Technology For Cellular Networks Research Articles

5G- Analysis and Characteristics in Comparison with Previous Generations

This paper explores the architecture and remarkable advantages of 5G technology in the current industry of wireless communication. The paper covers details of the recently developed 5th generation of networks and how its benefits overpower its drawbacks, majorly being its impact on health and environment. This study helps understanding 5G and highlights how this recent advancement has better chances of helping with wide area network connectivity, latency, economic growth, enhanced security features etc. While advancements in the cellular network technology continue to be one of the most important developments in the economic, telecom and healthcare sector among many others, many common beliefs about 5G which can be listed as its “drawbacks” have been brought to people’s attention recently, and with proper facts and studies, it can be easily proved how 5G, till this date, has no significant harm to any area, and simply has a few complexities which are natural with any advancement in technology. The paper covers the characteristics of the 5G network, and addresses common misconceptions and concerns surrounding health, security, and infrastructure.

Developing Laboratory Experiments to teach Undergraduate Engineering Students Multi-User Massive MIMO Technology for 5G Cellular Networks

An effective method of facilitating student learning in a laboratory environment is “practice by doing”. The study of modules related to signal-processing for digital communications requires deep mathematical and theoretical foundations but the practice goal is not really emphasized in the undergraduate curriculum at the University of Mauritius. This causes the students to lose interest in the corresponding modules resulting in high rate of failures. In this work, we propose to develop laboratory experiments with a view to bridge the gap between theoretical and practical aspects in the field of Massive Multiple-Input Multiple-Output (MIMO) systems for 5G cellular networks. Various laboratory scenarios are set up that consider a Maximum Ratio Combining (MRC) receiver in the uplink with an uncorrelated Rayleigh fading channel. Moreover, from a signal processing perspective to enhance the student’s understanding, we analyze the efficiency and error performance of Massive MIMO systems with MPSK and MQAM modulation schemes as well as perfect and imperfect channel estimates. The leading industry software package MATLAB R2022 is used to develop all laboratory experiments and the codes are elaborated in this analysis. Data collected from the experiments are used to generate spectral efficiency and error performance curves which can be used for future research. The findings underscore the significance of accounting for both scenarios and illuminate promising avenues for future research in the realm of massive MIMO education and learning. The assimilation of MATLAB® flowcharts for each MRC receiver, MPSK, and MQAM with perfect and imperfect Channel State Information (CSI) adds further depth to the study, ensuring a comprehensive understanding of the intricacies of massive MIMO systems. Ultimately, this contribution helps in the nurturing of expertise such that future generations of wireless communication pioneers can be inspired.

Graph Attention Network Enhanced Power Allocation for Wireless Cellular System

The importance of an efficient network resource allocation strategy has grown significantly with the rapid advancement of cellular network technology and the widespread use of mobile devices. Efficient resource allocation is crucial for enhancing user services and optimizing network performance. The primary objective is to optimize the power distribution method to maximize the total aggregate rate for all customers within the network. In recent years, graph-based deep learning approaches have shown great promise in addressing the challenge of network resource allocation. Graph neural networks (GNNs) have particularly excelled in handling graph-structured data, benefiting from the inherent topological characteristics of mobile networks. However, many of these methodologies tend to focus predominantly on node characteristics during the learning phase, occasionally overlooking or oversimplifying the importance of edge attributes, which are equally vital as nodes in network modeling. To tackle this limitation, we introduce a novel framework known as the Heterogeneous Edge Feature Enhanced Graph Attention Network (HEGAT). This framework establishes a direct connection between the evolving network topology and the optimal power distribution strategy throughout the learning process. Our proposed HEGAT approach exhibits improved performance and demonstrates significant generalization capabilities, as evidenced by extensive simulation results.

A novel enhanced security architecture for sixth generation (6G) cellular networks using authentication and acknowledgement (AA) approach

The sixth generation (6G) of cellular transmission is extremely adaptable. 6G will equip everyone with pervasive wireless connectivity and meet the needs of a fully connected world. It is anticipated that revolutionary ideas will increase in support for a fast-expanding variety of smart devices and applications. The sophisticated characteristics of 5G portable cellular network infrastructures produce novel threats and requirements. Comparing 6G cellular network technologies to 5G cellular networks, this paper discusses various security and privacy issues in 6G cellular networks based numerous security services. Proposes AA approach to evaluate the effectiveness of the methodology. Propose a new 6G wireless security architecture based on the analysis of secret key authentication and flexible position based identification, which serves as the foundation for an examination of identity management and flexible authentication. Demonstrates the benefits of the proposed architecture, analyzes BER against SINR and Measure Throughput Against various SINR values. Finally, Limitations and future recommendation for 6G cellular network security is presented.

