Next-generation Communication Systems Research Articles

AI Optimization-Based Heterogeneous Approach for Green Next-Generation Communication Systems

Traditional heterogeneous networks (HetNets) are constrained by their hardware design and configuration. These HetNets have a limited ability to adapt to variations in network dynamics. Software-defined radio technology has the potential to address this adaptability issue. In this paper, we introduce a software-defined radio (SDR)-based long-term evolution licensed assisted access (LTE-LAA) architecture for next-generation communication networks. We show that with proper design and tuning of the proposed architecture, high-level adaptability in HetNets becomes feasible with a higher throughput and lower power consumption. Firstly, maximizing the throughput and minimizing power consumption are formulated as a constrained optimization problem. Then, the obtained solution, alongside a heuristic solution, is compared against the solutions to existing approaches, showing our proposed strategy is drastically superior in terms of both power efficiency and system throughput. This study is then concluded by employing artificial intelligence techniques in multi-objective optimization, namely random forest regression, particle swarm, and genetic algorithms, to balance out the trade-offs between maximizing the throughput and power efficiency and minimizing energy consumption. These investigations demonstrate the potential of employing the proposed LTE-LAA architecture in addressing the requirements of next-generation HetNets in terms of power, throughput, and green scalability.

Advancing precision in pipeline analog-to-digital converters: Leveraging MATLAB for design and analysis in next-generation communication systems

The integration of MATLAB in designing and analyzing pipeline Analog-to-Digital Converters (ADCs) addresses the complexities of next-generation communication systems. This study reviews literature to identify trends and challenges in high-speed ADC designs. Mastery of MATLAB and its toolboxes, like Simulink and Signal Processing, is essential for advanced ADC modeling and analysis. Key challenges include maintaining accuracy with diminishing supply voltages in modern semiconductors. The study explores incorporating high-voltage analog components and develops strategies for superior accuracy using low-voltage transistors. MATLAB and pipeline architecture are crucial for advancing ADC design, providing innovative solutions for next-gen communication systems.

Digital twin based DDPG reinforcement learning for sum-rate maximization of AI-UAV communications

Construction of wireless infrastructure using unmanned aerial vehicle (UAV) can effectively expand the coverage and support high-density traffic of next-generation communication systems. Designing wireless systems including UAVs as aerial base stations (ABSs) is a challenging task, due to the mobility of ABSs causing time-varying nature of environmental surroundings and relative propagation paths to user equipment (UE) devices. Therefore, it is essential to have an accurate estimate of the channel for varying positioning of the UAVs. In this paper, we propose to adopt a digital twin based performance evaluation procedure for wireless systems including ABSs, providing enhanced accuracy of channel modeling for specific target deployment areas. Using ray-tracing channel models reflecting detailed building and terrain information of the transmission environment, an UAV position optimization algorithm based on reinforcement learning is presented. By utilizing deep deterministic policy gradient (DDPG), the proposed algorithm calculates the overall throughput in the digital twin and determines the desired states of the UAV. Performance evaluation results demonstrate the trajectory training ability of the algorithm and the performance advantage of the system with a reduced amount of shadow area compared to those with ground base stations (GBSs).

A Dual-Polarization Programmable Metasurface for Green and Secure Wireless Communication.

Dual-polarization programmable metasurfaces can flexibly manipulate electromagnetic (EM) waves while providing approximately twice the information capacity. Therefore, they hold significant applications in next-generation communication systems. However, there are three challenges associated with the existing dual-polarization programmable metasurfaces. This article aims to propose a novel design to address them. First, the design overcomes the challenge of element- and polarization-independent controls, enabling more powerful manipulations of EM waves. Second, by using more energy-efficient tunable components and reducing their number, the design can be nearly passive (maximum power consumption of 27.7mW), leading to a significant decrease in the cost and power consumption of the system (at least two orders of magnitude lower than the power consumption of conventional programmable metasurfaces). Third, the design can operate in a broad bandwidth, which is attractive for practical engineering applications. Both the element and array of the metasurface are meticulously designed, and their performance has been carefully studied. The experiments demonstrate that 2D wide-angle beam scanning can be realized. Moreover, secure communication based on directional information modulation can be implemented by exploiting the metasurface and an efficient discrete optimization algorithm, showing its programmable, multiplexing, broadband, green, and secure features.

