61 citations · 245 across the 30 of their papers we have counts for
7 papers · 1 filter
When Is Distributed Nonlinear Aggregation Private? Optimality and Information-Theoretical Bounds
Wenrui Yu, Jaron Skovsted Gundersen, Richard Heusdens +1
Nonlinear aggregation is central to modern distributed systems, yet its privacy behavior is far less understood than that of linear aggregation. Unlike linear aggregation where mat…
Optimal Privacy-Preserving Distributed Median Consensus
Wenrui Yu, Qiongxiu Li, Richard Heusdens +1
Distributed median consensus has emerged as a critical paradigm in multi-agent systems due to the inherent robustness of the median against outliers and anomalies in measurement. D…
Optimal Pilot Design for OTFS in Linear Time-Varying Channels
Ids van der Werf, Richard Heusdens, Richard C. Hendriks +1
This paper investigates the positioning of the pilot symbols, as well as the power distribution between the pilot and the communication symbols in the orthogonal time frequency spa…
Privacy-Preserving Distributed Optimisation using Stochastic PDMM
Sebastian O. Jordan, Qiongxiu Li, Richard Heusdens
Privacy-preserving distributed processing has received considerable attention recently. The main purpose of these algorithms is to solve certain signal processing tasks over a netw…
Sensor Selection using the Two-Target Cramér-Rao Bound for Angle of Arrival Estimation
Costas A. Kokke, Mario Coutiño, Laura Anitori +2
Sensor selection is a useful method to help reduce data throughput, as well as computational, power, and hardware requirements, while still maintaining acceptable performance. Alth…
Privacy-Preserving Distributed Optimization via Subspace Perturbation: A General Framework
Qiongxiu Li, Richard Heusdens, Mads Græsbøll Christensen
As the modern world becomes increasingly digitized and interconnected, distributed signal processing has proven to be effective in processing its large volume of data. However, a m…