5G Wireless Research Articles

Design and implementation of hybrid fed array antennae for Sub-6 GHz and 5G mm-wave communication and wireless applications

Abstract This paper proposes fractal-inspired array antennae for wideband applications. The proposed antennae have a resonance frequency range of 20–40 GHz. The modified fractal antennae are fabricated with a height of 1.6 mm, substrate width, and length of 100, 50, 25, and 18.75 mm2, and a simulated result shows that the gain is increased to 11.04, 11.9, 8.4, and 6 dBi, and the designed antennae radiate power with directivity of 11.3, 13.4, 9.29, and 7.17 dBi concerning proposed designs A, B, C, and D, respectively. The proposed antennae with 5G New Radio (NR) bands have more radiation concerning resonate frequencies in the 20–40 GHz range with Φ = 0°, Φ = 90°, and θ = 90°. Moreover, the bandwidths for applications covered in the 5G NR and sub-6G are 1.92, 0.73, 0.7, 2.4, 1.3, 5.3, and 1.26 GHz, and 3.4, 3.7, 2.67, and 4.65 GHz, and 2, 3.5, and 1.57 GHz, and 2.5, 1.5, and 1.0 GHz with the maximum return loss of 37 dB, 32.8 dB, 31.2 dB, and 23 dB with corresponding resonate frequencies as 21.5, 27.6, 33, and 27.6 GHz concerning designs A, B, C, and D, respectively. The proposed antennae have been implemented and validated using Computer Simulation Technology (CST), Vector Network Analyzer (VNA), spectrum analyzer, and power sensor.

An ultra-high-frequency memristor circuit model

In the context of sixth-generation (6G) wireless communications technology, advanced radio-frequency switches are required to accommodate high-frequency terahertz range and complex modulation techniques. This paper proposes a flexible charge-controlled memristor model specifically designed for ultra-high-frequency applications. It describes in detail the derivation of the behavior model of the proposed memristor circuit. The memristor circuit model is built around four inverters, two multipliers, one integrator, one adder, and one differentiator. Through PSPICE simulation, the typical hysteresis loop of the memristor is thoroughly analyzed, demonstrating its suitability for use in wireless communication systems. The model exhibits a good typical hysteresis loop that operates over a wide frequency range from 100 kHz to 20 THz, meeting the specific requirements of terahertz applications. Compared to existing memristor designs, it operates at a much higher frequency. However, the zero crossing of the typical hysteresis loop deviates when the operating frequency exceeds 20 THz. Furthermore, the proposed memristor model can be customized in terms of set/reset voltage, operating frequency and , and has been verified for use in high speed switches with switching speeds of 19.5 ps. Furthermore, this research fills the gap in ultra-high-frequency memristor modeling, offering valuable insights and guidance for the utilization of memristors in the 6G technology and ultra-high frequency fields.

Intelligent wireless resource management in industrial camera systems: Reinforcement Learning-based AI-extension for efficient network utilization

In this paper, we present an innovative method for replacing wired communication within an operational agile production cell with wireless communication, using a minimal number of access points. Our approach utilizes Reinforcement Learning (RL) to optimize the layout and minimize the required number of access points. We introduce an Artificial Intelligence (AI) agent that facilitates cooperative interaction between cameras and access points, optimizing camera stream utilization and radio coverage. This solution benefits from the recent standardization of The fifth generation of mobile communications (5G) Network Resource Management (NRM) features of the User Equipment (UE) attached to the cameras. To accommodate the dynamic nature of the production cell, our optimization algorithms run during cell operation, necessitating extended training times.Our contributions extend beyond the state-of-the-art by offering a Digital Twin (DT) environment equipped with physics and radio propagation capabilities, fast raytracing for radio propagation modeling, curriculum-learning-based reinforcement learning, and a Physical Twin (PT) of the radio-connected camera with self-adjusting scene setup capabilities. This comprehensive proposal combines the efficiency of 5G radio utilization with precise modeling and high-resolution simulations, while also significantly improving training speed.In the Agile Robotics for Industrial Automation Competition (ARIAC) 2020 environment, our methods showed compelling results, with curriculum learning achieving a remarkable 3x speed-up compared to non-curriculum approaches. We also demonstrated that high Quality of Service (QoS) demands can be reduced to just 2% of total time while maintaining consistent productivity Key Performance Indicators (KPIs). Furthermore, we explored the integration of these methods into Internet of Things (IoT) devices with limited performance capabilities. In conclusion, our approach offers significant benefits and savings for IoT devices, networks, edge clouds, and industry players.