Dynamic path planning in autonomous driving

With the development of emerging technologies such as the Internet of Things (IoT), Artificial Intelligence (AI) and fifth-generation cellular network technology (5G), good conditions are provided for the level of automation, providing the necessary assistance to coordinate the environment, planning decisions and path optimisation for self-driving vehicles. This paper briefly outlines and analyses the key technologies required to realize autonomous driving and summarizes the corresponding research results for each part; by considering the operation process of self-driving vehicles, this paper chooses path planning as the focus of research and presents it in the form of a methodology; finally, it concludes with a summary of personal opinions and a discussion of possible future research directions.

(Invited) Integration of InP Heterojunction Bipolar Transistors on Silicon Substrates for 6G Networks

The fast expansion of the global datasphere creates a huge demand on the future wireless communication technologies. Although 5G, the 5th generation of the cellular network technology, is still being rolled out, the potential of 6G is already intensively explored. The vision of 6G implies not only massive connectivity and higher data rate (up to 100 Gb/s and more) in ultra-reliable low-latency communication, but machine-to-machine interaction will dominate over those involving humans. AI (artificial intelligence) and machine learning will be omnipresent.6G network will address a frequency spectrum beyond 100 GHz, which provides wider bandwidths and, therefore, potentially simpler modulation schemes and eventually lower power consumption. However, a clear disadvantage of these mm-waves or sub-THz frequencies are the atmospheric absorption and blockage effect by physical obstacles or rain. These challenges must be tackled by a sufficiently high transceiver device density per area together with advanced beam steering and AI empowered networks.The power amplifier (PA) is one of the most critical components of the RF front-end module. Here, InP based heterojunction bipolar transistors (HBT) clearly outperform PAs based on CMOS or SiGe BiCMOS concerning saturated output power, energy efficiency and breakdown voltage. However, the limiting downside of InP HBTs is the missing cost-efficient and scalable fabrication, which hampers its adoption in high-volume 6G applications. In this paper we review various InP HBT fabrication concepts with the aim of lowering the production costs and maintaining high device performance.The best HBT device performance is demonstrated for the lattice-matched deposition on native small-diameter (≤ 150 mm) InP substrates due to perfect III-V crystal quality. Although device fabrication on these wafers cannot profit from the advanced tool park available in 200/300 mm fabs, the main drawbacks are the high cost and brittleness of InP substrates. Realizing InP HBTs on Si substrates allows to benefit from their robustness, low cost, and the access to a mature device fabrication on large-diameter wafers.In wafer reconstitution, numerous diced InP wafer tiles, which already contain the grown HBT layer stack, are bonded to a Si carrier to populate the wafer surface. After planarization, the reconstructed Si wafer can be further fabricated in a CMOS compatible 200/300 mm fab. In transfer printing a comparable approach is followed while only the active device stack is transferred to the Si carrier. Transferring only a thin InP layer to the Si carrier, which serves as a starting surface for the HBT deposition, leads to a so-called engineered substrate. Compared to the previous transfer methods, the III-V device deposition is carried out after bonding. The key advantage of all these heterogenous integration concepts is the access to a CMOS compatible and scalable device fabrication while maintaining the high III-V crystal quality. Nevertheless, the HBT production costs can only be significantly reduced with a certain re-usability of the InP substrates.The monolithic deposition directly on Si substrates would be the most cost-efficient integration approach. Unfortunately, the mismatch in lattice constant and thermal expansion coefficient between Si and III-V materials leads to the formation of relaxation defects, which degrade the HBT device performance. The growth of thick strain relaxation buffers allows to reduce the defect density in the device layers but bears new challenges such as wafer warpage or III-V crack formation.Nano-ridge engineering (NRE) is based on selective area growth (SAG) applying trench-patterned Si wafers. The III-V deposition starts inside very narrow trenches to achieve efficient aspect ratio trapping (ART) of misfit defects. After the trench is filled with III-V material, the growth is continued to engineer a broad and pristine nano-ridge (NR) which holds the device stack. A second oxide pattern prevents sidewall deposition around the NRs during the deposition of the HBT heterolayers.In the first part of this paper, pros, and cons of the most common InP HBT integration scenarios as summarized in figure will be compared in detail. Among all concepts, NRE holds the potential of being the most cost-efficient integration approach due to SAG in line with very limited III-V material deposition. However, the key open question is what NR crystal quality, and hence, device performance can be realized. This question will be addressed in the second part of the paper, reporting about the latest developments at imec. Figure 1

