arXiv subjects

Fabian Göttsch

Publications and source records attributed to Fabian Göttsch.

16 recordsLinked to original sources

arXiv2026

Rethinking Fronthaul Topologies for Cell-Free 6G Networks

Due to significant progress in physical layer (PHY) technologies, future 6G networks are expected to feature much denser antenna deployments. Cell-free MIMO network designs are one of the most promising candidates to enable denser networks. While significant effort has been put into its PHY research, the challenges it brings to networking disciplines remain relatively unexplored. In this work, we propose various fronthaul network designs for cell-free MIMO. Our results show that while tree topologies may suffice for small-scale deployments, they become infeasible as the number of antennas increases. In contrast, with growing network size, the proposed Clos topology performs almost as well as the optimal topology.

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arXiv2026

A Modular O-RAN Testbed Based on SRS Open Source O-CU/O-DU and Massive Beams Modular O-RU

In this paper, we present a modular open radio access network (O-RAN) consisting of the 5G Core, a central (O-CU) and distributed unit (O-DU) by Software Radio Systems (SRS) and an O-RAN radio unit (O-RU), MODRAD-SC, by Massive Beams (MB). OCUDU provides an open source 5G-compliant O-CU and O-DU solution developed by SRS, while MB's radio unit is a fully O-RAN compliant category A O-RU. According to O-RAN split 7.2a, OCUDU performs higher layer functions up to the high physical (PHY) layer, while the O-RU handles low PHY and RF functions. This results in an O-RAN-compliant 5G gNodeB. In an alternative configuration, OCUDU and MODRAD-SC operate in a software-defined radio fashion corresponding to split 8, facilitating non-real-time experiments among others. In both cases, the system provides full control over O-CU, O-DU, and O-RU. In addition, we will discuss the possibility to attach an analog beamformer to the O-RU, enabling hybrid digital-analog beamforming. The flexibility and modularity offered by OCUDU and MODRAD-SC enable the practical realization of a multitude of applications, ranging from 5G demonstrators to pre-6G experiments. The system addresses the requirements of academia and industry and is well-suited as an easy-to-use platform for experimental and practical deployments.

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arXiv2026

Towards Standardizing OTFS: A Candidate Waveform for Next-Generation Wireless Networks

The standardization of the sixth-generation (6G) has recently commenced to address the rapidly growing demands for enhanced wireless network services. Nevertheless, existing wireless systems, particularly at the physical layer waveform level, remain inadequate for achieving the ambitious key performance indicators (KPIs) envisioned for 6G. Specifically, orthogonal frequency division multiplexing (OFDM), the widely adopted waveform in fifth-generation new radio (5G-NR) networks, suffers from inherent limitations in satisfying these stringent requirements. In practice, OFDM can experience severe inter-carrier interference (ICI), resulting in a pronounced data rate error floor caused by high Doppler shifts. Additionally, the repetitive usage of cyclic prefixes (CPs), intended to combat multipath delays, results in significant spectral inefficiency. These fundamental drawbacks pose critical obstacles to fulfilling 6G performance objectives. Orthogonal time frequency space (OTFS) modulation has recently emerged as a promising waveform candidate, addressing the aforementioned challenges by exploiting the unique characteristics of the delay-Doppler (DD) domain channel. Unlike OFDM, OTFS is inherently resilient to channel distortions induced by delay and Doppler effects, while remaining sensitive to time and frequency shifts. Such intrinsic properties are instrumental in enabling OTFS, with joint communication and sensing capabilities, to embrace, rather than combat, dynamic channel conditions. Motivated by these compelling advantages, this article investigates the feasibility and practical implementation of OTFS modulation leveraging the current OFDM-based wireless systems.

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arXiv2025

Optimizing Fronthaul Quantization for Flexible User Load in Cell-Free Massive MIMO

We investigate the physical layer (PHY) spectral efficiency and fronthaul network load of a scalable user-centric cell-free massive MIMO system. Each user-centric cluster processor responsible for cluster-level signal processing is located at one of multiple decentralized units (DUs). Thus, the radio units in the cluster must exchange data with the corresponding DU over the fronthaul. Because the fronthaul links have limited capacity, this data must be quantized before it is sent over the fronthaul. We consider a routed fronthaul network, where the cluster processor placement and fronthaul traffic routing are jointly optimized with a mixed-integer linear program. For different numbers of users in the network, we investigate the effect of fronthaul quantization rates, a system parameter computed based on rate-distortion theory. Our results show that with optimized quantization rates, the fronthaul load is quite stable for a wide range of user loads without significant PHY performance loss. This demonstrates that the cell-free massive MIMO PHY and fronthaul network are resilient to varying user densities.

