Next-generation Mobile Communication Research Articles

Load-aware continuous-time optimization for multi-agent systems: toward dynamic resource allocation and real-time adaptability

In the realm of next-generation mobile communication networks, characterized by dynamic and evolving workloads, the efficient resource allocation becomes paramount for achieving optimal performance. This paper addresses the intricate challenges of multiagent resource management through the integration of stochastic learning automata and continuous-time optimization techniques, presenting an innovative solution for real-time adaptability and dynamic load balancing. The central aim is to achieve optimal values for local time-varying cost functions while taking into account resource constraints and the feasibility of local allocation. In the context of multi-agent resource allocation systems, where conditions vary over time, the algorithm exhibits a dynamic adaptability, continuously adjusting to the evolving optimal solutions tailored for each agent. Utilizing stochastic learning automata, the algorithm effectively addresses the time-varying load-balancing function in response to dynamic user demands. Furthermore, we introduced an scalable solution for mobility robustness optimization based on deep reinforcement learning (DRL-MRO). This method dynamically identifies network-wide optimal parameter values across the entire network to accommodate diverse mobility patterns, ensuring the effectiveness of load balancing parameters that seamlessly adapt to the dynamic configuration of the network. The overarching goal is to maintain a consistent quality of service level for each agent, thereby enhancing the overall system performance. Simulation outcomes unequivocally affirm the superior performance of the proposed load balancing approach, rooted in continuous-time optimization and stochastic learning automata, surpassing existing schemes across diverse system configurations.

RSMA-aided V2X communications: A multi-layer perspective

Rate-splitting multiple access (RSMA), a novel technology in next-generation mobile communications, has garnered increasing attention for its powerful and flexible interference management when compared to traditional multiple access methods. However, considering classical vehicle-to-everything (V2X) communication networks with multiple cells, the flexibility of decoding increases with an increasing number of users having different requests, which results in higher outage performance and additional energy consumption. In order to address these problems, this paper proposes a novel multi-layer (ML) RSMA scheme, aiming to enhance the system performance and decrease the decoding flexibility simultaneously. For the first layer, users enjoying optimal quality of service (QoS) are selected to aid the other cluster members. For the second layer, the cluster members are grouped following the QoS and request similarity. In addition, with respect to our proposed ML-V2X RSMA system, this paper investigates the performance over Rayleigh fading channels, where we derive closed-form expressions of achievable sum rate and outage probability, respectively. Numerical results reveal that: (1) For low SNR scenarios, the ML-V2X RSMA system achieves higher achievable sum rates than classical NOMA-aided V2X systems. (2) The outage probability of ML-V2X RSMA system is superior to that of NOMA-aided V2X systems and traditional cooperative communication systems.

A Comprehensive Review of UAV-Assisted FSO Relay Systems

The evolving requirements of next-generation mobile communications networks can be met by leveraging vertically deployed Unmanned Aerial Vehicle (UAV) platforms integrated with Free Space Optical communications (FSO). This integration offers a flexible and scalable architecture capable of delivering high-rate communication without requiring licenses while aligning with the multi-gigabit paradigm. In recent times, the increasing availability of commercial aerial platforms has facilitated experimental demonstrations of UAV-enabled FSO systems, which play a crucial role in proposed backhaul networks and point-to-point communications by overcoming Line-of-Sight (LOS) challenges. These systems can be rapidly deployed to meet sudden demand scenarios. This document provides a comprehensive review of relevant field demonstrations of UAV-enabled FSO relay systems, with a particular focus on commercially available, free-flying platforms that are driving advancements in this domain. It categorizes the different platforms by considering the operational altitudes of these systems and their payload actuation capacity, which determines their adaptability to variables. The analysis aims to distill the design considerations that lead to optimal performance regarding communications throughput and other relevant metrics. Moreover, it also attempts to highlight areas where design choices have fallen short, indicating gaps in current research efforts toward the widespread adoption of UAV-enabled FSO relay systems. Finally, this work endeavors to outline effective design considerations, guidelines, and recommendations to bridge these identified gaps. It serves as a valuable reference guide for researchers involved in developing UAV-enabled FSO relay systems, enabling them to make informed decisions and pave the way for the successful implementation of such systems.