High-performance electro-optic switches with compact multimode interference and Bezier S-bend waveguides

High-speed and energy-efficient electro-optic (EO) switches are crucial for next-generation data communication systems. This paper presents a novel EO switch utilizing a multimode interference (MMI) coupler-based approach on a lithium-niobate (LiNbO3) platform. The switch is designed with Bezier S-bend waveguides, leading to a significant reduction in bending loss to 0.18 dB. This Bezier-bend EO switch shows an excess loss of 0.33 dB and crosstalk of −20.44 dB for the bar port switching, while the cross port switching exhibits an excess loss of 0.64 dB and crosstalk of −13.66 dB. Applying a 3.27 V voltage achieves a balanced splitting ratio of 29:29:29 between the three outputs. The length of this EO switch is 4.09 mm, which requires 4.1 V to create a phase shift, showing a voltage efficiency of 1.68 V.cm. This paper presents a promising pathway for a novel EO switch design and introduces improved signal management for next-generation computing systems.

Directly modulated deformed-square-FP coupled-cavity laser with intracavity-mode photon-photon resonance

We propose and demonstrate a high-speed directly modulated laser based on a hybrid deformed-square-FP coupled cavity (DFC), aiming for a compact-size low-cost light source in next-generation optical communication systems. The deformed square microcavity is directly connected to the FP cavity and utilized as a wavelength-sensitive reflector with a comb-like and narrow-peak reflection spectrum for selecting the lasing mode, which can greatly improve the single-mode yield of the laser and the quality (Q) factor of the coupled mode. By optimizing the device design and operating condition, the modulation bandwidth of the DFC laser can be enhanced due to the intracavity-mode photon-photon resonance effect. Our experimental results show an enhancement of 3-dB modulation bandwidth from 19.3 GHz to 30 GHz and a clear eye diagram at a modulation rate of 25 Gbps.

All-optical high-contrast femtosecond switching using nonlinearity from an epsilon-near-zero effect in plasmonic metamaterials.

Metamaterials opened a new realm to control light-matter interactions at sub-wavelength scale by engineering meta-atoms. Recently, the integration of several emerging nonlinear materials with metamaterial structures enables ultra-fast all-optical switching at the nanoscale and thus brings enormous possibilities to realize next-generation optical communication systems. This Letter presents a novel, to the best of our knowledge, design of plasmonic metamaterials for high-contrast femtosecond all-optical switching. We leverage magnetic plasmon (MP) resonance combined with the nonlinear effects of an epsilon-near-zero (ENZ)-material. The proposed design comprises a periodic array of two closely spaced Au-nanogratings deposited on an optically thick Au-substrate to excite MP-resonance. To enable a dynamically tunable resonance, the nanogrooves in meta-atoms are filled with an ENZ-material, cadmium-oxide (CdO). The intraband transition-induced optical nonlinearities in the ENZ-medium are studied using a two-temperature model. The MP-resonance ensures strong light-matter interactions enabling enhancement of the nonlinearities of the proposed structure. We observe that the pump-induced refractive index change in the CdO layer causes a redshift of the MP-resonance dip wavelength in the reflectance spectrum, leading to a high modulation depth of 0.83 at 1.55 µm. With an ultra-fast response time of 776 fs while maintaining a low pump-fluence of 75 µJ/cm2, the proposed metamaterial could help in realizing switches for next-generation optical computation systems.

Energy Efficient Wireless Signal Detection: A Revisit through the Lens of Approximate Computing

In the pursuit of energy efficiency in next-generation communication systems, approximate computing is emerging as a promising technique. In the proposed work, efforts are made to address the challenge of bridging the gap between the level of approximation and the Quality-of-Service (QoS) of the system. The application of approximate multiplication to wireless signal detection is explored systematically, illustrated by employing Truncated Multiplication (TM) on Quadrature Phase Shift Keying (QPSK) Minimum Mean Square Error (MMSE) detection. The irregularities induced by approximation in the multiplication operation employed in wireless signal detection are captured by the Approximate Multiplication Noise (AMN) model, which aids in the analysis of signal fidelity and resiliency of the system. The energy efficiency gains through approximation are highlighted in the approximation analysis. Signal fidelity analysis provides the capability to predict system output for varying levels of approximation, which aids in improving the stability of the system. The higher approximation levels are advantageous in low Signal-to-Noise Ratio (SNR) regimes, whereas lower approximation levels prove beneficial in high SNR regimes.

