjusting the records of categories using Random Under-Sampling (RUS) and Generative Adversarial Network (GAN) models. The experiments show that the proposed approach has superior results in terms of the accuracy and some kinds of recall rates, compared to the evaluations of several previous studies. [ABSTRACT FROM AUTHOR]

The rapid evolution of mobile and optical communication technologies is driving the transition from 5G to 6G networks. This transition inevitably brings about changes in authentication scenarios, as new security demands emerge that go beyond the capabilities of existing frameworks. Therefore, it is necessary to address these evolving requirements and the associated key challenges: ensuring Perfect Forward Secrecy (PFS) to protect communications even if long-term keys are compromised and integrating Post-Quantum Cryptography (PQC) techniques to defend against the threats posed by quantum computing. These are essential for both radio and optical communications, which are foundational elements of future 6G infrastructures. The DMRN Protocol, introduced in 2022, represents a major advancement by offering both PFS and PQC while maintaining compatibility with existing 3rd Generation Partnership Project (3GPP) standards. Given the looming quantum-era challenges, it is imperative to analyze the protocol's security architecture through formal verification. Accordingly, we formally analyze the DMRN Protocol using SVO logic and ProVerif to assess its effectiveness in mitigating attack vectors, such as malicious or compromised serving networks (SNs) and home network (HN) masquerading. Our research found that the DMRN Protocol has vulnerabilities in key areas such as mutual authentication and key exchange. In light of these findings, our study provides critical insights into the design of secure and quantum-safe authentication protocols for the transition to 6G networks. Furthermore, by identifying the vulnerabilities in and discussing countermeasures to address the DMRN Protocol, this study lays the groundwork for the future standardization of secure 6G Authentication and Key Agreement protocols. [ABSTRACT FROM AUTHOR]

Drones integrated with 5G New Radio (NR) base stations have emerged as a promising solution for efficient victim search and localization in emergency zones where cellular networks are disrupted by natural disasters. Traditional approaches relying solely on uplink Sounding Reference Signal (SRS) for localization face limitations due to User Equipment (UE) power constraints. To overcome this, our paper introduces BWSAR, a novel three-stage Search-and-Rescue (SAR) methodology leveraging 5G-NR beam sweeping technologies. BWSAR utilizes downlink Synchronization Signal Block (SSB) for coarse-grained direction estimation, guiding the drone towards potential victim locations. Subsequently, finer-grained beam sweeping with Positioning Reference Signal (PRS) is employed within the identified direction, enabling precise three-dimensional UE coordinate estimation. Furthermore, we propose a trajectory optimization algorithm to expedite the drone's navigation to emergency areas. Simulation results underscore BWSAR's efficacy in reducing positioning errors and completing SAR missions swiftly, within minutes. [ABSTRACT FROM AUTHOR]

Fifth Generation (5G) cellular networks have been adopted worldwide since the rollout began around 2019. It brought with it many innovations and new services, such as Enhanced Mobile Broadband (eMBB), Ultra Reliable and Low-Latency Communications (URLLC), and Massive Internet of Things (mIoT). Furthermore, 5G introduced a more scalable approach to network operations using fully software-based Virtualized Network Functions (VNF) in Core Networks (CN) rather than the prior hardware-based approach. However, while this shift towards a fully software-based system design provides numerous significant benefits, such as increased interoperability, scalability, and cost-effectiveness, it also brings with it an increased cybersecurity risk. Security is crucial to maintaining trust between vendors, operators, and consumers. Cyberattacks are rapidly increasing in number and sophistication, and we are seeing a shift towards zero-trust approaches. This means that even communications between VNFs inside a 5G core must be scrutinized and hardened against attacks, especially with the advent of quantum computers. The National Institute of Standards and Technology (NIST), over the past 10 years, has led efforts to standardize post-quantum cryptography (PQC) to protect against quantum attacks. This paper covers a custom implementation of the open-source free5GC CN, to expand its HTTPS capabilities for VNFs by introducing PQC Key Encapsulation Methods (KEM) for Transport Layer Security (TLS) v1.3. This paper provides the details of this integration with a focus on the latency of different PQC KEMs in initial handshakes between VNFs, on packet size, and the implications in a 5G environment. This work also conducts a security comparison between the PQC-equipped free5GC and other open-source 5G CNs. The presented results indicate a negligible increase in UE connection setup duration and a small increase in connection setup data requirements, strongly indicating that PQC KEM's benefits far outweigh any downsides when integrated into 5G and 6G core services. To the best of our knowledge, this is the first work incorporating PQC into an open-source 5G core. Furthermore, the results from this effort demonstrate that employing PQC ciphers for securing VNF communications results in only a negligible impact on latency and bandwidth usage, thus demonstrating significant benefits to 5G cybersecurity. [ABSTRACT FROM AUTHOR]

This paper presents a Doherty power amplifier (DPA) integrated circuit (IC) designed to have enhanced gain, efficiency, and AM-AM characteristics through a dynamic power dividing technique, which can control the power dividing ratio according to the input power. Since this multi-purpose dynamic power dividing network also provides the phase offset and impedance matching at the interstage network needed for appropriate DPA operation, the active IC area could be reduced. To verify the proposed technique and its analysis, the DPA was implemented with a 28 nm bulk CMOS process for the fifth-generation (5G) new radio (NR) millimeter-wave frequency band of 23.5–27.5 GHz. The measured results showed a gain of 20.3–21.9 dB, saturated output power of 14.0–15.2 dBm, power added efficiency (PAE) of 22.8–26.7% at the peak power, and PAE of 14.6–17.6% at the 6 dB output power back-off (OBO). [ABSTRACT FROM AUTHOR]

