arXiv subjects

Stephan ten Brink

Publications and source records attributed to Stephan ten Brink.

At least 19 recordsLinked to original sources

arXiv2026

BASIIS: Bistatic Angular Sampling and Interpolation for ISAC Setups

Integrated Sensing and Communications (ISAC) is a defining feature of 6G, extending cellular networks with radar-like sensing at limited additional overhead. In bistatic deployments, sensing requires coordinating the transmitter (TX) and receiver (RX) arrays to scan the Cartesian product of angle of departure and arrival, resulting in a four-dimensional sampling problem in the angular domain. This work establishes a complete angular sampling framework for bistatic ISAC, extending the DFT-based optimal-sampling methodology to the full azimuth and elevation domains of both arrays. We show that the bistatic geometry couples the TX and RX elevation angles, and represent this coupling through the ortho-baseline coarray, a virtual array that captures the joint elevation aperture of the array pair. From the coarray we derive a minimal sampling and interpolation scheme, near-lossless and realizable with any beamforming architecture. Monte Carlo simulations confirm the proposed minimal acquisition essentially equalizes the detection accuracy of dense oversampled imaging while acquiring 3 to 5 times fewer TX-RX direction pairs. This allows having bistatic operations with drastically reduced overhead on the radio resource usage of ISAC systems.

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arXiv2026

Chase-like Decoding: Test-Pattern Design and Performance Analysis

Chase-like decoding algorithms are a popular choice for soft-input decoding of algebraic codes. We evaluate different test-pattern sets for Chase-like decoding. Structured sets, such as Chase-II patterns or patterns chosen by logistic weight, are analyzed using order statistics, while arbitrary sets are evaluated by calculating covered-space probabilities and by performing Monte Carlo simulation. We further propose an algorithm that designs test-pattern sets to cover likely error patterns, achieving comparable performance with half the number of test patterns compared with conventional sets for high-rate BCH codes.

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arXiv2026

Visualizing Wireless Propagation and Polarization in Augmented Reality with ESPARGOS

Wireless multipath propagation, beamforming, and polarization are central concepts in radio systems, but they are difficult to observe directly because radio-frequency fields are invisible to humans. This paper presents an augmented-reality visualization system that turns phase-coherent WiFi channel measurements from the ESPARGOS antenna array into a live camera overlay. The system estimates a two-dimensional beamspace representation, registers it with the optical camera view, and overlays the resulting angular spectrum onto the physical scene. Additional visual layers show relative path delay and polarization, the latter computed using Jones calculus from channel measurements captured from two separate antenna feeds. The result is an intuitive ``WiFi camera'' for science communication, teaching, and experimental debugging, while all displayed quantities remain directly derived from measured channel data.

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arXiv2026

SECS: A Soft Ensemble-Combining Stage for Low-Latency Decoding

Ensemble decoding is a promising technique for ultra-reliable low-latency communication, as it trades hardware parallelism for decoding latency by running M diverse belief propagation (BP) decoders in parallel. Conventional ensembles select their output from the candidates. Hence, decoding fails whenever no member finds the correct codeword. In this work, we show that shallow, diverse BP members are poor correctors, but excellent sorters. Based on this observation, we propose a soft ensemble-combining stage (SECS) that combines extrinsic messages after only a few iterations, yielding a reliability ordering whose most reliable positions are nearly error-free. A subsequent re-encoding stage (like ordered-statistics decoding (OSD)) converts this ordering into a near-maximum likelihood (ML) candidate codeword, at a fraction of the BP latency of a fully converged ensemble. We demonstrate the proposed scheme on three short codes: a (63,30) Bose-Ray-Chaudhuri-Hocquenghem code, an overcomplete PG(2,8) code, and a search-designed (105,53) cyclic code. In all cases, the SECS with OSD post-processing closes most of the gap to ML decoding, while significantly reducing the number of required BP iterations.

