Coverage Of Wireless Networks Research Articles

Compact size and wideband 4 × 4 MIMO antenna for 5G NR networks

Abstract In this paper, a crescent-shaped four-port MIMO is proposed to deploy in 5 G wireless network coverage with the advantages of wide bandwidth. The MIMO antenna is printed on an RO4003 substrate (ε r = 3.55) with a thickness of 0.203 mm and a rectangular slot in the ground plane to obtain the desired performance. The antenna is duplicated two times in an orthogonal arrangement to achieve 4 ports MIMO antenna for capacity improvement purposes. The antenna satisfies an impedance bandwidth of 20 GHz (20.5–40.5 GHz) with an isolation of ≥22 dB. Furthermore, the suggested 4-port MIMO antenna is fabricated and tested to validate the simulated outcomes, and good consistency between results is achieved in terms of scattering parameters, radiation patterns, gain, and diversity parameters. The presented 4-port MIMO antenna is considered a good candidate for future 5 G NR networks due to its competitive advantages.

Joint Computation Offloading and Trajectory Optimization for Edge Computing UAV: A KNN-DDPG Algorithm

Unmanned aerial vehicles (UAVs) are widely used to improve the coverage and communication quality of wireless networks and assist mobile edge computing (MEC) due to their flexible deployments. However, the UAV-assisted MEC systems also face challenges in terms of computation offloading and trajectory planning in the dynamic environment. This paper employs deep reinforcement learning to jointly optimize the computation offloading and trajectory planning for UAV-assisted MEC system. Specifically, this paper investigates a general scenario where multiple pieces of user equipment (UE) offload tasks to a UAV equipped with a MEC server to collaborate on a complex job. By fully considering UAV and UE movement, computation offloading ratio, and blocked relations, a joint computation offloading and trajectory optimization problem is formulated to minimize the maximum computational delay. Due to the non-convex nature of the problem, it is converted into a Markov decision process, and solved by the deep deterministic policy gradient (DDPG) algorithm. To enhance the exploration capability and stability of DDPG, the K-nearest neighbor (KNN) algorithm is employed, namely KNN-DDPG. Moreover, the prioritized experience replay algorithm, where the constant learning rate is replaced by the decaying learning rate, is utilized to enhance the converge. To validate the effectiveness and superiority of the proposed algorithm, KNN-DDPG is compared with the benchmark DDPG algorithm. Simulation results demonstrate that KNN-DDPG can converge and achieve 3.23% delay reduction compared to DDPG.

Efficient resource allocation using whale optimization for cell-free massive MIMO networks in 6G HetNet

The increase in data rate demands has driven the development of Cell-Free massive Multiple-Input Multiple-Output (CFmMIMO) technology in 6G Heterogeneous Networks (HetNets). This paper proposes an integration of Unmanned Aerial Vehicles (UAVs) and Device-to-Device (D2D) communication in CFmMIMO, aiming to enhance network capacity, coverage, and service delivery in next-generation wireless networks. The paper investigates uplink transmission in a network where Access Points (APs) have imperfect channel state information. It considers Cell-free User Equipment (CUE), UAVs, and D2D pairs, deriving closed-form uplink achievable rates for each user type. Moreover, two optimization problems are formulated to enhance user data rates: one focuses on maximizing the sum data rate through pilot assignment, while the other aims to achieve weighted max–min power control through power allocation. Furthermore, to address these problem, we propose a Modified Whale Optimization Algorithm (MWOA) and a novel Pilot Assignment based on Whale Optimization Algorithm (PAWOA). Performance studies demonstrate significant improvements over state-of-the-art algorithms.

Computation Offloading Based on a Distributed Overlay Network Cache-Sharing Mechanism in Multi-Access Edge Computing

Multi-access edge computing (MEC) enhances service quality for users and reduces computational overhead by migrating workloads and application data to the network edge. However, current solutions for task offloading and cache replacement in edge scenarios are constrained by factors such as communication bandwidth, wireless network coverage, and limited storage capacity of edge devices, making it challenging to achieve high cache reuse and lower system energy consumption. To address these issues, a framework leveraging cooperative edge servers deployed in wireless access networks across different geographical regions is designed. Specifically, we propose the Distributed Edge Service Caching and Offloading (DESCO) network architecture and design a decentralized resource-sharing algorithm based on consistent hashing, named Cache Chord. Subsequently, based on DESCO and aiming to minimize overall user energy consumption while maintaining user latency constraints, we introduce the real-time computation offloading (RCO) problem and transform RCO into a multi-player static game, prove the existence of Nash equilibrium solutions, and solve it using a multi-dimensional particle swarm optimization algorithm. Finally, simulation results demonstrate that the proposed solution reduces the average energy consumption by over 27% in the DESCO network compared to existing algorithms.