Aiming at the engineering problem that 5G base station antenna is difficult to locate efficiently in complex electromagnetic environment, a two-stage positioning method of 5G base station antenna substation is proposed, which considers signal path loss and antenna RF radiation. Firstly, the path loss solution model of the 5G base station antenna signal in the substation is established, and the RF radiation solution model generated by the coupling excitation of 5G high-frequency electromagnetic wave and the metal shell of the electrical equipment is constructed based on the big element physical optics method. Secondly, combining the advantages of particle swarm optimization (PSO) and interior point algorithm, the antenna positioning method considering path loss and RF radiation is constructed. Among them, in the first stage, the minimum loss of 5G signal path in the substation is taken as the goal, and the antenna stations in the substation are searched globally to get the optimal pre-selected position. In the second stage, the antenna position is calibrated according to the pre-selected position, so that the interference of RF radiation is minimized, and the final position is output. Finally, a 500 kV 5G substation in Henan Province was taken as the simulation object. Compared with the original scheme, the simulation results ensured the minimum 5G path loss in the substation and took into account the electromagnetic compatibility of the equipment in the substation. The effectiveness of the location strategy for maintaining the safe operation of the substation is verified, and it can provide a reference for the 5G base station antenna positioning project of the substation. Article highlights: Considering the influence of 5G high-frequency electromagnetic wave on the electrical equipment in the substation, the positioning accuracy of 5G base station antenna in the substation is improved. The large area physical optics method can improve the calculation time and accuracy of radiofrequency radiation field intensity Combining the advantages of particle swarm optimization and interior point method, it can effectively avoid the problem of local optimal solution of location selection The simulation results show that the proposed method not only improves the location accuracy of 5G base station antennas in substations, but also applies to 5G base station antennas in more complex engineering environments [ABSTRACT FROM AUTHOR]

Wireless connections in 5G technology are driving the rapid growth of intelligent transport systems and vehicle communications. Wireless channels are impacted by weather, which is most noticeable in millimeter wave bands. This includes rain, fog, snow, sand, and dust. 5G networks now support diverse applications with speed and quality. In an effort to enable the use of millimeter wave frequencies, a recent study examined the impact of dust and sand on 5G channels. This paper examines the impact of heavy and frequent rainfall, along with horizontal polarization, on the propagation of millimeter waves in urban and highway settings. Using theoretical and optimization techniques, the effects of rainfall attenuation, path loss, and connection margin are evaluated at various millimeter wave frequencies. Dependencies on rainfall rate, path variation, and operating frequency are shown by the simulation results. In urban and highway situations, mean path loss and error statistics are examined with and without rainy attenuation. It is observed that the particle swarm optimization approach achieves 94% accuracy in signal propagation, which will enhance the path loss, received power, and overall system performance. [ABSTRACT FROM AUTHOR]

A compact UWB-MIMO antenna designed for sub-6 GHz, Ku-band, and millimeter-wave applications with UWB capabilities is proposed. The antenna design consists of two inverted L-shaped MIMO elements with slot etching, deliberately positioned on an FR-4 material substrate, measuring 36 × 18 × 1.6 mm³. Utilizing inverted L-shaped elements and prudently arranged slots on the substrate, the design achieves wideband characteristics. For enhanced isolation, interconnected rectangular slots with a fork shape are etched in the bottom layer, ensuring the isolation of less than -25 dB between ports. The proposed design exhibits an impedance bandwidth of approximately 54% within the frequency range of 3 GHz to 40 GHz, making it suitable for sub-6 GHz 5G bands, Ku-band, and millimeter-wave applications. The advantages of compactness and low profile of the proposed design are best suitable for 5G, Ku-band, and millimeter applications with UWB capabilities. The proposed design is successfully fabricated and tested. [ABSTRACT FROM AUTHOR]

Background: The safety of new‐generation mobile phones using 5G networks in patients with modern‐generation pacemakers has not been studied. Objectives: This study aimed to compare the risk of electromagnetic interference (EMI) generated by a new‐generation mobile phone with 5G networks when positioned at the pacemaker pocket or the contralateral ear and assess the incidence of EMI with telemetry interrogation in patients with permanent pacemakers. Methods: We enrolled 489 patients with pacemakers from three different manufacturers. The pacemaker mode was programmed for overdrive pacing and sensing mode if an intrinsic rhythm was present. A smartphone (Samsung S21 + 5G) was placed directly over the pulse generator and right ear. The phone was tested under standby mode, 5G internet connection, and incoming and outgoing calls for each location. Real‐time electrocardiography (ECG) monitoring and patient symptoms were recorded to determine the occurrence of EMI. The possibility of EMI with interrogation telemetry was also investigated. Results: A total of 4824 tests were performed on 489 patients. Most pacemakers were dual‐chamber (82%) or magnetic resonance imaging (MRI)‐compatible systems (83%). EMI was not detected with both mobile phone positions. Interference with telemetry was demonstrated in 11.5% of patients. Almost all incidences of interference (98.2%) occurred during incoming calls. Single‐chamber pacemakers, non‐MRI‐compatible systems, older pulse generators, older leads, and unipolar settings were significantly related to a higher incidence of interference with interrogation telemetry. Conclusions: The risk of EMI between modern smartphones with 5G networks and pacemakers is low. Nevertheless, interference with the interrogation telemetry may still occur. [ABSTRACT FROM AUTHOR]

