Massive Machine Communication Research Articles

Enhancing Wireless Network Efficiency with the Techniques of Dynamic Distributed Load Balancing: A Distance-Based Approach.

The unique combination of the high data rates, ultra-low latency, and massive machine communication capability of 5G networks has facilitated the development of a diverse range of applications distinguished by varying connectivity needs. This has led to a surge in data traffic, driven by the ever-increasing number of connected devices, which poses challenges to the load distribution among the network cells and minimizes the wireless network performance. In this context, maintaining network balance during congestion periods necessitates effective interaction between various network components. This study emphasizes the crucial role that mobility management plays in mitigating the uneven load distribution across cells. This distribution is a significant factor impacting network performance, and effectively managing it is essential for ensuring optimal network performance in 5G and future networks. The study investigated the complexities associated with congested cells in wireless networks to address this challenge. It proposes a Dynamic Distance-based Load-Balancing (DDLB) algorithm designed to facilitate efficient traffic distribution among contiguous cells and utilize available resources more efficiently. The algorithm reacts with congested cells and redistributes traffic to its neighboring cells based on specific network conditions. As a result, it alleviates congestion and enhances overall network performance. The results demonstrate that the DDLB algorithm significantly improves key metrics, including load distribution and rates of handover and radio link failure, handover ping-pong, and failed attached requests.

Support of resourses redistribution in NB-IоT LTE networks

The NB-IoT is expected to be used with the deployed LTE network as well as future 5G networks. The rapid development of the IoT concept has entailed the need to provide wireless communication to a huge number of devices included in the infrastructure. As part of the 5G NR standard for such devices, Massive Machine Communications (m MTC) technology is focused on optimizing the use of network resources to support a large number of stable connections per unit area. The Narrowband Internet of Things (NB-IoT) has been analyzed to enable the connectivity of a wide range of new IoT devices and services to the mobile network. The NB-IoT is also shown to be designed for fixed devices with low data transmission and low consumption, leading to an increase in the number of interconnected devices. In turn, standard NB-IoT modules attempting to simultaneously request radio channel resources for uplink data transmission may suffer from random access preamble collision. The proposed model describes the macro- and microcells of an NB-IoT LTE cluster. An increase in the efficiency of using the bandwidth of networks based on macro- and microcells with a high concentration of users of the NB-IoT LTE networks is shown. Numerical results of an analysis of identifying factors affecting system performance are presented. A linear increase in throughput has been revealed depending on the throughput of the macrocell when using the shared resource of the macrocell for a microcell of equal size without prior repacking of channels when servicing moving subscribers. In the absence of moving subscribers, the additional load is serviced, and the efficiency of using a macro cell increases almost 3 times. In addition, repacking channels significantly increases system throughput.

Smart Collaborative Contract for Endogenous Access Control in Massive Machine Communications

Emerging information technologies have accelerated the construction of the Industrial Internet of Things (IIoT). Unfortunately, the explosive growth of various services has caused serious challenges to access control in terms of scalability and trustworthiness. In this paper, we proposed the smart collaborative contract based endogenous access control mechanism. First, access control procedures running on centralized servers are migrated to distributed equipment located inside the data plane, which can reduce the transmission overhead and improve service capacity. Second, the smart collaborative contract is designed for credibility enhancement since part of attackers may attempt to compromise access control. It covers terminal behavior assessment and service request recording. Experiments conducted in a prototype show that the performance of the proposed scheme is better than the traditional solution and is resistant to common attacks.

Energy Efficiency of User-Centric, Cell-Free Massive MIMO-OFDM with Instantaneous CSI.

