搜索结果：Glasnik. Belgrad. Higijenski institut NR Srbije

In this paper, we theoretically analyze and experimentally demonstrate the performance gains achievable by integrating an in-house built reconfigurable intelligent surface (RIS) with a 5G new radio (NR) system implemented using the OpenAirInterface (OAI) software stack. Unlike conventional RIS-assisted systems that rely on explicit channel state information (CSI) estimation followed by RIS phase configuration optimization, we adopt a low-complexity approach in which the RIS phase states are randomly switched among predefined configurations. The resulting channel fluctuations are opportunistically exploited by the inherent proportional fair (PF) scheduling mechanism of 5G NR. We develop a theoretical framework that characterizes the interaction between RIS switching dynamics and PF scheduling. Based on this framework and the associated analysis, we provide design guidelines for selecting the RIS switching time $T_s$ and the PF throughput averaging window $T_c$ that maximize the system throughput. Experimental evaluations on the 5G NR testbed demonstrate improvements in key performance metrics, including reference signal received power (RSRP), block error rate (BLER), modulation and

Cellular-connected unmanned aerial vehicles (UAVs) operating in 5G New Radio (NR) macro networks experience severe and spatially non-uniform downlink interference. This is primarily caused by the interference from the sidelobes of downtilted base station (BS) antennas serving terrestrial users, which limits the ability of the network to provide uniform and high-quality coverage to aerial users. Supporting aerial users requires boosting the coverage of certain cells or sectors, which can further exacerbate inter-cell interference in dense macro deployments. This motivates the need for inter-cell interference coordination (ICIC) in multi-cell 5G NR networks serving both aerial and terrestrial users. In this work, we propose an ICIC framework that jointly optimizes antenna-domain coordination through BS uptilt angle optimization and time-domain interference coordination (TDIC) through NR-compliant scheduling. The framework is formulated as a multi-cell NR macro deployment problem that maximizes the minimum UAV signal-to-interference ratio (SIR) over a spatial grid of UAV locations while maintaining acceptable performance for ground user equipment (GUEs). The resulting optimization pro

Comparison between existing, well-established satellite technologies, like the Digital Video Broadcasting (DVB) satellite specifications, and the emerging Third Generation Partnership Project (3GPP) specified 5th Generation New Radio (5G NR) Non-Terrestrial Networks (NTN) is an actively discussed topic in the satellite industry standardization groups. This article presents a thorough performance comparison between DVB Second Generation Satellite Extensions (DVBS2X) and Return Channel via Satellite 2nd Generation (DVBRCS2), and NR NTN in a Geostationary Orbit (GEO) satellite scenario, using system-level simulators (SLS) for evaluation, namely Satellite Network Simulator 3 (SNS3) and ALIX 5G (TN-)NTN SLS, built on the same Network Simulator 3 (ns-3) platform. With the satellite system geometry, beam layout, and link budget aligned to use the 3GPP NTN example parameterization for a fair comparison between DVB and NR NTN, the results show that DVB-S2X consistently achieves higher spectral efficiency than the NR Physical Downlink Shared Channel (PDSCH) on the forward user link. In contrast, on the return link, the NR Physical Uplink Shared Channel (PUSCH) demonstrates better spectral ef

We experimentally investigate the performance of semantically-secure physical layer security (PLS) in 5G new radio (NR) mmWave communications during the initial cell search procedure in the NR band n257 at 27 GHz. A gNB transmits PLS-encoded messages in the presence of an eavesdropper, who intercepts the communication by non-intrusively collecting channel readings in the form of IQ samples. For the message transmission, we use the physical broadcast channel (PBCH) within the synchronization signal block. We analyze different signal-to-noise ratio (SNR) conditions by progressively reducing the transmit power of the subcarriers carrying the PBCH channel, while ensuring optimal conditions for over-the-air frequency and timing synchronization. We measure the secrecy performance of the communication in terms of upper and lower bounds for the distinguishing error rate (DER) metric for different SNR levels and beam angles when performing beamsteering in indoor scenarios, such as office environments and laboratory settings.

