Mobile Communication Research Articles

Design and Evaluation of Steganographic Channels in Fifth-Generation New Radio

Mobile communication is ubiquitous in everyday life. The fifth generation of mobile networks (5G) introduced 5G New Radio as a radio access technology that meets current bandwidth, quality, and application requirements. Network steganographic channels that hide secret message transfers in an innocent carrier communication are a particular threat in mobile communications as these channels are often used for malware, ransomware, and data leakage. We systematically analyze the protocol stack of the 5G–air interface for its susceptibility to network steganography, addressing both storage and timing channels. To ensure large coverage, we apply hiding patterns that collect the essential ideas used to create steganographic channels. Based on the results of this analysis, we design and implement a network covert storage channel, exploiting reserved bits in the header of the Packet Data Convergence Protocol (PDCP). the covert sender and receiver are located in a 5G base station and mobile device, respectively. Furthermore, we sketch a timing channel based on a recent overshadowing attack. We evaluate our steganographic storage channel both in simulation and real-world experiments with respect to steganographic bandwidth, robustness, and stealthiness. Moreover, we discuss countermeasures. Our implementation demonstrates the feasibility of a covert channel in 5G New Radio and the possibility of achieving large steganographic bandwidth for broadband transmissions. We also demonstrate that the detection of the channel by a network analyzer is possible, limiting its scope to application scenarios where operators are unaware or ignorant of this threat.

Call Blocking Estimation Using Adaptive Channel Reservation for Hand‐Off Calls in Wireless Cellular Network

ABSTRACTThe wireless cellular network (WCN) provides services to many users with limited radio resources. In WCN, resource allocation is important to provide the desired quality of service (QoS). Among the two possible types of calls in WCN, hand‐off calls (HCs) have higher priority than new calls (NCs). In this paper, we developed a mathematical model to estimate call blocking using an optimal number of guard channel (GC) for HCs by considering target hand‐off call dropping probability (HCDP). We named this model the optimal guard channel reservation (OCR) policy. This analytical model assumes the long‐term average of the traffic parameters and so is far from making any correlation with the operation of the existing system. In real, the traffic parameters are dynamic. Further, we proposed an optimal adaptive guard channel reservation (OACR) policy to obtain optimal performance. It adjusts the GCs dynamically w.r.t the traffic conditions to keep HCDP below the target. We have implemented the OACR scheme by using a test bed. Finally, we have applied both mathematical model (i.e., OCR policy) and OACR policy to a wireless cellular network, that is, Global System for Mobile Communication (GSM) 900 system.

Borosilicate glass with low dielectric loss and low permittivity for 5G/6G electronic packaging applications

A phase-separated borosilicate glass, with a relative permittivity ranging from 3 to 3.5 and a loss tangent as low as 5.6 × 10−4, is presented for packaging applications for the next generation of mobile communications. Ionic polarizability for each borosilicate composition was calculated from the Clausius–Mossotti relationship for both the vitreous and crystalline structures, and the polarizability difference between the two is proportional to the dielectric loss. Small amounts of alkali modifier were added to improve the glass processability, and the loss tangent increased to the 1–7 × 10−3 range. The resulting glass is phase-separated, which has no impact in the millimeter-wave spectrum, as the wavelengths are considerably greater than the length scale of each immiscible phase.

Analysis and Prediction of Path Loss for Mobile Communication Lines in Nasarawa State Using Propagation Models