Introduction: As 5G networks become widespread and their application scenarios expand, massive amounts of traffic data are continuously generated. Properly analyzing this data is crucial for enhancing 5G services. Methods: This paper uses the visibility graph method to convert 5G traffic data into a visibility graph network, conducting a feature analysis of the 5G traffic data. Using the AfreecaTV dataset as the research object, this paper constructs visibility networks at different scales and observes the evolution of degree distribution with varying data volumes. The paper employs the Hurst index to evaluate the 5G traffic network and uses community detection to study the networks converted from 5G traffic data of different applications. Results: Experimental results reveal significant differences in node degree distribution and topological structures of 5G traffic data across different application scenarios, such as star structures and multiple subnetwork structures. It is found that the node degree distribution of 5G traffic networks exhibits heterogeneity, reflecting the uneven growth of node degrees during network expansion. The Hurst index analysis discovers that the 5G traffic network retains the long-term dependence and trends of the original data. Through community detection, it is observed that networks converted from 5G traffic data of different applications exhibit diverse community structures, such as high centrality nodes, star-like community structures, modularity, and multilayer characteristics. Discussion: These findings indicate that 5G traffic networks in different application scenarios exhibit complex and diverse characteristics. The heterogeneity of node degree distribution and differences in topological structures reflect the imbalance in node connection methods during network expansion. The results of the Hurst index show that the 5G traffic network inherits the long-term dependence of the original data, providing a basis for analyzing the dynamic characteristics of the network. The diverse community structures reveal the inherent modularity and hierarchy of the network, which helps to understand the performance and optimization directions of 5G networks in different applications. [ABSTRACT FROM AUTHOR]

This work proposes a new hybrid bidirectional standard single mode fiber (SSMF)/free space optical (FSO) dual polarization quadrature amplitude modulation (DP‐QAM) employing optical orthogonal frequency division multiplexing (OFDM). An optical multicarrier generator (OMG) source is utilized. The suggested model is simulated using VPI photonics software. Thirty‐two optical OFDM channels are used; each carrier's 30 Gbps information data with DP‐QAM are employed to improve the performance of the fifth‐generation passive optical network (5G‐PON) for downstream and upstream transmission. In addition, 16‐QAM signals are used in DP. The impact of continuous wavelength (CW) lasers and high data rates in the proposed 5G‐PON has been investigated for DP‐QAM‐OFDM. The results reveal 0.96 Tb/s and 0.1 Tb/s for the downstream and upstream directions, respectively, under different turbulence effects. Furthermore, the simulation results show that the proposed model can achieve an SSMF length and FSO propagation ranges of 20 km and 2 km, respectively, with the symbol error rate (SER) (<10−9) and error vector magnitude (EVM) (<0.186). [ABSTRACT FROM AUTHOR]

The new or future communication systems require much higher flexibility and scalability to support diverse scenarios. In this paper, a high-throughput low-density parity-check (LDPC) decoder on graphics processing unit is presented to meet the flexible and scalable requirements. A memory-reduced forward/backward approach for the check node update is proposed. Moreover, elaborate on-chip memory allocations are conducted to improve memory bandwidth. The proposed (26112, 8448) 5G LDPC decoder on RTX4090 achieves 27.6 Gbps decoding throughput with five layered iterations, while the latency is less than 1 ms. Compared with related works, the throughput speedups obtained by the presented LDPC decoder are from 1.18 × to 12.4 × . [ABSTRACT FROM AUTHOR]

In this paper, we proposed the distributed quantization and sparsity aware zero attracting least mean square (DQA‐ZA‐LMS) and its reweighted version (DQA‐RZA‐LMS) algorithms that can perform sparse spectrum sensing with the lowest power possible. The usage of the quantization aware diffusion adaptive networks has recently been proposed and they can be used in many possible mobile communicative applications. The sparsity aware feature of the proposed algorithm can help the network to track and estimate sparse random vectors that are shown to be the case with the spectrum of the new generation wireless communication systems such as 4G, 5G, 6G, and beyond. The spectrum sensing is considered in this paper to be performed by small cell eNode Bs (SC‐eNBs) for the 4th generation long term evolution (LTE) and the next generation eNB (ng‐eNB) networks for the 5th and 6th generation mobile communication systems that are scattered in an area collecting distributed quantized data from the environment and working collaboratively to estimate the sparse spectrum vectors. Our findings show that in comparison with the nonquantized version of the distributed ZA‐LMS (DZA‐LMS) and distributed regularized ZA‐LMS (DRZA‐LMS) algorithms, our proposed schemes perform considerably well using the quantized data and also reduce power consumption. [ABSTRACT FROM AUTHOR]

As 5G and early‐stage network technologies mature, a wealth of data and experience is accumulated. The ubiquitous sensing and communication network (USCN) can leverage these existing communication infrastructures to maximize resource utilization and reduce the costs of redeployment through integration with modern 6G and beyond 6G networks. However, implementing future integrated sensing and communication (ISAC) functions in USCN may possess different hardware capabilities and communication protocols, presenting significant challenges. This is due to the lack of a unified framework for managing and optimizing these heterogeneous resources, as well as the absence of reasonable performance metrics. This letter proposes a dynamic pricing coordinated resource allocation (DPCRA) mechanism to realize the emerging ISAC in legacy USCNs. The DPCRA is designed to optimize the spectrum efficiency (SE) of USCN and manages resource interactions between heterogeneous devices through price variables, thereby resolving resource conflicts and deadlocks. The novelties include: (1) employing a price mechanism to foster resource cooperation in non‐cooperative networks; (2) introducing an SE metric incorporating an information similarity factor for optimization; (3) dynamically selecting resources to enhance SE. Simulations demonstrate that the DPCRA effectively resolves device deadlock while maintaining high SE levels, promoting device collaboration. [ABSTRACT FROM AUTHOR]