Constellation design for PD-NOMA-based mmWave inter-satellite communication

The upcoming sixth-generation (6G) networks are supposed to utilize frequencies beyond the fifth-generation (B5G) and serve for satellite communications. During inter-satellite millimeter wave (mmWave) communications, the transmitting satellites may have identical simultaneous power transmissions, leading to the erroneous decoding of their information. This paper describes the application of a power-domain (PD) non-orthogonal multiple-access (NOMA) scheme for both terrestrial and inter-satellite communications consisting of two users or satellites. Specifically, the user (or satellite) symbol decoding is addressed under identical power transmissions. Both the user’s (transmitting satellite’s) data are extracted by minimizing the average probability of symbol errors using a designed constellation. Analytical/graphical results along with the simulation verify decent symbol decoding at a low average noise variance. At a noise variance of 0.01, the achieved average symbol-error probability reaches an order of up to 10−5. The proposed system results in a negligible error-vector magnitude (EVM) of −10 dB at higher end of the considered signal-to-interference-plus-noise ratio (SINR) range. Further, the proposed method alleviates the successive interference cancellation (SIC) pre-requisite of NOMA, strengthening the application of NOMA with mmWaves in next-generation satellite communication systems.

VO2/MoO3 Heterojunctions Artificial Optoelectronic Synapse Devices for Near-Infrared Optical Communication.

Artificial optoelectronic synapses (OES) have attracted extensive attention in brain-inspired information processing and neuromorphic computing. However, OES at near-infrared wavelengths have rarely been reported, seriously limiting the application in modern optical communication. Herein, high-performance near-infrared OES devices based on VO2/MoO3 heterojunctions are presented. The textured MoO3 films are deposited on the sputtered VO2 film by using the glancing-angle deposition technique to form a heterojunction device. Through tuning the oxygen defects in the VO2 film, the fabricated VO2/MoO3 heterojunction exhibits versatile electrical synaptic functions. Benefiting from the highly efficient light harvesting and the unique interface effect, the photonic synaptic characteristics, mainly including the short/long-term plasticity and learning experience behavior are successfully realized at the O (1342nm) and C (1550nm) optical communication wavebands. Moreover, a single OES device can output messages accurately by converting light signals of the Morse code to distinct synaptic currents. More importantly, a 3×3 artificial OES array is constructed to demonstrate the impressive image perceiving and learning capabilities. This work not only indicates the feasibility of defect and interface engineering in modulating the synaptic plasticity of OES devices, but also provides effective strategies to develop advanced artificial neuromorphic visual systems for next-generation optical communication systems.

Performance Comparison of IRS-Assisted SSK Modulation Over Rayleigh and Nakagami-m Fading Channels

To meet the needs of society, the next generation of communication systems will have to learn to juggle multiple responsibilities effectively. This is leading to exponential growth in both circuit complexity and error rates. It is possible to solve these issues by using the intelligent reflecting surface (IRS)-Assisted space shift keying (SSK) modulation technique. IRS is a cutting-edge technology that shows promise for future networks due to its low mistake rates and low-energy consumption. Similarly, SSK modulation is favored due to its preference for simpler hardware. Therefore, integrating IRS with SSK is preferable for minimizing both error rates and circuit complexity. In this article, a new framework is developed to characterize the average bit error rate (ABER) with the help of the moment generating function (MGF) over Nakagami-m fading channels. The ABER is derived by factoring the direct path and IRS reflected path at the receiver and also comparing the performance analysis over the Rayleigh fading channel. The analytical results are validated through Monte-Carlo simulations.

Synchronization of two chaotic microresonator frequency combs.

