In environments where multiple autonomous mobile robots (AMRs) operate in close proximity, electromagnetic noise radiated from their onboard printed circuit boards (PCBs) can significantly degrade the quality of nearby communication systems. Although proper shielding of the PCBs can effectively suppress this noise, conventional metal shields obscure visibility. In this paper, to mitigate electromagnetic interference while maintaining the visibility of the PCB, we prototyped a shielding case using a transparent flexible radio-wave reflective film and evaluated its noise suppression performance through near-field measurements. A Wi-Fi module operating in the 2.4 GHz band was placed inside an aluminum frame on a PCB, and we compared the impact of the film's application methods on shielding performance. The results showed that directly adhering the film to the frame achieved a noise suppression of 26.7 dB compared to the unshielded condition. Furthermore, a configuration employing conductive tape to ensure electrical bonding and gap sealing demonstrated a high noise suppression of 33.2 dB.
Unmanned Aerial Vehicles (UAVs) have attracted significant attention for disaster recovery applications because they can provide sensing, delivery, and temporary wireless networking services even in environments where ground transportation is difficult. However, UAV operation is constrained by limited battery capacity, requiring periodic returns for battery replacement or refueling. In conventional systems, separate UAV fleets are typically required for delivery and networking services, resulting in higher operational costs and increased battery consumption. To address this issue, this letter proposes a service-sharing temporary relay network construction scheme using delivery UAVs. In the proposed scheme, delivery UAVs simultaneously provide wireless network coverage while transporting packages between a logistics hub and delivery destinations. A delivery exclusion area is also introduced to distribute UAVs over a wider area and improve network coverage. Computer simulations were conducted to evaluate the coverage performance of the proposed scheme. The results demonstrate that the proposed scheme can provide stable wireless cover age while reducing coverage fluctuations caused by UAV departures and returns.
We present PARR, a perception-aware, risk-constrained replication-and-roaming policy for wireless links carrying time-sensitive-networking (TSN) flows in mobile robotics. PARR is not a MAC scheduler or a standalone predictor: IEEE 802.1CB frame replication (FRER) provides reliability, while LiDAR geometry and an online-calibrated shadow-fading residual decide when, where, and over which access points (APs) to replicate at minimum airtime. On a 3GPP TR 38.901 indoor-factory channel with correlated shadowing, PARR matches blanket-FRER reliability at about one-third of its airtime, stays robust as shadowing grows where threshold and reactive baselines fail, and, unlike blanket FRER which is harmful under contention, scales to sixteen coexisting robots.
We previously developed an indoor localization system based on Wi-Fi received signal strength (RSS), achieving room-, floor-, and corridor-level localizations within the Toyohashi University of Technology (TUT) campus. However, the error in corridor localization can be significant in certain areas, depending on the placement of access points (APs), due to the inherent limitations of weighted centroid localization (WCL). This study aims to improve localization errors by combining WCL with radio fingerprint localization (FPL). To achieve this combination, we develop a section estimation technique to determine whether to apply WCL or FPL for corridor-level localization. We demonstrate that the combined scheme achieves smaller localization errors than WCL. Furthermore, we show that it has been implemented and performs well on Android devices.
Radar Cross Section (RCS) measurement for a target on ground plane is important for many applications. In this letter, we propose a test device which is modified from The NASA almond to make sliding surface for pylon with single axis rotator be far away from a target under test. Design, manufacture and measurement of the proposed device are performed. In elevation angular region from 10 to 30deg., the proposed device is below −40 dBsm. The measured RCS of a rivet as an example of target and the simulated RCS of a rivet on an infinite grand plane have discrepancy less than 4.1dB at 10 GHz in same angular region.