The ultra‐dense deployment of pico cells in 5G heterogeneous networks (HetNets) has raised serious concerns regarding interference and energy consumption. Both industry and academia are focusing on enhancing network energy efficiency (EE) while maintaining satisfactory quality of service (QoS) levels. However, finding an optimal solution to NEE is very challenging, especially in ultra‐dense HetNets. Here, a user association and power management algorithm is presented that follows a heuristic approach and aims to maximize EE while satisfying other network requirements. The proposed algorithm associates users based on criteria that consider the users' EE and minimizes energy consumption by intermittently switching into sleep mode base stations with the highest impact on overall network EE. The performance of this solution is evaluated in a realistic multi‐cell two‐tier scenario considering both co‐tier and cross‐tier interference by comparing it with two other solutions: a heuristic approach based on standardized eICIC, and an optimization approach based on Lagrangian dual decomposition. The simulation results show that our solution outperforms benchmarking solutions in terms of EE, average user rate, and network throughput while minimizing energy consumption. [ABSTRACT FROM AUTHOR]

This study analyses the interference effect in a visible light‐non‐orthogonal multiple access (VL‐NOMA) network that considers the signal power parameters performance for near and far users. The light‐emitting diode (LED) as a carrier transmits signals, and we investigate the interference effect. The interference effect challenge is a result of unaligned signal power parameters, thereby producing noise or echo during the signal transmission. The signal power parameters are successfully aligned, and NOMA techniques are deployed, which improves the signal performance in terms of bit‐error rate (BER), achieved data rate, and signal‐to‐interference plus noise ratio (SINR). Furthermore, the deployed NOMA techniques, such as power allocations (PA) to assign the signals appropriately, then superposition coding (SC) encodes the entire signal, and successive interference cancellation (SIC) cancels the interference within the signals. The signal behavior of the aligned and the unaligned signal power parameters performance are used to investigate the interference effect. We observed that unaligned signal power parameters reduce the signal performance of achieved data rate, BER, and SINR. Further, the aligned signal power parameter with NOMA techniques improves the signal performance. Moreover, in the aligned signal power scenario of NOMA, the near user performed better than the far user. [ABSTRACT FROM AUTHOR]

Following the global progressive deployment of 5G networks, considerable attention has focused on assessing their potential impact on human health. This study aims to investigate autonomous nervous system changes by exploring skin temperature and electrodermal activity (EDA) among 44 healthy young individuals of both sexes during and after exposure to 3.5 GHz antenna‐emitted signals, with an electrical field intensity ranging from 1 to 2 V/m. The study employed a randomized, cross‐over design with triple‐blinding, encompassing both ‘real’ and ‘sham’ exposure sessions, separated by a maximum interval of 1 week. Each session comprised baseline, exposure and postexposure phases, resulting in the acquisition of seven runs. Each run initiated with a 150 s segment of EDA recordings stimulated by 10 repeated beeps. Subsequently, the collected data underwent continuous decomposition analysis, generating specific indicators assessed alongside standard metrics such as trough‐to‐peak measurements, global skin conductance and maximum positive peak deflection. Additionally, non‐invasive, real‐time skin temperature measurements were conducted to evaluate specific anatomical points (hand, head and neck). The study suggests that exposure to 3.5 GHz signals may potentially affect head and neck temperature, indicating a slight increase in this parameter. Furthermore, there was a minimal modulation of certain electrodermal metrics after the exposure, suggesting a potentially faster physiological response to auditory stimulation. However, while the results are significant, they remain within the normal physiological range and could be a consequence of an uncontrolled variable. Given the preliminary nature of this pilot study, further research is needed to confirm the effects of 5G exposure. [ABSTRACT FROM AUTHOR]

This paper introduces a new method for estimating the maximum Doppler shift using decision feedback channel estimation (DFCE). In highly mobile environments, which are expected to be covered beyond 5G and 6G systems, the relative movement between the transmitter and receiver causes Doppler shifts. This leads to inter-carrier interference (ICI), significantly degrading communication quality. To mitigate this effect, systems that estimate the maximum Doppler shift and adaptively adjust communication parameters have been extensively studied. One of the most promising methods for maximum Doppler shift estimation involves inserting pilot signals at both the beginning and end of the packet. Although this method achieves high estimation accuracy, it introduces significant latency due to the insertion of the pilot signal at the packet's end. To address this issue, this paper proposes a new method for rapid estimation using DFCE. The proposed approach compensates for faded signals using channel state information obtained from decision feedback. By treating the compensated signal as a reference, the Doppler shift can be accurately estimated without the need for pilot signals at the end of the packet. This method not only maintains high estimation accuracy but also significantly reduces the latency associated with conventional techniques, making it well-suited for the requirements of next-generation communication systems. [ABSTRACT FROM AUTHOR]

This study introduces distance metrics for quantized-channel-based precoding in multiuser multiantenna systems, aiming to enhance spectral efficiency in dense cellular networks. Traditional metrics, such as the chordal distance, face limitations when dealing with scenarios involving limited feedback and multiple receive antennas. We address these challenges by developing distance measures that more accurately reflect network conditions, including the impact of intercell interference. Our distance measures are specifically designed to approximate the instantaneous rate of each user by estimating the unknown components during the quantization stage. This approach enables the associated users to efficiently estimate their achievable rates during the quantization process. Our distance measures are specifically designed for block diagonalization precoding, a method known for its computational efficiency and strong performance in multi-user multiple-input and multiple-output systems. The proposed metrics outperform conventional distance measures, particularly in environments where feedback resources are constrained, as is often the case in 5G and emerging 6G networks. The enhancements are especially significant in dense cellular networks, where accurate channel state information is critical for maintaining high spectral efficiency. Our findings suggest that these new distance measures offer a robust solution for improving the performance of limited-feedback-based precoding in cellular networks. [ABSTRACT FROM AUTHOR]