The design of future-generation mobile communication systems depends critically on the path loss prediction methods and their suitability to various signal propagation regions. Even though 5G has been launched in Nigeria, its deployment still faces significant challenges especially in the suburban, and non-urban regions which still depends on 4G. Many operators are still in the process of upgrading their existing 4G networks to support network coverage and higher speed data throughput. Due to the unique mix of Nasarawa State with diverse terrains, in this study, path loss prediction for the key telecommunication networks in Nasarawa State was carried out using Signal Strength Info App. Data was collected for a period of eight weeks (August, 2nd to September, 4th 2023) focusing on 4G LTE networks operating within the 1800 MHz frequency band. Analysis of path loss using empirical models such as Hata, Egli, and COST-231 Hata models were compared with the measured path loss in different terrains of urban, sub-urban, and non-urban environments. The Root Mean Square Error (RMSE) analysis was carried out between empirical and measured path losses. Results shows that, the order of mean predicted path loss at 5km was free space model (BN>CN>DN.AN), Hata model (DN>BN>CN>AN), Cos-231 Hata model (CN>AN>BN>DN), and Egli model (AN>BN>DN>CN). Hate model predicted the highest path loss values while Egli model predicted the lowest values. Overall, Egli model is found to be the most reliable and suitable path loss prediction model for entire Nasarawa State with RMSE value 5.99dBm, 2.90dBm and 3.14dBm for Nasarawa, Keffi and Akwanga LGA respectively. However, Cost-231 Hata model with RMSE value of 5.71dBm is suitable for path loss prediction in Karu due to its irregular terrain. The findings of this study are significant for practical applications in network planning, base station coverage, frequency allocation, and signal strength management, ensuring optimal mobile network performance across various terrains.

Development of methods for monitoring and optimization of underground drainage systems using wireless sensor networks and ultra-wideband antennas

This research focuses on optimizing ultra-wideband (UWB) antennas, which are critical in modern communication systems due to their wide frequency range (3.1–10.6 GHz) and high data transmission capabilities. The study addresses the challenge of optimizing key antenna parameters – such as return loss, peak gain, and radiation efficiency – while also ensuring energy efficiency and network longevity. Traditional optimization methods, such as LEACH-C, often fail to balance these factors, leading to suboptimal performance. To solve this problem, the researchers developed the Generalized Position-based Optimization Neural Network (GPON) for UWB antenna optimization. They also evaluated the Position-based Hybrid Neural Network (PAN) method, comparing its performance with existing algorithms including LEACH-C, Firefly Algorithm (FA), HFAPSO, FA-ANN, and HWOABCA. The GPON model reduced return loss to 25.5 dB at 3.5 GHz and improved peak gain to 4.2 dB i, while maintaining 92 % radiation efficiency. In contrast, PAN demonstrated a 15–25 % improvement in residual energy and extended network lifetime by 20 % compared to LEACH-C. These improvements were due to the integration of advanced neural network techniques in GPON and the effective use of positional data in PAN, enabling more precise and adaptive optimization. The ability to balance multiple performance metrics simultaneously – a challenge previous models struggled with – is a key feature. This balance is crucial for UWB antennas in communication systems where both performance and energy efficiency are vital. The findings are especially relevant for practical applications in wireless sensor networks, mobile communications, and radar systems, requiring long-term network reliability and optimal antenna performance

Optimizing SMS Spam Detection Using Machine Learning: A Comparative Analysis of Ensemble and Traditional Classifiers

With the rapid rise of mobile communication, Short Message Service (SMS) has become an essential platform for transmitting information. However, the growing volume of unsolicited and harmful spam messages presents significant challenges for both users and mobile network operators. This study explores the effectiveness of various machine learning models, including Random Forest, Gradient Boosting, AdaBoost, Support Vector Machine (SVM), Logistic Regression, and an Ensemble Voting Classifier, in detecting SMS spam. A dataset containing 5,572 SMS messages, labeled as either spam or ham (legitimate), was used to evaluate these models. Hyperparameter tuning was performed on each model to optimize accuracy, and the models were assessed using metrics such as precision, recall, F1-score, and accuracy. The results indicated that the SVM and Ensemble Voting Classifier achieved the highest performance, with accuracies of 0.9857 and 0.9848, respectively. Both models demonstrated superior recall for spam messages, making them highly effective for real-world spam detection systems. While Random Forest, Gradient Boosting, and AdaBoost also performed well, their slightly lower recall for spam suggests that they may misclassify some spam as legitimate messages. The study highlights the effectiveness of machine learning models in addressing the SMS spam problem, particularly when using ensemble methods. Future research should focus on addressing class imbalance and exploring deep learning approaches to further enhance model performance. These findings offer valuable insights for developing more accurate and scalable SMS spam detection systems.