ITUAVs: Intermittently Tethered UAVs for Future Wireless Networks

We propose the intermittently tethered unmanned aerial vehicle (iTUAV) as a tradeoff between the power availability of a tethered UAV (TUAV) and the flexibility of an untethered UAV. An iTUAV can provide cellular connectivity while being temporarily tethered to the most adequate ground anchor. Also, it can flexibly detach from one anchor, travel, then attach to another one to maintain/improve the coverage quality for mobile users. Hence, we discuss here the existing UAV-based cellular networking technologies, followed by a detailed description of the iTUAV system, its components, and mode of operation. Subsequently, we present a comparative study of the existing and proposed systems highlighting the differences in key features such as mobility and energy. To emphasize the potential of iTUAV systems, we conduct a case study, evaluate the iTUAV performance, and compare it to benchmarks. Obtained results show that with only 10 anchors in the area, the iTUAV system can serve up to 90% of the users covered by the untethered UAV swapping system. Moreover, results from a small case study prove that the iTUAV allows to balance performance/cost and can be implemented realistically. For instance, when user locations are clustered, with only 2 active iTUAVs and 4 anchors, achieved performance is superior to that of the system with 3 TUAVs, while when considering a single UAV on a 100 minutes event, a system with only 6 anchors outperforms the untethered UAV as it combines location flexibility with increased mission time.

Performance analysis of pulse shaping rectangular pulse through frequency selective fading transmission channel in OFDM system

- Long Term Evolution or LTE is a fourth generation (4G) cellular network technology that uses OFDM as its multiplexing technique for fast and effective wireless communication services. OFDM uses the concept of orthogonality for bandwidth efficiency by multiplexing overlapping subcarriers. But in its implementation, this system will have problems in the transmission channel. In addition, OFDM has the major drawback of being susceptible to frequency offset between the transmitter and receiver. This offset frequency will cause the orthogonal character built in the OFDM system to experience a decrease in performance. This decrease in performance is due to the occurrence of ICI. To overcome this, a method is needed to improve system performance. The method used in this research is Rectangular Pulse. Therefore, this research is made to combine the advantages of OFDM and pulse shaping and is expected to produce a superior system and can contribute to the improvement of 4G-LTE implementation. The approach method in this research applies a quantitative descriptive approach to analyze system performance and in this research uses the simulation method as a reference to obtain research data using the Matlab application.

Medium Access Control Techniques for Massive Machine-Type Communications in Cellular IoT Networks

A key component of the Internet of things (IoT) ecosystem is wide-area network connectivity, for which cellular network technologies are a promising option through their support of massive machine-type communications (mMTC). However, numerous devices transmitting sporadically small data packets in a highly synchronized way can generate overload on the radio access network. This situation leads to a shortage of resources, especially those associated with the random access procedure for contention, control, and data transmission, causing preamble collision, control message blocking, and data collision. As a result, mMTC traffic can jeopardize the provisioning of quality of service (QoS) to end-devices, decrease the network efficiency, and increase access latency and device energy consumption. This paper proposes medium access control (MAC) techniques for addressing problems related to the support of mMTC in cellularnetworks. First, a solution for allocating control resources with QoS provisioning and access differentiation is provided, including a resource management model, a scheduling algorithm, and a message prioritization policy. Second, a mechanism for reducing data collisions is also proposed. This solution comprises a protocol in which every device with scheduled retransmission uses a probabilistic policy to decide whether to retransmit, a novel method at the device to estimate the number of nodes trying random access, and two different retransmission policies employing this estimation. Results show that the proposals support QoS, decrease access latency, decrease the device energy consumption, and increase resource utilization under massive random access.