The study investigates the feasibility of utilizing 5G and its future iterations (B5G) networks for the transmission of multi-sensory data, including audio, visual, haptic, olfactory, and gustatory data. The advent of 5G and B5G technologies has enabled the transmission of a wide range of sensory information in real-time or near real-time, thanks to their exceptional speed, low latency, and large capacity. The idea behind this review is to explore the technological developments that facilitate the transmission of data, such as layered protocols. This article aims to provide an overall survey and use cases for sensory data transmitted using 5G and B5G networks. The objective of this survey is to focus on challenges for multiple sensor data transmission using 5G and beyond network technologies, as well as how significant is to receive this information without losing them. Moreover, it tackles the inherent difficulties associated with guaranteeing adequate bandwidth, minimal latency, high quality of service, and robust security for the transmission of multi-sensory data via wireless networks. The goal is to provide an introductory overview for researchers, engineers, and practitioners who are interested in exploiting 5G and B5G networks to leverage the revolutionary capabilities of multi-sensory data transmission. The future scope at the end also highlights how to add enhancement in this field. [ABSTRACT FROM AUTHOR]

The rapid developments of 5G and B5G networks have posed higher demands on retransmission in certain scenarios. This article reviews classical finite-length coding performance prediction formulas and proposes rate prediction formulas for coded modulation retransmission scenarios. Specifically, we demonstrate that a recently proposed model for correcting these prediction formulas also exhibits high accuracy in coded modulation retransmissions. To enhance the generality of this model, we introduce a range variable P final to unify the predictions with different SNRs. Finally, based on simulation results, the article puts forth recommendations specific to retransmission with a high spectral efficiency. [ABSTRACT FROM AUTHOR]

Wireless hierarchical federated learning (WHFL) is an implementation of wireless federated Learning (WFL) on a cloud–edge–client hierarchical architecture that accelerates model training and achieves more favorable trade-offs between communication and computation. However, due to the broadcast nature of wireless communication, the WHFL is susceptible to eavesdropping during the training process. Apart from this, recently ultra-reliable and low-latency communication (URLLC) has received much attention since it serves as a critical communication service in current 5G and upcoming 6G, and this motivates us to study the URLLC-WHFL in the presence of physical layer security (PLS) issue. In this paper, we propose a secure finite block-length (FBL) approach for the multi-antenna URLLC-WHFL, and characterize the relationship between privacy, utility, and PLS of the proposed scheme. Simulation results show that when the eavesdropper's CSI is perfectly known by the edge server, our proposed FBL approach not only almost achieves perfect secrecy but also does not affect learning performance, and further shows the robustness of our schemes against imperfect CSI of the eavesdropper's channel. This paper provides a new method for the URLLC-WHFL in the presence of PLS. [ABSTRACT FROM AUTHOR]

Positioning service is a critical technology that bridges the physical world with digital information, significantly enhancing efficiency and convenience in life and work. The evolution of 5G technology has proven that positioning services are integral components of current and future cellular networks. However, positioning accuracy is hindered by non-line-of-sight (NLoS) propagation, which severely affects the measurements of angles and delays. In this study, we introduced a deep autoencoding channel transform-generative adversarial network model that utilizes line-of-sight (LoS) samples as a singular category training set to fully extract the latent features of LoS, ultimately employing a discriminator as an NLoS identifier. We validated the proposed model in 5G indoor and indoor factory (dense clutter, low base station) scenarios by assessing its generalization capability across different scenarios. The results indicate that, compared to the state-of-the-art method, the proposed model markedly diminished the utilization of device resources and achieved a 2.15% higher area under the curve while reducing computing time by 12.6%. This approach holds promise for deployment in future positioning terminals to achieve superior localization precision, catering to commercial and industrial Internet of Things applications. [ABSTRACT FROM AUTHOR]

An air-filled substrate-integrated waveguide (AF-SIW) circularly polarized (CP) 1 × 8 mm wave antenna array is presented for fifth-generation (5G) applications. The presented slot antenna array consists of three layers of PCB and one layer of aluminum, which serve as the AF-SIW feeding network and the metal cavity radiation element, respectively. The CP characteristic is achieved by the use of an S-shaped aluminum radiation cavity on the top of the AF-SIW feeding network. The air-filled substrate-integrated waveguide technique is unitized to achieve high radiation efficiency. A wide input impedance bandwidth of 18.4% is obtained for the proposed antenna scheme, ranging from 34.5 GHz to 41.5 GHz, with a peak gain of 18 dBic. As for CP characteristic, the proposed antenna possesses a wide 3 dB axial ratio (AR) bandwidth, which is 16.4% (36.5 GHz to 43 GHz). The antenna scheme is fabricated and measured to verify the potential application as well as the promising performance. The measured results of the 1 × 8 antenna array shows that the wide AR as well as the input impedance are simultaneously achieved, which coincide well with the simulated results. Also, the measured results indicate that the proposed antenna scheme might be a good candidate for future mobile applications. [ABSTRACT FROM AUTHOR]

In mobile communication networks for integrated sensing and communication, site planning of access points fundamentally determines both communication quality and sensing performance. This paper aims to tackle the AP placement problem under the setting of cell‐free massive multiple‐input multiple‐output, which represents a promising direction for network architecture evolution. Seeking a balance between the sum‐throughput of communication and the Cramér–Rao lower bound of target sensing, the access points are first pre‐placed by solving a convex optimization and further adjusted with optimal angular geometry. The final step involves employing nearest neighbour projection to refine access point positions in the cell‐free massive multiple‐input multiple‐output system, ensuring alignment with integrated sensing and communication requirements. The numerical results show that the proposed algorithm achieves 90% of the optimal communication sum‐rate and 95% of the optimal target localization accuracy. [ABSTRACT FROM AUTHOR]