This paper studies a reconfigurable intelligent surface (RIS)-assisted integrated sensing, communication, and energy harvesting system. The sensing beampattern gain is maximized by jointly optimizing the base station beamforming and RIS phase shifts under communication and energy constraints. A semidefinite relaxation (SDR) benchmark and a low-complexity (LC) alternating algorithm are developed. The SDR method provides a performance reference, while the LC design relies on Lagrangian dual updates and coordinate descent for practical implementation. Numerical results further show that the proposed design maintains sensing performance under different communication and harvesting requirements. Simulations show that the LC design achieves near-SDR performance with lower complexity and effectively captures the tradeoff among sensing, communication, and energy harvesting.
The proliferation of counterfeit electronic parts, including integrated circuits (ICs) and other components, threatens system functionality and can lead to critical failures. This paper presents a device identification method based on spectral emission differences as a fundamental step toward board-level authenticity assurance. The proposed method actively extracts device-to-device differences originating in semiconductor manufacturing and observes them together with additional variations introduced by components, interconnects, and printed circuit boards (PCBs). Specifically, a marker signal in the MHz band is generated inside the IC. As this signal propagates through and radiates from the PCB, the characteristics of the source, path, and antenna are superimposed on the observed spectrum. The peak amplitudes of the fundamental and harmonic components are then used as identification features. An evaluation using six commercial microcontrollers showed that all devices were correctly identified by averaging three measurements, and that the maximum misidentification rate was limited to 5.6% even for a single measurement.
This letter focuses on a wildlife monitoring system to remotely monitor and control the status of cages deployed to capture wild animals. We introduce a system employing diversified range IoT (DR-IoT), which is a private radio operating in the VHF band. The usage of VHF band allows us to achieve a long-range transmission, however, it also poses several challenges due to its low achievable data rates. In this letter, we investigate how to increase the capacity (number of supported cages) by employing multi-channel transmissions and enhance its reliability. In addition to the basic experimental evaluations of the interference problem in a multichannel DR-IoT system, we present results obtained by our field trial in an actual mountainous area.
This paper proposes a novel beamforming method based on generalized eigenvalue decomposition (GEVD) to address severe same-color interference in spaceborne multibeam antenna systems. By constructing distinct signal and interference subspaces through spatial smoothing, the approach optimizes weighting vectors to maximize edge-of-coverage gain while robustly suppressing side lobes. Simulations demonstrate that, compared to traditional analytical methods, this technique significantly improves edge gain by 2.26 dB, reduces interference area side-lobe levels by 5.58 dB, and enhances the carrier-to-interference (C/I) ratio by 7.92 dB, effectively boosting overall spectrum efficiency.
Applying generative AI to advanced network operations requires structuring network diagrams, which exist as unstructured data at operational sites. However, in diagrams with crossing lines and overlapping, congested shapes, conventional image-only methods often misread the connections between devices. Noting that such diagrams are often drawn with general-purpose tools whose internal representation is a markup language such as XML, we propose structuring based on cross-modal analysis of markup language and images, in which a generative AI agent reads a diagram by mutually complementing the two modalities. On the public JPNM48 dataset, the proposed method improved the edge (connection) F1 from an image-only baseline of 0.806 ± 0.034 to 0.966 ± 0.077 (Welch's t-test, p < 0.001, Cohen's d = 2.71).
This letter explores the Tsetlin Machine (TM) as a universal, reconfigurable logic-centric framework for learnable channel decoding on edge devices. Using a Hamming(7, 4) code case study on an ESP32 microcontroller, we demonstrate a TM-based decoder capable of discovering decoding rules from data in just 24 seconds. To ensure robust convergence under hardware constraints, the on-device model doubles the scale of the offline model, yet maintains an ultra-low decoding latency of 37 µs, translating to a real-time throughput of over 100 kbps. Bit error rate simulations confirm that the TM decoder matches the performance of conventional hard-decision decoder. These findings highlight the inherent hardware-friendliness and scalability of TMs, offering a promising path for reconfigurable, self-learning decoders on resource-constrained platforms.
