arXiv subjects

Sara Willhammar

Publications and source records attributed to Sara Willhammar.

8 recordsLinked to original sources

arXiv2025

Distributed MIMO Positioning: Fundamental Limit Analysis and User Tracking Framework Design

This paper presents a comprehensive study on the 3D positioning capabilities in distributed multiple-input multiple-output (MIMO) systems. Unlike previous studies that mainly rely on idealized isotropic antenna models, we adopt a polarimetric model that takes advantage of effective aperture distribution functions to characterize realistic antenna patterns, placements, and polarization effects. Based on this model, we analyze the fundamental limits of UE positioning using the Fisher information matrix (FIM) and the position error bound (PEB). The FIM is shown to be expressed as a weighted sum of the information contributions from individual access point (AP)-UE pairs, with each contribution interpreted geometrically across distance, azimuth, and elevation dimensions. The impact of the UE tilt and the spatial distribution of APs on the PEBs is further analyzed. As a further advancement, we propose a complete positioning framework from a UE tracking perspective. By integrating a global probability hypothesis density filter and a PEB-aware AP management strategy, the framework enables accurate tracking while optimizing AP scheduling. Finally, we present a distributed MIMO channel measurement campaign to validate the proposed framework. The results demonstrate a centimeter-level tracking accuracy. In addition, the PEB-aware AP management strategy is shown to maintain robust tracking performance while significantly reducing the number of concurrently active APs, thus lowering the overall system overhead.

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arXiv2025

3D Cooperative User Tracking for Distributed Integrated Sensing and Communication

As integrated sensing and communication (ISAC) becomes an integral part of 6G networks, distributed ISAC (DISAC) is expected to enhance both sensing and communication performance through its decentralized architecture. This paper presents a complete framework to address the challenge of cooperative user tracking in DISAC systems. By incorporating a global probability hypothesis density (PHD) filter and a field-of-view-aware access point (AP) management strategy, the framework enables accurate user tracking using radio signals while optimizing AP scheduling. In addition, a real-world distributed MIMO channel measurement campaign is performed to evaluate the effectiveness of the framework. The results demonstrate that a centimeter-level root mean-square trajectory error can be achieved. Furthermore, the results show that it is not necessary to keep APs active at all times to maintain high tracking accuracy, indicating the need for robust and efficient AP management. These findings provide valuable insights into practical deployments and the further development of cooperative user tracking techniques in DISAC systems.

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arXiv2025

Experimental Analysis of Multipath Characteristics in Indoor Distributed Massive MIMO Channels

Distributed multiple-input multiple-output (MIMO), also known as cell-free massive MIMO, has emerged as a promising technology for sixth-generation (6G) wireless networks. This letter introduces an indoor channel measurement campaign designed to explore the behavior of multipath components (MPCs) in distributed MIMO channels. Fully coherent channels were measured between eight distributed uniform planar arrays (128 elements in total) and a 12-meter user equipment route. A method is introduced to determine the order (single- or multi-bounce) of MPC interaction by leveraging map information and MPC parameters. In addition, a Kalman filter-based framework is used for identifying the MPC interaction mechanisms (reflection or scattering/diffraction/mixed). Finally, a comprehensive MPC-level characterization is performed based on the measured channels, including the significance of single-bounce MPCs, common single-bounce MPCs, spherical wavefront features, birth-and-death processes of the MPCs, and spatial distribution of reflections. The findings serve as a valuable reference for understanding the propagation behavior of MPCs, which is necessary for future modeling of indoor distributed MIMO channels.

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arXiv2025

Interacting Object-Enabled Clustering and Characterization of Distributed MIMO Channels

Distributed multiple-input multiple-output (MIMO), also known as cell-free massive MIMO, emerges as a promising technology for sixth-generation (6G) systems to support uniform coverage and reliable communication. For the design and optimization of such systems, measurement-based investigations of real-world distributed MIMO channels are essential. In this paper, we present an indoor channel measurement campaign, featuring eight distributed antenna arrays with 128 elements in total. Multi-link channels are measured at 50 positions along a 12-meter user route. A clustering algorithm enabled by interacting objects is proposed to identify clusters in the measured channels. The algorithm jointly clusters the multipath components for all links, effectively capturing the dynamic contributions of common clusters to different links. In addition, a Kalman filter-based tracking framework is introduced for cluster prediction, tracking, and updating along the user movement. Using the clustering and tracking results, cluster-level characterization of the measured channels is performed. First, the number of clusters and their visibility at both link ends are analyzed. Next, a maximum-likelihood estimator is utilized to determine the entire cluster visibility region length. Finally, key cluster-level properties, including the common cluster ratio, cluster power, shadowing, spread, among others, are statistically investigated. The results provide valuable insights into cluster behavior in typical multi-link channels, necessary for accurate modeling of distributed MIMO channels.