The transition towards the fifth generation (5G) of communication systems has been fueled by the need for compact, high-speed and wide-bandwidth systems. These advancements necessitate the development of novel and highly efficient antenna designs characterized by the compact size. In this paper, a novel antenna design with a hexagonal-shaped resonating element and two U-shaped open-ended stubs is presented. Millimeter-wave (mmWave) frequency range suffers from attenuation due to atmosphere and path loss because of higher frequencies. To address these issues, the deployment of a high-gain antenna is imperative. This design is created through an evolutionary process to work best in the mmWave frequency range with a high gain. A thin Rogers RT5880 substrate with a thickness of 0. 254 mm, a dielectric constant of 2. 3 and a loss tangent of 0. 000 9 supports the copper-based radiating element. A partial ground plane with a square slot and trimmed corners at the bottom enhances the antenna's bandwidth. The single-element antenna exhibits a wide bandwidth of nearly 6 GHz and a gain of 4. 58 dBi. By employing the proposed antenna array, the antenna gain is significantly enhanced to 14. 90 dBi while maintaining an ultra-compact size of 24 mm × 46 mm at the resonant frequency of 31 GHz. The antenna demonstrates a wider impedance bandwidth of 15. 73% (28 - 34 GHz) and an efficiency of 94%. The proposed design works well for 5G communication and satellite communication, because it has a simple planar structure and focused dual-beam radiation patterns from a simple feeding network. [ABSTRACT FROM AUTHOR]

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Millimetre-waves (mmWaves), a critical part of 5G, have not been extensively studied in the sub-Saharan tropical environment. This study was conducted to model the outdoor propagation path loss of mmWaves in four Nigerian cities at 28, 38, 60, and 73 GHz for 5G mobile systems: Abuja, Lagos, Ibadan, and Port Harcourt. The study utilised simulation data from a Composite Raytracing-Image-Method propagation model in MATLAB 2023a with OpenStreetMap 3D building maps to formulate the Close-In free-space Reference Distance (CI), Floating Intercept (FI), and Alpha–Beta-Gamma (ABG) large-scale path loss models. This model considered the specific atmospheric conditions, terrain, building materials and structures, and geographical layouts of each site. The study found that the path loss exponent ranged from 2.712 to 3.819 in line-of-sight scenarios, with shadow fading standard deviation (σCI) ranging from 11.778 to 37.199. In non-line-of-sight scenarios, the path loss exponent ranged from 3.375 to 5.033, with σCI ranging from 12.441 to 44.181 across the four frequencies studied. The ABG model consistently provided the most accurate predictions compared to CI and FI, particularly the mean absolute error and root mean square error values. However, performance varied across cities, frequencies, and scenarios, with Port Harcourt exhibiting the highest path loss values across all frequencies and scenarios, followed by Lagos. Furthermore, the omnidirectional large-scale path loss increases marginally as the frequency increases, except at 60 GHz, which had a higher path loss per distance than 73 GHz. Finally, the findings showed that the propagation characteristics of mmWaves for 5G networks in sub-Saharan tropical environments, such as Nigeria, exhibit significant variability based on factors such as atmospheric conditions, terrain, building materials, and geographical layouts. The formulated path loss models can be used to predict the coverage area and signal quality of millimetre-wave communication systems at these frequencies and locations. Article Highlights: Millimetre-waves path loss in Nigerian cities varies significantly with frequency, environmental and structural factors. Path loss increases with frequency, but 60 GHz suffers more loss over distance than 73 GHz due to oxygen absorption. The ABG path loss model outperforms others, providing more accurate predictions for sub-Saharan tropical environments. [ABSTRACT FROM AUTHOR]

Aiming at the problems of traditional ship cold chain monitoring systems being easily affected by environmental factors, difficult to achieve real‐time monitoring in the open sea without network signals, and low efficiency in transmitting Beidou short message data, a multi‐link compressed transmission ship cold chain monitoring system was designed by combining 5G technology, Beidou short message transmission technology, and multi‐protocol transmission technology. The system can adaptively switch the strength of wireless signals to ensure that information transmission is not lost. At the same time, a Beidou short message compressed transmission method was proposed to improve transmission efficiency. Test results show that the system can accurately complete data collection and processing, with small system errors, effectively improving the reliability and efficiency of the monitoring system, and has high application value. [ABSTRACT FROM AUTHOR]

[Purpose] The debate over Net Neutrality (NN) that dominated discussion in the domain of Internet and telecommunications for over two decades, has largely been settled in favour of the principle of an open, non-discriminatory regime for all traffic travelling over networks. The rapid commercialisation of 5G mobile telecom technologies in telecom markets, however, draws regulatory attention once again, to aspects of NN regimes in apparent conflict with the requirements of the new technology. The emerging discussion has prompted reviews of NN policies in many countries. [Methodology] This paper uses a policy Delphi to assess expert and stakeholder opinion on the likely impact of 5G of the NN regime in India and what, if any, modifications and alterations are required to enable proliferation of 5G services in the country. [Findings] The paper arrives at a set of policy recommendations for management of the NN regime in India in the context of 5G technology, markets and services. [Practical Implications and Value] These recommendations would be of practical utility to regulators and administrators in other countries as 5G is adopted in their telecommunications sectors. [ABSTRACT FROM AUTHOR]

In the 5G era, the demand for high-bandwidth computing, transmission, and storage has led to the development of optoelectronic interconnect technology. This technology has evolved from traditional board-edge optical modules to smaller and more integrated solutions. Co-packaged optics (CPO) has evolved as a solution to meet the growing demand for data. Compared to typical optoelectronic connectivity technology, CPO presents distinct benefits in terms of bandwidth, size, weight, and power consumption. This study presents an overview of CPO, highlighting its fundamental principles, advantages, and distinctive features. Additionally, it examines the current research progress of two distinct approaches utilizing Vertical-Cavity Surface-Emitting Laser (VCSEL) and silicon photonics integration technology. Additionally, it provides a concise overview of the many application situations of CPO. Expanding on this, the analysis focuses on the CPO using 2D, 2.5D, and 3D packaging techniques. Lastly, taking into account the present technological environment, the scientific obstacles encountered by CPO are analyzed, and its future progress is predicted. [ABSTRACT FROM AUTHOR]