Autonomous driving may be the most important application scenario of next generation, the development of wireless access technologies enabling reliable and low-latency vehicle communication becomes crucial. To address this, 3GPP has developed Vehicle-to-Everything (V2X) specifications based on 5G New Radio (NR) technology, where Mode 2 Side-Link (SL) communication resembles Mode 4 in LTE-V2X, allowing direct communication between vehicles. This supplements SL communication in LTE-V2X and represents the latest advancement in cellular V2X (C-V2X) with improved performance of NR-V2X. However, in NR-V2X Mode 2, resource collisions still occur, and thus degrade the age of information (AOI). Therefore, a interference cancellation method is employed to mitigate this impact by combining NR-V2X with Non-Orthogonal multiple access (NOMA) technology. In NR-V2X, when vehicles select smaller resource reservation interval (RRI), higher-frequency transmissions take ore energy to reduce AoI. Hence, it is important to jointly consider AoI and communication energy consumption based on NR-V2X communication. Then, we formulate such an optimization problem and employ the Deep Reinforcement Learning (DR

We experimentally demonstrate the performance gains achieved by an in-house built reconfigurable intelligent surface (RIS) integrated with a real-time 5G new radio (NR) system implemented using the OpenAirInterface (OAI) framework. We first quantify the gain in throughput achievable by integrating an RIS with a 5G system. Next, we show that randomly setting the RIS phase configuration and leveraging the inherent proportional fair (PF) scheduling mechanism of 5G NR can yield near-optimal throughput, provided the throughput averaging window of the PF scheduler is chosen judiciously. This occurs because, in each time slot, the PF scheduler naturally prioritizes data transmission to the user equipment (UE) that experiences the best channel conditions, namely, the UE to which the randomly configured RIS is aligned. Subsequently, we experimentally evaluate key performance metrics, including the reference signal received power (RSRP), block error rate (BLER), modulation and coding scheme (MCS) index, and throughput, under random RIS configurations. These results confirm that even a randomly configured RIS with negligible overhead can deliver performance comparable to optimized RIS designs

In the Dark Matter (DM) direct detection community, the absence of convincing signals has become a "new normal" for decades. Among other possibilities, the "new normal" might indicate that DM-matter interactions could generate not only the hypothetical NR (Nuclear Recoil) events but also the ER (Electron Recoil) ones, which have often been tagged as backgrounds historically. Further, we argue that ER and NR-like DM signals could co-exist in a DM detector's same dataset. So in total, there would be three scenarios we can search for DM signals: (i) ER excess only, (ii) NR excess only, and (iii) ER and NR excesses combined. To effectively identify any possible DM signal under the three scenarios, a DM detector should (a) have the minimum ER and NR backgrounds and (b) be capable of discriminating ER events from NR ones. Accordingly, we introduce the newly established project, ALETHEIA, which implements liquid helium-filled TPCs (Time Projection Chambers) in hunting for DM. Thanks to the nearly single-digit number of ER and NR backgrounds on 1 ton*yr exposure, presumably, the ALETHEIA detectors could identify any form of DM-induced excess in its ROI (Research Of Interest). As far as we

5G NR sidelink communication enables new possibilities for direct device-to-device interactions, supporting applications from vehicle-to-everything (V2X) systems to public safety, industrial automation, and drone networks. However, these advancements come with significant security challenges due to the decentralized trust model and increased reliance on User Equipment (UE) for critical functions like synchronization, resource allocation, and authorization. This paper presents the first comprehensive security analysis of NR V2X sidelink. We identify vulnerabilities across critical procedures and demonstrate plausible attack, including attacks that manipulate data integrity feedback and block resources, ultimately undermining the reliability and privacy of sidelink communications. Our analysis reveals that NR operational modes are vulnerable, with the ones relying on autonomous resource management (without network supervision) particularly exposed. To address these issues, we propose mitigation strategies to enhance the security of 5G sidelink communications. This work establishes a foundation for future efforts to strengthen 5G device-to-device sidelink communications, ensuring its

The integration of sensing capabilities into 5G New Radio (5G NR) networks offers an opportunity to enable the detection of airborne objects without the need for dedicated radars. This paper investigates the feasibility of using standardized Positioning Reference Signals (PRS) to detect UAVs in Urban Micro (UMi) and Urban Macro (UMa) propagation environments. A full 5G NR radar processing chain is implemented, including clutter suppression, angle and range estimation, and 3D position reconstruction. Simulation results show that performance strongly depends on the propagation environment. 5G NR radars exhibit the highest missed detection rate, up to 16%, in UMi, due to severe clutter. Positioning error increases with target distance, resulting in larger errors in UMa scenarios and at higher UAV altitudes. In particular, the system achieves a position error within 4m in the UMi environment and within 8m in UMa. The simulation platform has been released as open-source software to support reproducible research in integrated sensing and communication (ISAC) systems.