Doherty power amplifiers (DPAs) are widely utilized in modern communication systems for their high efficiency, but they exhibit severe nonlinearities and memory effects when driven into saturation. Among various linearization techniques, digital predistortion (DPD) has become the mainstream solution to compensate for these impairments. However, traditional Generalized Memory Polynomial (GMP) models struggle to achieve high modeling accuracy for such highly nonlinear DPAs. To address this limitation, this paper proposes a novel DPD method based on joint magnitude and phase segmentation. By partitioning the complex signal plane into a polar grid, the proposed approach achieves a more precise fitting of the DPA's strong nonlinear behaviors and memory effects. Moreover, a high-throughput hardware actuator tailored for the proposed method is designed based on a multi-branch Look-Up Table architecture and deployed on a Xilinx Zynq UltraScale+ MPSoC platform. Measurements on a 50 W DPA driven by a 20 MHz OFDM signal show that the method reduces the Normalized Mean Square Error to −35.07 dB and the Adjacent Channel Power Ratio to −46.16 dBc (lower) and −44.56 dBc (upper), outperforming the conventional GMP baseline.
The functional disaggregation of optical transport equipment is underway to create optical transport networks that offer faster time-to- market and optimized performance. In parallel, multi-vendor environments are being increasingly adopted by network operators. Even in the resulting disaggregated environments, network control should remain unified. To satisfy this requirement, we are developing a controller that incorporates an adapter function to absorb differences in control commands across multivendor devices. The adapter internally maintains control scripts written in an intermediate language and abstracts vendor-specific commands to hide inter-vendor differences. This paper proposes a method in which a large language model (LLM) assists in generating control scripts written in a domain-specific language (DSL). Compared with baseline approaches, the proposed method reduced the number of syntax/formatting errors in control scripts by 50%. Furthermore, key technical findings extracted from an evaluation and analysis are summarized, and prospects for further advancement of the proposed method are discussed.
Line-of-sight optical wireless communication has difficulty in consistently aligning a photodiode receiver with an LED transmitter. Currently, however, to overcome this drawback, a camera can accurately capture LED position, and the photodiode can be aligned with the LED. In this study, narrow field of view (FOV) photodiode is individually aligned with 5-wavelength LEDs including infrared LEDs. Space and wavelength division multiplexing (SDM/WDM) is implemented to achieve a higher transmission rate. Photodiode receivers with a narrow FOV of 1.57° achieved 5 Mbit/s SDM/WDM transmission (2 SDM × 5 WDM × 0.5 Mbit/s) based on the camera's LED position detection.
Although the use of carbon fiber reinforced plastic (CFRP) in automotive components has been expanding, its electrical properties in high-frequency band have not been fully investigated. In this letter, we constructed a microstrip structure using CFRP plate to examine electrical properties of the CFRP and identified its effective conductivity over a wide frequency range, including the GHz band. One advantage of this method is that the direction of the current along CFRP sample in the measurement system is same as the direction of the return path of the common-mode current flowing through automotive components that adopt CFRP. In the letter, we first measured transmission characteristics of a microstrip structure with a CFRP plate as the signal line. By comparing the transmission loss with full-wave simulation, we were able to identify the effective conductivity of the CFRP is approximately 10,000 S/m. Furthermore, we confirmed that applying CFRP as the return plane did not affect common-mode noise compared to the conventional metal planes.
This letter proposes an antenna affiliation switching and received signal selection in uplink for a distributed antenna systems (DAS). The proposed scheme is applied to a macrocell system in which each macrocell consists of multiple picocells. Conventional approach improves throughput by allowing antennas located at the boundary of a macrocell to switch their affiliation to an adjacent macrocell. However, no interference suppression by selecting received signals has been investigated. Therefore, this letter introduces a DAS system that controls received signal selection in addition to antenna affiliation switching in a DAS. Markov chain Monte Carlo methods and e-greedy algorithms are applied for antenna affiliation switching and received signal selection. Numerical results obtained through computer simulation show that the proposed scheme improves the throughput by at most 0.30 bps/Hz/cell. Furthermore, the proposed scheme maintains a comparable fairness index compared to the conditional scheme.