Designing a pedagogical framework for mobile-assisted language learning

With the high penetration of mobile devices and wide coverage of wireless networks, mobile-assisted language learning (MALL) has been widely utilized to enhance language teaching and learning. However, the integration of MALL into language pedagogy has been hampered by a lack of a cohesive and unified framework for MALL pedagogy. Most of the existing frameworks were not specifically designed for language pedagogy and failed to balance the technological and pedagogical dimensions of MALL pedagogy. This study sought to promote the incorporation of MALL and tertiary EFL pedagogy by designing a pedagogical framework for MALL (PF4M) using design-based research (DBR) as the overarching research methodology. The DBR investigation adopted a mixed research approach, incorporating systematic review, expert survey, thematic analysis, and expert review. The resulting PF4M is anticipated to aid in the integration of MALL into language pedagogy by offering practical and theoretical guidance for effective teaching and learning. The findings may also suggest future directions for pedagogical innovations in MALL.

PERFORMANCE ANALYSIS OF ACHIEVABLE BIT RATES IN RIS-ASSISTED MASSIVE MIMO NETWORKS AT 28 GHz BAND

Reconfigurable intelligent surface (RIS) technology is a smart way of controlling the radio signal propagation to improve the capacity and coverage of wireless networks. RIS tunes the phase shifts of the incident signals in a dynamic fashion. Channel modeling is an important aspect in RIS-based mmWave communication for the next-generation wireless networks. However, to achieve maximum benefit from RIS-assisted wireless systems, it is essential to provide accurate channel state information (CSI). But, it is very challenging to get accurate CSI because of large number of RIS elements, their passive nature, and the training overhead involved during the channel estimation. To overcome the higher training overhead, in this article we aimed to take advantage of the correlation and sparsity of channels in RIS-assisted channel estimation. The objective of this work is to propose a simplified channel model for the RIS-assisted physical channel of a massive multi-input-multi-output (mMIMO) wireless communication system and analyze its performance in terms of transmitted powers, MIMO configurations, and achievable bit rates. The simulated results proved that the strategic placement of RIS with optimal phase shifts and optimal MIMO configuration can enhance the maximum achievable rate. The achievable rates of the proposed channel modeling are compared with the existing state-of-the-art methods to prove its efficiency. Also, the combination of mMIMO technology along with RIS-assisted communication provides degrees of freedom in terms of signal coverage, energy consumption, and system complexity.

Reviews Based on the Reconfigurable Intelligent Surface Technical Issues

Reconfigurable intelligent surfaces (RISs) are programmable metasurface structures that can control the propagation of electromagnetic waves by changing the electrical and magnetic properties of the surface. They can be used to intelligently reconfigure the wireless environment to improve the capacity and coverage of wireless networks. In recent years, numerous theoretical innovations and prototype tests have demonstrated that the RIS has the advantages of low cost, low power consumption, and easy deployment, and creates many potential opportunities and broad application prospects in 5G and future 6G networks. In this paper, starting from the technological development of RISs, we discussed the technical issues of RISs. The standardization of RISs, types of RISs according to operation modes, channel modeling, considerations for hardware implementation, differences from existing communication modules and the need for active RIS implementation, noise and power characteristics to ensure the efficiency of RISs, and performance parameters of RISs and field test results of RISs in indoor and outdoor environments were reviewed. By resolving the current technical issues of RISs, it is expected that RISs will be successfully used for B5G/6G communication through commercialization.

Coverage Strategy for Small-Cell UAV-Based Networks in IoT Environment

In wireless communication, small cells are low-powered cellular base stations that can be used to enhance the coverage and capacity of wireless networks in areas where traditional cell towers may not be practical or cost-effective. Unmanned aerial vehicles (UAVs) can be used to quickly deploy and position small cells in areas that are difficult to access or where traditional infrastructure is not feasible. UAVs are deployed by telecommunication service providers to provide aerial network access in remote rural areas, disaster-affected areas, or massive-attendance events. In this paper, we focus on the scheduling of beaconing periods as an efficient means of energy consumption optimization. The conducted study provides a sub-modular game perspective of the problem and investigates its structural properties. We also provide a learning algorithm that ensures convergence of the considered UAV network to a Nash equilibrium operating point. Finally, we conduct extensive numerical investigations to assist our claims about the energy and data rate efficiency of the strategic beaconing policy (at Nash equilibrium).