Vehicle-to-Infrastructure (V2I) technology enables information exchange between vehicles and road infrastructure. Specifically, when a vehicle approaches a roadside unit (RSU), it can exchange information with the RSU to obtain accurate data that assists in driving. With the release of the 3rd Generation Partnership Project (3GPP) Release 16, which includes the 5G New Radio (NR) Vehicle-to-Everything (V2X) standards, vehicles typically adopt mode-2 communication using sensing-based semi-persistent scheduling (SPS) for resource allocation. In this approach, vehicles identify candidate resources within a selection window and exclude ineligible resources based on information from a sensing window. However, vehicles often drive at different speeds, resulting in varying amounts of data transmission with RSUs as they pass by, which leads to unfair access. Therefore, it is essential to design an access scheme that accounts for different vehicle speeds to achieve fair access across the network. This paper formulates an optimization problem for vehicular networks and proposes a multi-objective optimization scheme to address it by adjusting the selection window in the SPS mechanism of 5G NR

This paper presents an analytical framework for evaluating beam misalignment in 3GPP mmWave NR systems implementing analog beamforming. Our approach captures the interaction between user mobility, beam sweeping mechanisms, and deployment configurations, focusing on long-term average performance metrics. Specifically, we model the beam misalignment rates at both the base station (BS) and user equipment (UE) as Poisson processes and derive expressions for the expected misalignment duration, misalignment fraction, and overall beamforming gain. The framework accounts for practical constraints in NR such as Synchronization Signal Blocks (SSB) periodicity, TDD frame structures, and SSB overhead. Through numerical evaluation based on 3GPP mmWave parameters, we identify key trade-offs between beam counts, user mobility, and SSB timing, providing actionable design insights for robust and efficient beam management in future high-frequency networks.

In this work, we propose and evaluate the performance of a 5th generation (5G) New Radio (NR) bistatic Integrated Sensing and Communication (ISaC) system. Unlike the full-duplex monostatic ISaC systems, the bistatic approach enables sensing in the current cellular networks without significantly modifying the transceiver design. The sensing utilizes data channels, such as the Physical Uplink Shared Channel (PUSCH), which carries information on the air interface. We provide the maximum likelihood estimator for the delay and Doppler parameters and derive a lower bound on the Mean Square Error (MSE) for a single target scenario. Link-level simulations show that it is possible to achieve significant throughput while accurately estimating the sensing parameters with PUSCH. Moreover, the results reveal an interesting tradeoff between the number of reference symbols, sensing performance, and throughput in the proposed 5G NR bistatic ISaC system.

Industry 4.0 has brought to attention the need for a connected, flexible, and autonomous production environment. The New Radio (NR)-sidelink, which was introduced by the third-generation partnership project (3GPP) in Release 16, can be particularly helpful for factories that need to facilitate cooperative and close-range communication. Automated Guided Vehicles (AGVs) are important for material handling and carriage within these environments, and using NR-sidelink communication can further enhance their performance. An efficient resource allocation mechanism is required to ensure reliable communication and avoid interference between AGVs and other wireless systems in the factory using NR-sidelink. This work evaluates the 3GPP standardized resource allocation algorithm for NR-sidelink for a use case of cooperative carrying AGVs. We suggest further improvements that are tailored to the quality of service (QoS) requirements of an indoor factory communication scenario with cooperative AGVs.The use of NR-sidelink communication has the potential to help meet the QoS requirements for different Industry 4.0 use cases. This work can be a foundation for further improvements in NR-sidelink in

In December 2019, the 3GPP defined the road-map for Release-17, which includes new features on the operation of New Radio (NR) in millimeter-wave bands with highly directional communications systems, i.e., up to 52.6 GHz. In this paper, a system-level simulation based study on the coexistence of NR-based access to unlicensed spectrum (NR-U) and an IEEE technology, i.e., 802.11ad Wireless Gigabit (WiGig), at 60 GHz bands is conducted. For NR-U, an extension of NR Release-15 based model is used such that the 60 GHz regulatory requirements are satisfied. First, the design and capabilities of the developed open source ns-3 based simulator are presented and then end-to-end performance results of coexistence with different channel access mechanisms for NR-U in a 3GPP indoor scenario are discussed. It is shown that NR-U with Listen-Before-Talk channel access mechanism does not have any adverse impact on WiGig performance in terms of throughput and latency, which demonstrates that NR-U design fulfills the fairness coexistence objective, i.e., NR-U and WiGig coexistence is proven to be feasible.

