arXiv subjects

Ljiljana Simić

Publications and source records attributed to Ljiljana Simić.

At least 19 recordsLinked to original sources

arXiv2026

Cell-Free Massive MIMO Under Mobility: A Fairness-Differentiated Handover Scheme

While cell-free massive MIMO (CF-mMIMO) offers high and uniform network-wide throughput in static networks, its performance in mobile networks is not yet fully addressed. In this paper, we evaluate the throughput performance of urban mobile CF-mMIMO networks under a comprehensive throughput model and show that it suffers from large performance degradation due to the combined effect of channel aging and handover overheads. To restore the uniformly good performance of CF-mMIMO under mobility, we formulate a novel optimization problem to maximize the nett throughput that considers both channel aging and handover cost. We derive a near-optimal solution nearOpt for our transformed and relaxed optimization problem with Newton's method. We then design a heuristic handover algorithm, FairDiff, to differentiate prioritized and optional handovers using a policy threshold based on Jain's fairness index, in order to achieve uniform throughput over the network. Our extensive evaluation of the mobile throughput performance of our handover schemes in realistic urban mobile networks shows that, unlike the existing literature benchmarks that obtain very low throughput under mobility, our FairDiff scheme consistently achieves the near-optimal throughput comparable to nearOpt and highest network-wide throughput with the lowest computational complexity among all considered schemes. We thus for the first time propose a handover scheme that delivers the promise of uniformly good throughput for mobile CF-mMIMO, making it a feasible architecture for practical mobile networks.

cs.NI↗

arXiv2026

The Price of the Golden 6G Band: Evaluation of Beam Management Effort in FR3

Frequency Range 3 (FR3), 7.125-24.25 GHz, regarded as the "golden band" for 6G networks, has less challenging propagation characteristics than FR2 while offering much wider bandwidth for high data rate applications than FR1. Reusing existing FR1 infrastructure for FR3 network deployments requires gNodeBs (gNBs) to employ antenna arrays and perform beam management, which has proven challenging at FR2. In this paper, we extensively study and characterize the beam management effort in an FR3 urban network, in terms of: beam alignment sensitivity, number of directional link opportunities, gNB handover and beam switch rates, and beam steering distance. Our results show that achieving a high and stable mobile throughput requires significant beam management effort across FR3 bands. While the beam tracking requirements are less stringent at the lower frequencies due to wider beams, the beam switching rate to a non-adjacent beam is relatively comparable at FR3 and FR2.

cs.NI↗

arXiv2026

UnifSrv: AP Selection for Achieving Uniformly Good Performance of CF-mMIMO in Realistic Urban Networks

Under the ideal assumption of uniform propagation, cell-free massive MIMO (CF-mMIMO) provides uniformly high throughput over the network by effectively surrounding each user with its serving access point (AP) set. However, in realistic non-uniform urban propagation environments, it is difficult to consistently select good limited serving AP sets, resulting in significantly degraded throughput, especially for the worst-served (formerly "cell-edge") users. To restore the uniformly good performance of scalable CF-mMIMO in realistic urban networks, we formulate a novel multi-objective optimization problem to jointly achieve high throughput by maximizing the sum data rate, uniform throughput by maximizing Jain's fairness index of the throughput per user, and scalability by minimizing the serving AP set size. We then propose the UnifSrv AP selection algorithms to solve this optimization problem, consisting of a deep reinforcement learning (DRL)-based algorithm UnifSrv-DRL and a heuristic algorithm UnifSrv-heu. We conduct a comprehensive performance evaluation of scalable CF-mMIMO under realistic urban network distributions, propagation, and mobility patterns. Our results show that UnifSrv significantly outperforms the prior benchmark AP selection schemes, and for the first time achieves uniformly high throughput of CF-mMIMO under non-uniform urban propagation. Importantly, our heuristic algorithm achieves equivalent throughput to our DRL one, but with orders of magnitude lower complexity. We thus for the first time propose a practical AP selection algorithm that makes CF-mMIMO viable in realistic urban networks.