Co-Channel Interference Mitigation in 5g Network using Particle Swarm Optimization

The co-channel interference problem in 5G wireless networks is the subject of this research project. Even with the improvements brought forth by 5G, co-channel interference still degrades network speed and signal quality. Particle Swarm Optimization (PSO) is the method used in this study to minimize this interference and improve network performance by fine-tuning resource allocation settings. PSO-based interference mitigation, network modeling, simulation, an overview of the literature, and comparative analysis are all included in the study. The study is valuable for communication engineers since it explores PSO as a means of improving network quality and expanding our knowledge of wireless technology, even though it is restricted to co-channel interference and PSO. In the sphere of 5G wireless communication, this discovery represents a substantial advancement. The application of particle swarm optimization has shown to be innovative in addressing the complex problem of co-channel interference. Insights into the possibilities of clever optimization strategies for interference reduction can be gained from the applied models and results. With 5G networks set to revolutionize the digital environment, these findings provide a strong basis for future research efforts focused at refining interference avoidance techniques and ultimately boosting the performance and dependability of these networks.

Design and implementation of nonlinear precoding for MIMO-SDMA toward 6G wireless

Design and implementation of nonlinear precoding for MIMO-SDMA toward 6G wireless

Metamaterial-based Octagonal Ring Penta-band Antenna for Sub-6 GHz 5G, WLAN, and WiMAX Wireless Applications

Metamaterial-based Octagonal Ring Penta-band Antenna for Sub-6 GHz 5G, WLAN, and WiMAX Wireless Applications

Design and realization of Lora wireless communication and 5G based middle and long distance running system under the healthy development of innovative sports

Abstract In innovative sports, integrating new-generation technologies is revolutionizing how we approach and analyze athletic performance. Our research focuses on developing a sophisticated middle and long-distance running system that harnesses the power of modern communication tech, including LoRa connectivity and 5G edge computing. By applying the IMF method, we effectively minimize data noise, enhancing the fidelity of sports signal analysis. Our system’s prowess is evident in its low latency (2.97 ms at 100 nodes), high accuracy (rating of 6.8), and impeccable anti-collision capabilities during competitive events. In practical tests over 1000 meters, it dramatically reduced timing errors to a mere fraction of manual methods, demonstrating its precision and potential to transform physical training and education. This innovation stands as a beacon for the future of sports, driving the integration of technology and athletics.

A Hybrid Machine Learning Approach for Improvised QoE in Video Services over 5G Wireless Networks

A Hybrid Machine Learning Approach for Improvised QoE in Video Services over 5G Wireless Networks

The Design of Low-Profile, High Gain Meta-Surface Based Microstrip Antenna for 5G Wireless Communication Systems

The Design of Low-Profile, High Gain Meta-Surface Based Microstrip Antenna for 5G Wireless Communication Systems

Adaptive VNF Placement Considering Overall Latency and 5G Wireless Channel Reliability in Industry 4.0: A Reinforcement Learning Based Approach

Adaptive VNF Placement Considering Overall Latency and 5G Wireless Channel Reliability in Industry 4.0: A Reinforcement Learning Based Approach

DESIGN OF A SWITCHED BEAM ANTENNA SYSTEM USING A 4 × 4 BUTLER MATRIX FOR WIRELESS COMMUNICATION APPLICATIONS

Demand for quality service within the cellular network, which has many cells within the cluster, has certain requirements to satisfy the customer or subscriber at any cost. Hence, a reliable approach to provide quality service to the subscriber is needed, and in that attempt, a switched beam system is proposed, which is composed of a Butler matrix operating at 2 GHz for 5G wireless communication systems. The Butler matrix operates at 2 GHz, however, and has an overall bandwidth of 1.2 GHz, ranging from 1.8 GHz to 3 GHz. The beamforming operation is completed by incorporating an antenna array; typically for such applications a linear array with half lambda spacing is preferred. Here, the antenna array is made of a dielectric material, hence forming a dielectric resonator array operating at the same frequency as that of the Butler matrix. To complete the switched beam system, a radiofrequency source is chosen, typically USRP 2900 from National Instruments, to provide excitation to the Butler matrix throughout its operation. The simulation is carried out in Ansys HFSS and PCB Antenna Designer from MathWorks. This article gives the simulation as well as measured results of the Butler matrix and dielectric resonator antenna and draws a conclusion of the performance of the system based on simulated and measured results.