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arXiv2026

When to Stop? Dynamic Early Termination of Sequential Ensembles

Ordered-statistics decoding (OSD) post-processing substantially improves the performance of belief propagation (BP) ensembles, but it also removes their natural syndrome-based stopping criterion. The high computational complexity of ensemble decoding and OSD can be reduced by sequential activation of ensemble members paired with an early termination. Instead of a syndrome-based termination we therefore apply dynamic ensemble termination (DET) to sequential ensembles: members are evaluated one at a time and decoding stops when the estimated risk that an unseen member would correct the current decision falls below an offline-fitted threshold. With hardware-oriented design in mind, we instantiate the framework with layered normalized min-sum component decoders, a row-boosted ensemble, conditional low-order OSD on the dual code, and a conventional low-cost decoder gate. A decision tree estimates the residual risk from statistics of the current candidate list. Member-dependent thresholds then target a prescribed frame error rate (FER) loss. We validate this framework on mutliple IEEE 802.11 low-density parity-check (LDPC) codes with blocklengths $648,1296$, and $1944$ at rates $1/2$ and $5/6$. At each code's design point, where the full $64$-member list reaches an FER of $10^{-3}$, the DET decoder processes $1.04$ to $1.15$ members on average. On the $(648,540)$ code, it reduces BP work by $39\times$ and OSD activations by $18\times$ against the full list while retaining an signal-to-noise ratio (SNR) gain of about $0.4\,\mathrm{dB}$.

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arXiv2026

Row-Boosted Ensemble Belief Propagation for Short LDPC Codes

Belief-propagation (BP) decoding of short and moderate-length low-density parity-check (LDPC) codes is limited by finite-length graph effects: a single decoder trajectory can become trapped or oscillatory even when an alternative trajectory would decode the received word. Existing ensemble-BP decoders create the required diversity through multiple parity-check matrices, automorphisms, modified schedules, subcodes, or altered update rules. We introduce row-boosted ensemble (RBE) decoding as a minimal decoder-side diversity mechanism: all ensemble members share the same parity-check matrix and the same BP kernel, and differ only in a small set of parity-check rows whose outgoing messages are boosted. On the 5G~NR BG1 $(144,96)$ code, RBE with $32$ members lowers the frame-error rate of BP with $20$ iterations (BP-20) from $1.6\times10^{-2}$ to $1.6\times10^{-3}$ at $E_\mathrm{b}/N_0=4.0\,\mathrm{dB}$, outperforming saturated-min-sum and affine subcode ensembles of equal size. Increasing the ensemble size yields additional gains, indicating that RBE provides a scalable performance-complexity tradeoff. The gains transfer across 5G~NR block lengths and rates, to non-5G short LDPC codes, and across flooding and layered schedules.

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arXiv2026

Auxiliary Nodes for BP Decoding of Quantum LDPC Codes

Many recently proposed Calderbank-Shor-Steane (CSS) quantum low-density parity-check (QLDPC) codes have sparse decoding graphs, enabling syndrome-based belief propagation (BP) decoding at low complexity. Their construction, however, often results in properties that impair BP performance, such as short cycles and degeneracy. In this work, we propose a general framework for introducing auxiliary variable nodes (AVNs) and auxiliary check nodes (ACNs) into the decoding graph of CSS codes, compatible with the standard stabilizer measurement framework. This provides an additional degree of freedom in the design of the decoding graph itself and can be used to tackle the aforementioned shortcomings. We show that recently proposed techniques, 4-cycle removal and subcode ensemble decoding, can be interpreted as instances of this framework. For 4-cycle removal, we find that the gains depend strongly on the BP iteration count and check-node message scaling. Building on this framework, we further propose a graph-derived subcode ensemble decoder and demonstrate under circuit-level noise that it substantially reduces the per-round logical error rate compared with BP on the corresponding 4-cycle-free decoding graph.

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arXiv2026

Signal Space-Transformed Expectation Propagation for Symbol Detection in ISI Channels

Iterative message passing detection based on expectation propagation (EP) has demonstrated near-optimum performance in many signal processing and communication scenarios. The method remains feasible even for channel impulse responses (CIRs), where the optimal Bahl-Cocke-Jelinek-Raviv (BCJR) detector is infeasible. However, significant performance degradation occurs for channels with strong inter-symbol interference (ISI), where the initial linear minimum mean square error (LMMSE) estimate is inaccurate. We propose an EP-based detector that operates in a transformed signal space. Specifically, instead of the conventional approach that iterates between an LMMSE estimator and a non-linear symbol-wise demapper, the proposed method iterates between a linear channel shortening filter-based estimator and a non-linear BCJR detector with reduced memory compared to the actual channel. Additionally, we propose a deliberate mismatch between the initialized messages and the initialized covariance used in the linear estimator in the first iteration for faster convergence. The proposed approach is evaluated for the well-known Proakis-C ISI channel and for CIRs from a wireless measurement campaign. We demonstrate improvements of up to 6 dB at 2 bits per channel use and an improved performance-complexity trade-off over conventional EP-based detection

