Future Wireless Communication Networks Research Articles

An integrative numerical method for evaluating Ergodic capacity of multi-user NOMA over faded channels with imperfect-CSI and SIC

With increased demand for the internet and the Internet of Things (IoT), future wireless communication networks are draw more attention to afford the massive connectivity, capacity, and extensive coverage requirements. Recently, multi-user (MU) NOMA was introduced as a potential technique to address these challenges. Owing to the wide applicability of MU-NOMA, precise expressions for Ergodic capacity under realistic scenarios are very much required to evaluate its performance. Hence, in this paper, we derive the ergodic capacity expressions for MU-NOMA for generalized fading channels. To achieve precision, we have taken imperfect-successive interference cancellation (SIC) and channel state information (CSI) into account. The impact of imperfect SIC and CSI and fading parameters is investigated over Nakagami-m, Rayleigh, and Rician fading channels. The proposed approach is valid for any type fading channels. The obtained expressions for the Ergodic capacity over various fading channels are validated through the simulation results.

Wireless quantum key distribution at terahertz frequencies: Opportunities and challenges

AbstractQuantum key distribution (QKD) is one of the major applications of quantum information technology. It can provide ultra‐secure key distribution with security guaranteed by the laws of quantum physics. Quantum key distribution is necessary to protect data transmission from quantum computing attacks in future communication networks. The laws of quantum mechanics dictate that as opposed to microwave frequencies, quantum coherence is preserved at room temperatures for terahertz (THz) frequencies. This makes the THz band a promising solution for room‐temperature QKD implementation in future wireless communication networks. The authors present the principles of continuous variable QKD (CV‐QKD) systems and review the latest developments in the design and analysis of CV‐QKD systems operating at microwave and THz frequencies. The authors also discuss how multiple‐input multiple‐output transmission can be incorporated into the quantum communications framework to improve the secret key rates and increase the coverage distances of the THz CV‐QKD system. Furthermore, major hardware challenges that must be surmounted to practically realise THz CV‐QKD systems are highlighted.

Cell-free ISAC massive MIMO systems with capacity-constrained fronthaul links

Integrated sensing and communication (ISAC), millimeter wave (mmWave) massive multiple-input multiple-output (MIMO), and cell-free networks are emerged as some of the most potential physical layer enablers for the future wireless communication networks. In this paper, we consider a cell-free ISAC mmWave massive MIMO system with hybrid analog and digital precoders while accounting for the impacts of capacity-constrained fronthaul links. In the system, the digital baseband processing is dictated at a geographical scale while the analog precoders are carried out at each transmit access point (AP). Based on the characteristics of the considered model, we formulate the optimization problem as a function of power allocation and fronthaul compression strategies. To address this problem, two block coordinate descend (BCD)-based methods are proposed to alternatively solve the three decomposed subproblems corresponding to the power allocation, the downlink and backward fronthaul compression strategies. Simulation results indicate that the proposed schemes can achieve 90% performance of the optimal full-search (FS) method with much lower computational complexity. In addition, there exists an optimal configuration of APs, UEs, and antennas for a cell-free ISAC system with capacity-constrained fronthaul links.

GAMP-Based Low-Complexity Sparse Bayesian Learning Channel Estimation for OTFS Systems in V2X Scenarios

Vehicle to everything (V2X) is widely regarded as a critical application for future wireless communication networks. In V2X, large relative speeds between vehicles may severely deteriorate the performance of communication between vehicles. Orthogonal time frequency space (OTFS) modulation, which converts time- and frequency-selective channels into non-selective channels in the delay-Doppler (DD) domain, provides a solution for establishing reliable wireless communications in V2X scenarios. However, in the complex multi-scattering scenarios, the channel also suffers from a serious inter-Doppler interference (IDI) problem, which poses a great challenge to the accurate demodulation of OTFS receiver signals. To address the above problems, this paper considers the variation of Doppler sampling points within one symbol when deriving the channel model, which effectively overcomes the IDI problem, and employs a basis expansion model (BEM) to convert the channel estimation into a sparse recovery problem for the basis coefficients. In addition, to better utilize the sparse nature of the OTFS channel, a generalized approximate message passing-sparse Bayesian learning (GAMP-SBL)-based algorithm is employed to estimate the basis coefficients of the channel. The complexity of this algorithm is greatly reduced compared to the conventional SBL algorithm. Finally, system simulation results are reported to verify the superiority of the proposed scheme.