Reliability Assessment of Power Distribution Cyber–Physical Systems Considering the Impact of Wireless Access Networks

With the rapid increase in the number of various terminal devices in distribution systems, the important impact of communication networks on power supply reliability in cyber–physical distribution systems (CPDSs) is becoming increasingly prominent. The traditional wired communication method makes it difficult to meet the demand in some scenarios due to high cost and construction difficulty. For this reason, this study evaluated the reliability of power distribution cyber–physical systems, considering fifth-generation (5G) mobile communication technology wireless access conditions. First, a reliability model of a communication channel in a 5G communication network was established, and the indirect impact of information system failure on the power distribution system was analyzed. Secondly, a reliability assessment method based on the improved least path method was devised by combining switch action failure, self-healing processing, and load transfer. The simulation results show that 5G communication technology has significant advantages in improving system reliability, and the proposed method is closer to the development direction of future power distribution systems, which provides an effective reference basis for the optimized operation of power distribution cyber–physical systems.

Performance Analysis of Millimeter-Wave Propagation Characteristics for Various Channel Models in the Indoor Environment

Due to the recent surge in the proliferation of smart wireless devices that feature higher data speeds, there has been a rise in demand for faster indoor data communication services. Moreover, there is a sharp increase in the amount of mobile data being generated worldwide, and much of this data comes from residential wireless applications like high-definition TV, device-to-device communication, and high data rate indoor networks (i.e., local and cellular). These technologies need large capacity, high data rate indoor wireless networks with huge bandwidth. Consequently, a greater interest exists in implementing an effective and trustworthy indoor propagation model for next-generation wireless systems operating in the massively bandwidth-rich millimeter wave (mm-wave) frequency range. The analysis of mm-wave propagation characteristics in an indoor environment using the ray tracing approach is proposed in this paper. Propagation modeling for 60 GHz bands is included. The aspects of wideband propagation characteristics such as angular spread, path loss, delay spread, and power delay profile are modeled in this paper. The position of transceivers, antenna effect, and attenuation, in the hallways, and stairwells will all be considered while determining the propagation parameters. This includes wave propagation characteristics like absorption, reflection, and diffraction by building structures and furniture. The specifications for propagation characteristics are included in the article for developing indoor local and cellular networks. In this paper, the IRT model has been tested at 60 GHz for potential mobile communication and is identified as the best method for predicting signal attenuation caused by objects, barriers, or humans within buildings in internal millimeter wave transmission.

Double Deep Q- energy aware Service allocation based on Dynamic fractional frequency reusable technique for lifetime maximization in HetNet-LTE network

The development of mobile communication in heterogeneous networks is incredible in providing various services through wireless cellular communication through advanced long-term evaluation networks. Increasing multi-concern services and frequencies in spectrum channels are highly layered to select the bandwidth to provide the fastest network without interference. Selecting the channel through macro cell selection is essential to improve network communication and provide the quickest service. Most frequency reuse techniques use service optimality and route selection-based protocols to enrich the packet flow. Still, the improper spectrum delights create more delay tolerance due to short-range service optimality due to energy loss by selecting the short spectrum signal to reuse, which doesn't support the lifetime improvement of the LTE network. To resolve these problems, we propose a Double Deep Q- energy-aware Service allocation based on a Dynamic fractional frequency reusable technique for lifetime maximization in the HetNet-LTE network. Initially, the heterogenous communication environment and node deplanement were carried out to construct the LTE network under the WCC. The communication logs are Route Table (RT), and its services are taken by all node LTE Communication Impact Rate (LTE-CIR). Then, the Backhaul Traffic Algorithm (BTA) is applied to predict the interference on traffic rate from the channel frequency margin. Select the balanced node using the Channel Interference Macro Cell Selection (CIMCS) technique. Considering frequency limits with the Double Deep Q- Network (DDQN) approach, energy-aware selects the optimal route to reuse the frequency level using Frequency Domain Packet Scheduling (FDPS) to improve communication. The proposed system improves the overall throughput by up to 97.8 % with adopted channel selection from the macro unit to improve the latency performance. Also, the interference frequency limits are dynamically reused at an energy optimal level with low-level delay tolerance to improve the link stability by up to 98.4 % with higher lifetime maximation in the LTE network.