Reinforcement learning-based resource allocation for dynamic aggregated WiFi/VLC HetNet

High transmission rates and low power consumption make visible light communication (VLC) a highly promising supplementary technology for the next generation of mobile communication. Taking into account the limited coverage area, VLC can be combined with WiFi as a heterogeneous network (HetNet), thanks to their non-overlapping spectrum. In order to fully utilize the advantages of the WiFi and VLC technologies, a new aggregated WiFi/VLC HetNet consisting of a single WiFi AP and multiple VLC APs, is designed, where the user equipment (UE), for the first time, can access multiple VLC APs and one WiFi AP simultaneously, and be allowed to acquire multiple resource blocks (RB) in each AP at the same time. To optimize the performance of the above designed HetNet, a multi-objective optimization problem (MOOP) is formulated, which aims to maximize system throughput while reducing the handover rate. Since the above MOOP is non-convex and nonlinear, the traditional resource allocation (RA) algorithm has a complex calculation process and poor timeliness performance to deal with this problem. To solve the above MOOP, a reinforcement learning (RL)-based RA algorithm is proposed, and considering the RB handover overhead in the aggregated WiFi/VLC HetNet, a reward function related to the system throughput and the UE handover rate is carefully designed. System throughput, system handover rate, user satisfaction, as well as user fairness performance are analyzed under three typical indoor illumination layouts. Finally, compared with the greedy algorithm and the hypergraph-based carrier aggregation algorithm, numerical results show that the proposed RL-based RA algorithm could improve the system throughput over the former two algorithms by 30.26% and 19.71%, while reducing the system handover rate by 0.15% and 0.02%, respectively.

PPO-Based Joint Optimization for UAV-Assisted Edge Computing Networks

In next-generation mobile communication scenarios, more and more user terminals (UEs) and edge computing servers (ECSs) are connected to the network. To ensure the experience of edge computing services, we designed an unmanned aerial vehicle (UAV)-assisted edge computing network application scenario. In the considered scenario, the UAV acts as a relay node to forward edge computing tasks when the performance of the wireless channel between UEs and ECSs degrades. In order to minimize the average delay of edge computing tasks, we design the optimization problem of joint UE–ECS matching and UAV three-dimensional hovering position deployment. Further, we transform this mixed integer nonlinear programming into a continuous-variable decision process and design the corresponding Proximal Policy Optimization (PPO)-based joint optimization algorithm. Sufficient data pertaining to latency demonstrate that the suggested algorithm can obtain a seamless reward value when the number of training steps hits three million. This verifies the algorithm’s desirable convergence property. Furthermore, the algorithm’s efficacy has been confirmed through simulation in various environments. The experimental findings ascertain that the PPO-based co-optimization algorithm consistently attains a lower average latency rate and a minimum of 8% reduction in comparison to the baseline scenarios.

Next-generation mobile communication leveraging cutting-edge photonic technologies (Photonic 6G)

Next-generation mobile communication leveraging cutting-edge photonic technologies (Photonic 6G) Our aim is to develop ‘Photonic 6G’, an all-photonic THz communication technology, by integrating advanced photonic methods. This includes generating low-phase-noise THz waves with microcombs and converting modulated THz waves into optical carrier signals. By leveraging these advancements, we aim to enable advanced modulation and multiplexing in the optical domain, ultimately achieving the integration for photonic 6G.

Comprehensive Simulation Framework for Space-Air-Ground Integrated Network Propagation Channel Research.

The space-air-ground integrated network (SAGIN) represents a pivotal component within the realm of next-generation mobile communication technologies, owing to its established reliability and adaptable coverage capabilities. Central to the advancement of SAGIN is propagation channel research due to its critical role in aiding network system design and resource deployment. Nevertheless, real-world propagation channel research faces challenges in data collection, deployment, and testing. Consequently, this paper designs a comprehensive simulation framework tailored to facilitate SAGIN propagation channel research. The framework integrates the open source QuaDRiGa platform and the self-developed satellite channel simulation platform to simulate communication channels across diverse scenarios, and also integrates data processing, intelligent identification, algorithm optimization modules in a modular way to process the simulated data. We also provide a case study of scenario identification, in which typical channel features are extracted based on channel impulse response (CIR) data, and recognition models based on different artificial intelligence algorithms are constructed and compared.