This paper presents a novel reconfigurable multi-band antenna with a partially dredged cloverleaf shape that is tailored for size reduction and suitable for compact devices and urban environments. The antenna is capable of covering three distinct frequency bands: 3.22–4.06 GHz, 4.44–6.12 GHz, and 3.8–4.77 GHz, with respective bandwidths of 22%, 31.8%, and 22.6%, demonstrating its wideband capabilities. Utilizing various feeding configurations, the antenna enables the realization of multiple radiation patterns and frequency tuning. Validated through simulations and measurements, this design shows promise for 5G and advanced communication systems. [ABSTRACT FROM AUTHOR]

This paper presents a compact, highly isolated tri-band MIMO antenna for 5G and X-band communication applications. The overall dimensions of the antenna are 43 mm × 30 mm × 1.6 mm. It consists of two monopole radiating units and a metal base with branches and slit slots. The antenna achieves tri-band characteristics by improving the shape of the radiating patch. The isolation of the antenna is enhanced by slotting the floor and loading I- and T-shaped branches to absorb coupling currents. S12 > 15 dB is achieved in the frequency ranges of 3.3 GHz–4.06 GHz, 4.62 GHz–5.28 GHz, and 8.14 GHz–9.28 GHz. Measurement results show that the measured S-parameters do not change significantly compared with the simulation. It also has a low envelope correlation coefficient and good radiation performance. [ABSTRACT FROM AUTHOR]

A metamaterial-based non-uniform dipole array antenna is presented for high gain 5G millimeter-wave applications with a wideband characteristic. Initially, a non-uniform dipole array is designed on a 0.202 mm thick Rogers RO4003C substrate, offering a wide operating bandwidth ranging from 23.1 GHz to 44.8 GHz. The dipole array antenna emits unidirectional end-fire radiation with a maximum gain of 8.1 dBi and an average gain of 6.7 dBi. Subsequently, to achieve high gain performance, a 5 × 7 metamaterial structure is designed in the direction of the antenna radiation. The implemented metamaterial structure is optimized for the operating frequency, enhancing the directivity of the antenna radiation and resulting in a gain increment of more than 3 dBi compared to the dipole array alone. The developed metamaterial-integrated dipole array antenna offers an operating bandwidth (S11 < −10 dB) of more than 21 GHz (63.92%), ranging from 23.1 GHz to 44.8 GHz, covering the most commonly used 5G millimeter-wave frequency bands (n257, n258, n259, n260, and n261). Furthermore, the presented antenna yields a stable high gain with a peak gain of 11.21 dBi and a good radiation efficiency of more than 64%. The proposed antenna is an excellent option for millimeter-wave 5G systems due to its overall properties, particularly its high gain and end-fire radiation characteristics, combined with a wide operating bandwidth. [ABSTRACT FROM AUTHOR]

Due to the extensively accessible bandwidth of many tens of GHz, millimeter-wave (mmWave) and sub-terahertz (THz) frequencies are anticipated to play a significant role in 5G and 6G wireless networks and beyond. This paper presents investigations on mmWave bands within the indoor environment based on extensive simulations; the study considers the behavior of the omnidirectional and directional propagation characteristics, including path loss exponents (PLE) delay spread (DS), the number of clusters, and the number of rays per cluster at different frequencies (28 GHz, 39 GHz, 60 GHz and 73 GHz) in both line-of-sight (LOS) and non-LOS (NLOS) propagation scenarios. This study finds that the PLE and DS show dependency on frequency; it was also found that, in NLOS scenarios, the number of clusters follows a Poisson distribution, while, in LOS, it follows a decaying exponential distribution. This study enhances understanding of the indoor channel behavior at different frequency bands within the same environment, as many research papers focus on single or two bands; this paper considers four frequency bands. The simulation is important as it provides insights into omnidirectional channel behavior at different frequencies, essential for indoor channel planning. [ABSTRACT FROM AUTHOR]

The Internet of Things is currently one of the fastest-growing branches of computer science. The development of 5G wireless networks and modern data transmission protocols offers excellent opportunities for rapid development in this field. The article presents an overview of monitoring and control systems based on the Internet of Things. The authors discuss various aspects of these systems, including their architecture, applications, and challenges. We focus on analyzing the latest achievements in this field, considering technological innovations and practical applications in various sectors. Also, we emphasize the importance of integrating data from multiple sources and developing data analysis algorithms to ensure the effectiveness and precision of IoT-based monitoring and control systems. The article provides a valuable overview of the current state of knowledge in this dynamic area, inspiring further research and technological development. It also includes case studies showing various IoT device applications and energy consumption management. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive evaluation of the previously introduced multidisciplinary model to quantify human uncertainty (MMtQHU) within a realistic 5G-enabled cyber–physical–social systems (CPSS) environment. The MMtQHU, which integrates human, social, and environmental factors into CPSS modeling, is applied to the Ingolstadt traffic scenario (InTAS), a detailed urban simulation reflecting high-traffic conditions. By modeling unpredictable driver behaviors, such as deviations from optimal routes, the study assesses the model's effectiveness in managing human-induced uncertainties in vehicle-for-hire (VFH) applications. The evaluation shows that human uncertainty significantly impacts 5G network resource allocation and traffic dynamics. A comparative analysis of traditional resource allocation methods reveals their limitations in handling the dynamic nature of human behavior. These findings underscore the necessity for advanced, adaptive strategies, potentially leveraging artificial intelligence and machine learning to enhance the resilience and efficiency of 5G networks in CPSS environments. The study offers valuable insights for future advancements in robust and adaptive 5G infrastructure by highlighting the critical role of integrating human behavior into CPSS models. [ABSTRACT FROM AUTHOR]