eess.SY↗

arXiv2025

Unleashing Sensor-Aided Environment Awareness for Beam Management in Beyond-5G Networks: An OpenAirInterface Experimental Platform

Large antenna arrays and beamforming techniques are key components for exploiting the spectrum-rich FR2 bands in next-generation mobile communication networks. Given the site-specific spatio-temporal variations of the mm-wave channel, non-RF sensor inputs and environment awareness can be leveraged to greatly enhance beam management decisions, e.g. via machine learning (ML) techniques. However, the current literature lacks open platforms to gather datasets for the training of such ML techniques and to evaluate novel beam management approaches in real-time, real-world scenarios and full-stack endto-end networks. In this work, we present our SDR-based experimental platform based on OpenAirInterface and are the first to integrate popular low-cost antenna array transceivers, beam sweeping capabilities, and a highly-modular sensor framework and associated interfaces into such a full-stack experimental platform. This enables beam management experimentation in real-world, real-time scenarios and facilitates gathering datasets necessary for developing ML-based beam management protocols that incorporate environment awareness via sensor modalities.

eess.SP↗

arXiv2025

Performance of Cell-Free Massive MIMO in Realistic Urban Propagation Environments

While UE-centric cell-free massive MIMO (CF-mMIMO) provides high and uniform throughput performance under the assumption of a uniform propagation environment modeled by the log-distance path loss channel model, the performance under a realistic urban propagation environment is not yet fully addressed. In this paper we conduct the first comparative performance study of CF-mMIMO under both the widely assumed log-distance channel model and the realistic urban propagation environment obtained via raytracing using real 3D city layouts and practical AP locations. Our results show that with the raytracing channel model, CF-mMIMO cannot achieve as high and uniform throughput performance as observed with the log-distance channel model, putting into question the attractiveness in practice of CF-mMIMO for real urban deployments.

cs.NI↗

arXiv2025

Cross-Environment Transfer Learning for Location-Aided Beam Prediction in 5G and Beyond Millimeter-Wave Networks

Millimeter-wave (mm-wave) communications requirebeamforming and consequent precise beam alignmentbetween the gNodeB (gNB) and the user equipment (UE) toovercome high propagation losses. This beam alignment needs tobe constantly updated for different UE locations based on beamsweepingradio frequency measurements, leading to significantbeam management overhead. One potential solution involvesusing machine learning (ML) beam prediction algorithms thatleverage UE position information to select the serving beamwithout the overhead of beam sweeping. However, the highlysite-specific nature of mm-wave propagation means that MLmodels require training from scratch for each scenario, whichis inefficient in practice. In this paper, we propose a robustcross-environment transfer learning solution for location-aidedbeam prediction, whereby the ML model trained on a referencegNB is transferred to a target gNB by fine-tuning with a limiteddataset. Extensive simulation results based on ray-tracing in twourban environments show the effectiveness of our solution forboth inter- and intra-city model transfer. Our results show thatby training the model on a reference gNB and transferring themodel by fine-tuning with only 5% of the target gNB dataset,we can achieve 80% accuracy in predicting the best beamfor the target gNB. Importantly, our approach improves thepoor generalization accuracy of transferring the model to newenvironments without fine-tuning by around 75 percentage points.This demonstrates that transfer learning enables high predictionaccuracy while reducing the computational and training datasetcollection burden of ML-based beam prediction, making itpractical for 5G-and-beyond deployments.

eess.SP↗

arXiv2024

Multi-Band mm-Wave Measurement Platform Towards Environment-Aware Beam Management

Agile beam management is key for providing seamless millimeter wave (mm-wave) connectivity given the site-specific spatio-temporal variations of the mm-wave channel. Leveraging non radio frequency (RF) sensor inputs for environment awareness, e.g. via machine learning (ML) techniques, can greatly enhance RF-based beam steering. To overcome the lack of diverse publicly available multi-modal mm-wave datasets for the design and evaluation of such novel beam steering approaches, we demonstrate our software-defined radio multi-band mm-wave measurement platform which integrates multi-modal sensors towards environment-aware beam management.

eess.SP↗

arXiv2024

RF-Flashlight Testbed for Verification of Real-Time Geofencing of EESS Radiometers and Millimeter-Wave Ground-to-Satellite Propagation Models