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arXiv2025

Achieving Distributed MIMO Performance with Repeater-Assisted Cellular Massive MIMO

In what ways could cellular massive MIMO be improved? This technology has already been shown to bring huge performance gains. However, coverage holes and difficulties to transmit multiple streams to multi-antenna users because of insufficient channel rank remain issues. Distributed MIMO, also known as cell-free massive MIMO, might be the ultimate solution. However, while being a powerful technology, it is expensive to install backhaul, and it is a difficult problem to achieve accurate phase alignment for coherent multi-user beamforming on downlink. Another option is reflective intelligent surfaces - but they have large form factors and require a lot of training and control overhead, and probably, in practice, some form of active filtering to make them sufficiently band-selective. We propose a new approach to densification of cellular systems, envisioning repeater-assisted cellular massive MIMO, where a large numbers of physically small and cheap wireless repeaters are deployed. They receive and retransmit signals instantaneously, appearing as active scatterers. Meaning that they appear as ordinary channel scatterers but with amplification. We elaborate on the requirements of such repeaters, show that the performance of these systems could potentially approach that of distributed MIMO, and outline future research directions.

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arXiv2024

A Measurement-Based Spatially Consistent Channel Model for Distributed MIMO in Industrial Environments

Future wireless communication systems are envisioned to support ultra-reliable and low-latency communication (URLLC), which will enable new applications such as compute offloading, wireless real-time control, and reliable monitoring. Distributed multiple-input multiple-output (D-MIMO) is one of the most promising technologies for delivering URLLC. This paper classifies obstructions and derives a channel model from a D-MIMO measurement campaign carried out at a carrier frequency of 3.75 GHz with a bandwidth of 35 MHz using twelve fully coherent distributed dipole antennas in an industrial environment. Channel characteristics are investigated, including statistical measures such as small-scale fading, large-scale fading, delay spread, and transition rates between line-of-sight and obstructed line-of-sight conditions for the different antenna elements, laying the foundations for an accurate channel model for D-MIMO systems in industrial environments. Furthermore, to ensure spatial consistent simulation results the correlations of large-scale fading between antennas are modeled using Gaussian random fields. Lastly, tail distributions are included to enable proper evaluations of reliability and rare events. Based on the results, a channel model for D-MIMO in industrial environments is presented together with a recipe for its implementation.

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arXiv2024

Spatial separation of closely-spaced users in measured distributed massive MIMO channels

Aiming for the sixth generation (6G) wireless communications, distributed massive multiple-input multiple-output (MIMO) systems hold significant potential for spatial multiplexing. In order to evaluate the ability of a distributed massive MIMO system to spatially separate closely spaced users, this paper presents an indoor channel measurement campaign. The measurements are carried out at a carrier frequency of 5.6 GHz with a bandwidth of 400 MHz, employing distributed antenna arrays with a total of 128 elements. Multiple scalar metrics are selected to evaluate spatial separability in line-of-sight, non line-of-sight, and mixed conditions. Firstly, through studying the singular value spread, it is shown that in line-of-sight conditions, better user orthogonality is achieved with a distributed MIMO setup compared to a co-located MIMO array. Furthermore, the dirty-paper coding (DPC) capacity and zero forcing (ZF) precoding sum-rate capacities are investigated across varying numbers of antennas and their topologies. The results show that in all three conditions, the less complex ZF precoder can be applied in distributed massive MIMO systems while still achieving a large fraction of the DPC capacity. Additionally, in line-of-sight conditions, both sum-rate capacities and user fairness benefit from more antennas and a more distributed antenna topology. However, in the given NLoS condition, the improvement in spatial separability through distributed antenna topologies is limited.

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arXiv2022

Fading in reflective and heavily shadowed industrial environments with large arrays

One of the use cases for 5G systems and beyond is ultra-reliability low-latency communication (URLLC). An enabling technology for URLLC is massive multiple-input multiple-output (MIMO), which can increase reliability due to improved user separation, array gain and the channel hardening effect. Measurements have been performed in an operating factory environment at 3.7 GHz with a co-located massive MIMO array and a unique randomly distributed array. Channel hardening can appear when the number of antennas is increased such that the variations of channel gain (small-scale fading) is decreased and it is here quantified. The cumulative distribution function (CDF) of the channel gains then becomes steeper and its tail is reduced. This CDF is modeled and the required fading margins are quantified. By deploying a distributed array, the large-scale power variations can also be reduced, further improving reliability. The large array in this rich scattering environment, creates a more reliable channel as it approaches an independent identically distributed (i.i.d.) complex Gaussian channel, indicating that one can rethink the system design in terms of e.g. channel coding and re-transmission strategies, in order to reduce latency. To conclude, massive MIMO is a highly interesting technology for reliable connectivity in reflective and heavily shadowed industrial environments.

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