The Nakagami-n (Rician) fading model is essential for characterizing line-of-sight (LOS) wireless channels in 5G and 6G networks. While the Nakagami-n model underpins LOS channel modeling in next-generation networks, the complexity of the modified Bessel function often necessitates the use of the Small Limit Argument Approximation (SLAA). However, the validity domain of this approximation has not been rigorously defined. This study quantifies the SLAA's accuracy limits, specifically examining the interplay between fading severity (K), SNR (p), and diversity order (m). Our analysis reveals that the SLAA maintains structural fidelity (Root Mean Square Error (RMSE) < 10−3) only under near-Rayleigh conditions (K < 0.04). Furthermore, we observe that approximation error exhibits a linear dependence on m, despite a marginal reduction at higher SNRs. Consequently, the SLAA is unsuitable for strong Rician (K ≥ 1) or high-diversity systems, limiting its utility primarily to asymptotic analyses in weak LOS channels. These findings establish critical design guidelines for the safe application of SLAA in next-generation wireless system analysis.
In this paper, we demonstrate a millimeter-wave active phased array antenna. Our phased array antenna has three features. 1) Planar and back-to-back structure; all electronic components are mounted on the reverse side of the antenna. Our waveguide to microstrip line transition enables the interconnection between both sides of the substrate. 2) Optimized RF-IC placement; the ICs can be placed just behind the transitions in order to reduce attenuation. 3) Low cost; we utilize our original ICs and manufacturing technologies for automotive radars. We designed and fabricated the prototype active phased array with 6 transmitting channels. The radiation patterns were successfully formed both for the boresight beam and for beam scanning. Narrow beam (approximately 2 deg) was obtained. We also confirmed that the waveguide to microstrip line transition did not affect the radiation pattern while the transitions were colocated on the antenna surface.
Ad hoc multi-hop communication enables flexible connectivity but introduces challenges in securely joining the network without direct access to infrastructure. In such environments, nodes may frequently lose connectivity to an access point (AP) due to mobility or environmental factors, requiring efficient mechanisms to re-establish secure participation without overloading intermediate nodes. Prior work addressed proxy assisted secure bootstrap using proxy nodes (PNs) and client puzzles to throttle request traffic. However, computational throttling is less suitable in modern environments due to increased processing capabilities and the resulting need for larger puzzle parameters to achieve comparable delays, leading to higher computational overhead and limited adaptability. This letter proposes an authorization-based relay admission scheme, in which an AP issues short-lived relay tokens to previously authenticated nodes to control PN-assisted forwarding during re-bootstrap attempts. A PN for wards a request only when a valid token is presented, while authentication and network admission remain AP-terminated. The proposed approach replaces computational throttling with authorization-based control, reducing unnecessary request propagation while preserving the original bootstrap architecture. Furthermore, the proposed scheme enables lightweight and policy-based control of relay usage without imposing additional computa tional burden on legitimate nodes.
This paper presents a comparative evaluation of angle-of-arrival (AoA)-based localization methods using both measured data and simulation results. Several conventional and robust estimators, including least squares (LS), weighted least squares (WLS), weighted linearized least squares (WLLS), two-step error-variance least squares (TELS), and Outlier Sparsity-Promoting Linear Regression (OSPLR), are investigated. While conventional methods provide reasonable performance, they are highly sensitive to outliers caused by measurement errors under severe multipath conditions. Experimental results show that conventional methods achieve comparable accuracy under nominal conditions but suffer severe degradation in the presence of strong AoA outliers. Tofurtherinterpret these observations, measurement-informed Monte Carlo simulations are conducted by incorporating realistic error statistics and controlled outlier patterns. The results confirm that increasing the number of sensors consistently improves localization accuracy and approaches the Cramér-Rao lower bound (CRLB). In contrast to existing approaches, OSPLR demonstrates superior robust ness against severe outliers while maintaining competitive performance under outlier-free conditions. These findings highlight the effectiveness of sparsity-based outlier modeling for practical AoA-based indoor localization in multipath-rich indoor environments.