A simple 'RF-flashlight' (or ground to satellite) interference testbed is proposed to experimentally verify real-time geofencing (RTG) for protecting passive Earth Exploration Satellite Services (EESS) radiometer measurements from 5G or 6G mm-wave transmissions, and ground to satellite propagation models used in the interference modeling of this spectrum coexistence scenario. RTG is a stronger EESS protection mechanism than the current methodology recommended by the ITU based on a worst-case interference threshold while simultaneously enabling dynamic spectrum sharing and coexistence with 5G or 6G wireless networks. Similarly, verifying more sophisticated RF propagation models that include ground topology, buildings, and non-line-of-sight paths will provide better estimates of interference than the current ITU line-of-sight model and, thus, a more reliable basis for establishing a consensus among the spectrum stakeholders.

eess.SP↗

arXiv2024

HBF MU-MIMO with Interference-Aware Beam Pair Link Allocation for Beyond-5G mm-Wave Networks

Hybrid beamforming (HBF) multi-user multiple-input multiple-output (MU-MIMO) is a key technology for unlocking the directional millimeter-wave (mm-wave) nature for spatial multiplexing beyond current codebook-based 5G-NR networks. In order to suppress co-scheduled users' interference, HBF MU-MIMO is predicated on having sufficient radio frequency chains and accurate channel state information (CSI), which can otherwise lead to performance losses due to imperfect interference cancellation. In this work, we propose IABA, a 5G-NR standard-compliant beam pair link (BPL) allocation scheme for mitigating spatial interference in practical HBF MU-MIMO networks. IABA solves the network sum throughput optimization via either a distributed or a centralized BPL allocation using dedicated CSI reference signals for candidate BPL monitoring. We present a comprehensive study of practical multi-cell mm-wave networks and demonstrate that HBF MU-MIMO without interference-aware BPL allocation experiences strong residual interference which limits the achievable network performance. Our results show that IABA offers significant performance gains over the default interference-agnostic 5G-NR BPL allocation, and even allows HBF MU-MIMO to outperform the fully digital MU-MIMO baseline, by facilitating allocation of secondary BPLs other than the strongest BPL found during initial access. We further demonstrate the scalability of IABA with increased gNB antennas and densification for beyond-5G mm-wave networks.

cs.NI↗

arXiv2022

Will Emerging Millimeter-Wave Cellular Networks Cause Harmful Interference to Weather Satellites?

We study whether realistic 5G mm-wave cellular networks would cause harmful out-of-band interference to weather satellites sensing in the 23.8 GHz band. We estimate uplink and downlink interference from a single interferer and a network of interferers in New York City, using real 3D building data and realistic antenna patterns. We perform detailed ray-tracing propagation simulations, for locations of the MetOp-B weather satellite and its scanning orientations and ground interferer antenna orientations for representative urban cell sites. In addition to the ITU-R threshold of -136 dBm/200 MHz, we propose an alternative set of harmful interference thresholds directly related to the sensitivity of the satellite sensor. Our results show that the 3GPP power leakage limits are sufficient to ensure that interference from a single 5G device is not harmful if considering the ITU-R threshold, but not if the weather prediction software can tolerate only very low interference levels. Importantly, aggregate interference resulting in practice from a 5G network with realistic network densities is often harmful, even considering the least conservative ITU-R threshold. Overall, our comprehensive coexistence study thus strongly suggests that additional engineering and/or regulatory solutions will be necessary to protect weather satellite passive sensing from mm-wave cellular network interference.

cs.NI↗

arXiv2022

Mobility Performance Analysis of Scalable Cell-Free Massive MIMO

While scalable cell-free massive MIMO (CF-mMIMO) shows advantages in static conditions, the impact of its changing serving access point (AP) set in a mobile network is not yet addressed. In this paper we first derive the CPU cluster and AP handover rates of scalable CF-mMIMO as exact numerical results and tight closed form approximations. We then use our closed form handover rate result to analyse the mobility-aware throughput. We compare the mobility-aware spectral efficiency (SE) of scalable CF-mMIMO against distributed MIMO with pure network- and UE-centric AP selection, for different AP densities and handover delays. Our results reveal an important trade-off for future dense networks with low control delay: under moderate to high mobility, scalable CF-mMIMO maintains its advantage for the 95th-percentile users but at the cost of degraded median SE.