In the user-centric, cell-free, massive multi-input, multi-output (MIMO) orthogonal frequency division multiplexing (OFDM) system, a large number of deployed access points (APs) serve user equipment (UEs) simultaneously, using the same time–frequency resources, and the system is able to ensure fairness between each user; moreover, it is robust against fading caused by multi-path propagation. Existing studies assume that cell-free, massive MIMO is channel-hardened, the same as centralized massive MIMO, and these studies address power allocation and energy efficiency optimization based on the statistics information of each channel. In cell-free, massive MIMO systems, especially APs with only one antenna, the channel statistics information is not a complete substitute for the instantaneous channel state information (CSI) obtained via channel estimation. In this paper, we propose that energy efficiency is optimized by power allocation with instantaneous CSI in the user-centric, cell-free, massive MIMO-OFDM system, and we consider the effect of CSI exchanging between APs and the central processing unit. In addition, we design different resource block allocation schemes, so that user-centric, cell-free, massive MIMO-OFDM can support enhanced mobile broadband (eMBB) for high-speed communication and massive machine communication (mMTC) for massive device communication. The numerical results verify that the proposed energy efficiency optimization scheme, based on instantaneous CSI, outperforms the one with statistical information in both scenarios.

Convergence application of handle platform for industrial data classification and grading and 5G technology

With the continuous upgrading of the national industrial Internet, the traditional application-centric data organization method has gradually been unable to meet the requirements of large-scale interoperability and sharing of industrial data and data security in the era of big data. With the help of the classification and grading of industrial data, cross-regional, cross-departmental, and cross-domain information query and sharing can be realized at the macro level; at the micro level, product information can be traced through identification analysis, and information can be achieved safely and controllably through its internal security management mechanism. In the field of industrial Internet, network equipment is usually required to have a large-scale connection expansion capability; in some fields such as telemedicine and industrial control, it requires the communication process to have low latency and high reliability capabilities; and in some areas such as autonomous driving and ultra-high-definition live transmission, the communication process requires the ability to transmit large-bandwidth data. Compared with 4G technology, 5G communication technology, its massive machine communication capabilities and high reliability and low latency characteristics make it a reliable technical guarantee for the Internet of Everything at this stage. Therefore, it is urgent to realize the integration of 5G technology and industrial data classification and grading technology. Based on the in-depth interpretation of the characteristics of 5G technology and the detailed description of the handle system, this paper proposes a method of fusion of the handle platform and 5G technology, laying the cornerstone for the effective implementation of industrial data classification and grading.

A Deep-Learning Method for Device Activity Detection in mMTC Under Imperfect CSI Based on Variational-Autoencoder

Large-scale deployment of massive device connectivity is a crucial communication challenge for Internet of Things (IoT) networks, which consist of a huge number of devices with sporadic traffic. In massive Machine Communication Scenario (mMTC), it is very important for the serving base-station (BS) to identify the active devices in each coherence block. This paper proposes a deep neural network (DNN) based on variational autoencoder (VAE) for device activity detection in mMTC under imperfect channel state information (CSI). A framework of variational optimization is constructed and the learning network structure is also designed. The derivation on the loss function for network training is presented and numerical results are provided to illustrate the accuracy of our method. The performance demonstrates the merits of the proposed method by comparison with the traditional compressed sensing algorithms, which are widely applied in multi-user detection.

Efficient network coding-based data transfer framework for multihop wireless communication

With the growing demands of wireless applications and mobile data connections, wireless communication is expected to provide the ever-increasing demand for higher data rate and efficient data communication. Energy is also one of the hot issues needed to be considered for future wireless networks. In this paper, an efficient network coding-based data transfer (E-neco) framework is developed to achieve more energy-saving and bandwidth-efficient data communication for data transmission, data collection and data sharing services. For these data transfer applications, we propose new network coding-based transmission schemes and medium access control protocols. Topology and network coding techniques are utilised in the framework. This is a conceptual framework developed for future generation wireless communication such as multihop communication, massive machine communication, device-to-device communication and new techniques can be added to support future demanding services. Simulation results reveal an improvement in terms of throughput, latency, fairness, energy consumption and network lifetime.