Buoyant airborne turbines in B5G/6G wireless networks: Opportunities, challenges, applications, and future directions

Buoyant airborne turbines (BATs) are powerful, energy-efficient, adaptive, and environment-friendly. They can be utilized as aerial base stations to expand the wireless network coverage, increase capacity and reliability, improve energy efficiency, and provide a higher line of sight (LoS) probability as they work at higher altitudes. The paper bears the question, what if we equipped a BAT with a complete wireless network base station stack and considered it a new beyond fifth generation/sixth generation (B5G/6G) wireless network device? Therefore, this article discusses enabling BATs as new B5G/6G wireless network equipment. We provide the preliminaries that make the BATs suitable for wireless network applications. We propose the expected configuration and architecture for BATs-based B5G/6G wireless networks. We discuss the opportunities, desired applications, and deployment challenges of BATs in B5G/6G wireless networks. Using simulations, we present the evidence and viability of enabling BATs for extending wireless networks.

Joint Relay Selection and Beam Management Based on Deep Reinforcement Learning for Millimeter Wave Vehicular Communication

Cooperative relays improve reliability and coverage in wireless networks by providing multiple paths for data transmission. Relaying will play an essential role in vehicular networks at higher frequency bands, where mobility and frequent signal blockages cause link outages. To ensure connectivity in a relay-aided vehicular network, the relay selection policy should be designed to efficiently find unblocked relays. Inspired by recent advances in beam management in mobile millimeter wave (mmWave) networks, this paper addresses the question: <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">how can the best relay be selected with minimal overhead from beam management?</i> In this regard, we formulate a sequential decision problem to jointly optimize relay selection and beam management. We propose a joint relay selection and beam management policy based on deep reinforcement learning (DRL) using the Markov property of beam indices and beam measurements. The proposed DRL-based algorithm learns time-varying thresholds that adapt to the dynamic channel conditions and traffic patterns. Numerical experiments demonstrate that the proposed algorithm outperforms baselines without prior channel knowledge. Moreover, the DRL-based algorithm can maintain high spectral efficiency under fast-varying channels.

Hybrid Deployment of Multi-Hierarchical RISs for Probabilistic LoS Communication in Dense Urban

Reconfigurable intelligent surface (RIS) is an emerging technology for enabling the manipulation of wireless environments, which shows great potential for the coverage and capacity enhancements of wireless networks. In this letter, a hybrid deployment scheme of terrestrial and aerial RISs (TRIS, ARIS) is proposed to avoid the obstruction of light-of-sight (LoS) communication in dense urban. The objective is to maximize the minimum average rate of users located in different blind zones of dense urban by jointly optimizing transmit beamforming at BS, the reflecting coefficients of TRISs and ARIS, and the height deployment of ARIS. Due to the non-convexity of this problem, an effective iterative method including fractional programming, projected subgradient method, and local region optimization is proposed to divide and conquer each subproblem. Numerical simulations indicate the effectiveness of the joint optimization on the passive beamformings of multi-hierarchical RISs and the height deployment of the ARIS for enhancing system performance, and demonstrate a clear gain of the proposed scheme of hybrid deployment compared with the benchmark schemes.

Multi-Active/Passive-IRS Enabled Wireless Information and Power Transfer: Active IRS Deployment and Performance Analysis

Intelligent reflecting surfaces (IRSs), active and/or passive, can be densely deployed in complex environments to significantly enhance wireless network coverage for both wireless information transfer (WIT) and wireless power transfer (WPT). In this letter, we study the downlink WIT/WPT from a multi-antenna base station to a single-antenna user over a multi-active/passive IRS (AIRS/PIRS)-enabled wireless link. In particular, we derive the location of the AIRS with those of the other PIRSs being fixed to maximize the received signal-to-noise ratio (SNR) and signal power at the user in the cases of WIT and WPT, respectively. The derived solutions reveal that the optimal AIRS deployment is generally different for WIT versus WPT due to the different roles of AIRS-induced amplification noise. Furthermore, both analytical and numerical results are provided to show the conditions under which the proposed AIRS deployment strategy yields superior performance to other baseline deployment strategies as well as the conventional all-PIRS enabled WIT/WPT.

