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Adrian Kliks

Publications and source records attributed to Adrian Kliks.

At least 19 recordsLinked to original sources

A Unified E2E Energy Efficiency Testing Framework for Open RAN

Energy efficiency (EE) is one of the key challenges for contemporary and future mobile networks, including within the Open Radio Access Network (O-RAN) architecture. However, there is a significant gap in common procedures for comparing the EE of both hardware (HW) and software (SW) solutions offered by various vendors. Usually, EE improvements of both SW and HW solutions are demonstrated in a specific scenario defined by individual vendors avoiding comparisons and benchmarking under various network conditions. This paper outlines the need for unified end-to-end (E2E) EE testing for O-RAN. First, it analyzes the standards to identify missing parts. Based on the analysis, a novel O-RAN E2E EE Testing framework is proposed. The framework aims to test the EE of the xApp/rApp pair cooperating on the cell on/off switching using a commercial RAN emulator and real-world network topology data from a mobile network operator (MNO). The test results show up to 57% improvement in EE compared to the baseline.

cs.NI

ACCoRD: Actor-Critic Conflict Resolution with Deep learning for O-RAN xApps

Conflict Mitigation (ConMit) is a crucial part of intelligent network control in Open Radio Access Networks (O-RAN). In this paper, we propose a method named ACCoRD to resolve detected control conflicts in Near-Real Time RAN Intelligent Controller using a Conflict Resolution (CR) Agent with an Artificial Neural Network (ANN) trained with a reinforcement learning algorithm PPO-Clip. The implemented ANN analyzes data about the network and conflicting control decisions to infer optimal CR actions. The CR Agent gathers feedback from the network after each resolved conflict to assess its efficiency and adjust the ANN's weights during batch training. The evaluation of the proposed approach is based on simulation data. A new methodology for evaluating CR solutions is proposed. Results show that the proposed ANN-based method improves on the efficiency of rule-based approaches by significantly reducing negative network events caused by conflicting control decisions in medium and high traffic scenarios.

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Sustainable Load Balancing for Wireless Networks With Renewable Energy Sources

Future wireless networks powered by renewable energy sources and storage systems (e.g., batteries) require energy-aware mechanisms to ensure stability in critical and high-demand scenarios. These include large-scale user gatherings, especially during evening hours when solar generation is unavailable, and days with poor wind conditions that limit the effectiveness of wind-based energy harvesting. Maintaining network performance under such constraints, while preserving stored energy, remains a key challenge. This work proposes an enhanced Proactive-Reactive Load Balancing algorithm that integrates energy conditions into mobility management. By leveraging standardized mobility events, the algorithm optimizes traffic distribution and energy utilization (avoiding complete drainage of stored energy), thereby preventing service degradation. Simulations show improved energy sustainability and network performance under congestion and limited solar availability.

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RIS-Aided Mobile Network Design

In this paper, we examine the distribution of radio signal propagation within the city of Poznan (Poland) to determine optimal locations for deploying Reconfigurable Intelligent Surfaces (RIS). The study focuses on designing a 5G/6G Radio Access Network (RAN), incorporating eight Base Stations (BSs) that utilize either Single Input Single Output (SISO), or Multiple Input Multiple Output (MIMO) antenna technologies, depending on the network cell configuration. Through detailed simulations and analyses, we explore various propagation scenarios in both Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS) conditions, considering the complex urban landscape characterized by high-rise buildings. The results demonstrate the potential of using RISs in mobile networks to enhance radio signal quality in urban environments through strategic placements. Our findings suggest that RISs can significantly mitigate Path Loss (PL) and improve signal coverage in challenging urban environments, particularly in areas where traditional base station deployment alone would be insufficient. Furthermore, the study highlights the role of RISs in reducing the need for additional base stations, thereby optimizing network costs and infrastructure while maintaining high-quality service delivery. The insights gained from this research provide valuable guidelines for network planners and engineers seeking to implement RIS technology in future 5G and beyond networks, ensuring more efficient and robust urban communication systems.

cs.NI

Predicting Conflict Impact on Performance in O-RAN

The O-RAN Alliance promotes the integration of intelligent autonomous agents to control the Radio Access Network (RAN). This improves flexibility, performance, and observability in the RAN, but introduces new challenges, such as the detection and management of conflicts among the intelligent autonomous agents. A solution consists of profiling the agents before deployment to gather statistical information about their decision-making behavior, then using the information to estimate the level of conflict among agents with different goals. This approach enables determining the occurrence of conflicts among agents, but does not provide information about the impact on RAN performance, including potential service degradation. The problem becomes more complex when agents generate control actions at different timescales, which makes conflict severity hard to predict. In this paper, we present a novel approach that fills this gap. Our solution leverages the same data used to determine conflict severity but extends its use to predict the impact of such conflicts on RAN performance based on the frequency at which each agent generates actions, giving more weight to faster applications, which exert control more frequently. Via a prototype, we demonstrate that our solution is viable and accurately predicts conflict impact on RAN performance.