Intelligent Access to Unlicensed Spectrum: A Mean Field Based Deep Reinforcement Learning Approach

As the demand for mobile data traffic continues to grow, offloading data traffic to unlicensed spectrum is a promising approach that can relieve the pressure on cellular systems. Therefore, it is an urgent need to propose an unlicensed spectrum access method to guarantee the harmonious and efficient coexistence between cellular network technologies such as LTE and incumbent users such as WiFi in the unlicensed spectrum. However, existing coexistence schemes such as licensed assisted access (LAA) and LTE-unlicensed (LTE-U) still suffer from inefficient spectrum utilization and unsatisfactory fairness. In the paper, we formulate the optimization problem of the unlicensed spectrum access among multiple small bases (SBSs) as a game, and then solve the Nash Equilibrium (NE) with cooperative and distributed multi-agent deep reinforcement learning (MADRL). Specifically, a two level access framework for the coexistence scenario, which consists of feedback cycle and executive cycle, is first proposed, and then the key elements of MADRL including state, action, reward and Q-network are designed in detail based on the proposed access framework. To overcome the problems of learning divergence and prohibitive computation overhead in the coexistence scenario with multiple SBSs due to the non-stability phenomena, we adopt the mean field technology to solve the NE, which can simplify the process of solving NE by converting the interaction of an agent with the remaining multiple agents into an action with the average effect of them. Simulation results show that 1) the proposed algorithm can overcome the learning divergence problem and converge to the NE quickly, and 2) the proposed algorithm can achieve the bi-objective optimization of total throughput and fairness of the coexistence network, and can achieve better performance in terms of throughput and fairness compared with the baseline methods such as Cat-4 LBT, Cooperative LBT and Random schemes.

Parallel and Memory-Efficient Distributed Edge Learning in B5G IoT Networks

Nowadays we are witnessing rapid development of the Internet of Things (IoT), machine learning, and cellular network technologies. They are key components to promote wireless networks beyond 5G (B5G). The plenty of data generated from numerous IoT devices, such as smart sensors and mobile devices, can be utilised to train intelligent models. But it still remains a challenge to efficiently utilise IoT networks and edge in B5G to conduct model training. In this paper, we propose a parallel training method which uses operators as scheduling units during training task assignment. Besides, we discuss a pebble-game-based memory-efficient optimisation in training. Experiments based on various real world network architectures show the flexibility of our proposed method and good performance compared with state of the art.

Toward 5G Edge Computing for Enabling Autonomous Aerial Vehicles

Offloading processes responsible for a robot’s control operation to external computational resources has been in the spotlight for many years. The vision of having access to a full cloud cluster for any autonomous robot has fueled many scientific fields. Such implementations rely strongly on a robust communication link between the robot and the cloud and have been tested over numerous network architectures. However, various limitations have been highlighted upon the realization of such platforms. For small-scale local deployments, technologies such as Wi-Fi, Zigbee, and blacktooth are inexpensive and easy to use but suffer from low transmit power and outdoor coverage limitations. In this study, the offloading time-critical control operations for an unmanned aerial vehicle (UAV) using cellular network technologies were evaluated and demonstrated experimentally, focusing on the 5G technology. The control process was hosted on an edge server that served as a ground control station (GCS). The server performs all the computations required for the autonomous operation of the UAV and sends the action commands back to the UAV over the 5G interface. This research focuses on analyzing the low-latency needs of a closed-loop control system that is put to the test on a real 5G network. Furthermore, practical limitations, integration challenges, the intended cellular architecture, and the corresponding Key Performance Indicators (KPIs) that correlate to the real-life behavior of the UAV are rigorously studied.

SSB-Based Signal Processing for Passive Radar Using a 5G Network

This paper presents an alternative processing chain for the passive radar using fifth-generation (5 G) standard technology for broadband cellular networks as illuminators of opportunity. The proposition is to use a 5 G synchronization signal block's (SSB) periodically transmitted modulated pulse in 5G-based passive coherent location (PCL) system processing. Although the SSB periodicity limits the velocity ambiguity, the paper describes a solution to tackle this problem in a single target scenario. The method is advantageous when there is a lack of transmission in the telecommunication channel, and the 5 G SSB is the only existing signal. The paper proposes a signal processing pipeline for 5G-based PCL that is inspired by passive radars using non-cooperative pulse radar as an illumination source. The method has been validated using simulated and real-life 5 G data measurements. The results presented in the paper show the possibility of detecting a moving target with a lack of data transmission in the 5 G network, using only the SSB when the classical passive radar signal processing fails. The presented results prove the possibility for a significant increase of 5 G network-based PCL utilization in short-range applications.

