VTC 2025 Spring Conference’s Shorts

Switching off unused bands and optimal DUs placement on O-RAN multi-band system

Currently, the Open Radio Access Network (O-RAN) architecture is the best solution for deploying Radio Access Network (RAN). This architecture presents several challenges, i.e., function splitting, function placement and energy consumption. The aim of this study is to satisfy user demand while minimizing costs. In this work we combine the O-RAN architecture and the multiband system. We consider that the RAN network load varies during the day and we study the optimal placement of the Distributed Unit (DU) function and switch off unnecessary frequency bands. First, we propose an algorithm to find the number of frequency bands needed to satisfy user demand for different smoothing periods. Based on these results, we formulate the problem of DU placement and frequency band switch-off as an Integer Linear Programming (ILP) whose objective is to minimize computing and routing cost while respecting delay and capacity constraints. Evaluation of our model on real topology has shown that our model with frequency band extinction has a much lower system cost than our model without band extinction.Switching off unused bands and optimal DUs placement on O-RAN multi-band systemAmath NDAO, IMT Atlantique; Xavier Lagrange, IMT Atlantique, IRISA; Nicolas Huin, Loutfi Nuaymi, Geraldine Texier, IMT Atlantique

Queue-Aware Hybrid RIS-Assisted Cell-Free Communication Systems

In this paper, we investigate the cross-layer design in hybrid reconfigurable intelligent surface (RIS)-assisted cell-free systems. To maximize long-term energy efficiency while ensuring network stability, we formulate a queue-aware stochastic problem that jointly optimizes the beamforming matrices at the remote antenna units (RAUs) and hybrid RIS, along with the operation modes of RIS elements. By utilizing the Lyapunov theory, the formulated stochastic optimization problem is decomposed into a sequence of slot-level problems that maximize energy efficiency while minimizing the Lyapunov drift. To tackle the formulated non-convex slot-level problem, we propose an alternating optimization algorithm to transform the slot-level problem into transmission and element mode switching subproblems. In particular, for efficient RIS element selection, we first derive the number upper bound of the elements that can be activated given the RIS power budget, and then the element selection optimization is transformed into multiple tractable smaller problems that can be solved in parallel by utilizing a greedy algorithm. Simulation results demonstrate that the proposed algorithm outperforms the baseline schemes in terms of energy efficiency and can effectively improve system stability as well as user fairness.Queue-Aware Hybrid RIS-Assisted Cell-Free Communication SystemsYuanmeng Song, Bo Liu, Yu Qian, Qinyuan Zheng, Pengcheng Zhu, Southeast University

PSO-Aided Reinforcement Learning for Beam and Power Management in RIS-Assisted mmWave Netw...

This paper proposes a novel Particle Swarm Optimization-Aided Reinforcement Learning (PSO-RL) framework for efficient beam and power management in reconfigurable intelligent surface (RIS)-assisted millimeter-wave (mmWave) networks. To optimize dynamic beam coordination and resource allocation, we introduce a reinforcement learning (RL)-based approach that integrates value and policy networks, with the policy network enhanced by a target policy network (TPN). By employing PSO, we refine TPN parameters to accelerate convergence and enhance solution exploration. Simulation results validate the effectiveness of the proposed PSO-RL framework, demonstrating significant performance improvements in RIS-assisted network deployments. The method enhances system capacity by 29.75% and improves edge user capacity by 36.65%. These results highlight the potential of PSO-RL for optimizing beam allocation in dynamic urban network environments.PSO-Aided Reinforcement Learning for Beam and Power Management in RIS-Assisted mmWave NetworksHuan-Hsung Lin, Sau-Hsuan Wu, Yu-Hsiang Lo, Chun-Hsien Ko, Yu-Chih Huang, National Yang Ming Chiao Tung University

Intelligent Reflecting and Refracting Surfaces for SWIPT-Enabled 6G RF-Based Communication...