Reconfigurable Wide‐Angle Beam‐Steering Terahertz Metasurfaces Based on Vanadium Dioxide

AbstractThe sixth generation (6G) wireless network is envisioned to provide faster and more reliable communication by utilizing electromagnetic waves in the terahertz spectrum. However, terahertz waves suffer from high propagation loss and, hence, wavefront manipulation solutions to focus and redirect terahertz waves are of paramount importance. Reconfigurable intelligent surface (RIS) is one such promising dynamic wavefront engineering solution proposed for 6G networks, but the technological realization of 6G (>100 GHz) RIS is still largely lacking. Here, spatially‐selective vanadium dioxide (VO2) patches incorporating coding metasurfaces for dynamic beam steering of terahertz waves are presented. The reversible and abrupt insulator‐to‐metal phase transition property of VO2 is exploited to achieve a reconfigurable transmission angle for the normal incident terahertz wave. By designing metasurfaces with specific linear phase gradients and designer phase sequencing, electrically switchable beam steering is achieved from co‐polarized 0° (normal transmission) in the OFF state to cross‐polarized 0° (control), 11°, 23°, 36°, and 52° in the ON state at 0.6 THz. Scaling up the proposed concept to achieve individual control of each active element (VO2) within the metasurface will enable a complete 6G RIS solution for full 3D terahertz beam manipulation to support the future THz wireless communication networks.

An endogenous intelligent architecture for wireless communication networks

AbstractThe challenges posed by the future wireless communication network, which will be a huge system with more complex structures, diverse functions, and massive communication ends, will be addressed by intelligent wireless communication technologies. These technologies are playing an increasingly important role in network architecture, computing architecture, resource allocation algorithm design, etc., thanks to the rapid development of artificial intelligence technologies, particularly the deep learning technologies, and their extensive application in various domains. In this paper, an endogenous intelligent architecture is developed to effectively clarify and understand in-depth the relationship among the factors by constructing wireless knowledge graph for the air interface transmission, the core network, as well as the network environment, and so on. Furthermore, the knowledge graph simultaneously reveals the structure and operation mechanism of the whole wireless communication networks. Cause tracing, intelligent optimization, and performance evaluation are sequentially implemented based on the knowledge graph, thus forming a complete closed-loop for endogenous intelligent wireless communication networks.

Energy-Efficient Resource Allocation for Aggregated RF/VLC Systems

Visible light communication (VLC) is envisioned as a core component of future wireless communication networks due to, among others, the huge unlicensed bandwidth it offers and the fact that it does not cause any interference to existing radio frequency (RF) communication systems. In order to take advantage of both RF and VLC, most research on their coexistence has focused on hybrid designs where data transmission to any user could originate from either an RF or a VLC access point (AP). However, hybrid RF/VLC systems fail to exploit the distinct transmission characteristics (e.g., susceptibility of VLC transmissions to blockages, limited field-of-view of VLC APs and receivers, more coverage and better reliability of RF systems, etc.) of RF and VLC systems to fully reap the benefits they can offer. Aggregated RF/VLC systems, in which any user can be served simultaneously by both RF and VLC APs, have recently emerged as a more promising and robust design for the coexistence of RF and VLC systems. To this end, this paper, for the first time, investigates AP assignment, subchannel allocation (SA), and transmit power allocation (PA) to optimize the energy efficiency (EE) of aggregated RF/VLC systems while considering the effects of interference and VLC line-of-sight link blockages. A novel and challenging EE optimization problem is formulated for which an efficient joint solution based on alternating optimization is developed. More particularly, an energy-efficient AP assignment algorithm based on matching theory is proposed. Then, a low-complexity SA scheme that allocates subchannels to users based on their channel conditions is developed. Finally, an effective PA algorithm is presented by utilizing the quadratic transform approach and a multi-objective optimization framework. Extensive simulation results reveal that: 1) the proposed joint AP assignment, SA, and PA solution obtains significant EE, sum-rate, and outage performance gains with low complexity, and 2) the aggregated RF/VLC system provides considerable performance improvement compared to hybrid RF/VLC systems.