This paper introduces a 4-port antenna tailored for 5G, operating in the 4.4 to 7.25 GHz (Fractional Bandwidth is 48.9%) range with a 10 dB impedance bandwidth. The operating bandwidth includes the n79 band (4.4–5 GHz), 5G WLAN band (5.125–5.825 GHz), and Wi-Fi 6E band (5.925 to 7.125 GHz). Constructed on a compact FR4 substrate (0.057λ × 0.057λ × 0.0018λ (where λ is the wavelength at 4.4 GHz), it exhibits robust performance in fabrication and measurements. The single antenna covers a total area as small as 20×17.6 mm², which enables the compactness of the MIMO antenna with a gain of up to 6 dBi and 85% radiation efficiency; it supports MIMO with a low correlation coefficient (< 0.02), high diversity gain (up to 9.98 dB), and minimal channel capacity loss (0.25 bps/Hz). The Total Active Reflective Coefficient (TARC) is computed to validate MIMO performance over the operating bandwidth. Featuring bidirectional radiation patterns in both E-plane and H-plane, the antenna is well suited for 5G applications, demonstrating potential for future wireless systems. [ABSTRACT FROM AUTHOR]

This work discusses a novel approach to a simulation-based cell selection that does not depend on static counts of cells or simplified models used in the cell selection process. The proposed method of cell selection uses advanced simulation to analyse the actual conditions and dynamically select the optimal cell to better suit the real conditions of the network and preference of the client. This research makes important theoretical and practical contributions that increase any simulation's performance and reliability aspects. The simulations conducted in the study demonstrate several major advantages. The method results in substantially lower call drops and higher throughputs of data. The outcome of the study is an adaptive and inherently interactive method that can be used in a plurality of networking circumstances, from 4 to 5G networks. The work more than adequately addresses the issue of cell selection and connecting, and improves the reliability and efficiency of any network that uses this method. This product can be easily implemented and can be used by network developers to ameliorate their networks' performance. The work's main theoretical contribution is the fact that optimal methods are made that undoubtedly make a simulation a more efficient phenomenon and that the components would interact more effectively together. Article Highlights: Dynamic cell selection improves performance, reducing call drops and enhancing throughput. Simulation framework adapts to real-time conditions, offering flexibility for 4G and 5G networks. Scalable method provides valuable insights for optimizing cellular network efficiency and QoS. [ABSTRACT FROM AUTHOR]

The metaverse concept has been evolving from static, pre-rendered virtual environments to a new frontier: the real-time metaverse. This survey paper explores the emerging field of real-time metaverse technologies, which enable the continuous integration of dynamic, real-world data into immersive virtual environments. We examine the key technologies driving this evolution, including advanced sensor systems (LiDAR, radar, cameras), artificial intelligence (AI) models for data interpretation, fast data fusion algorithms, and edge computing with 5G networks for low-latency data transmission. This paper reveals how these technologies are orchestrated to achieve near-instantaneous synchronization between physical and virtual worlds, a defining characteristic that distinguishes the real-time metaverse from its traditional counterparts. The survey provides a comprehensive insight into the technical challenges and discusses solutions to realize responsive dynamic virtual environments. The potential applications and impact of real-time metaverse technologies across various fields are considered, including live entertainment, remote collaboration, dynamic simulations, and urban planning with digital twins. By synthesizing current research and identifying future directions, this survey provides a foundation for understanding and advancing the rapidly evolving landscape of real-time metaverse technologies, contributing to the growing body of knowledge on immersive digital experiences and setting the stage for further innovations in the Metaverse transformative field. [ABSTRACT FROM AUTHOR]

The analysis and interpretation of enormous amounts of data generated by 5G networks present several challenges related to noise, precision, and feasibility validation. Therefore, this study aims to evaluate the effectiveness of channel equalisation in the network and enhance it by distributing signals over all subcarriers and symbols. The error‐free signal received ensures the reliable transmission of signals in the network connection. These simulations were undertaken to fulfil the needs of and adapt the transmission properties according to the specific conditions of the channel. The dataset consists of artificially generated radio waves to train signals through neural networks (NNs) and machine learning algorithms to detect errors properly. The primary objective is to achieve optimal signal performance. In this regard, an artificial neural network (ANN) was initially employed, explicitly utilising the back‐propagation technique and a feedforward multilayer perceptron (MLP). In addition, the signals were subjected to train using a real‐time simulator, employing feedforward neural network and support vector machine (SVM) to validate the proposed methodology. Feedforward MLP achieved the highest performance in simulations compared to SVM. The scheme is promising to achieve optimal signal performance in real‐time. [ABSTRACT FROM AUTHOR]

Human Carbonic Anhydrases (hCA) are enzymes that contribute to cancer's development and progression. Isoforms IX and XII have been identified as potential anticancer targets, and, more specifically, hCA IX is overexpressed in hypoxic tumor cells, where it plays an important role in reprogramming the metabolism. With the aim to find new inhibitors towards IX and XII isoforms, the hybridization of the privileged scaffolds isatin, dihydrothiazole, and benzenesulfonamide was investigated in order to explore how it may affect the activity and selectivity of the hCA isoforms. In this respect, a series of isatin thiazolidinone hybrids have been designed and synthesized and their biological activity and selectivity on hCA I, hCA II, hCA IX, and hCA XII explored. The new compounds exhibited promising inhibitory activity results on isoforms IX and XII in the nanomolar range, which has highlighted the importance of substituents in the isatin ring and in position 3 and 5 of thiazolidinone. In particular, compound 5g was the most active toward hCA IX, while 5f was the most potent inhibitor of hCA XII within the series. When both potency and selectivity were considered, compound 5f appeared as one of the most promising. Additionally, our investigations were supported by molecular docking experiments, which have highlighted the putative binding poses of the most promising compound. [ABSTRACT FROM AUTHOR]