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arXiv2026

Affine Subcode Ensemble Decoding of Linear Block Codes

In the short block length regime, ensemble decoding schemes with their inherently parallel structure can improve error correction performance and reduce latency compared to stand-alone suboptimal decoders such as belief propagation (BP). In this work, we introduce affine subcode ensemble decoding (aSCED), which uses an ensemble of decoders operating on linear block codes and both linear and strictly affine subcodes. This generalizes the recently proposed subcode ensemble decoding (SCED), which is restricted to linear subcodes. We derive BP update rules for affine subcodes and show that aSCED simplifies ensemble design compared to SCED, multiple bases BP, and automorphism ensemble decoding. Monte-Carlo simulations of two low-density parity-check codes and two Bose-Chaudhuri-Hocquenghem (BCH) codes demonstrate improved error correction performance of aSCED over competing existing ensemble schemes. Notably, for one BCH code, when combining ensemble design with algorithms for constructing high-performance parity-check matrices, aSCED achieves near-maximum likelihood performance using only 64 BP decoding paths.

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arXiv2026

Experimental Demonstration of Multi-Target Tracking in Integrated Sensing and Communication

For a wide range of envisioned integrated sensing and communication (ISAC) use cases, it is necessary to incorporate tracking techniques into cellular communication systems. While numerous multi-target tracking (MTT) algorithms exist, they have not yet been applied to real-world ISAC, with its challenges such as clutter and non-optimal hardware with design emphasis on communication instead of sensing. In this work, we showcase MTT based on the probability hypothesis density (PHD) filter in the range and radial speed domain. The measurements are taken with a 5G compliant ISAC proof-of-concept in a real factory environment, where the pedestrian-like targets are generated by a radar target emulator. We detail the complete pipeline, from measurement acquisition to evaluation, with a focus on the post-processing of the raw captured data and the tracking itself. Our end-to-end evaluation and comparison to simulations show good MTT performance with mean absolute ranging error <1.5m and detection rates >91% for realistic but challenging scenarios.

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arXiv2026

Towards a Unified Coding Scheme for 6G

The growing demand for higher data rates necessitates continuous innovations in wireless communication systems, particularly with the emergence of 6G. Channel coding plays a crucial role in this evolution. In 5G systems, rate-adaptive raptor-like quasi-cyclic irregular low-density parity-check codes are used for the data link, while polar codes with successive cancellation list decoding handle short messages on the synchronization channel. However, to meet the stringent requirements of future 6G systems, a versatile and unified coding scheme should be developed - one that offers competitive error-correcting performance alongside low complexity encoding and decoding schemes that enable energy-efficient hardware implementations. This white paper outlines the vision for such a unified coding scheme. We explore various 6G communication scenarios that pose new challenges to channel coding and provide a first analysis of potential solutions.

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arXiv2026

Bistatic ISAC: Practical Challenges and Solutions

This article presents and discusses challenges and solutions for practical issues in bistatic integrated sensing and communication (ISAC) in 6G networks. Considering orthogonal frequency-division multiplexing as the adopted waveform, a discussion on system design aiming to achieve both a desired sensing key performance indicators and limit the impact of hardware impairments is presented. In addition, signal processing techniques to enable over-the-air synchronization and generation of periodograms with range, Doppler shift, and angular information are discussed. Simulation results are then presented for a cellular-based ISAC scenario considering system parameterization compliant to current 5G and, finally, a discussion on open challenges for future deployments is presented.

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arXiv2025

Three-Dimensional Radio Localization: A Channel Charting-Based Approach

Channel charting creates a low-dimensional representation of the radio environment in a self-supervised manner using manifold learning. Preserving relative spatial distances in the latent space, channel charting is well suited to support user localization. While prior work on channel charting has mainly focused on two-dimensional scenarios, real-world environments are inherently three-dimensional. In this work, we investigate two distinct three-dimensional indoor localization scenarios using simulated, but realistic ray tracing-based datasets: a factory hall with a three-dimensional spatial distribution of datapoints, and a multistory building where each floor exhibits a two-dimensional datapoint distribution. For the first scenario, we apply the concept of augmented channel charting, which combines classical localization and channel charting, to a three-dimensional setting. For the second scenario, we introduce multistory channel charting, a two-stage approach consisting of floor classification via clustering followed by the training of a dedicated expert neural network for channel charting on each individual floor, thereby enhancing the channel charting performance. In addition, we propose a novel feature engineering method designed to extract sparse features from the beamspace channel state information that are suitable for localization.