The geopolitics of next generation mobile communication standardization: The case of open RAN

The U.S. confrontation with China in technology has been escalating. One of the triggers is China's rise in 5G standardization and its lead in the telecommunications equipment market, which causes security concerns. In response, the U.S. promotes Open RAN as an alternative to the Chinese providers' proprietary solutions. It is claimed to enable the establishment and operation of open and safer networks for 5G and beyond. This paper examines why and how the U.S. promotes Open RAN and what the responses are from other countries. We find that the U.S. government's strong support for the development and dissemination of Open RAN signals its techno-nationalistic turn in international standardization. The origin of Open RAN is geopolitical in the sense that it represents a reaction to China's lead in 5G standardization. The geopolitical perspective is strengthened as we find the formation of alliances in support of Open RAN. A refreshed approach of the U.S. to standardization has introduced a new dynamic to cooperation and competition for setting the global rules on next-generation mobile communication technologies as well as emerging technologies. Standards are increasingly at the core of the ongoing geopolitical technology competition, and as such further investigation is required.

A Study on Exposure to Electromagnetic Fields From User Equipment Antennas Above 100 GHz

The next-generation mobile communication technology may exploit the higher frequency spectrum beyond 100 GHz, while most studies on electromagnetic field exposure from mobile communication devices focus on frequencies below 100 GHz. In this article, the electromagnetic field exposure from subterahertz antennas designed for future mobile communication is evaluated with a multilayer flat tissue phantom. It is demonstrated that the deposited electromagnetic fields can be evaluated by neglecting the deep tissue in the simplified phantom. Then, the temperature distribution in the full-size phantom can be evaluated using the solution to the simplified electromagnetic problem to reduce the overall computation time. Considering different sizes of the averaging area for absorbed power density, the results show a good correlation between the peak rising temperature and the peak absorbed power density averaged over a small area of around one square centimeter.

K-XMSS and K-SPHINCS+: Enhancing Security in Next-Generation Mobile Communication and Internet Systems with Hash Based Signatures Using Korean Cryptography Algorithms.

As Mobile Communication and Internet Systems (MCIS) have rapidly developed, security issues related to MCIS have become increasingly important. Therefore, the development and research of security technologies for mobile communication and internet systems are actively being conducted. Hash-Based Signature (HBS) uses a hash function to construct a digital signature scheme, where its security is guaranteed by the collision resistance of the hash function used. To provide sufficient security in the post-quantum environment, the length of hash should be satisfied for the security requirement. Modern HBS can be classified into stateful and stateless schemes. Two representative stateful and stateless HBS are eXtended Merkle Signature Scheme(XMSS) and SPHINCS+, respectively. In this paper, we propose two HBS schemes: K-XMSS and K-SPHINCS+, which replace internal hash functions of XMSS and SPHINCS+ with Korean cryptography algorithms. K-XMSS is a stateful signature, while K-SPHINCS+ is its stateless counterpart. We showcase the reference implementation of K-XMSS and K-SPHINCS+ employing Lightweight Secure Hash (LSH) and two hash functions based on block ciphers (i.e., CHAM and LEA) as the internal hash function. In addition, K-XMSS and K-SPHINCS+ using Advanced Vector Extensions 2 (AVX2) have been provided, demonstrating that they can be optimized for better performance using advanced implementation techniques than previous approaches.