In this paper, we introduce a novel architecture for simultaneous wireless information and power transfer (SWIPT) featuring a single transmitter, an Intelligent Reflecting and Refracting Surface with multiple elements, and two users respectively receiving the reflected and refracted signals. A time-switching (TS) architecture of SWIPT is employed at the receivers, enabling orthogonal energy harvesting (EH) and information decoding. We formulate an optimization problem to maximize the sum throughput while meeting the EH constraints at both users. The optimal transmit power is determined while ensuring constraint satisfaction. A bisection method is used to find the optimal TS ratio, leveraging the unimodal nature of the throughput and EH functions for computational efficiency and guaranteed convergence. Numerical simulations validate the proposed approach, demonstrating significant performance gains in SWIPT systems.Intelligent Reflecting and Refracting Surfaces for SWIPT-Enabled 6G RF-Based CommunicationsSumit Gautam, Indian Institute of Technology - Indore

3D Stochastic Geometry Model for Aerial Vehicle-Relayed Ground-Air-Satellite Connectivity

Due to their flexibility, aerial vehicles (AVs), such as unmanned aerial vehicles and airships, are widely employed as relays to assist communications between massive ground users (GUs) and satellites, forming an AV-relayed ground-air-satellite solution (GASS). In GASS, the deployment of AVs is crucial to ensure overall performance from GUs to satellites. This paper develops a stochastic geometry-based analytical model for GASS under Matérn hard-core point process (MHCPP) distributed AVs. The 3D distributions of AVs and GUs are modeled by considering their locations on spherical surfaces in the presence of high-altitude satellites. Accordingly, we derive an overall connectivity analytical model for GASS, which includes the average performance of AV-relayed two-hop transmissions. Extensive numerical results validate the accuracy of the connectivity model and provide essential insights for configuring AV deployments.3D Stochastic Geometry Model for Aerial Vehicle-Relayed Ground-Air-Satellite ConnectivityYulei Wang, South-Central Minzu University; Yalin Liu, Yaru Fu, Hong Kong Metropolitan University; Yujie Qin, University of Electronic Science and Technology of China; Zhongjie Li, South-Central Minzu University

Power Efficient Networking Support for Digital Twins with Age of Information Targets

This paper studies network resource allocation for multiple IoT devices as physical systems (PSs) tasked with maintaining their digital twins (DTs) at a shared edge server (ES) through a shared communication channel. The problem is formulated as a constrained Markov decision process with an objective of reducing the average transmission power of the PSs while keeping the age of information (AoI) at the DTs below predetermined targets. A hybrid decision making frame is proposed, where multiple agent reinforcement learning is used to make decisions for the transmission power of the PSs in a distributed way, and a centralized and deterministic algorithm is proposed to allocate the computation resources of the ES among the DTs. Simulation results show that, compared with the multi-agent duelling double deep Q-Network, the proposed multi-agent deep deterministic policy gradient for power allocation together with the urgency-baed computation resource allocation solution achieves much lower the average power consumption of the PSs while maintaining low AoI violation rate at the DTs.Power Efficient Networking Support for Digital Twins with Age of Information TargetsAmirhosein Aghaei, Kiana Noroozi, Dongmei Zhao, McMaster University

Network Energy Saving Optimization in Advanced Mobile Networks

In the fifth generation (5G) mobile networks, the growing energy consumption of base stations (BS) has made network energy saving (NES) an increasingly important issue. This paper proposed optimized schemes, including the BS-oriented NES (B-NES), the user equipment (UE)-oriented NES (U-NES), and the hybird NES (H-NES), for the NES function (NESF) to make the BS energy-saving decision. The first two schemes employ heuristic algorithms, while the last scheme adopts the Harris Hawks Optimization (HHO) or Whale Optimization Algorithm (WOA), based on an evolutionary approach. With the proposed schemes, each UE periodically measures the received signal reference power (RSRP) of both the serving and neighboring BSs and reports candidate BSs with an RSRP at least as high as that of the serving BS to the NESF. Additionally, each BS periodically reports its current and predicted traffic load to the NESF. The information is utilized by the NESF to optimize network energy efficiency by determining the transition of each BS between energy saving and active states, while maintaining the quality of service of UEs. Simulation results show that the H-NES scheme achieves the best energy efficiency, however its computational complexity is the highest. In contrast, the U-NES scheme, which has the lowest computational complexity, outperforms the B-NES scheme and performance lower than that of the H-NES scheme. In conclusion, the proposed schemes not only enable energy-efficient networks but also exhibit adaptability for deployment in the sixth-generation (6G) mobile networks.Network Energy Saving Optimization in Advanced Mobile NetworksChen-Hsin Lee, Ping Chang, Shiann-Tsong Sheu, National Central University