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arXiv2025

Angular Estimation Comparison with ISAC PoC

The introduction of Integrated Sensing and Communications (ISAC) in cellular systems is not expected to result in a shift away from the popular choice of cost- and energy-efficient analog or hybrid beamforming structures. However, this comes at the cost of limiting the angular capabilities to a confined space per acquisitions. Thus, as a prerequisite for the successful implementation of numerous ISAC use cases, the need for an optimal angular estimation of targets and their separation based on the minimal number of angular samples arises. In this work, different approaches for angular estimation based on a minimal, DFT-based set of angular samples are evaluated. The samples are acquired through sweeping multiple beams of an ISAC proof of concept (PoC) in the industrial scenario of the ARENA2036. The study's findings indicate that interpolation approaches are more effective for generalizing across different types of angular scenarios. While the orthogonal matching pursuit (OMP) approach exhibits the most accurate estimation for a single, strong and clearly discriminable target, the DFT-based interpolation approach demonstrates the best overall estimation performance.

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arXiv2025

ORCAS Codes: A Flexible Generalization of Polar Codes with Low-Complexity Decoding

Motivated by the need for channel codes with low-complexity soft-decision decoding algorithms, we consider the recursive Plotkin concatenation of optimal low-rate and high-rate codes based on simplex codes and their duals. These component codes come with low-complexity maximum likelihood (ML) decoding which, in turn, enables efficient successive cancellation (SC)-based decoding. As a result, the proposed optimally recursively concatenated simplex (ORCAS) codes achieve a performance that is at least as good as that of polar codes. For practical parameters, the proposed construction significantly outperforms polar codes in terms of block error rate by up to 0.5 dB while maintaining similar decoding complexity. Furthermore, the codes offer greater flexibility in codeword length than conventional polar codes.

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arXiv2025

Nested Symmetric Polar Codes

In this paper, we propose a data-driven algorithm to design rate- and length-flexible polar codes. While the algorithm is very general, a particularly appealing use case is the design of codes for automorphism ensemble decoding (AED), a promising decoding algorithm for ultra-reliable low-latency communications (URLLC) and massive machine-type communications (mMTC) applications. To this end, theoretic results on nesting of symmetric polar codes are derived, which give hope in finding a fully nested, rate-compatible sequence suitable for AED. Using the proposed algorithms, such a flexible polar code design for automorphism ensemble successive cancellation (SC) decoding is constructed, outperforming existing code designs for AED and also the 5G polar code under cyclic redundancy check (CRC)-aided successive cancellation list (SCL) decoding.

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arXiv2025

Long Polar vs. LDPC Codes under Complexity-Constrained Decoding

The prevailing opinion in industry and academia is that polar codes are competitive for short code lengths, but can no longer keep up with low-density parity-check (LDPC) codes as block length increases. This view is typically based on the assumption that LDPC codes can be decoded with a large number of belief propagation (BP) iterations. However, in practice, the number of iterations may be rather limited due to latency and complexity constraints. In this paper, we show that for a similar number of fixed-point log-likelihood ratio (LLR) operations, long polar codes under successive cancellation (SC) decoding outperform their LDPC counterparts. In particular, simplified successive cancellation (SSC) decoding of polar codes exhibits a better complexity scaling than $N \log{N}$ and requires fewer operations than a single BP iteration of an LDPC code with the same parameters.

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arXiv2025

CSI Obfuscation: Single-Antenna Transmitters Can Not Hide from Adversarial Multi-Antenna Radio Localization Systems

The ability of modern telecommunication systems to locate users and objects in the radio environment raises justified privacy concerns. To prevent unauthorized localization, single-antenna transmitters can obfuscate the signal by convolving it with a randomized sequence prior to transmission, which alters the channel state information (CSI) estimated at the receiver. However, this strategy is only effective against CSI-based localization systems deploying single-antenna receivers. Inspired by the concept of blind multichannel identification, we propose a simple CSI recovery method for multi-antenna receivers to extract channel features that ensure reliable user localization regardless of the transmitted signal. We comparatively evaluate the impact of signal obfuscation and the proposed recovery method on the localization performance of CSI fingerprinting, channel charting, and classical triangulation using real-world channel measurements. This work aims to demonstrate the necessity for further efforts to protect the location privacy of users from adversarial radio-based localization systems.

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