We explore the synchronization of chaotic microresonator frequency combs, emphasizing the modulation instability state, which is known for its inherent chaotic behaviors. Our study confirms that the synchronization of two such combs is feasible by injecting the output from the lead microresonator into the next microresonator's input. We also identify the optimal parameters for this synchronization. Remarkably, even partial injection from the leader is sufficient for synchronization, paving the way for versatile future system configurations. Such systems could simultaneously utilize distinct spectral components for synchronization and transmission. This work advances our understanding of chaotic microresonator combs, showing them to be pivotal elements in next-generation optical communication systems.

Key Technologies for 6G-Enabled Smart Sustainable City

With the advancement of information and communication technologies (ICTs), the way we live and communicate with each other is changing rapidly. As urban environments continue to evolve, the smart sustainable city (SSC) has sparked considerable attention. We are hoping for a new era in which numerous devices and machines including vehicles, sensors, and robots are all connected to communicate, respond, and operate in real time. The next-generation communication system, the sixth generation (6G), is expected to play a crucial role in improving the efficiency of urban operations and services. In this paper, we first provide the recent trends and key features of standardization in the SSC. To make the future SSC, we highlight key candidate technologies of 6G such as non-terrestrial networks, advanced mobile edge computing, vision-aided wireless communication, artificial intelligence (AI)-based wireless communication, and integrated sensing and communication. We put forth the main technical challenges given to each prime technology along with the potential benefits to pave the way for 6G-enabled SSC. We further address how the potential benefits of prime technologies enable various urban practice cases for 6G-enabled SSC.

An Efficient Matching Game Approach to Association Formation in UAV-Enabled Hierarchical Distributed Learning.

Distributed machine learning has emerged as a promising data processing technology for next-generation communication systems. It leverages the computational capabilities of local nodes to efficiently handle large datasets, creating highly accurate data-driven models for analysis and prediction purposes. However, the performance of distributed machine learning can be significantly hampered by communication bottlenecks and node dropouts. In this article, a novel unmanned aerial vehicle (UAV)-enabled hierarchical distributed learning architecture is proposed to support machine learning applications, e.g., regional monitoring. Multiple UAV receivers (URs) are introduced as wireless relays to improve the communication between the UAV transmitters (UTs) and the cloud server. Our objective is to identify the optimal UT-UR association to maximize the social welfare of the network, which is distinctly different from the existing works that focus on the unilateral profit-maximizing problem. We formulate a two-side many-to-one matching game to model the UT-UR association problem, and a two-phase many-to-one matching algorithm is designed to identify the stable matching. The validity of our proposed scheme is verified through in-depth numerical simulations.

Design and Performance Evaluation of Orthogonally Polarized Corporate Feed MIMO Antenna Array for Next-Generation Communication System

Design and Performance Evaluation of Orthogonally Polarized Corporate Feed MIMO Antenna Array for Next-Generation Communication System

A Study on Microstrip Array Antenna with FSS for Next Generation Cellular Communication

Abstract: Fifth-generation wireless, often known as 5G, is the next version of cellular technology and is intended to provide major improvements to the speed and responsiveness of wireless networks. In addition, the increased bandwidth and improved antenna technologies that come with 5G make it possible for a significant increase in the quantity of data that can be transmitted via a wireless network. In order to build a successful next-generation cellular communication system in the terahertz (THz) regime, it is necessary to create high-directivity antennas, which will enable the signal to travel further than 0.1 km. This will allow the system to function effectively. Concurrently, large bandwidth antennas should be designed in order to facilitate the information's transmission

Hybrid Active–Passive Reconfigurable Intelligent Surface for Cooperative Transmission Systems

Reconfigurable intelligent surfaces (RISs) are acknowledged as one of the key technologies for the next-generation communication systems due to their low cost, high-energy efficiency, and the ability to intelligently control the wireless propagation environment. In this paper, we present a hybrid active–passive reconfigurable intelligent surface (HAPR) for cooperative transmission system, where HAPR can intelligently change its operating mode according to the channel environment, eliminating the “multiplicative fading” effect of traditional passive RIS (P-RIS) and higher power consumption of active RIS (A-RIS), and combining the advantages of both to effectively improve the system performance. First, we investigate the ideal reflection coefficient of RIS reflecting elements (REs) under the condition of a limited power budget. Using the compound Simpson formula, the closed-form approximation expression for the system outage probability (OP) has been derived. Finally, Monte Carlo simulation is used to confirm the accuracy of the expression. The simulation results demonstrate that HAPR has a better performance than both A-RIS and P-RIS, which can achieve a lower OP.