cs.NI

Communication Technologies for Intelligent Transportation Systems: From Railways to UAVs and Beyond

This white paper aims to comprehensively analyze and consolidate the state of the art in communication technologies supporting modern and future Information and Communication Technology (ICT). Its primary objective is to establish a common understanding of how communication solutions enable automation, safety, and efficiency across multiple transport domains, including railways, road vehicles, aircraft, and unmanned aerial vehicles. The document seeks to identify key communication requirements and technological enablers necessary for interoperable and reliable ITS operation. It also assesses the limitations of current systems and proposes pathways for integrating emerging technologies such as 5G, Sixth Generation (6G), and Artificial Intelligence (AI)-driven network control. The white paper also intends to support harmonization between different transport modes through a unified framework for communication modeling, testing, and standardization. It highlights the importance of accurate channel modeling and empirical validation to design efficient, robust, and scalable systems. Another objective is to explore the use of reconfigurable intelligent surfaces, integrated sensing and communication, and digital twin concepts within ITS. The document emphasizes the role of spectrum management and standardization efforts in ensuring interoperability among diverse communication systems. Finally, the paper seeks to stimulate collaboration among academia, industry, and standardization bodies to advance the design of resilient and adaptive communication infrastructures for future transportation systems.

cs.NI

On the Placement and Sustainability of Drone FSO Backhaul Relays

We consider free-space optical (FSO) communication links for the backhaul connectivity of small cells (SCs) where a UAV with an FSO apparatus can serve as a backhaul relay node. We demonstrate how such drone relay stations (DRSs) can be deployed in a high-rise urban area in order to provide FSO line-of-sight (LOS) links that are unobstructed by buildings. Also, in our solution we consider the case where solar panels are mounted on DRSs such that placing the DRS in a sunny location is prioritized, and we show the gain in terms of number of required trips to recharge the UAV.

cs.NI

Energy-efficient User Clustering for UAV-enabled Wireless Networks Using EM Algorithm

Unmanned Aerial Vehicles (UAVs) can be used to provide wireless connectivity to support the existing infrastructure in hot-spots or replace it in cases of destruction. UAV-enabled wireless provides several advantages in network performance due to drone small cells (DSCs) mobility despite the limited onboard energy. However, the problem of resource allocation has added complexity. In this paper, we propose an energy-efficient user clustering mechanism based on Gaussian mixture models (GMM) using a modified Expected-Maximization (EM) algorithm. The algorithm is intended to provide the initial user clustering and drone deployment upon which additional mechanisms can be employed to further enhance the system performance. The proposed algorithm improves the energy efficiency of the system by 25% and link reliability by 18.3% compared to other baseline methods.

cs.NI

Experimental evaluation of xApp Conflict Mitigation Framework in O-RAN: Insights from Testbed deployment in OTIC

Conflict Mitigation (CM) in Open Radio Access Network (O-RAN) is a topic that is gaining importance as commercial O-RAN deployments become more complex. Although research on CM is already covered in terms of simulated network scenarios, it lacks validation using real-world deployment and Over The Air (OTA) Radio Frequency (RF) transmission. Our objective is to conduct the first assessment of the Conflict Mitigation Framework (CMF) for O-RAN using a real-world testbed and OTA RF transmission. This paper presents results of an experiment using a dedicated testbed built in an O-RAN Open Test and Integration Center (OTIC) to confirm the validity of one of the Conflict Resolution (CR) schemes proposed by existing research. The results show that the implemented conflict detection and resolution mechanisms allow a significant improvement in network operation stability by reducing the variability of the measured Downlink (DL) throughput by 78%.

cs.NI

RIS-Measurements for Codebook Design

Reconfigurable Intelligent Surfaces (RIS) have gained significant attention for some time. Thanks to the possibility of individual steering of each reflecting element of the boards, they are envisaged to impact the propagation environment significantly. In this work, we concentrate on the practical verification of this concept. We present the results of detailed measurements of the reflection characteristics of the RIS boards, which have been conducted intentionally in the real environment. Various potential impacting factors have been considered (impact of azimuth and elevation angle, polarization, number of RIS boards, and distance). Achieved measurement results constituted the basis for conceptual analysis on the practical possibility of creating a codebook (consisting of RIS patterns - codewords) for some applications.

cs.NI

Enhancing V2X Communications with UAV-mounted Reconfigurable Intelligent Surfaces