CoRMAC: A Connected Random Topology Formation With Maximal Area Coverage in Wireless Ad-Hoc Networks

R1C2Random geometric graphs can be used in constructing topology formations for wireless ad-hoc networks (WANETs), including wireless sensor networks, flying ad-hoc networks, and others. They are useful for energy-saving schemes where a randomly alternating subset of deployed nodes is turned off temporarily (without compromising the network connectivity). This also improves network security by periodically re-routing the data flow, which makes it harder for third parties to run a traffic analysis. In the area and target coverage scenarios, a WANET deployment is desired to have maximal area coverage efficiency, which implies covering the largest possible area using the fewest number of nodes by maintaining the connectivity as well. Although deterministic topology formations offering optimal area coverage are known, a random node deployment method that grants connectivity and area coverage maximality has not been presented, to the best of our knowledge. This study introduces a novel topology formation method, called CoRMAC, that consistently yields tree-formed random geometric graphs that are guaranteed to be connected and offer maximal area coverage for any given area size and node cardinality. The area coverage maximality of CoRMAC is formally proven. Extensive theoretical and computational analyses have been provided to demonstrate its graph-theoretic, Euclidean, and networking features. Moreover, comparisons were made with other approaches to show the effectiveness of the proposed method.

A Tutorial on Holographic MIMO Communications—Part III: Open Opportunities and Challenges

Holographic multiple-input multiple-output (HMIMO) technology, which uses spatially continuous surfaces for signal transmission and reception, is envisioned to be a promising solution for improving the data rate and coverage of wireless networks. In Parts I and II of this three-part tutorial on HMIMO communications, we provided an overview of channel modeling and highlighted the state-of-the-art in holographic beamforming. In this part, we will discuss the unique properties of HMIMO systems, highlighting the open challenges and opportunities that arise as the transceiver array apertures become denser and electromagnetically larger. Additionally, we explore the interplay between HMIMO and other emerging technologies in next-generation networks.

From Liquid Crystal on Silicon and Liquid Crystal Reflectarray to Reconfigurable Intelligent Surfaces for Post-5G Networks

This communication aims to address the recent surge of interest in reconfigurable intelligent surfaces (RISs) among both academic and industrial communities, which has largely neglected the historical developments of two other underpinning technologies, i.e., liquid crystal on silicon (LCOS) and liquid crystal reflectarray antenna (LCRA). Specifically, this communication focuses on the state of the art of LC-RIS, highlighting the unique features of this newly raised enabling technology for post-5G (6G) networks and comparing it to LCOS, which operates at different frequencies and is suited to different use cases. Drawing on insights from existing knowledge of LCOS and LCRA, opportunities and challenges are explored for LC-RIS’s technical advancements in enhancing the coverage, capacity, and energy efficiency of wireless networks. In particular, the development status and roadmap of LC-RIS in China is reviewed.

Títul Research on Wireless Network Coverage for Transformation and Upgrading of Exhibition Management with Artificial Intelligence Technology

Abstract The rapid development of artificial intelligence and modern communication technology provides a powerful opportunity to realize the transformation, upgrading and high-quality development of exhibition management. To solve the optimal coverage problem of wireless network in the exhibition area, a new generation of artificial intelligence algorithm is introduced to propose a novel method for solving the network coverage problem based on Harris Hawk optimization (HHO) algorithm. From the perspective of maximizing coverage and minimizing coverage redundancy, the multi-objective coverage optimization problem of wireless network nodes is optimally extracted into a function and solved using the improved HHO (IHHO) algorithm. Through the simulation of the wireless network coverage in the exhibition area, the experimental results show that the comprehensive evaluation index score of the optimization algorithm reaches 98.03%, which is higher than the traditional particle swarm optimizer (PSO) and the standard HHO. The proposed IHHO algorithm can be effectively applied to the network coverage problem and has a greater advantage over the traditional optimization methods in terms of improving node coverage, and has great practicality.

