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Radioengineering

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Proceedings of Czech and Slovak Technical Universities

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September 2026, Volume 35, Number 3 [DOI: 10.13164/re.2026-3]

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M. Khajavi, E. Farshidi, M. Soroosh, S. Ajabi [references] [full-text] [DOI: 10.13164/re.2026.0335] [Download Citations]
Design and Analysis of Novel Bandpass Filters with Adjustable Center Frequency and Bandwidth

This paper presents a novel design of microstrip bandpass filters combining stepped-impedance resonators (SIR). Initially, a stepped- impedance resonator is considered as the basic structure, and then the basic design is progressively modified and improved. These enhancements include adding resonators to the basic structure, modifying their dimensions, fundamentally changing their arrangement and connections, and creating air gaps between resonators. These modifications result in significant changes in the frequency response characteristics, shifting the center frequency of the basic model to the X-band. Subsequent steps focus on improving filter parameters such as bandwidth, insertion loss, and return loss, ultimately leading to a dual-band bandpass filter. The single-band filter proposed in this paper has a center frequency of 9 GHz, a bandwidth of 1.83 GHz, an insertion loss of 1.7 dB, and a return loss of 54.6 dB. The dual-band bandpass filter features center frequencies of 7.4 GHz and 10.7 GHz, with bandwidths of 110 MHz and 530 MHz, insertion losses of 1.4 dB and 2.3 dB, and return losses of 22.4 dB and 31.1 dB, respectively. The designed filters are characterized by compact size, high integration, low insertion and return losses, and wide bandwidth. A good agreement is observed between the measured results of the fabricated sample and the simulation results.

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Keywords: Bandpass filter, microstrip, SIR resonator, air gap, insertion loss, return loss

Y. Zhang, H. M. Liu, Y. Meng, Z. B. Wang [references] [full-text] [DOI: 10.13164/re.2026.0349] [Download Citations]
A Wideband 1×3 Filtering Beamforming Network Featuring Input-Reflectionless and Extended Phase Reconfigurability

In the paper, a wideband 1×3 filtering beamforming network (BFN) with extended phase reconfigurability and input-reflectionless feature is presented for the first time by employing three-way reflectionless power divider, switched 0°/180° phase shifter (PS), and multiway polyphase filtering differential phase shifter (D-PS). The three-way power divider and D-PS provide wideband filtering with high frequency selectivity while ensuring an input-reflectionless characteristic across the entire frequency range. Six distinct output phase differences (PDs) can be realized using only three groups of D-PSs in combination with the switched 0°/180° PSs, enabling extended beam directions without additional phase-shifting components added. The designs of the three-way power divider and D-PS are presented, with the D-PS accompanied by derivation of equations and parametric analysis for clarification. To verify, a prototype is fabricated and measured. Measurements verify six differential PDs of –120°, –90°, –30°, 60°, 90°, and 150°. For all six states, the prototype achieves a 3-dB passband bandwidth exceeding 70% with |S11| below -10dB across the entire frequency range. In addition, the fractional bandwidth corresponding to a ±7° PD error reaches 40%.

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Keywords: Beamforming network, filtering, input reflectionless, phase reconfigurability, multiway polyphase phase shifter.

X. Fan, Q. Yao, J. Chen [references] [full-text] [DOI: 10.13164/re.2026.0358] [Download Citations]
A New Variable Step-size LMS Algorithm and Its Analysis

The LMS (least mean square) algorithm is an adaptive filtering algorithm widely used in the fields of signal processing and system identification. To avoid the compromise between the convergence speed and the steady-state error for fixed step-size LMS algorithm, a variable step-size LMS algorithm (named ELVSLMS algorithm) based on error autocorrelation estimation and logarithmic function is proposed and analyzed in this paper. In the proposed algorithm, the variable step-size filter is replaced by a filter whose step-size function is a modified function based on error autocorrelation estimation and logarithmic function. Thus, logarithmic nonlinear relationship between the step-size and the error autocorrelation is constructed. Therefore, the slow convergence speed and the weak anti-jamming ability of fixed step-size LMS are conquered. Simulation results show that the proposed ELVSLMS algorithm, compared to LMS algorithm, SVSLMS algorithm (whose step-size adjustment function is based on sigmoid function), TLVSLMS algorithm (whose step-size adjustment function is based on versoria function) and HSVSLMS algorithm (whose step-size adjustment function is based on hyperbolic secant function), not only has superior capability of tracking in the presence of noise and in a stable and even non-stable environment, but also can maintain a better convergence and smaller steady-state error.