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arXiv2025

A Comparison among Single Carrier, OFDM, and OTFS in mmWave Multi-Connectivity Downlink Transmissions

In this paper, we perform a comparative study of common wireless communication waveforms, namely the single carrier (SC), orthogonal frequency-division multiplexing (OFDM), and orthogonal time-frequency-space (OTFS) modulation in a millimeter wave (mmWave) downlink multi-connectivity scenario, where multiple access points (APs) jointly serve a given user under imperfect time and frequency synchronization errors. For a fair comparison, all the three waveforms are evaluated using variants of common frequency domain equalization (FDE). To this end, a novel cross domain iterative detection for OTFS is proposed. The performance of the different waveforms is evaluated numerically in terms of pragmatic capacity. The numerical results show that OTFS significantly outperforms SC and OFDM at cost of reasonably increased complexity, because of the low cyclic-prefix (CP) overhead and the effectiveness of the proposed detection.

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arXiv2024

Joint Fronthaul Load Balancing and Computation Resource Allocation in Cell-Free User-Centric Massive MIMO Networks

We consider scalable cell-free massive multiple-input multiple-output networks under an open radio access network paradigm comprising user equipments (UEs), radio units (RUs), and decentralized processing units (DUs). UEs are served by dynamically allocated user-centric clusters of RUs. The corresponding cluster processors (implementing the physical layer for each user) are hosted by the DUs as software-defined virtual network functions. Unlike the current literature, mainly focused on the characterization of the user rates under unrestricted fronthaul communication and computation, in this work we explicitly take into account the fronthaul topology, the limited fronthaul communication capacity, and computation constraints at the DUs. In particular, we systematically address the new problem of joint fronthaul load balancing and allocation of the computation resource. As a consequence of our new optimization framework, we present representative numerical results highlighting the existence of an optimal number of quantization bits in the analog-to-digital conversion at the RUs.

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arXiv2024

Fairness Scheduling in User-Centric Cell-Free Massive MIMO Wireless Networks

We consider a user-centric cell-free massive MIMO wireless network with $L$ remote radio units, each with $M$ antennas, serving $K_{\rm tot}$ user equipments (UEs). Most of the literature considers the regime $LM \gg K_{\rm tot}$, where the $K$ UEs are active on each time-frequency slot, and evaluates the system performance in terms of ergodic rates. In this paper, we take a quite different viewpoint. We observe that the regime of $LM \gg K_{\rm tot}$ corresponds to a lightly loaded system with low sum spectral efficiency (SE). In contrast, in most relevant scenarios, the number of UEs is much larger than the total number of antennas, but users are not all active at the same time. To achieve high sum SE and handle $K_{\rm tot} \gg ML$, users must be scheduled over the time-frequency resource. The number of active users $K_{\rm act} \leq K_{\rm tot}$ must be chosen such that: 1) the network operates close to its maximum SE; 2) the active user set must be chosen dynamically over time in order to enforce fairness in terms of per-user time-averaged throughput rates. The fairness scheduling problem is formulated as the maximization of a concave componentwise non-decreasing network utility function of the per-user rates. Intermittent user activity imposes slot-by-slot coding/decoding which prevents the achievability of ergodic rates. Hence, we model the per-slot service rates using information outage probability. To obtain a tractable problem, we make a decoupling assumption on the CDF of the instantaneous mutual information seen at each UE $k$ receiver. We approximately enforce this condition with a conflict graph that prevents the simultaneous scheduling of users with large pilot contamination and propose an adaptive scheme for instantaneous service rate scheduling. Overall, the proposed dynamic scheduling is robust to system model uncertainties and can be easily implemented in practice.

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arXiv2024

User-Centric Cell-Free Wireless Networks for 6G: Communication Theoretic Models and Research Challenges

This paper presents a comprehensive communication theoretic model for the physical layer of a cell-free user-centric network, formed by user equipments (UEs), radio units (RUs), and decentralized units (DUs), uniformly spatially distributed over a given coverage area. We consider RUs equipped with multiple antennas, and focus on the regime where the UE, RU, and DU densities are constant and therefore the number of such nodes grows with the coverage area. A system is said scalable if the computing load and information rate at any node in the network converges to a constant as the network size (coverage area) grows to infinity. This imposes that each UE must be processed by a (user-centric) finite-size cluster of RUs, and that such cluster processors are dynamically allocated to the DUs (e.g., as software defined virtual network functions) in order to achieve a balanced computation load. We also assume that the RUs are connected to the DUs through a packet switching network, in order to achieve adaptive routing and load balance. For this model, we define in details the dynamic cluster formation and uplink pilot allocation. As a consequence of the pilot allocation and the scalability constraint, each cluster processor has a partial view of the network channel state information. We define the condition of ``ideal partial CSI'' when the channel vectors that can be estimated are perfectly known (while the ones that cannot be estimated are not know at all). We develop two attractive cluster-based linear receiver schemes for the uplink, and an uplink-downlink duality that allows to reuse such vectors as precoders for the downlink.