With the burgeon deployment of the fifth-generation new radio (5G NR) networks, the codebook plays a crucial role in enabling the base station (BS) to acquire the channel state information (CSI). Different 5G NR codebooks incur varying overheads and exhibit performance disparities under diverse channel conditions, necessitating codebook adaptation based on channel conditions to reduce feedback overhead while enhancing performance. However, existing methods of 5G NR codebooks adaptation require significant overhead for model training and feedback or fall short in performance. To address these limitations, this letter introduces a federated reservoir computing framework designed for efficient codebook adaptation in computationally and feedback resource-constrained mobile devices. This framework utilizes a novel series of indicators as input training data, striking an effective balance between performance and feedback overhead. Compared to conventional models, the proposed codebook adaptation via federated reservoir computing (CA-FedRC), achieves rapid convergence and significant loss reduction in both speed and accuracy. Extensive simulations under various channel conditions demonstr

The Third Generation Partnership Project (3GPP) has recently published its Release 16 that includes the first Vehicle to-Everything (V2X) standard based on the 5G New Radio (NR) air interface. 5G NR V2X introduces advanced functionalities on top of the 5G NR air interface to support connected and automated driving use cases with stringent requirements. This paper presents an in-depth tutorial of the 3GPP Release 16 5G NR V2X standard for V2X communications, with a particular focus on the sidelink, since it is the most significant part of 5G NR V2X. The main part of the paper is an in-depth treatment of the key aspects of 5G NR V2X: the physical layer, the resource allocation, the quality of service management, the enhancements introduced to the Uu interface and the mobility management for V2N (Vehicle to Network) communications, as well as the co-existence mechanisms between 5G NR V2X and LTE V2X. We also review the use cases, the system architecture, and describe the evaluation methodology and simulation assumptions for 5G NR V2X. Finally, we provide an outlook on possible 5G NR V2X enhancements, including those identified within Release 17.

In recent years, Vehicle-to-Everything (V2X) communication opens an ample amount of opportunities to increase the safety of drivers and passengers and improve traffic efficiency which enables direct communication between vehicles. The Third Generation Partnership Project (3GPP) has specified a 5G New Radio (NR) Sidelink (SL) PC5 interface for supporting Cellular V2X (C-V2X) communication in Release 16 in 2017. 5G NR V2X communication is expected to provide high reliability, extra-low latency, and a high data rate for vehicular networks. In this paper, the newly introduced features of 5G NR standards like flexible numerology, variable Subcarrier Spacing (SCS), and allocated Physical Resource Blocks (PRBs) have been inspected in 5G NR V2X communications. Moreover, the 5G NR V2X data packet will be distributed to all nearby User Equipment (UE) by the Transmitter (Tx). However, there may be instances where certain UEs fail to receive the data packets in a single transmission. Unfortunately, the SL Tx lacks a feedback channel to verify if the Receivers (Rxs) have received the information. To meet the stringent reliability and latency requirements of C-V2X communication, we suggest and a

New radio (NR) positioning in the Third Generation Partnership Project (3GPP) Release 18 (Rel-18) enables 5G-advanced networks to achieve ultra-high accuracy positioning without dependence on global navigation satellite systems (GNSS) with key enablers such as the carrier phase positioning technique, standardized for the first time in a cellular communications standard and setting a new baseline for future generations. In addition, Rel-18 NR supports positioning functionalities for reduced capability (RedCap) user equipment and bandwidth aggregation for positioning measurements. Moreover, the low power solutions are designed for low power high accuracy positioning use cases. Lastly, sidelink-based positioning is introduced in Rel-18. This article constitutes a comprehensive treatment of the Rel-18 NR positioning enhancements crucial for the development of next-generation networks.

The fifth generation new radio (5G NR) technology is expected to fulfill reliable and accurate positioning requirements of industry use cases, such as autonomous robots, connected vehicles, and future factories. Starting from Third Generation Partnership Project (3GPP) Release-16, several enhanced positioning solutions are featured in the 5G standards, including the multi-cell round trip time (multi-RTT) method. This work presents a novel framework to estimate the round-trip time (RTT) between a user equipment (UE) and a base station (gNB) in 5G NR. Unlike the existing scheme in the standards, RTT can be estimated without the need to send timing measurements from both the gNB and UE to a central node. The proposed method relies on obtaining multiple coherent uplink wide-band channel measurements at the gNB by circumventing the timing advance control loops and the clock drift. The performance is evaluated through experiments leveraging a real world 5G testbed based on OpenAirInterface (OAI). Under a moderate system bandwidth of 40MHz, the experimental results show meter level range accuracy even in low signal-to-noise ratio (SNR) conditions.