Joint Training of Predistortion, Power Back-Off and Constellation for Satellite Power Ampl...

The deployment of satellite mega constellations may enable global coverage, even for direct transmission from satellite to handheld device. Such transmissions come with increased demands in power efficiency. The traveling wave-tube amplifier (TWTA) in satellite payloads fundamentally limits the transmit power and causes distortions to the transmit signal when power efficient transmission close to amplifier saturation is desired. This work introduces a novel joint training paradigm of constellation, amplifier power back-off and data predistortion to maximize the throughput of single carrier transmission over transparent satellite links. The joint design is enabled by means of communication autoencoders, where transmitter and receiver components are adapted together to achieve the lowest bit error rate (BER). We show how constrained constellation optimization can improve performance on selected configurations from the broadcasting standard DVB-S2X. Results are presented in terms of coded BER and information rates.Joint Training of Predistortion, Power Back-Off and Constellation for Satellite Power Amplifiers using Neural NetworksDavid Kopyto, Marius Tietze, Gerhard Bauch, Hamburg University of Technology

Energy Aware Throughput Maximization in Tag-to-Multiple-tag Backscattering Networks

Backscatter tag-to-tag networks offer a sustainable and energy-efficient solution for large-scale Internet-of-Things (IoT) applications. In this paper, we propose a novel backscatter tag-to-multiple-tag network protocol based on a dual-phase system, partitioning the operational time into energy-harvesting and backscatter-communication phases. By utilising a multi-antenna reader and jointly optimising the beamforming vectors for the dual-phase problem, our design maximises the sum-throughput and substantially enhances overall system performance. To solve the non-convex transceiver optimisation problem, we derive closed-form solutions for the first phase and employ fractional programming with semidefinite relaxation for the second phase. Simulation results validate the effectiveness of the proposed solution and provide valuable insights for practical deployment, achieving an enhancement of around 3 dB over the benchmarks.Energy Aware Throughput Maximization in Tag-to-Multiple-tag Backscattering NetworksTianyi Zhang, University of New South Wales; Deepak Mishra, University of New South Wales (UNSW) Sydney; Jinhong Yuan, University of New South Wales; A. Seneviratne, UNSW Sydney

An Energy Effcient Design of Hybrid NOMA Based on Flexible SIC Methods

This paper aims to reveal the potential of hybrid non-orthogonal multiple access (NOMA) in improving energy efficiency, which combines the advantages of NOMA and conventional orthogonal multiple access (OMA). In particular, a novel hybrid NOMA scheme is proposed, which can be implemented as a simple add-on to the legacy OMA network. Specifically, in the proposed hybrid NOMA scheme, a user can transmit signals by using not only its own allocated channel resource block as in OMA, but also sharing the channel of other users via NOMA. To release the potential of hybrid NOMA, a flexible successive interference cancellation (SIC) method is adopted. Rigorous analysis is provided, which indicates that even with less energy consumption, the proposed hybrid NOMA scheme offers a higher data rate than the conventional OMA scheme. The numerical results support the analysis and highlight the superior performance of HSIC in comparison to FSIC.An Energy Effcient Design of Hybrid NOMA Based on Flexible SIC MethodsYanshi Sun, Wei Cao, Hefei University of Technology; Ning Wang, China University of Mining and Technology; Momiao Zhou, Hefei University of Technology; Zhiguo Ding, Khalifa University