Use of mobile communication technology to overcome vaccine skepticism

Despite significant advances in clinical medicine, infectious diseases and their prevention remain the leading problem of our time. Low literacy of the population reggarding immunization, combined with high activity of the anti-vaccination movement, creates unhealthy skepticism about immunoprophylaxis and the risks of epidemics. The work uses theoretical analysis of literature, methods of anonymous questionnaires of students of medical and non-medical specialties, methods of statistical and bioinformatics data processing, and modern internet technologies: the platform of the social network “Vkontakte” and the program for creating a chatbot “Senler”. The analysis of commitment to vaccination of medical and non-medical students showed that 65.8% to 96.2% of respondents have a positive attitude to preventive health measures. From 1.9% to 6% believe the disease is easier to treat than to prevent, and almost 30% of respondents do not think about prevention and diseases in general, considering themselves young. Almost 10% of non-medical students (1 group) consider vaccination useless, 8.4% dangerous for immunity, 18.3% know nothing about vaccinations and cannot compare the benefits of vaccination with the risk of infectious pathology. In order to form medical literacy of the population, including in strategic issues of preserving the health of the nation, the team of authors developed and implemented through the social network “Vkontakte” chatbot “Vaccine and point” containing up-to-date information about vaccines, methods multiplicity and age features of their use. People [n = 156] used the chatbot during the month of work, noting its high informational value, motivating to vaccination. Analysis of commitment to vaccination of students of medical and non-medical specialties showed an insufficient level of trust in domestic preventive medicine, which forms an unhealthy attitude to vaccine prevention. Insufficient vaccine coverage creates real threats to the spread of infectious diseases at the population level. Developed and implemented in real practice, the “Vaccine and point” chatbot is an effective tool for increasing the knowledge of compatriots about the real possibilities of protection against the main vaccine-controlled infections and an additional attempt to overcome anti-vaccination skepticism.

Perceived Health Risks Associated with Smartphone Use Among Health College Students at Qassim University in Saudi Arabia

Background Smartphones have evolved into a fusion of traditional personal digital assistants and cellular phones, integrating mobile communication capabilities with features parallel to those of a handheld computer. Objective This study aimed to assess the health risks associated with smartphone use and the prevalence and nature of observed health issues among health college students at Qassim University in Saudi Arabia. Methods Employing a descriptive cross-sectional research design, this study surveyed a convenience sample of 511 health college students at Qassim University. The data collection instrument comprised two sections: Section 1 assessed sociodemographic, academic, and health-related information, while Section 2 evaluated the health risks as perceived by students. Results The majority of the participants were women (71%) and were studying nursing (26%). A significant proportion (39.9%) reported blurred vision, while 38.6% indicated a lack of adequate sleep. Notably, no significant association was observed between the health complaints and sociodemographic information. The analysis also revealed no significant relationship between health complaints and smartphone usage patterns. Conclusion The findings highlight a critical need for further research to investigate the factors contributing to the effect of smartphone use on the physiological well-being of university students. Such research is essential for developing targeted interventions to mitigate the associated health risks.