Enhanced 5G Throughput using UFMC Multiplexing

The next era of communication, fifth generation (5G), substituted the fourth generation (4G) in different aspects. For instance, 5G should support massive machine communications (MMC), which uses very small message signals. The cyclic prefix orthogonal frequency division multiplexing (CP-OFDM), which is adopted in 4G systems, requires a huge number of bits as an overhead along with the cyclic prefix.Moreover, the sinc-shape of the subcarriers in the frequency domain makes the rectangular pulse in the time domain have long tails; therefore, it is not conceivable to transmit short message signals, which requires no synchronization, while CP-OFDM requires tight synchronization both in time and frequency domain. Accordingly, a new air-interface has to be introduced to overcome the CP-OFDM shortcomings. Various candidates have been suggested such as the universal filtered multicarrier (UFMC). UFMC divides the allocated band into several sub-bands and filter them individually, rather than filtering completely the band. Thus, enabling low tails, this gives more flexibility for MMC signals. In this paper, a comparison and design parameters have been set up, the simulation results show that the UFMC outperforms the CP-OFDM with respect to power spectral density efficiency and the throughput with different signal-to-noise ratios with low and high user equipment velocities.

Upcoming 5-G Wireless technology and its security concept

Abstract: The abbreviation of 5G technology is fifth generation technology. Today globalization in telecommunication has seen lots of improvements like 0G, 1G to 2.5G and from 3G to 5G. 5G is a major phase of mobile telecommunication beyond 4G standard. 5G technology is not currently commercially used for any country of the world. 5G supported voice over IP (VOIP) enabled devices. The advantages of 5G technology are that users can simultaneously connect to the multiple wireless devices. The aim of 5G planning is to provide the higher density of mobile broadband users and supporting device-to-device ultra-reliable and massive machine communications and lower latency than 4G and lower battery consumption for better implementation of the internet of things.5G wireless technology is depend on IEEE 802.11 wireless technology. Wireless local area network (WLAN) wireless metropolitan area (WLAN) and AD-hoc wireless technology are included in 5G wireless technology. This paper cover the security of 5G wireless technology. The main aim is to provide protection of 5G wireless technology

Guest Editorial Special Issue on 5G Wireless Systems With Massive MIMO

The goals of the fifth generation (5G) cellular communication systems are to achieve 10–100 times higher typical user data rates, ranging from 1 to 10 Gbps in dense urban environments. 5G may support 10–100 times more connected devices. Furthermore, the energy efficiency for low-power massive machine communications is to be improved more than ten times. However, there is no clear roadmap to achieve such high performance targets. The introduction of new technologies in 5G systems is necessary. The aim of the papers in this special section highlight how massive MIMOmeet 5G requirements with developing mobile networks. These papers focus on new technologies being investigated that have great potential to let massive MIMO be practical.

A flexible 5G frame structure design for frequency-division duplex cases

A 5G frame structure designed for efficient support of users with highly diverse service requirements is proposed. It includes support for mobile broadband data, mission-critical communication, and massive machine communication. The solution encompasses flexible multiplexing of users on a shared channel with dynamic adjustment of the transmission time interval in coherence with the service requirements per link. This allows optimizing the fundamental tradeoffs between spectral efficiency, latency, and reliability for each link and service flow. The frame structure is based on in-resource physical layer control signaling that follows the corresponding data transmission for each individual user. Comparison against the corresponding LTE design choices shows attractive benefits.

Scenarios for 5G mobile and wireless communications: the vision of the METIS project

METIS is the EU flagship 5G project with the objective of laying the foundation for 5G systems and building consensus prior to standardization. The METIS overall approach toward 5G builds on the evolution of existing technologies complemented by new radio concepts that are designed to meet the new and challenging requirements of use cases today's radio access networks cannot support. The integration of these new radio concepts, such as massive MIMO, ultra dense networks, moving networks, and device-to-device, ultra reliable, and massive machine communications, will allow 5G to support the expected increase in mobile data volume while broadening the range of application domains that mobile communications can support beyond 2020. In this article, we describe the scenarios identified for the purpose of driving the 5G research direction. Furthermore, we give initial directions for the technology components (e.g., link level components, multinode/multiantenna, multi-RAT, and multi-layer networks and spectrum handling) that will allow the fulfillment of the requirements of the identified 5G scenarios.