Olive Branch Learning: A Topology-Aware Federated Learning Framework for Space-Air-Ground Integrated Network

The space-air-ground integrated network (SAGIN), one of the key technologies for next-generation mobile communication systems, can facilitate data transmission for users all over the world, especially in some remote areas where vast amounts of informative data are collected by Internet of remote things (IoRT) devices to support various data-driven artificial intelligence (AI) services. However, training AI models centrally with the assistance of SAGIN faces the challenges of highly constrained network topology, inefficient data transmission, and privacy issues. To tackle these challenges, we first propose a novel topology-aware federated learning framework for the SAGIN, namely Olive Branch Learning (OBL). Specifically, the IoRT devices in the ground layer leverage their private data to perform model training locally, while the air nodes in the air layer and the ring-structured low earth orbit (LEO) satellite constellation in the space layer are in charge of model aggregation (synchronization) at different scales. To further enhance communication efficiency and inference performance of OBL, an efficient Communication and Non-IID-aware Air node-Satellite Assignment (CNASA) algorithm is designed by taking the data class distribution of the air nodes as well as their geographic locations into account. Furthermore, we extend our OBL framework and CNASA algorithm to adapt to more complex multi-orbit satellite networks. We analyze the convergence of our OBL framework and conclude that the CNASA algorithm contributes to the fast convergence of the global model. Extensive experiments based on realistic datasets corroborate the superior performance of our algorithm over the benchmark policies.

Alignment-free twisted-split-ring metasurface on single substrate with 2π phase range for linearly polarized sub-terahertz wave.

To achieve high-speed, large-capacity communication, next-generation mobile communication systems will require manipulation of the propagation of sub-terahertz waves in the propagation channel. In this paper, we propose the use of a novel split-ring resonator (SRR) structure as a metasurface unit cell for manipulating the linearly polarized incident and transmission waves used in mobile communication systems. In this SRR structure, the gap is twisted by 90° to efficiently use cross-polarized scattered waves. By changing the twist direction and gap size of the unit cell, 2π phase designability can be achieved, which enables linear polarization conversion efficiencies of -2 dB with a backside polarizer and -0.2 dB with two polarizers. In addition, a complementary pattern of the unit cell was fabricated, and a measured conversion efficiency of more than -1 dB at the peak with only the backside polarizer on a single substrate was verified. In the proposed structure, the 2π phase designability and efficiency gain are obtained independently by the unit cell and polarizer, respectively, thus enabling alignment-free characteristics, which are highly advantageous from an industrial viewpoint. Metasurface lenses with binary phase profiles of 0 and π were fabricated using the proposed structure with a backside polarizer on a single substrate. The lenses' focusing, deflection, and collimation operations were experimentally verified with a lens gain of 20.8 dB, which agreed well with our calculated results. Our metasurface lens has the great advantages of easy fabrication and implementation, and it has the potential to enable dynamic control by combining it with active devices because of the simple design methodology, which entails only changing the twist direction and the gap's capacitance component.

Fully-Decoupled Radio Access Networks: A Flexible Downlink Multi-Connectivity and Dynamic Resource Cooperation Framework

To enable flexible base stations (BS) association and dynamic resource management for personalized user equipment (UE) download service provision in the next-generation mobile communication network (6G), in this paper, we investigate the downlink (DL) transmission scenario in an origin fully-decoupled radio access network (FD-RAN) architecture. Considering the unique fully-decoupled UL/DL access feature, we propose an efficient two-stage DL channel estimation method in the FD-RAN. We formulate a novel multi-connectivity and dynamic resource cooperation problem with joint multiple-BS and multiple-UE association and coordinated beamforming, aiming at maximizing the weighted sum achievable rate in DL FD-RAN. By leveraging the many-to-many swap-matching theory and fractional relaxation approach, we solve the dynamic UE scheduling problem with multiple-BS and multiple-UE association and the coordinated beamforming problem, respectively. Extensive simulation results based on standard 3GPP 36.873 urban micro channel demonstrate that the proposed framework can improve the average spectral efficiency by 34.9% as compared to the traditional maximum ratio transmission beamforming method.