Influence of 4th generation broadband cellular network technology on undergraduate education

The influence of 4th generation broadband cellular network technology on education is explored in this paper. With the widespread use of smartphones and tablets, students are increasingly using mobile devices to access learning resources, communicate with peers, and complete assignments. The advent of 4G technology has had a revolutionary impact on undergraduate education, transforming the way students access information and interact with course materials. With 4G, students can now quickly and easily access online resources, download and stream multimedia content, collaborate with classmates in real-time, and participate in remote learning. This technology has had a profound influence on the way education is managed today, providing faster and more efficient access to educational resources and a personalized learning experience while streamlining administrative processes and assisting teachers in instruction. 4G technology has completely revolutionized the way education is thought of and experienced, creating an open environment, interactivity, and increasingly specialized training for students and professionals alike.

An Efficient Beamformer for Interference Suppression Using Rectangular Antenna Arrays

Over the past ten years, the development of fifth-generation cellular network technology opens the door to the deployment of huge sensors inside the Internet of Things (IoT), challenging the technologies of communications. IoT establishes wireless communication between numerous physical things to connect them over the Internet, as a result, these things may seriously pollute the environment for electromagnetic propagation. This paper proposes an efficient beamformer based on binary bat algorithm for interference suppression in wireless technology applications. The proposed beamformer utilizes the technique of controlling only the phase of excitation weights in uniform rectangular arrays. This beamformer can produce optimal patterns with minimal distortions in sidelobe regions while maintaining the main lobe and placing nulls in the direction of interfering signals. To demonstrate this ability, the proposed beamformer is evaluated through several scenarios and compared to a beamformer based on Binary Particle Swarm Optimization (BPSO). The results show that the proposed beamformer maintains the main lobe toward the desired user direction while imposing nulls in unwanted user directions (interferences) and that it surpassed BPSO-based beamformers in terms of convergence speed and interference suppression ability.

A New Vertical Handover Prediction Method for Heterogeneous Wireless Networks

Long Term Evolution (LTE) is the fourth generation (4G) cellular network technology that provides improved performance that related to data rate, coverage and capacity compared to earlier cellular systems. The addition of many small cells in a heterogeneous network configuration provides a means to enhance capacity through extreme frequency reuse. The heterogeneous environment of different network technologies can provide high data rate and enhance multimedia services, but it is challenging to provide optimized handover (HO). In this paper, a new method is proposed to select the optimal network from available networks to which a UE may be handed over to achieve better QoS performance. The aggregation of multiple criteria for calculation of overall ranking of networks is obtained by Analytical Hierarchy Process (AHP) [1] and is combined with the history of previously visited cells and regression analysis of the Layer 1 (L1) and Layer 3 (L3) filtered Received Signal Strength (RSS) data for prediction of future values. The AHP is used to calculate the weights for the system attributes and to rank the available networks based on multiple criteria Multiple Attribute Decision Making (MADM). The sequence of visited cells is used in target network selection as it reduces frequent handover. The sequence of visited cells would be modeled as a Markov Chain. To assess RSS, beside L1, L3 filtering RSS prediction and smoothing is used to predict future signal samples to hasten the process of HO. RSS forecasting is used to predict handover necessity so as to reduce the handover delay. The results show that the number of handovers is reduced by up to 50% compared to the conventional AHP. The results also show that the threshold crossing rate and average duration of fades are reduced by 47% compared with the AHP. Handover delay is also reduced by up to 40 ms due to RSS forecasting.

Future Ready Banking with Smart Contracts - CBDC and Impact on the Indian Economy

India is significantly diverse in culture and how it promotes business transactions. Though we are very acquainted with cash, cards, and online mode of payment, the Indian rural economy still believes in the barter system. At this juncture, India is evolving as a tech power house, and its economy is thriving to embrace cryptocurrency as a medium of exchange. After the Indian finance minister declared the same last February that India is working towards building its legal tender called Central Bank-backed Digital Currency (CBDC), this paper is making an impact in explaining our strengths, weakness, market readiness, and necessity to adopt a digital rupee when India's economy is highly regarded as a cashoriented economy. Is our country ready to accept the new technological shift in smart banking in the form of a digital rupee? The paper highlights the socioeconomic and technical challenges our planners need to understand before changing the Central banks' monetary policies. The deployment of fifth-generation (5G) cellular network technology has sparked renewed interest in the potential of blockchain to automate different cellular network use cases. 5G is projected to open up new market prospects for small and large businesses. The article highlights the unique instrument of the digital rupee to enhance peer-to-peer transactions with the evolution of 5G mobile technology.

5G/B5G mmWave Cellular Networks with MEC Prefetching Based on User Context Information.