This paper addresses the crucial need for reliable wireless communication in vehicular networks, particularly vital for the safety and efficacy of (semi-)autonomous driving amid increasing traffic. We explore the use of Reconfigurable Intelligent Surfaces (RISes) mounted on Drone Relay Stations (DRS) to enhance communication reliability. Our study formulates an optimization problem to pinpoint the optimal location and orientation of the DRS, thereby creating an additional propagation path for vehicle-to-everything (V2X) communications. We introduce a heuristic approach that combines trajectory optimization for DRS positioning and a Q-learning scheme for RIS orientation. Our results not only confirm the convergence of the Q-learning algorithm but also demonstrate significant communication improvements achieved by integrating a DRS into V2X networks.

cs.NI

Signal Propagation in RIS-Aided 5G Systems

In this paper, we conduct an in-depth analysis of radio signal propagation characteristics within the urban environment of Poznan (Poland). The study specifically addresses the deployment of a 5th generation (5G NR - New Radio) Radio Access Network (RAN), which comprises 8 strategically positioned Base Stations (BSs). These base stations are configured with either Single Input Single Output (SISO) or Multiple Input Multiple Output (MIMO) antenna technologies, contingent upon the specific requirements of the network cells they serve. A key focus of our research is the integration of 15 reflecting arrays, known as Reconfigurable Intelligent Surfaces (RISs), which were installed throughout the study area. These RISs were deployed at various suspension heights to evaluate their impact on radio signal propagation and coverage. By exploring the influence of these RIS matrices, our research sheds light on their potential to significantly enhance signal quality, particularly in urban environments.

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Charakterystyka odbiciowa inteligentnych matryc antenowych

This paper presents the results of reflection characteristics measurements for reconfigurable intelligent surfaces (RIS). The measurements were carried out in a non-ideal environment, i.e. typical for subsequent practical use of RISes. During the experiments, popular matrices implemented in the open-source project OpenSource- RIS were used. The study focused on obtaining two types of reflection characteristics - two- and three-dimensional.

cs.NI

Indoor Localization Based on MSC Map

In this short paper, we propose a technique for AI-based identification of modulation and coding schemes (MCS) in surrounding cellular signals. Based on the created MCS map, we evaluate the performance of indoor localization techniques.

cs.NI

Large-Scale AI in Telecom: Charting the Roadmap for Innovation, Scalability, and Enhanced Digital Experiences

This white paper discusses the role of large-scale AI in the telecommunications industry, with a specific focus on the potential of generative AI to revolutionize network functions and user experiences, especially in the context of 6G systems. It highlights the development and deployment of Large Telecom Models (LTMs), which are tailored AI models designed to address the complex challenges faced by modern telecom networks. The paper covers a wide range of topics, from the architecture and deployment strategies of LTMs to their applications in network management, resource allocation, and optimization. It also explores the regulatory, ethical, and standardization considerations for LTMs, offering insights into their future integration into telecom infrastructure. The goal is to provide a comprehensive roadmap for the adoption of LTMs to enhance scalability, performance, and user-centric innovation in telecom networks.

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Rozproszone Wykrywanie Zajętości Widma Oparte na Uczeniu Federacyjnym

Spectrum occupancy detection is a key enabler for dynamic spectrum access, where machine learning algorithms are successfully utilized for detection improvement. However, the main challenge is limited access to labeled data about users transmission presence needed in supervised learning models. We present a distributed federated learning approach that addresses this challenge for sensors without access to learning data. The paper discusses the results of the conducted hardware experiment, where FL has been applied for DVB-T signal detection.

cs.NI

V2V Path Loss Modeling at 26 GHz Based on Real-Traffic Measurements

In this letter, we investigate single-slope path loss models complemented with shadowing effects in the context of vehicular communications. We present several models obtained based on extensive measurement campaigns with inter-vehicle transmission conducted at 26.555 GHz in real-traffic experiments, mainly along high-speed roads. Particular attention has been put on the impact of aerial characteristics (omnidirectional versus directional), surrounding environment (e.g., urban versus rural), and their mounting point on cars (at the rooftop, on the bumper, and below the car chassis). Finally, the effect of signal ducting and of the number of blocking cars has been analyzed and the decorrelation time has been discussed

cs.NI

Radio signal propagation in 5G systems equipped with RISs (PL: Propagacja sygnału radiowego w systemach 5G wyposażonych w matryce IPR)

In this paper, the characteristics of radio signal propagation within the boundaries of the city of Poznan (Poland) are analyzed. The study considers the use of a Radio Access Network (RAN) of the 5th generation wireless system (5G NR - New Radio), which includes 8 base stations (BSs) utilizing Single Input Single Output (SISO) or Multiple Input Multiple Output (MIMO) antenna technology depending on the adopted configuration of network cells. Additionally, 15 reflecting arrays known as Reconfigurable Intelligent Surfaces (RISs) were placed in the studied area, and their impact on radio signal propagation at different suspension heights was taken into account.

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