Theoretical investigation of Rayleigh surface acoustic wave propagation characteristics in c-axis-zigzag ScAlN film/silicon substrate structure

Surface acoustic wave (SAW) resonators are key components of mobile communication systems, and the development of wideband SAW resonators is especially required because next-generation mobile communication systems require high-speed data transmission using wide frequency bands. In this study, two layered structures—(i) a c-axis-tilted ScAlN bilayer film/silicon substrate and (ii) a c-axis-zigzag ScAlN film/silicon substrate—are proposed for highly coupled SAW resonators, and the electromechanical coupling coefficient K2 of the non-leaky Rayleigh-mode SAW propagating in these structures is investigated theoretically. With a proper c-axis tilt angle and thickness selection of the ScAlN film, the first-mode Rayleigh SAW in the c-axis-tilted ScAlN bilayer film/silicon substrate and c-axis-zigzag ScAlN film/silicon substrate offers high K2. The maximum K2 was 9.56%, obtained in the c-axis-zigzag ScAlN film/silicon substrate structure, which was 2.5 times the maximum K2 in the c-axis-tilted ScAlN monolayer film/silicon substrate structure; this is because the c-axis-zigzag ScAlN films increase the shear vertical component of the SAW particle displacement, most of which is concentrated in the c-axis-zigzag ScAlN film on the silicon substrate. It is also important that the second-mode SAW (Sezawa wave) in the c-axis-zigzag ScAlN film/silicon substrate structure is not excited when the K2 value of the first-mode SAW is maximized. The techniques for fabricating a c-axis-tilted ScAlN film and a c-axis-zigzag ScAlN film have been reported, and well-established micromachining technology related to silicon semiconductors offers significant advantages in the manufacturing and processing of SAW resonators. Therefore, the c-axis-zigzag ScAlN film/silicon substrate structure has significant potential for SAW device applications.

Extremely Lightweight Constant-Round Membership-Authenticated Group Key Establishment for Resource-Constrained Smart Environments toward 5G

AbstractWith rapid development of next-generation mobile networks and communications (5G networks), group-oriented applications in resource-constrained smart environments (RSEs), such as smart homes and smart classrooms, have attracted great attentions. Due to the insecure communications between resource-constrained devices, secure group communications in RSE toward 5G face many challenges. In RSE toward 5G, lightweight communications and low computational overheads are crucial. Besides, the private tokens used to generate the group key are expected to be reused multiple times. However, the conventional frameworks for secure group communications cannot meet these requirements. A practical construction of extremely lightweight constant-round membership authenticated group key establishment framework is proposed in this paper for RSE toward 5G, which not only implements identity authentication among the members and group key establishment but also ensures extremely lightweight computation and communication costs by each group member. In our proposed scheme, the increase in the number of group members will not lead to a linear or logarithmic increase in the communication and calculation costs at the member side. Our framework also resists external and internal attacks and meets all the desirable security features. In this framework, the privacy of tokens can be well protected, so that they can be reused for multiple times. Therefore, our scheme significantly reduces the costs of communication and calculation, and it is more efficient compared with the related schemes in the literature. This proposal is fairly suitable for lightweight membership authentication and group key establishment in RSE toward 5G.

Markov chain modelling of ordered Rayleigh fading channels in non‐orthogonal multiple access wireless networks

AbstractA first‐order finite‐state Markov chain (FSMC) typically models the Rayleigh fading channel in the open literature because the first‐order FSMC is analytically tractable and can derive closed‐form results. Non‐orthogonal multiple access (NOMA) has been recognised as a novel wireless technology that addresses challenges in the next generation of mobile communications. According to the power‐domain NOMA protocol, channels in the NOMA wireless network are sorted by the channel gain. Then considering NOMA, there is insufficient information on how to further form a suitable model for ordered Rayleigh fading channels based on the first‐order FSMC. Given the mathematical statement on how to model the order statistics of multidimensional Markov chains for ordered Rayleigh fading channels, the authors consider these order statistics as a Markov chain, and propose specific processes of representing the state space and constructing the transition probability matrix accordingly. Numerical and simulation results validate the mathematical correctness and accuracy of these novel processes. In addition, for ordered Rayleigh fading channels, the performances of various methods of partitioning the entire signal‐to‐noise ratio range are compared. The performance comparison results are the same as those obtained for the individual unordered Rayleigh fading channel.