5G Wireless Communication Technology Concepts and Related Applications

5G Wireless Communication Technology Concepts and Related Applications

Distributed Adaptive Robust Restoration Scheme of Cyber-Physical Active Distribution System With Voltage Control

The increasing penetration of distributed generators (DGs) and the advancement of information and communication technologies (ICTs) will facilitate the transformation of the traditional passive distribution network towards a cyber-physical active distribution system (CPADS). With the increasing risks of extreme events, such as natural disasters (e.g., flooding) and cyber-physical attacks, it is critical for CPADS to formulate a restoration scheme to improve its resilience. Therefore, in this paper, a distributed adaptive robust restoration scheme with voltage/var control is presented to cope with the high-impact but low-frequency events. First, a detailed cyber-physical system model is established, including the dynamic routing and the quality-of-services (QoS) in both optical fiber networks and 5G wireless networks. Then, the interactions between the cyber system and the physical system are analyzed. Based on the cyber-physical system model, a two-stage restoration scheme with voltage/var control is proposed by coordinately scheduling different network assets in day-ahead and in real-time. The formulated problem is solved by adaptive robust optimization (ARO). To further enhance the resilience of the CPADS, a distributed restoration framework is proposed. The distributed problem is solved by the alternating direction method of multipliers (ADMM) algorithm, and the convergence of the discrete problem is ensured by introducing the alternating optimization procedure (AOP). Considering the cyber faults, a boundary variable compensation and residual relaxation mechanism is proposed in ADMM. The proposed framework and methodology are verified in the case study. The convergence and the efficiency of the proposed algorithm are verified. Compared with the state-of-art works, the advantages in load restoration capability of the proposed method are shown.

A Novel MIMO Antenna Integrated With a Solar Panel and Employing AI-Equalization for 5G Wireless Communication Networks

A Novel MIMO Antenna Integrated With a Solar Panel and Employing AI-Equalization for 5G Wireless Communication Networks

Massive MIMO for Serving Federated Learning and Non-Federated Learning Users

With its privacy preservation and communication efficiency, federated learning (FL) has emerged as a promising learning framework for beyond 5G wireless networks. It is anticipated that future wireless networks will jointly serve both FL and downlink non-FL user groups in the same time-frequency resource. While in the downlink of each FL iteration, both groups simultaneously receive data from the base station in the same time-frequency resource, the uplink of each FL iteration requires bidirectional communication to support uplink transmission for FL users and downlink transmission for non-FL users. To overcome this challenge, we present half-duplex (HD) and full-duplex (FD) communication schemes to serve both groups. More specifically, we adopt the massive multiple-input multiple-output technology and aim to maximize the minimum effective rate of non-FL users under a quality of service (QoS) latency constraint for FL users. Since the formulated problem is nonconvex, we propose a power control algorithm based on successive convex approximation to find a stationary solution. Numerical results show that the proposed solutions perform significantly better than the considered baselines schemes. Moreover, the FD-based scheme outperforms the HD-based counterpart in scenarios where the self-interference is small or moderate and/or the size of FL model updates is large.

SER Analysis of GFDM System οver 𝜶 – 𝝁 Fading Channel for 5G Wireless Applications

SER Analysis of GFDM System οver 𝜶 – 𝝁 Fading Channel for 5G Wireless Applications

Graphene-based antenna for 5G wireless communications - a bibliometric-thematic analysis and future directions

Graphene-based antenna for 5G wireless communications - a bibliometric-thematic analysis and future directions

5G Wireless Technology: New Era of Connectivity

5G Wireless Technology: New Era of Connectivity

Fuzzy Logic for the Improving of Handover Decision and the Adaptive Adjustment of Control Parameters in 5G Wireless Networks

Handover process is one of the most important aspects of mobility management in 5G wireless networks. It becomes a hot topic for researchers because it constitutes a guarantee of communication continuity during the user's movement, in addition to being the basic step on which the mobility load balancing process depends to distribute the load between the cells. The focus on this process is whether by providing solutions to improve the handover decision-making, or by modifying the values of the handover control parameters in a way that it guarantees the reduction of handover problems, because the inaccurate or unnecessary modification of these parameters values will cause a degradation in the quality of service. This paper presents a study targeting two mechanisms to improve handover decision-making and selection of handover control parameters adaptively based on different schemes. The first one, based on a learning model called LIM2 and the second one is based on fuzzy logic and is called RHOT-FLC. The results show that the RHOT-FLC mechanism, which relies on fuzzy logic and takes into account the user's velocity provides better performance in term of average throughput, packet drop rate, average HOPP probability, average HO latency, HO failure.

Self-Optimization of Handover Control Parameters for 5G Wireless Networks and Beyond

Self-Optimization of Handover Control Parameters for 5G Wireless Networks and Beyond