A novel artificial intelligence‐based antenna designing model for optimizing 5G mobile communication

AbstractAntenna designing involves the creation of devices to transmit or receive electromagnetic signals for various applications. It encompasses optimizing parameters such as size, shape, and frequency response to achieve desired performance characteristics, including signal strength, bandwidth, and efficiency, across diverse communication systems and frequencies. In this research, we intend to establish a novel artificial intelligence (AI)‐based antenna designing model for optimizing 5th generation (5G) mobile communication. We proposed Multi‐Objective Zebra Optimization (MOZO) to enhance 5G antenna design, aiming to minimize return loss () and maximize gain (G) concurrently. MOZO efficiently explores design space, offering Pareto‐optimal solutions that balance objectives. This approach ensures optimal antenna performance across the desired frequency range, advancing 5G communication efficiency. Our model enhances the functionality of a small, rectangular patch antenna designed for the 5G band, specifically operating at 30 GHz. Additionally, we conducted a comparative analysis between the performance of our optimized rectangular 5G antenna and several recently employed 5G‐millimeter wave (mmWave) antennas. This comparison sheds light on the efficacy and competitiveness of our optimized design within the 5G‐mmWave antenna landscape.

Construction and Application of a Private 5G Standalone Medical Network in a Smart Health Environment: Exploratory Practice From China.

To date, the differentiated requirements for network performance in various health care service scenarios-within, outside, and between hospitals-remain a key challenge that restricts the development and implementation of digital medical services. This study aims to construct and implement a private 5G (the 5th generation mobile communication technology) standalone (SA) medical network in a smart health environment to meet the diverse needs of various medical services. Based on an analysis of network differentiation requirements in medical applications, the system architecture and functional positioning of the proposed private 5G SA medical network are designed and implemented. The system architecture includes the development of exclusive and preferential channels for medical use, as well as an ordinary user channel. A 3-layer network function architecture is designed, encompassing resource, control, and intelligent operation layers to facilitate management arrangements and provide network open services. Core technologies, including edge cloud collaboration; service awareness; and slicing of access, bearer, and core networks, are employed in the construction and application of the 5G SA network. The construction of the private 5G SA medical network primarily involves system architecture, standards, and security measures. The system, featuring exclusive, preferential, and common channels, supports a variety of medical applications. Relevant standards are adhered to in order to ensure the interaction and sharing of medical service information. Security is achieved through mechanisms such as authentication, abnormal behavior analysis, and dynamic access control. Three typical medical applications that rely on the 5G network in intrahospital, interhospital, and out-of-hospital scenarios-namely, mobile ward rounds, remote first aid, and remote ultrasound-were conducted. Testing of the 5G-enabled mobile ward rounds showed an average download rate of 790 Mbps and an average upload rate of 91 Mbps. Compared with 4G, the 5G network more effectively meets the diverse requirements of various business applications in prehospital emergency scenarios. For remote ultrasound, the average downlink rate of the 5G network is 4.82 Mbps, and the average uplink rate is 2 Mbps, with an average fluctuation of approximately 8 ms. The bandwidth, performance, and delay of the 5G SA network were also examined and confirmed to be effective. The proposed 5G SA medical network demonstrates strong performance in typical medical applications. Its construction and application could lead to the development of new medical service models and provide valuable references for the further advancement and implementation of 5G networks in other industries, both in China and globally.

Innovative Management Strategies and Competitive Advantage of Global System for Mobile Communication (GSM) Service Providers in Taraba State, Nigeria

This study investigates the effects of product, service, process, and technological innovations on the competitive advantage of GSM service providers in Jalingo, Taraba State, Nigeria. It aims to determine how these different types of innovations influence market positioning and operational efficiency within the regional telecommunications sector. The research is framed using Dynamic Capabilities Theory, which emphasizes the role of strategic adaptability and resource reconfiguration in achieving and sustaining competitive advantage in rapidly changing markets. Employing a mixed-methods approach, the study integrates quantitative data from structured questionnaires distributed to 115 staff across major telecom providers and qualitative insights from industry reports. A total of 102 responses were analyzed using regression analysis in SPSS to evaluate the effect of innovation types on competitive advantage. The findings reveal that all types of innovation—product, service, process, and technological—significantly enhance the competitive advantage of GSM providers in Jalingo. Service innovation showed the strongest effect, followed by technological, product, and process innovations. The study underscores the critical importance of a holistic innovation strategy that includes diverse forms of innovation to improve competitive advantage. GSM providers in Jalingo who embrace comprehensive innovation strategies are more likely to secure greater market share and achieve long-term profitability. The study recommends that GSM service providers should prioritize developing new service offerings and enhancing existing services. This could include investing in customer relationship management systems to personalize services, implementing loyalty programs, or introducing flexible pricing models that cater to different customer segments.