AI in SAGIN: Building Deep Learning Service-Oriented Space-Air-Ground Integrated Networks

In next-generation mobile communications, spaceair- ground integrated networks (SAGINs) is an emerging infrastructure in future wireless access networks. Since artificial intelligence (AI) applications become more and more important, it is essential to build a deep learning service-oriented SAGINs. In this article, we present a hierarchical intelligent computing structure focusing on processing deep learning tasks in future SAGINs. An optimization strategy is also proposed to improve the quality-of-service (QoS) of deep learning tasks in the proposed structure. We test our work in small testbed and simulations. The evaluation results show that the proposed work outperforms other offloading strategies in a SAGIN environment.

Energy Harvesting Modulation for Integrated Control State and Energy Transfer in Industrial IoT

With the development of wireless communications, the technology of industrial Internet of Things (IIoT) has been considered as a candidate for the next generation of mobile communications, which could provide automatic services for the smart factory. Massive low-power devices are swarming into the scenario for providing network intelligence. These energy-thirsty devices all require efficient control state delivery. In this letter, an energy harvesting modulation (EHM) scheme is proposed for integrated control state and energy transfer (ICSET) towards these low-power devices. The performance of wireless energy transfer (WET) and wireless control state transfer (WCST) are also analysed theoretically. The ICSET performance is optimized by ensuring the control reliability. Simulation results validate the theoretical analysis. They also demonstrate that an appropriate time slot number within a period should be selected to increase the effective control rate, while ensuring the energy harvesting performance and the control reliability of IIoT.

Evaluating RF Hardware Characteristics for Automotive JCRS Systems Based on PMCW-CDMA at 77GHz

Joint communications and radar sensing (JCRS) applications are currently being hailed as the innovation of the next generation of mobile communications. The combination of communications and sensor technology on one hardware platform offers various advantages, such as significant savings in space and costs. The two technologies are no longer being optimized and developed side by side, as has been the case in the past, but jointly. The physical channel is used by both simultaneously, including the transmitter and receiver structures, which must be optimized for the combined application. This inevitably leads to an influence on the performance of both systems. In this work, this influence is considered and analyzed with respect to the effects of the radio frequency components. For this purpose, our previously published code-division multiple access (CDMA)-based and vehicle-to-vehicle-focused model is extended to a JCRS model and evaluated according to the achieved bit error rate as well as the mean deviation of the detected distance and velocity in Simulink. The influence of the non-ideal hardware components (mixers, power amplifier, low noise amplifier, filter, antenna) and characteristics (S-parameters, non-linearity of the amplifiers and the noise) on the sensing and communications are analyzed and compared in this automotive context. The results reveal that the noise of the low noise amplifier at the receiver side has the most decisive influence. In contrast, the noise generated by the power amplifier at the transmitter has no effect due to the relatively high signal power. The non-linearity of amplifiers at the transmitter also significantly impacts the available sensing range by limiting and compressing signal power. Besides, the phase noise with a frequency offset higher than 10MHz can increase the communications and sensing error rate. In contrast, the influence of S-parameters is negligible, as the performance of communications and sensing is almost unchanged with different S-parameters. In the future, the proposed single-target scene will be further extended to a multi-target one.

Joint multi-domain channel estimation based on sparse Bayesian learning for OTFS system

Since orthogonal time-frequency space (OTFS) can effectively handle the problems caused by Doppler effect in high-mobility environment, it has gradually become a promising candidate for modulation scheme in the next generation of mobile communication. However, the inter-Doppler interference (IDI) problem caused by fractional Doppler poses great challenges to channel estimation. To avoid this problem, this paper proposes a joint time and delay-Doppler (DD) domain based on sparse Bayesian learning (SBL) channel estimation algorithm. Firstly, we derive the original channel response (OCR) from the time domain channel impulse response (CIR), which can reflect the channel variation during one OTFS symbol. Compare with the traditional channel model, the OCR can avoid the IDI problem. After that, the dimension of OCR is reduced by using the basis expansion model (BEM) and the relationship between the time and DD domain channel model, so that we have turned the underdetermined problem into an overdeter-mined problem. Finally, in terms of sparsity of channel in delay domain, SBL algorithm is used to estimate the basis coefficients in the BEM without any priori information of channel. The simulation results show the effectiveness and superiority of the proposed channel estimation algorithm.