Network Digital Twins (NDTs) offer a structured framework for modeling, predicting, and optimizing wireless networks. This paper presents a modular NDT implementation based on the GreyCat platform, integrating graph-based data models and external functional algorithms for indoor radio coverage prediction. For the first time, we implement an NDT system aligned with ITU-T Recommendation Y.3090, covering both basic and functional model instantiation from modular and interoperable abstract structures. We generated a practical dataset using a software-defined radio (SDR)-based OpenAirInterface5G setup, with a gNB and commercial UE deployed in a controlled environment. This real-world dataset was used to benchmark Gaussian Process Regression (GPR) and Convolutional Neural Network (CNN) models for predicting RSRP-based radio coverage. Our results show that CNN outperforms GPR in under-sampled conditions, and we demonstrate how the modular architecture supports flexible model integration and benchmarking. This work represents a significant step toward practical, data-driven NDT deployments for wireless systems.

Lower layer retransmission schemes in 5G Non-Terrestrial Networks (5G-NTN), in particular Hybrid Automatic Repeat Request (HARQ) from the Medium Access Control (MAC) layer, are severely hampered by the large Round Trip Times (RTTs) imposed by satellite components. In this demonstration, we show that enabling Radio Link Control (RLC) layer retransmissions can significantly increase throughput without additional processing complexity. Using the OpenAirInterface (OAI) 5G-NTN suite, we showcase the effectiveness of RLC Acknowledged Mode (AM) retransmissions in facilitating early recovery of lost packets and maintaining reasonable Quality of Service (QoS), even in the absence of HARQ feedback from the MAC layer.

In this paper, a novel robust beamforming for an intelligent reflecting surface (IRS) assisted FD system is presented. Since perfect channel state information (CSI) is often challenging to acquire in practice, we consider the case of imperfect CSI and adopt a statistically robust beamforming approach to maximize the ergodic weighted sum rate (WSR). We also analyze the achievable WSR of an IRS-assisted FD with imperfect CSI, for which the lower and the upper bounds are derived. The ergodic WSR maximization problem is tackled based on the expected Weighted Minimum Mean Squared Error (WMMSE), which is guaranteed to converge to a local optimum. The effectiveness of the proposed design is investigated with extensive simulation results. It is shown that our robust design achieves significant performance gain compared to the naive beamforming approaches and considerably outperforms the robust Half-Duplex (HD) system.

The new era of space exploration demands a significant increase in the number of human and robotic missions, thus resulting in novel communication and service requirements. To satisfy such requirements, the fifth generation of mobile communication systems (5G), despite providing connectivity on Earth, has the potential to serve as a communication standard for space resource missions, particularly the ones targeting the Moon. In fact, 5G non-terrestrial networks (NTNs) are already in the standardization process and new techniques are being proposed in order to counteract the peculiarities of the non-terrestrial channel. However, going one step ahead and deploying constellations of satellites around the Earth or the Moon, requires first a detailed analysis and testing of the validity of the proposed techniques. Therefore, in this paper, we introduce the 5G Space Communications Lab, which has been developed with the purpose of simulating space-based 5G communications. The designed testbed proposed here increases the technology readiness level (TRL) of NTN-based 5G systems, demonstrating over a laboratory environment successful 5G communication via space links.

Distributed antenna arrays, fractionated payloads and cooperative platforms can provide unprecedented performance in the next generation of spaceborne communications and remote sensing systems. Remote phase synchronization of physically separated oscillators is the first step towards a coherent operation of distributed systems. This work shows the preliminary results of a TDD remote phase synchronization algorithm with a master-follower architecture. Herein, we describe the implementation and validation of the proposed algorithm. The implementation has been conducted in a Cubesat-ready software defined radio and validated at the end-to-end satellite communications testbed available at the University of Luxembourg.

To fulfill the exponential growth of mobile traffic demands, 3GPP has standardized the use of LTE in the 5 GHz unlicensed band in the Release 13 dedicated to LTE Licensed-Assisted Access (LTE-LAA). Simulations and field trials have shown that incumbent WiFi (802.11ac) in the 5 GHz unlicensed band will be the victim in such co-channel deployment with LTE-LAA. Hence a concern is being raised about fair co-existence. In this work, we investigate the limits of Successive Interference Cancellation (SIC) to recover the WiFi packets corrupted by LTE-LAA in the event of a collision. For an indoor deployment, which is the most probable battleground for WiFi and LTE-LAA, we propose a method to perform SIC by using stored clean channel estimates of stronger signals obtained during an interference-free period. Our approach leverages the slow fading channel and hence high coherence time of the indoor channel. For an experimental proof of this phenomenon, we simulated a scenario with interference between 20 MHz 802.11ac and 20 MHz LTE-LAA at different inter-frame-intervals (IFI) of LTE-LAA frames. Our results show that for an LTE-LAA IFI up to 2 milliseconds, the proposed method of using stored channel estimates to perform SIC can achieve significant transmit power gain (TPG) compared to the conventional way of using instantaneous channel estimates. Our method complements the conventional approach to ensure improved WiFi Frame Detection and Decoding while applying SIC. Moreover, our method does not require any coordination between WiFi and LTE-LAA transceivers and hence can be deployed within existing infrastructure with minimal modifications.

Narrowband transmitters such as IEEE 802.15.4 (ZigBee) operating in 2.4 GHz ISM band cause significant degradation of throughput to the co-channel IEEE 802.11g (WiFi). The phenomenon is common in smart factories and smart homes which generously use ZigBee sensors for process monitoring and automation. This interferes with omnipresent WiFi in the same 2.4 GHz ISM band. In our demonstration, we will present Software Defined Radio (SDR) based single antenna and multi-antenna prototype of standard-compliant IEEE 802.11g receiver. Our receiver prototype is capable of significantly reducing the packet error rate while facing multiple co-channel narrowband ZigBee interferers. We also demonstrate a real-time SDR implementation of Soft Bit Maximal Ratio Combiner capable of decoding frames from standard compliant IEEE 802.11g transmitters. This is a first of its kind implementation to the best of author's knowledge. The demonstrations use Ettus B210 as SDR hardware and a combination of signal processing modules from two different SDR packages: GNU Radio and Openairinterface.

The rapid increase in wireless devices and inherent limitation of RF spectrum is causing Co-Channel Interference (CCI). Effects of CCI are prevalent in Industrial Scientific Medical (ISM) bands which lack centralized control over devices operating on heterogeneous standards, a situation entirely different from cellular networks. In this study, we propose physical layer signal processing techniques for multi-antenna OFDM receivers in ISM band for mitigating narrowband CCI. Our work focuses only on receiver side modifications for interoperability with the existing infrastructure. We first analyze two such prominent multi-antenna interference mitigation methods: Optimal Combiner (OC) and Technology-Independent MIMO (TIMO). Optimal Combiner, although theoretically optimal, requires statistics of interferer which is difficult to obtain in practice. TIMO does not benefit from diversity gain despite having two antennas. We propose MLSC (Maximal Ratio Combiner with LLR Scaling) for multi-antenna OFDM receivers which mitigates CCI caused by narrowband interferers as well as benefits from diversity gain. For a given Packet Error Rate (PER), MLSC achieves comparable Transmit Power Gain (TPG) to OC without needing the statistics of the interferer. In addition, MLSC achieves significant TPG compared to TIMO. Further, we propose an improvement to TIMO: DC-TIMO (Diversity Combiner TIMO) which enables it to perform joint interference nulling and diversity combining.