Private compression for intermediate feature in IoT-supported mobile cloud inference

In the emerging Internet of Things (IoT) paradigm, mobile cloud inference serves as an efficient application framework that relieves the computation and storage burden on resource-constrained mobile devices by offloading the workload to cloud servers. However, mobile cloud inference encounters computation, communication, and privacy challenges to ensure efficient system inference and protect the privacy of mobile users’ collected information. To address the deployment of deep neural networks (DNN) with large capacity, we propose splitting computing (SC) where the entire model is divided into two parts, to be executed on mobile and cloud ends respectively. However, the transmission of intermediate data poses a bottleneck to system performance. This paper initially demonstrates the privacy issue arising from the machine analysis-oriented intermediate feature. We conduct a preliminary experiment to intuitively reveal the latent potential for enhancing the privacy-preserving ability of the initial feature. Motivated by this, we propose a framework for privacy-preserving intermediate feature compression, which addresses the limitations in both compression and privacy that arise in the original extracted feature data. Specifically, we propose a method that jointly enhances privacy and encoding efficiency, achieved through the collaboration of the encoding feature privacy enhancement module and the privacy feature ordering enhancement module. Additionally, we develop a gradient-reversal optimization strategy based on information theory to ensure the utmost concealment of core privacy information throughout the entire codec process. We evaluate the proposed method on two DNN models using two datasets, demonstrating its ability to achieve superior analysis accuracy and higher privacy preservation than HEVC. Furthermore, we provide an application case of a wireless sensor network to validate the effectiveness of the proposed method in a real-world scenario.

Ultrathin, flexible, and high-performance bacterial cellulose/copper nanowires film for broadband electromagnetic interference shielding and photothermal conversion

The swift advancements in wearable electronics, implantable medical devices, fifth-generation mobile communication, unmanned aerial vehicles, and military stealth technology have led to a surge in demand for highly flexible multifunctional films. Consequently, the enhancement of electromagnetic radiation and the requirement for normal operation in extreme environments have posed significant challenges for flexible electromagnetic interference (EMI) shielding films. In this paper, ultra-thin, flexible bacterial cellulose (BC)/copper nanowires (CuNWs) (BCu) films with Janus structure are prepared by the combination of microwave-assisted hydrothermal synthesis and vacuum filtration method, which can be used for broadband EMI shielding and photothermal conversion. BCu films demonstrate exceptional mechanical properties, boasting a tensile strength range from 48.5 to 77.3 MPa, accompanied fracture strain 4.1–5.9 %. When CuNWs mass in Janus film increases to 10 mg, the conductivity of BCu-4 Janus films can reach 4761.90 S cm−1. The ultra-strong EMI shielding effectiveness (SE, above 56.00 dB) is achieved in 6–26.5 GHz for BCu-4 film with an ultra-thin thickness (16 μm). Moreover, the specific EMI SE of BCu-4 is as high as 4294.38 dB mm−1. Furthermore, BCu Janus films exhibit outstanding photothermal conversion performance. A saturation temperature of BCu-4 Janus film reaches as high as 75 °C under irradiation of one sunlight (100 mW cm−2). The facile and collaborative strategy is provided for fabricating ultra-thin, flexible multifunctional Janus films with EMI shielding and photothermal conversion capabilities, addressing EMI problems in modern electronic technology and offering new avenues for applications in various fields.