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arXiv2023

User-Centric Clustering Under Fairness Scheduling in Cell-Free Massive MIMO

We consider fairness scheduling in a user-centric cell-free massive MIMO network, where $L$ remote radio units, each with $M$ antennas, serve $K_{\rm tot} \approx LM$ user equipments (UEs). Recent results show that the maximum network sum throughput is achieved where $K_{\rm act} \approx \frac{LM}{2}$ UEs are simultaneously active in any given time-frequency slots. However, the number of users $K_{\rm tot}$ in the network is usually much larger. This requires that users are scheduled over the time-frequency resource and achieve a certain throughput rate as an average over the slots. We impose throughput fairness among UEs with a scheduling approach aiming to maximize a concave component-wise non-decreasing network utility function of the per-user throughput rates. In cell-free user-centric networks, the pilot and cluster assignment is usually done for a given set of active users. Combined with fairness scheduling, this requires pilot and cluster reassignment at each scheduling slot, involving an enormous overhead of control signaling exchange between network entities. We propose a fixed pilot and cluster assignment scheme (independent of the scheduling decisions), which outperforms the baseline method in terms of UE throughput, while requiring much less control information exchange between network entities.

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arXiv2022

Fairness Scheduling in Dense User-Centric Cell-Free Massive MIMO Networks

We consider a user-centric scalable cell-free massive MIMO network with a total of $LM$ distributed remote radio unit antennas serving $K$ user equipments (UEs). Many works in the current literature assume $LM\gg K$, enabling high UE data rates but also leading to a system not operating at its maximum performance in terms of sum throughput. We provide a new perspective on cell-free massive MIMO networks, investigating rate allocation and the UE density regime in which the network makes use of its full capability. The UE density $K$ approximately equal to $\frac{LM}{2}$ is the range in which the system reaches the largest sum throughput. In addition, there is a significant fraction of UEs with relatively low throughput, when serving $K>\frac{LM}{2}$ UEs simultaneously. We propose to reduce the number of active UEs per time slot, such that the system does not operate at ``full load'', and impose throughput fairness among all users via a scheduler designed to maximize a suitably defined concave componentwise non-decreasing network utility function. Our numerical simulations show that we can tune the system such that a desired distribution of the UE throughput, depending on the utility function, is achieved.

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arXiv2022

Subspace-Based Pilot Decontamination in User-Centric Scalable Cell-Free Wireless Networks

We consider a cell-free wireless system operated in Time Division Duplex (TDD) mode with user-centric clusters of remote radio units (RUs). Since the uplink pilot dimensions per channel coherence slot is limited, co-pilot users might incur mutual pilot contamination. In the current literature, it is assumed that the long-term statistical knowledge of all user channels is available. This enables Minimum Mean-Square Error channel estimation or simplified dominant subspace projection, which achieves significant pilot decontamination under certain assumptions on the channel covariance matrices. However, estimating the channel covariance matrix or even just its dominant subspace at all RUs forming a user cluster is not an easy task. In fact, if not properly designed, a piloting scheme for such long-term statistics estimation will also be subject to the contamination problem. In this paper, we propose a new channel subspace estimation scheme explicitly designed for cell-free wireless networks. Our scheme is based on 1) a sounding reference signal (SRS) using latin squares wideband frequency hopping, and 2) a subspace estimation method based on robust Principal Component Analysis (R-PCA). The SRS hopping scheme ensures that for any user and any RU participating in its cluster, only a few pilot measurements will contain strong co-pilot interference. These few heavily contaminated measurements are (implicitly) eliminated by R-PCA, which is designed to regularize the estimation and discount the ``outlier'' measurements. Our simulation results show that the proposed scheme achieves almost perfect subspace knowledge, which in turns yields system performance very close to that with ideal channel state information, thus essentially solving the problem of pilot contamination in cell-free user-centric TDD wireless networks.

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arXiv2022

Overloaded Pilot Assignment with Pilot Decontamination for Cell-Free Systems

The pilot contamination in cell-free massive multiple-input-multiple-output (CF-mMIMO) must be addressed for accommodating a large number of users. In previous works, we have investigated a decontamination method called subspace projection (SP). The SP separates interference from co-pilot users by using the orthogonality of the principal components of the users' channel subspaces. Non-overloaded pilot assignment (PA), where each radio unit (RU) does not assign the same pilot to different users, limits the spectral efficiency (SE) of the system, since SP channel estimation is able to deal with co-pilot users that have nearly orthogonal subspaces. Motivated by this limitation, this paper introduces overloaded PA methods adjusted for the decontamination in order to improve the sum SE of CF systems. Numerical simulations show that the overloaded PA methods give higher SE than that of non-overloaded PA at a high user density scenario.