cs.IT↗

arXiv2020

Limitations of Stochastic Geometry Modelling for Estimating the Performance of CSMA Networks

This letter considers stochastic geometry modelling (SGM) for estimating the signal-to-interference-and-noise ratio (SINR) and throughput of CSMA networks. We show that, despite its compact mathematical formulation, SGM has serious limitations in terms of both accuracy and computational efficiency. SGM often severely underestimates the SINR versus ns-3 simulations, yet as it neglects the sensing overhead when mapping SINR to throughput, SGM usually overestimates the throughput substantially. We propose our hybrid model for CSMA, which we argue is a superior modelling approach due to being significantly more accurate and at least one order of magnitude faster to compute than SGM.

cs.NI↗

arXiv2020

Multi-User Provisioning in Millimeter-Wave Urban Cellular Networks

In this paper we present the first comprehensive study of the multi-user capacity of millimeter-wave (mm-wave) urban cellular networks, using site-specific ray-tracing propagation data and realistic antenna array patterns. We compare the performance of TDMA and SDMA (time and spatial division multiple access, respectively) for diverse network scenarios and antenna configurations. We propose a greedy heuristic algorithm to solve the network-wide directional link allocation problem, thereby estimating the achievable capacity and coverage of multi-user mm-wave networks. Our results show that inter-cell interference is negligible, so that TDMA performance is strictly limited by air-time sharing. By contrast, the major limiting factor for SDMA is intra-cell interference, emphasizing the impact of real antenna array sidelobes. Nonetheless, SDMA significantly outperforms TDMA in terms of average UE throughput, by up to 2 Gbps using 8x8 arrays. As an important design insight, our results show that larger base station antenna arrays limit intra-cell interference while compensating for small UE arrays, reducing costs and beamforming requirements in practical SDMA networks. Our analysis also shows that the limited number of antenna sub-arrays in a practical hybrid beamforming architecture may force SDMA to drop UEs with good coverage, highlighting a tradeoff between base station densification and antenna resources.

cs.NI↗

arXiv2020

Urban Outdoor Measurement Study of Phased Antenna Array Impact on Millimeter-Wave Link Opportunities and Beam Misalignment

Exploiting multi-antenna technologies for robust beamsteering to overcome the effects of blockage and beam misalignment is the key to providing seamless multi-Gbps connectivity in millimeter-wave (mm-wave) networks. In this paper, we present the first large-scale outdoor mm-wave measurement study using a phased antenna array in a typical European town. We systematically collect fine-grained 3D angle-of-arrival (AoA) and angle-of-departure (AoD) data, totaling over 50,000 received signal strength measurements. We study the impact of phased antenna arrays in terms of number of link opportunities, achievable data rate and robustness under small-scale mobility, and compare this against reference horn antenna measurements. Our results show a limited number of 2--4 link opportunities per receiver location, indicating that the mm-wave multipath richness in a European town is surprisingly similar to that of dense urban metropolises. The results for the phased antenna array reveal that significant losses in estimated data rate occur for beam misalignments in the order of the half-power beamwidth, with significant and irregular variations for larger misalignments. By contrast, the loss for horn antennas is monotonically increasing with the misalignment. Our results strongly suggest that the effect of non-ideal phased antenna arrays must be explicitly considered in the design of agile beamsteering algorithms.

eess.SP↗

arXiv2019

Should We Worry About Interference in Emerging Dense NGSO Satellite Constellations?