Integration of Optical and Free Space Optics Network Architecture for High-Speed Communication in Adverse Weather using suitable Optical Bands

Free Space Optics (FSO) is a highly viable solution for high-speed wireless communication and is widely preferred over radio frequency communication systems because of its faster data transmission, no regulatory requirements and highly secure long-range operations. However, the capacity and availability of FSO optical bands are a significant concern in varying atmospheric conditions. Our objective is to enhance network flexibility and expand wireless network coverage in adverse weather conditions by combining optical and FSO links using optical bands C, S, and O. The study analyzed the performance of a hybrid 4 channels FSO-WDM system with a 100GHz or 0.8 nm channel spacing under different conditions, including adverse weather and varying data rates. An attenuation of 0.25 dB/km was fixed, and the system's performance was analyzed up to 3 km. The results showed that as the data rate increased, the system's performance declined, and the O band was the best performer up to 25 Gbit/s. BER values were analyzed at different weather conditions using the Kim model, and the O band consistently outperformed the S and C bands. Eye diagrams were used to evaluate the signal quality, and the O band was shown to perform better than the other two bands, even in adverse weather conditions. Overall, the study suggests that FSO is a viable solution for high-speed wireless communication, particularly when using the O band.

Joint Active and Passive Beamforming Design for RIS-Aided IBFD IoT Communications: QoS and Power Efficiency Considerations

In a reconfigurable intelligent surface (RIS) aided communication network, a RIS equipped with multiple passive reflecting elements assists in extending the coverage of wireless networks by overcoming the effects of non-line-of-sight propagation. Accordingly, to present the case for utilizing RIS panels in future consumer internet of things (IoT) networks, in this paper, we focus on a RIS-aided IoT network operating in in-band full-duplex (IBFD) mode. Since all the IoT node pairs communicate simultaneously through individual IBFD links at the same time-frequency resources, the nodes suffer from strong self-interference (SI) and inter-node interference. Consequently, in this paper, we investigate a joint active and passive beamforming design at each IoT node and the RIS, respectively, by minimizing the total transmission power of the network, subject to a minimum rate constraint for each IoT node and a constraint that guarantees a unit modulus phase shift at the RIS. As the original joint active and passive beamforming design problem is non-convex and intractable, we decompose the problem into two sub-problems. For a given passive beamformer design, we solve the original problem to obtain the optimal beamforming vectors at each IoT node. Next, for the obtained active beamformer, we propose two algorithms based on i) gradient descent (GD) search and ii) Riemannian conjugate gradient (RCG) to obtain the optimal passive beamformer at the RIS. Through extensive numerical analysis, we verify the effectiveness of the proposed algorithms and also show the effects of using RIS and transmitting in IBFD mode on the average rate and power of the considered consumer IoT network. We investigate the impact of several system parameters such as RIS elements, node pairs, level of hardware impairments at the transmitter and receiver, etc. We also highlight the trade-off between performance improvement and complexity due to elements used at RIS.

GCWCN: 6G-Based Global Coverage Wireless Communication Network Architecture

At present, the world is experiencing a significant transformation from the fifth generation (5G) wireless communication network to the sixth generation (6G) wireless communication network. An important goal is to achieve seamless global coverage of wireless signals. The combination of space network, air network and ground network has been proved to be effective, but the maritime network has not been taken into account. Therefore, how to effectively achieve the global coverage of wireless networks is a challenging topic. This paper first compares the performance of 5G and 6G, and analyzes the possibility of a wireless communication network with global coverage based on 6G technology. After that, we respectively analyze the typical characteristics of space network, air network, terrestrial network and maritime network, and then lead to the key enabling technologies to combine them. Based on the typical characteristics of the above heterogeneous networks and combined with the enabling technologies, we try to propose a 6Gsupported space-air-ground-sea integrated network (SAGSIN) architecture, to achieve seamless global wireless signal coverage. In the end, we rationally analyze a series of challenges and difficulties that may be faced in implementing the architecture.

Computationally efficient phase control algorithm for intelligent reflecting surface-aided multiuser systems

The intelligent reflecting surface (IRS) technology can enhance coverage in wireless networks by detouring a blocked path, where the phases of its passive elements are controlled to reinforce reflected signals in the desired directions, as the massive MIMO does. As a massive IRS system is introduced in the millimeter wave (mmWave) and tera-hertz (THz) bands, the optimal phase control induces computational complexity, and its complexity is doubled in multiuser systems. We propose a computationally efficient phase control algorithm in IRS-aided multiuser systems, where the reflected signals are sequentially aligned to search for optimal phases to maximize the total SNR of all users in service. The proposed scheme is evaluated with continuous phase and discrete phases with 1, 2, and 3 bits and compared with the random phase and full-search cases.