To deal with recent increasing mobile traffic, ultra-broadband communication with millimeter-wave (mmWave) has been regarded as a key technology for 5G cellular networks. In a previous study, a mmWave heterogeneous network was composed of several mmWave small cells overlaid on the coverage of a macro cell. However, as seen from the optical fiber penetration rate worldwide, it is difficult to say that backhaul with Gbps order is available everywhere. In the case of using mmWave access under a limited backhaul capacity, it becomes a bottleneck at the backhaul; thus, mmWave access cannot fully demonstrate its potential. On the other hand, the concept of multi-access edge computing (MEC) has been proposed to decrease the response latency compared to cloud computing by deploying storage and computation resources to the user side of mobile networks. This paper introduces MEC into mmWave heterogeneous networks and proposes a content prefetching algorithm to resolve such backhaul issues. Context information, such as the destination, mobility, and traffic tendency, is shared through the macro cell to the prefetch application and data that the users request. Prefetched data is stored in the MEC and then transmitted via mmWave without a backhaul bottleneck. The effectiveness is verified through computer simulations where we implement realistic user mobility as well as traffic and backhauling models. The results show that the proposed framework achieved 95% system capacity even under the constraint of a 1 Gbps backhaul link.

Real-Time Temperature Distribution Monitoring in Chinese Solar Greenhouse Using Virtual LAN

The internal air temperature of Chinese solar greenhouse (CSG) has the problem of uneven spatial and temporal distribution. To determine temperature distribution at different locations, we designed a greenhouse temperature real-time monitoring system based on virtual local area network (VLAN) and estimate, including interpolation estimation module, data acquisition, and transmission module. The temperature data were obtained from 24 sensors, and the Ordinary Kriging algorithm estimated the temperature distribution of the whole plane according to the data. The results showed that the real-time temperature distribution monitoring method established was fast and robust. In addition, data validity rate for VLAN technology deployed for data transmission was 2.64% higher than that of cellular network technology. The following results are obtained by interpolation estimation of temperature data using gaussian model. The average relative error (ARE) of estimate, mean absolute error (MAE), root mean square error (RMSE), and determination coefficient (R2) were −0.12 °C, 0.42 °C, 0.56 °C, and 0.9964, respectively. After simple optimization of the number of sensors, the following conclusions are drawn. When the number of sensors were decreased to 12~16, MAE, RMSE, and R2 were 0.40~0.60 °C, 0.60~0.80 °C, and >0.99, respectively. Furthermore, temperature distribution in the greenhouse varied in the east–west and north–south directions and had strong regularity. The calculation speed of estimate interpolation algorithm was 50~150 ms, and greenhouse Temperature Distribution Real-time Monitoring System (TDRMS) realized simultaneous acquisition, processing, and fast estimate.

Comprehensive use of 6G cellular technology accounting activity costs and cyber security

The purpose of this study was in the research of prospects for simultaneous use of 6G generation cellular communications for the purposes of automatization of cost accounting of the activity of enterprises of various branches and cybersecurity of accounting information. The theoretical and methodological aspects of the use of 6G cellular network technologies for accounting and cybersecurity purposes have been studied on the basis of general research methods – institutional and innovative; economic and mathematical methods of analysis using Excel spreadsheets were used to predict the pace of implementation of cellular communication of new generations; to determine perspective areas of use of 6G technology – methods of bibliographic and comparative analysis using the information resource "ResearchGate". The methods of permanent collection and transmission of accounting data about the production process and the procedure for monitoring the stay of employees or outsiders at the workplace using production equipment connected to the 6G cellular network has been developed. The procedure for combining the functional abilities of Global Positioning System (GPS) and cellular positioning (mobile subscribers) for accounting of transport costs and control over the movement and economic use of vehicles has been proposed.The procedure for combining unmanned aerial vehicles in a cluster on the basis of 6G communication with the purpose of aerovisual surveillance of agricultural and construction activities for automated accounting of production costs and prevention of unauthorized getting into an enterprise of persons (drones). The methods for determining the cost of rental space from the lessor based on counting the popularity among visitors and identifying offenders (thieves of information and material resources) through automated monitoring of the location of 6G cellular subscribers. The practical implementation of the developments presented in the article on the use of 6G cellular technologies will contribute to reliable costing and accounting of production costs of production, agricultural, construction, trade activities in combination with effective cyber protection of enterprises in preventing and detecting violators of information and territorial security. Further research is needed on the methods of management of business entities on the basis of accounting information obtained with the use of 6G cellular network technology.