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arxiveess.SP2026-06-25

Single-Base-Station Indoor Localization via Super-Resolved Relative Power Delay Profiles

Fangqing Xiao, Dirk T. M. Slock

Indoor multipath is shaped by surrounding reflectors, scatterers, and blockages, so a relative power-delay profile (PDP) can serve as a location fingerprint without an identifiable LoS path, angle information, or absolute time-of-arrival ranging. However, a communication receiver observes finitely many noisy pilot-frequency samples rather than an ideal PDP. This paper models the resulting Dirichlet blur, delay folding, and off-grid mismatch, and reconstructs a posterior-power profile using expectation-maximization sparse Bayesian learning. In spatially consistent QuaDRiGa simulations, twofold SBL raises 20-dB Top-1 accuracy from 75.79\% (native PDP) and 87.24\% (threefold zero-padding) to 93.27\%, with 0.392~m mean error.

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arxivcs.NIeess.SP2026-07-01

Robust Base Station Placement in Agricultural IoT via Bayesian Optimization

Gourav Prateek Sharma, Durgesh Singh, James Gross

Precision-agriculture networks based on private 5G NR should ensure reliable connectivity for IoT sensor nodes throughout the crop growing season, yet the propagation environment changes dramatically as vegetation grows and matures. We formulate $K$-base-station~(BS) placement as…

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arxiveess.SP2026-07-19

Fourth-Order Cyclostationary Analysis of Power-Based Nonlinear Gardner Timing Error Detectors in Coherent Optical Systems

Zhongxing Tian, Zeyu Feng, Huan Huang, Dongdong Zou, Gangxiang Shen, Yi Cai

Power-based nonlinear Gardner timing error detectors (TEDs) can enhance clock-tone (CT) extraction in low-roll-off and bandwidth-limited coherent optical systems. However, their nonlinear power-domain operations make the extracted CT components depend on higher-order cyclic stati…

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arxiveess.SP2026-07-24

Depthwise Separable CNN for D-MIMO Indoor Localization with Data Reduction

Georgios Mystriotis, Rodney Martinez Alonso, Achiel Colpaert, Sofie Pollin

Indoor localization using Distributed Multiple-Input Multiple-Output (D-MIMO) and machine learning (ML) achieves sub-centimeter accuracy but faces midhaul capacity bottlenecks when transmitting raw Channel State Information (CSI) in Open Radio Access Networks (O-RAN) architecture…

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arxiveess.SPcs.ET2026-07-06

Optimal Base Station Placement for Beyond 5G Networks with Non-Convex Topology

Mohamed Shalma, Amr Mansour, Ahmed El-Mahdy

This paper investigates the optimal placement of a millimeter-wave (mmWave) base station (BS) within a realistic U-shaped environment with non-convex topology. The problem is challenging and NP-hard due to the non-convex topology and the non-convex objective functions which are t…

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arxiveess.SP2026-07-03

A Sheaf-Theoretic Framework for Distributed Multi-Site Channel Charting

Enrico Grimaldi, Leonardo Di Nino, Mario Edoardo Pandolfo, Gabriele D'Acunto, Sergio Barbarossa, Paolo Di Lorenzo

Channel charting (CC) enables data-driven user localization in wireless networks by embedding channel state information (CSI) into low-dimensional representations. In multi-cell scenarios, each base station independently learns a local chart via neural encoders, leading to misali…

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arxiveess.SP2026-07-09

Doppler-Resilient Rydberg Atomic Receiver for High-Dynamic Communication Networks via Adaptive Local Oscillator Tracking

Yiyue Xiang, Jianxiong Pan, Qiaolin Ouyang, Bichen Kang, Bin Qi, Neng Ye

Rydberg atomic receiver has emerged as promising candidate for next-generation wireless communication, due to the exceptional sensitivity and ability to overcome the physical limitations of traditional radio frequency antennas. Utilizing the resonant response of atomic energy lev…

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