6G Broadband and High Directive Microstrip Antenna with SIW and FSSs

Sixth-Generation (6G) wireless communication networks require the fabrication of broadband and high directivity microstrip antennas to offset the high atmospheric path loss beyond 100 Gigahertz (GHz). In this paper, we designed and proposed a couple of high-gain and broadband microstrip array antennas that have been designed within a Finite Integration Technique (FIT) solver at Computer Simulation Technology Microwave Studio (CST MWS) software in a series-parallel feeding method for a resonance frequency above 107 GHz. A Substrate-Integrated Waveguide (SIW) with dual outputs has been used at these antennas and with WR-08 waveguide that covers the 90-140 GHz frequency range, while the first was without Frequency Selective Surfaces (FSSs), and the second was with the FSSs to increase the antenna directivity further. The first design was simulated with a Finite Element Method (FEM) solver at Ansys High-Frequency Structure Simulator (HFSS) to compare the simulation results of this antenna. This comparison's peak gain and Bandwidth (BW) were correspondingly 25.3 dB, 12.5 GHz, 23.1 dB, and 11 GHz from the Ansys HFSS and the CST MWS. Thus, the accuracy and the slight deviation of the compared simulation results from each other validated the offered 6G antenna designs. Therefore, after experimental verification, the proposed antennas can be employed in 6G future wireless communication networks.

An electromechanically reconfigurable intelligent surface for enhancing sub-6G wireless communication signal

Reconfigurable intelligent surface (RIS) is emerged as a promising technique to solve the challenges faced by future wireless communication networks. Although the most commonly used electrically-controlled RISs can achieve millisecond-scale speed of dynamic switch, they have a large number of microwave circuit elements (such as PIN diodes or varactors) which will bring non-negligible insertion loss, and the complicity of the bias network to electrically addressing each element will increase with the expansion of the RIS aperture. Aiming at further reducing the fabrication cost and power consumption, herein an electromechanical RIS used for sub-6G wireless communication is proposed. The electromechanical RIS is designed with a passive metasurface and step-motor driver modules, providing simultaneous high-efficiency reflection (over 80%) and continuous reflection phase coverage of 360°. Through electromechanical control, the RIS system can realize different reflective wavefront shaping, and has been employed in the indoor sub-6G wireless environment demonstrating a maximum signal improvement of 8.3 ​dB. The proposed electromechanical RIS is particularly useful for wireless signal enhancement in static blind area, and has the obvious advantage of not requiring continuous power supply after the RIS being regulated. Therefore, it greatly reduces the overall cost and power consumption which may have potentials in indoor application scenarios for improving wireless communication performance.

Terahertz Meets AI: The State of the Art.

Terahertz (THz) is a promising technology for future wireless communication networks, particularly for 6G and beyond. The ultra-wide THz band, ranging from 0.1 to 10 THz, can potentially address the limited capacity and scarcity of spectrum in current wireless systems such as 4G-LTE and 5G. Furthermore, it is expected to support advanced wireless applications requiring high data transmission and quality services, i.e., terabit-per-second backhaul systems, ultra-high-definition streaming, virtual/augmented reality, and high-bandwidth wireless communications. In recent years, artificial intelligence (AI) has been used mainly for resource management, spectrum allocation, modulation and bandwidth classification, interference mitigation, beamforming, and medium access control layer protocols to improve THz performance. This survey paper examines the use of AI in state-of-the-art THz communications, discussing the challenges, potentials, and shortcomings. Additionally, this survey discusses the available platforms, including commercial, testbeds, and publicly available simulators for THz communications. Finally, this survey provides future strategies for improving the existing THz simulators and using AI methods, including deep learning, federated learning, and reinforcement learning, to improve THz communications.

Low-Latency Hybrid NOMA-TDMA: QoS-Driven Design Framework

Enabling ultra-reliable and low-latency communication services while providing massive connectivity is one of the major goals to be accomplished in future wireless communication networks. In this paper, we investigate the performance of a hybrid multi-access scheme in the finite blocklength (FBL) regime that combines the advantages of both non-orthogonal multiple access (NOMA) and time-division multiple access (TDMA) schemes. Two latency-sensitive application scenarios are studied, distinguished by whether the queuing behaviour has an influence on the transmission performance or not. In particular, for the latency-critical case with one-shot transmission, we aim at a certain physical-layer quality-of-service (QoS) performance, namely the optimization of the reliability. And for the case in which queuing behaviour plays a role, we focus on the link-layer QoS performance and provide a design that maximizes the effective capacity. For both designs, we leverage the characterizations in the FBL regime to provide the optimal framework by jointly allocating the blocklength and transmit power of each user. In particular, for the reliability-oriented design, the original problem is decomposed and the joint convexity of sub-problems is shown via a variable substitution method. For the effective-capacity-oriented design, we exploit the method of Lagrange multipliers to formulate a solvable dual problem with strong duality to the original problem. Via simulations, we validate our analytical results of convexity/concavity and show the advantage of our proposed approaches compared to other existing schemes.