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arXiv2022

Optimal User Load and Energy Efficiency in User-Centric Cell-Free Wireless Networks

Cell-free massive MIMO is a variant of multiuser MIMO and massive MIMO, in which the total number of antennas $LM$ is distributed among the $L$ remote radio units (RUs) in the system, enabling macrodiversity and joint processing. Due to pilot contamination and system scalability, each RU can only serve a limited number of users. Obtaining the optimal number of users simultaneously served on one resource block (RB) by the $L$ RUs regarding the sum spectral efficiency (SE) is not a simple challenge though, as many of the system parameters are intertwined. For example, the dimension $τ_p$ of orthogonal Demodulation Reference Signal (DMRS) pilots limits the number of users that an RU can serve. Thus, depending on $τ_p$, the optimal user load yielding the maximum sum SE will vary. Another key parameter is the users' uplink transmit power $P^{\rm ue}_{\rm tx}$, where a trade-off between users in outage, interference and energy inefficiency exists. We study the effect of multiple parameters in cell-free massive MIMO on the sum SE and user outage, as well as the performance of different levels of RU antenna distribution. We provide extensive numerical investigations to illuminate the behavior of the system SE with respect to the various parameters, including the effect of the system load, i.e., the number of active users to be served on any RB. The results show that in general a system with many RUs and few RU antennas yields the largest sum SE, where the benefits of distributed antennas reduce in very dense networks.

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arXiv2022

Robust PCA for Subspace Estimation in User-Centric Cell-Free Wireless Networks

We consider a scalable user-centric cell-free massive MIMO network with distributed remote radio units (RUs), enabling macrodiversity and joint processing. Due to the limited uplink (UL) pilot dimension, multiuser interference in the UL pilot transmission phase makes channel estimation a non-trivial problem. We make use of two types of UL pilot signals, sounding reference signal (SRS) and demodulation reference signal (DMRS) pilots, for the estimation of the channel subspace and its instantaneous realization, respectively. The SRS pilots are transmitted over multiple time slots and resource blocks according to a Latin squares based hopping scheme, which aims at averaging out the interference of different SRS co-pilot users. We propose a robust principle component analysis approach for channel subspace estimation from the SRS signal samples, employed at the RUs for each associated user. The estimated subspace is further used at the RUs for DMRS pilot decontamination and instantaneous channel estimation. We provide numerical simulations to compare the system performance using our subspace and channel estimation scheme with the cases of ideal partial subspace/channel knowledge and pilot matching channel estimation. The results show that a system with a properly designed SRS pilot hopping scheme can closely approximate the performance of a genie-aided system.

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arXiv2022

Uplink-Downlink Duality and Precoding Strategies with Partial CSI in Cell-Free Wireless Networks

We consider a scalable user-centric wireless network with dynamic cluster formation as defined by Björnsson and Sanguinetti. After having shown the importance of dominant channel subspace information for uplink (UL) pilot decontamination and having examined different UL combining schemes in our previous work, here we investigate precoding strategies for the downlink (DL). Distributed scalable DL precoding and power allocation methods are evaluated for different antenna distributions, user densities and UL pilot dimensions. We compare distributed power allocation methods to a scheme based on a particular form of UL-DL duality which is computable by a central processor based on the available partial channel state information. The new duality method achieves almost symmetric "optimistic ergodic rates" for UL and DL while saving considerable computational complexity since the UL combining vectors are reused as DL precoders.

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arXiv2021

The Impact of Subspace-Based Pilot Decontamination in User-Centric Scalable Cell-Free Wireless Networks

We consider a scalable user-centric wireless network with dynamic cluster formation as defined by Björnsson and Sanguinetti. Several options for scalable uplink (UL) processing are examined including: i) cluster size and SNR threshold criterion for cluster formation; ii) UL pilot dimension; iii) local detection and global (per cluster) combining. We use a simple model for the channel vector spatial correlation, which captures the fact that the propagation between UEs and RRHs is not isotropic. In particular, we define the ideal performance based on ideal but partial CSI, i.e., the CSI that can be estimated based on the users to antenna heads cluster connectivity. In practice, CSI is estimated from UL pilots, and therefore it is affected by noise and pilot contamination. We show that a very simple subspace projection scheme is able to basically attain the same performance of perfect but partial CSI. This points out that the essential information needed to pilot decontamination reduces effectively to the dominant channel subspaces.

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