High-speed flexible near-infrared organic photodiode for optical communication.

Optical communication is a particularly compelling technology for tackling the speed and capacity bottlenecks in data communication in modern society. Currently, the silicon photodetector plays a dominant role in high-speed optical communication across the visible-near-infrared spectrum. However, its intrinsic rigid structure, high working bias and low responsivity essentially limit its application in next-generation flexible optoelectronic devices. Herein, we report a narrow-bandgap non-fullerene acceptor (NFA) with a remarkable π-extension in the direction of both central and end units (CH17) with respect to the Y6 series, which demonstrates a more effective and compact 3D molecular packing, leading to lower trap states and energetic disorders in the photoactive film. Consequently, the optimized solution-processed organic photodetector (OPD) with CH17 exhibits a remarkable response time of 91ns (λ = 880nm) due to the high charge mobility and low parasitic capacitance, exceeding the values of most commercial Si photodiodes and all NFA-based OPDs operating in self-powered mode. More significantly, the flexible OPD exhibits negligible performance attenuation (<1%) after bending for 500 cycles, and maintains 96% of its initial performance even after 550h of indoor exposure. Furthermore, the high-speed OPD demonstrates a high data transmission rate of 80MHz with a bit error rate of 3.5 [Formula: see text] 10-4, meaning it has great potential in next-generation high-speed flexible optical communication systems.

Securing the Future: A Resourceful Jamming Detection Method Utilizing the EVM Metric for Next-Generation Communication Systems

This paper addresses the escalating threat of malicious jamming in next-generation communication systems, propelled by their continuous advancement in speed, latency, and connectivity. Recognizing the imperative for communication security, we propose an efficient jamming detection method with distinct innovations and contributions. Motivated by the growing sophistication of jamming techniques, we advocate the adoption of the error vector magnitude (EVM) metric, measured in IQ symbols, deviating from traditional received signal strength and bit error rate-based measurements. Our method achieves enhanced jamming detection sensitivity, surpassing existing approaches. Furthermore, it introduces low complexity, ensuring resource-effective detection. Crucially, our approach provides vital jammer frequency information, enhancing counteraction capabilities against jamming attacks. It demonstrates stable results against varying system parameters, such as modulation type and code rate, thereby contributing to adaptability. Emphasizing practicality, the method seamlessly integrates into 5G and LTE systems without imposing additional overhead. Versatility is demonstrated through successful operations in diverse scenarios that are run by extended simulation conditions. Theoretical analysis substantiates these advantages, reinforcing the validity of our methodology. The study’s success is further validated through laboratory experiments, providing empirical evidence of its effectiveness. The proposed method represents a significant step toward fortifying next-generation communication systems against evolving jamming threats.

Massive Connectivity and Low-Latency for Next-Generation Internet of Things: A Filtered OFDM-based Deep Learning Approach

Abstract The Internet of Things (IoT) is one of the numerous services offered by sixth-generation (6G) mobile communications. It is necessary to meet heterogeneous criteria for large connectivity and low latency to serve the various kinds of IoT applications. In order to concurrently provide enormous connectivity and meet the low-latency conditions in the uplink IoT network, we proposed filtered orthogonal frequency division multiplexing (FOFDM) based on a service group adopting the deep learning (DL) technique. The proposed FOFDM-DL platform focuses on two key areas: first, it works for the concurrence of different time-frequency granularity appropriate for distinct service-based grouping, and secondly, it facilitates low latency and massive connectivity to deliver dependable communications. The suggested FOFDM-DL architecture may accommodate the needs of massive machine-type communication referred as mMTC and ultra-reliable and low-latency communications known as uRLLC concurrently for the next-generation communication systems. However, the uRLLC and mMTC requirements can only be supported separately by the new radio (NR)-5G, beyond 5G (or 6G). In comparison to the traditional scheme, simulation results demonstrate that the suggested FOFDM-DL platform works surprisingly well in the next-generation IoT network.