Stackelberg Game for Secure CR-NOMA Networks Against Internal Eavesdropper

The combination of CR-NOMA has enormous potential interest to improve spectral efficiency and increase system capacity in future wireless communication networks. Hence, according to the broadcast nature of the CR-NOMA wireless channel, handling the confidentiality of information is one of the most important requirements of the network. In this paper, PLS against internal Eve is investigated by the CR-NOMA under the limitations of joint delay and confidentiality rate. First, initial power allocation for SU based on the PU interference threshold is constructed. Then, a multi-objective problem based on different SUs demands is formulated based on Stackelberg game modeling. After that, the SE is studied and explored. At the final stage, an overall algorithm has been proposed whereby SE strategies are frequently updated to find the best parameters for the proposed system model. The simulation results show the superiority of the proposed scheme in achieving a higher average utility function, spectral efficiency, fairness index, up to 44%, 90%, and 54.7%, respectively, and reliability compared to the conventional scheme.

Ultra-Wideband, Directive and Circular Polarization Lens Antennas for Future Communications

This paper presents a potential featured antenna for future wireless communication networks. The use of a hemispherical dielectric lens combined with an equiangular spiral printed antenna is proposed to achieve a radiator design with high gain, operating in a frequency range between 8.0 GHz to 15.6 GHz in circular polarization. Numerical analyses performed by the ANSYS HFSS software, and experimental measurements validated the functionality of the proposed structure, reaching gains greater than 14.2 dBi.

Physical-Layer Authentication for Ambient Backscatter-Aided NOMA Symbiotic Systems

Ambient backscatter communication (AmBC) and non-orthogonal multiple access (NOMA) are two promising technologies for the future wireless communication networks owing to their high energy and spectral efficiencies. The AmBC-aided NOMA symbiotic radio is a promising technology because of possessing advantages of AmBC and NOMA. Nonetheless, when a number of devices with limited power and computation capability access to the AmBC-based NOMA symbiotic networks, communication security becomes a critical issue. In this paper, we investigate physical-layer authentication (PLA) to identify the users and prevent illegal access and malicious activities for AmBC-based NOMA symbiotic networks. Moreover, channel estimation errors are considered when calculating the probability of false alarm (PFA) and probability of detection (PD) of the far user and near user. To enhance the authentication performance, three PLA schemes for the considered networks are designed according to the multiplexing form of the authentication tags: i) PLA with shared authentication tag (PLA-SAT); ii) PLA with space division multiplexing authentication tags; iii) PLA with time-division multiplexing authentication tags. To characterize the proposed PLA schemes, we first derive the PFA and the PD of the considered AmBC-based NOMA symbiotic networks. Then, the covertness is studied in terms of outage probability and asymptotic behavior in the high signal-to-noise ratio regime. Extensive analytical and computer simulated results show that: i) The PLA-SAT scheme has better performance than the other two authentication schemes with the same threshold; ii) The outage performance of systems employing authentication schemes is worse than those without authentication; iii) There exists a trade-off between robustness and covertness.

Interference alignment solution with low complexity based on ring-typed chain design

The future wireless communication network will suffer more serious interference by frequency and spatial reuse. Interference alignment (IA) is an effective transmission strategy to cancel interference, but the closed-form IA solution of low complexity for general interference networks has not been solved well. In this paper, a novel closed-form IA solution method based on improved ring-typed chain design is proposed, for generalized multiple user multiple-input multiple-output (MIMO) interference network. The main idea of this method is to divide each IA transmit matrix into a certain number of sub-matrices, and design elaborately the ring-typed sub-matrix chains to align interfering signal space. Then based on that, the closed-form transmit matrices are derived. Compare with IA solution method proposed in our previous work, this method can achieve more degrees of freedom (DoFs) of each user. Simulation results show the high system sum-rate performance and low computational complexity of the proposed IA solution method.

A Novel Bio-Inspired Energy Optimization for Two-Tier Wireless Communication Networks: A Grasshopper Optimization Algorithm (GOA)-Based Approach

Energy consumption has become one of the most challenging problems in future wireless communication networks. One of the promising methods in fifth generation (5G) cellular networks to meet the ever-increasing demand for high data traffic is wireless heterogeneous networks (HetNets). Adding more base stations may improve network coverage, but leads to the consumption of a significant amount of power. The scheme of two-tier networks contains small cell base stations (SCBs) that cooperate with macro cell base stations (MCBs) to provide wider coverage. Some small cell base station SCBs are experiencing light traffic loads due to the movement of user equipment (UEs), but these SCBs still consume a considerable amount of energy. Therefore, to reduce SCBs’ power consumption and maximize the overall energy efficiency (EE) of a two-tier network, some SCBs need to be switched off. In this paper, we extend the operation modes for BSs and present a novel mechanism to select an appropriate operation mode for each SCB that is based on bio-inspired behavior. We employ a bias function to manage the power consumption of each operation mode. Each SCB has four power mode selections: On, Standby, Sleep, and Off. We formulate the EE maximization problem under a set of constraints and present a Grasshopper Optimization Algorithm-based Variant Power Mode Selection (GOA-VPMS) to solve it. The proposed algorithm scheme outperforms previous work and provides a higher EE, according to the simulation results.