Many satellite operators are planning to deploy NGSO systems for broadband communication services in the Ku-, Ka-, and V-band, where some of them have already launched. Consequently, new challenges are expected for inter-system satellite coexistence due to the increased interference level and the complexity of the interactions resulting from the heterogeneity of the constellations. This is especially relevant for the Ku-band, where the NGSO systems are most diverse and existing GSO systems, which often support critical services, must be protected from interference. It is thus imperative to evaluate the impact of mutual inter-system interference, the efficiency of the basic interference mitigation techniques, and whether regulatory intervention is needed for the new systems. We conduct an extensive study of inter-satellite coexistence in the Ku-band, where we consider all recently proposed NGSO and some selected GSO systems. Our throughput degradation results suggest that existing spectrum regulation may be insufficient to ensure GSO protection from NGSO interference, especially due to the high transmit power of the LEO Kepler satellites. This also results in strong interference towards other NGSO systems, where traditional interference mitigation techniques like look-aside may perform poorly. Specifically, look-aside can be beneficial for large constellations, but detrimental for small constellations. Furthermore, we confirm that band-splitting among satellite operators significantly degrades throughput, also for the Ku-band. Our results overall show that the complexity of the inter-satellite interactions for new NGSO systems is too high to be managed via simple interference mitigation techniques. This means that more sophisticated engineering solutions, and potentially even more strict regulatory requirements, will be needed to ensure coexistence in emerging, dense NGSO deployments.

cs.NI↗

arXiv2019

Performance of Radar and Communication Networks Coexisting in Shared Spectrum Bands

Recent technological advancements are making the use of compact, low-cost, low-power mm-wave radars viable for providing environmental awareness in a number of applications, ranging from automotive to indoor mapping and radio resource optimisation. These emerging use-cases pave the road towards networks in which a large number of radar and broadband communications devices coexist, sharing a common spectrum band in a possibly uncoordinated fashion. Although a clear understanding of how mutual interference influences radar and communications performance is key to proper system design, the core tradeoffs that arise in such scenarios are still largely unexplored. In this paper, we provide results that help bridge this gap, obtained by means of an analytical model and extensive simulations. To capture the fundamental interactions between the two systems, we study mm-wave networks where pulsed radars coexist with communications devices that access the channel following an ALOHA policy. We investigate the effect of key parameters on the performance of the coexisting systems, including the network density, fraction of radar and communication nodes in the network, antenna directivity, and packet length. We quantify the effect of mutual interference in the coexistence scenario on radar detection and communication network throughput, highlighting some non-trivial interplays and deriving useful design tradeoffs.

cs.NI↗

arXiv2018

The Importance of Being Earnest: Performance of Modulation Classification for Real RF Signals

Digital modulation classification (DMC) can be highly valuable for equipping radios with increased spectrum awareness in complex emerging wireless networks. However, as the existing literature is overwhelmingly based on theoretical or simulation results, it is unclear how well DMC performs in practice. In this paper we study the performance of DMC in real-world wireless networks, using an extensive RF signal dataset of 250,000 over-the-air transmissions with heterogeneous transceiver hardware and co-channel interference. Our results show that DMC can achieve a high classification accuracy even under the challenging real-world conditions of modulated co-channel interference and low-grade hardware. However, this only holds if the training dataset fully captures the variety of interference and hardware types in the real radio environment; otherwise, the DMC performance deteriorates significantly. Our work has two important engineering implications. First, it shows that it is not straightforward to exchange learned classifier models among dissimilar radio environments and devices in practice. Second, our analysis suggests that the key missing link for real-world deployment of DMC is designing signal features that generalize well to diverse wireless network scenarios. We are making our RF signal dataset publicly available as a step towards a unified framework for realistic DMC evaluation.

eess.SP↗

arXiv2018

Stochastic Geometry Interference Analysis of Radar Network Performance

This work characterises the effect of mutual interference in a planar network of pulsed-radar devices. Using stochastic geometry tools and a strongest interferer approximation, we derive simple closed-form expressions that pinpoint the role played by key system parameters on radar detection range and false alarm rate in the interference-limited region. The fundamental tradeoffs of the system between radar performance, network density and antenna directivity are captured for different path-loss exponents in the no-fading and Rayleigh-fading cases. The discussion highlights practical design hints for tuning the radar parameters. The accuracy of the model is verified through network simulations, and the role of random noise on detection in sparse, non interference-limited networks is characterised.

cs.NI↗