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Keywords: Least mean square (LMS) filter, error autocorrelation estimation, logarithmic function, performance analysis

J. W. Liu [references] [full-text] [DOI: 10.13164/re.2026.0365] [Download Citations]
3D Radiation Pattern Reconstruction from Reduced Far-Field Sampling via Iterative Spectral Interpolation

This paper presents a method for reconstructing the three-dimensional antenna radiation pattern from reduced sampled far-field measurements, thereby reducing the need for extensive mechanical probe scans. The sampling density is selected according to planar near-field measurement principles, enabling an initial plane-wave representation of the radiation field. An iterative interpolation procedure in the spectral domain is then used to recover the missing angular data while accounting for practical measurement resolution limits. The complete source code written in Julia programming language for the reconstruction algorithm is publicly available to support reproducibility and future research.

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Keywords: Antenna radiation, reconstruction algorithm, far-field pattern measurement, near-to-far field transformation.

A. Tatovic, M. Milosevic, D. Damnjanovic [references] [full-text] [DOI: 10.13164/re.2026.0375] [Download Citations]
Propagation-Aware Link Budget and Availability Analysis of a 15 GHz TETRA Radio Relay Link in Mountainous and Tunnel Environments

Reliable design of radio relay links in complex propagation environments remains a significant challenge for mission-critical communication systems. This paper presents a propagation-aware link budget methodology that integrates terrain morphology, Fresnel zone clearance, atmospheric attenuation (including gaseous absorption and precipitation), and multipath propagation into a unified analytical framework in accordance with ITU-R recommendations. The main contribution lies in the systematic integration of multiple propagation mechanisms into a unified procedure for link availability estimation and propagation-aware radio-relay link assessment. A representative 15 GHz radio relay link between the Laz tunnel and the Ovcar site, designed for a capacity of 100 Mb/s within a TETRA system, is used as a case study for verification. Analytical calculations of received signal power, fade margin, and link availability are supported by simulation-based verification using Radio Mobile. Good agreement between analytical and simulation-based predictions was obtained, with a received signal level difference below 2 dB. Multipath propagation is identified as the dominant degradation mechanism, while rain attenuation has a secondary impact. The achieved link availability exceeds 99.99%, demonstrates practical applicability for the considered case study.

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Keywords: Radio relay link design, propagation-aware modeling, link budget analysis, multipath fading, TETRA communication systems

X. Rui, R. Chen, X. Zhao, J. Yang, J. Chen [references] [full-text] [DOI: 10.13164/re.2026.0392] [Download Citations]
Lightweight LLM-based End-to-End CSI Prediction for MIMO-OFDM Systems

Accurate channel state information (CSI) is essential for multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems, yet fast time-varying channels pose significant prediction challenges. Traditional approaches fail under high mobility, while deep learning methods rely heavily on large labeled datasets, limiting generalization with scarce training data. Although large language models (LLMs) show promise, their massive parameter count hinders deployment on resource-constrained edge devices. This paper proposes a lightweight, end-to-end CSI prediction framework built upon a general LLM. A time-frequency dual-domain feature extraction module captures subcarrier correlations and temporal dynamics from historical CSI, overcoming single-domain limitations. The end-to-end design maps historical CSI directly to future states, avoiding error propagation inherent in explicit channel estimation. Parameter efficiency is achieved through low-rank adaptation (LoRA) combined with knowledge distillation from a pre-trained LLM, enabling effective few-shot learning at low computational cost. Simulations demonstrate that the proposed scheme delivers robust prediction accuracy across diverse mobility scenar-ios, maintains strong performance under limited training data, and exhibits zero-shot cross-scenario generalization, significantly outperforming both conventional and deep learning baselines in TDD and FDD modes.

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Keywords: Channel prediction, multiple-input multiple-output (MIMO), orthogonal frequency division multiplexing (OFDM), large language model (LLM), knowledge distillation, low-rank adaptation (LoRA)