Joint Beamforming Design for Intelligent Omni Surface Assisted Wireless Communication Systems

Intelligent reflecting surface (IRS) has been widely considered as one of the key enabling techniques for future wireless communication networks owing to its ability of dynamically controlling the phase shift of reflected electromagnetic (EM) waves to construct a favorable propagation environment. While IRS only focuses on signal reflection, the recently emerged innovative concept of intelligent omni-surface (IOS) can provide the dual functionality of manipulating reflecting and transmitting signals. Thus, IOS is a new paradigm for achieving ubiquitous wireless communications. In this paper, we consider an IOS-assisted multi-user multi-input single-output (MU-MISO) system where the IOS utilizes its reflective and transmissive properties to enhance the MU-MISO transmission. Both power minimization and sum-rate maximization problems are solved by exploiting the second-order cone programming (SOCP), Riemannian manifold, weighted minimum mean square error (WMMSE), and block coordinate descent (BCD) methods. Simulation results verify the advancements of the IOS for wireless systems and illustrate the significant performance improvement of our proposed joint transmit beamforming, reflecting and transmitting phase-shift, and IOS energy division design algorithms. Compared with conventional IRS, IOS can significantly extend the communication coverage, enhance the strength of received signals, and improve the quality of communication links.

Formation-of-Arrays Antenna Technology for High-Throughput Mobile Non-Terrestrial Networks

Effective integration of terrestrial and non-terrestrial segments is one of the key research avenues in the design of current and future wireless communication networks. To this aim, modern communication-satellite constellations intend to attain sufficiently high throughput in terms of bit rate per unit area on the ground by rather aggressive patterns of spatial frequency reuse. This goal calls for on-board narrow-beam antennas, whose size turns out to be in many cases incompatible with the size/mass and accommodation constraints of the hosting satellite. This paper investigates the attainable performance of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">large distributed arrays of antennas</i> implemented as the ensemble of a few to many simpler sub-antennas of smaller sizes, carried by one (small) satellite each. The sub-antennas can in their turn be implemented like (regular) 2D arrays of simple radiating elements, realizing an overall (distributed) antenna architecture that we call “formation of arrays” (FoA). The satellites that implement this radiating architecture need to be relatively close to each other and constitute a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">formation</i> of flying objects, to be coordinated and controlled as a whole. In this paper, we develop a theoretical analysis of an FoA antenna, and we show how to take advantage of this new technology to improve network throughput in a multi-beam S-band mobile communication network with low-earth or geostationary orbiting satellites directly providing 5G-like communication services to hand-held user terminals.

Deep neural network based resource allocation in D2D wireless networks

The increased complexity of future 5G wireless communication networks presents a fundamental issue for optimal resource allocation. This continuous, constrained optimal control problem must be solved in real-time since the power allocation should be consistent with the instantly evolving channel state. This paper emphasizes the application of deep learning to develop solutions for radio resource allocation problems in multiple-input multiple-output systems. We introduce a supervised deep neural network model combined with particle swarm optimization to address the issue using heuristic-generated data. We train the model and evaluate its ability to anticipate resource allocation solutions accurately. The simulation result indicates that the trained DNN-based model can deliver the nearoptimal solution.

Deep Learning-Based Channel Estimation for Double-RIS Aided Massive MIMO System

Reconfigurable Intelligent Surface (RIS) is considered as an energy-efficient solution for future wireless communication networks due to its fast and low-cost configuration. In this letter, we consider the estimation of cascaded channels in a double-RIS aided massive multiple-input multiple-output system, which is a critical challenge due to the large number of antennas equipped at the base station and passive RIS elements. To tackle this challenge, we propose a skip-connection attention (SC-attention) network that utilizes self-attention layers and skip-connection structure to improve the channel estimation performance from the noisy pilot-based observations. Simulation results compare the proposed SC-attention network with other benchmark methods and show that SC-attention network can effectively improve the accuracy performance on normalized mean square error (NMSE) for cascaded links in a double-RIS aided system.