A Power Control and Intervention Algorithm for Co-Existing IMT Base Stations and Satellite Services

IMT-2020 (International Mobile Telecommunications-2020) is the prevailing mobile communication technology at the moment, significantly affecting societal progress. Nevertheless, the roll-out of the IMT-2020 system has introduced numerous interferences to existing services. The coexistence with fixed satellite services has become a topical issue currently under consideration. This paper discusses the compatibility and interference issues between IMT-2020 and the 14 GHz FSS (fixed-satellite service) uplink, as well as the spectrum access issue solved by artificial intelligence methods. The study shows that the interference from IMT-2020 macro-base stations to FSS space stations exceeds the ITU standard by approximately 10 dB. To control the interference, a partition-based power control algorithm is proposed, which divides ground base stations into multiple areas and virtualizes each area’s base stations into a single large base station then applies power control to maximize the total transmission power of the base stations within the area. Furthermore, three intra-partition power control algorithms are introduced: average power allocation, power allocation based on channel gain, andna power allocation method based on the maximum intra-partition sum rate. Additionally, under the assumption that dynamic satellite nodes are available in the system for ground user access, a spectrum access algorithm utilizing deep reinforcement learning is designed. Simulation results confirm the effectiveness of the proposed scheme, which can reduce the interference from the IMT-2020 system to the FSS service below the threshold, ensuring harmonious coexistence of the two services.

Resource optimization of multi-UAV assisted communication system based on user scheduling

In order to improve the transmission rate of the multi-user mobile communication downlink wireless transmission system, a resource optimization method for multi-unmanned aerial vehicle (UAV) assisted communication system based on user scheduling and trajectory optimization is proposed. The proposed method establishes an optimization problem with the maximization of the total multi-user throughput as the criterion under the constraints of user scheduling, total energy consumption of UAVs and user service quality requirements. In order to solve this non-convex problem, the original non-convex problem is decomposed into three easy-to-handle non-convex sub-problems by using the block coordinate descent method (BCD). The sub-problems are transformed and solved by introducing slack variables, first-order Taylor expressions, continuous convex approximation (SCA) and other methods, and then alternately iteratively optimized to obtain an approximate suboptimal solution to the original non-convex problem. Simulation results show that the proposed algorithm can effectively improve the total system throughput and has good convergence in both single and multi-UAV communication systems.

A rapid fingerprint positioning method based on deep convolutional neural network for MIMO-OFDM systems

The combination of fingerprint positioning and 5G (the 5th Generation Mobile Communication Technology) offers broader application prospects for indoor positioning technology, but also brings challenges in real-time performance. In this paper, we propose a fingerprint positioning method based on a deep convolutional neural network (DCNN) using a classification approach in a single-base station scenario for massive multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) systems. We introduce an angle-delay domain fingerprint matrix that simplifies the computation process and increases the location differentiation. The cosine distance is chosen as the fingerprint similarity criterion due to its sensitivity to angular differences. First, the DCNN model is used to determine the sub-area to which the mobile terminal belongs, and then the weighted K-nearest neighbor (WKNN) matching algorithm is used to estimate the position within the sub-area. The positioning performance is simulated in a DeepMIMO indoor environment, showing that the classification DCNN method reduces the positioning time by 77.05% compared to the non-classification method, with only a 1.08% increase in average positioning error.

Epoxy-imine vitrimer having low dielectric constant and high wave transmission efficiency for mobile communication applications

The rapid growth of telecommunication technology calls for express evaluation and development for low dielectric constant (Dk) materials with higher performance requirements. At mean time, the extensive use of these dielectric materials generates increasing concerns over their crosslinking structures that cannot be readily recycled without causing environment pollution. Herein, a curing agent comprising dynamically exchangeable imine bonds was synthesized via the condensation of terephthalaldehyde (TPA) and isophorondiamine (IPDA). Epoxy vitrimers cured by this curing agent exhibited low Dk (2.75–2.79) and excellent wave transmission efficiency (>90.5 %) at high frequency range of 8.2–12.4 GHz. The cured resins can also be recycled through chemical degradation, producing reusable monomers. The cured resins demonstrate vitreous properties and its dielectric, thermal properties and wave transmission efficiency maintained unchanged after reprocessing. This work offers a strategy to prepare low Dk epoxy vitrimer used in communication field.