Vol. 151
Latest Volume
All Volumes
PIERC 151 [2025] PIERC 150 [2024] PIERC 149 [2024] PIERC 148 [2024] PIERC 147 [2024] PIERC 146 [2024] PIERC 145 [2024] PIERC 144 [2024] PIERC 143 [2024] PIERC 142 [2024] PIERC 141 [2024] PIERC 140 [2024] PIERC 139 [2024] PIERC 138 [2023] PIERC 137 [2023] PIERC 136 [2023] PIERC 135 [2023] PIERC 134 [2023] PIERC 133 [2023] PIERC 132 [2023] PIERC 131 [2023] PIERC 130 [2023] PIERC 129 [2023] PIERC 128 [2023] PIERC 127 [2022] PIERC 126 [2022] PIERC 125 [2022] PIERC 124 [2022] PIERC 123 [2022] PIERC 122 [2022] PIERC 121 [2022] PIERC 120 [2022] PIERC 119 [2022] PIERC 118 [2022] PIERC 117 [2021] PIERC 116 [2021] PIERC 115 [2021] PIERC 114 [2021] PIERC 113 [2021] PIERC 112 [2021] PIERC 111 [2021] PIERC 110 [2021] PIERC 109 [2021] PIERC 108 [2021] PIERC 107 [2021] PIERC 106 [2020] PIERC 105 [2020] PIERC 104 [2020] PIERC 103 [2020] PIERC 102 [2020] PIERC 101 [2020] PIERC 100 [2020] PIERC 99 [2020] PIERC 98 [2020] PIERC 97 [2019] PIERC 96 [2019] PIERC 95 [2019] PIERC 94 [2019] PIERC 93 [2019] PIERC 92 [2019] PIERC 91 [2019] PIERC 90 [2019] PIERC 89 [2019] PIERC 88 [2018] PIERC 87 [2018] PIERC 86 [2018] PIERC 85 [2018] PIERC 84 [2018] PIERC 83 [2018] PIERC 82 [2018] PIERC 81 [2018] PIERC 80 [2018] PIERC 79 [2017] PIERC 78 [2017] PIERC 77 [2017] PIERC 76 [2017] PIERC 75 [2017] PIERC 74 [2017] PIERC 73 [2017] PIERC 72 [2017] PIERC 71 [2017] PIERC 70 [2016] PIERC 69 [2016] PIERC 68 [2016] PIERC 67 [2016] PIERC 66 [2016] PIERC 65 [2016] PIERC 64 [2016] PIERC 63 [2016] PIERC 62 [2016] PIERC 61 [2016] PIERC 60 [2015] PIERC 59 [2015] PIERC 58 [2015] PIERC 57 [2015] PIERC 56 [2015] PIERC 55 [2014] PIERC 54 [2014] PIERC 53 [2014] PIERC 52 [2014] PIERC 51 [2014] PIERC 50 [2014] PIERC 49 [2014] PIERC 48 [2014] PIERC 47 [2014] PIERC 46 [2014] PIERC 45 [2013] PIERC 44 [2013] PIERC 43 [2013] PIERC 42 [2013] PIERC 41 [2013] PIERC 40 [2013] PIERC 39 [2013] PIERC 38 [2013] PIERC 37 [2013] PIERC 36 [2013] PIERC 35 [2013] PIERC 34 [2013] PIERC 33 [2012] PIERC 32 [2012] PIERC 31 [2012] PIERC 30 [2012] PIERC 29 [2012] PIERC 28 [2012] PIERC 27 [2012] PIERC 26 [2012] PIERC 25 [2012] PIERC 24 [2011] PIERC 23 [2011] PIERC 22 [2011] PIERC 21 [2011] PIERC 20 [2011] PIERC 19 [2011] PIERC 18 [2011] PIERC 17 [2010] PIERC 16 [2010] PIERC 15 [2010] PIERC 14 [2010] PIERC 13 [2010] PIERC 12 [2010] PIERC 11 [2009] PIERC 10 [2009] PIERC 9 [2009] PIERC 8 [2009] PIERC 7 [2009] PIERC 6 [2009] PIERC 5 [2008] PIERC 4 [2008] PIERC 3 [2008] PIERC 2 [2008] PIERC 1 [2008]
2024-12-11
PIER C
Vol. 151, 33-43, 2025
download: 17
Design and Analysis of Linear Primary Permanent Magnet Vernier Machines with Different Winding Configurations
Zhijian Ling , Qi Zhang and Meimei Xu
This paper investigates the effects of winding configurations on force density and fault tolerance in linear primary permanent magnet vernier (LPPMV) machines. Firstly, the LPPMV machines with integral slot distributed windings (ISDWs) and fractional slot concentrated windings (FSCWs) are discussed. Due to the high modulation ratio of ISDW machine, it has the potential to achieve higher thrust force capabilities. Then, the operation principle of the LPPMV machines is analyzed from the perspective of air-gap magnetic modulation. Furthermore, it should be noted that the winding configurations of ISDW machine has larger spans, resulting in insufficient fault-tolerance. To solve this limitation, a new modular ISDW LPPMV machine was proposed and optimized. In the modular ISDW LPPMV machine, a 3×3-phase winding configuration is employed. It is demonstrated that modular ISDW LPPMV machines exhibit superior characteristics in both thrust density and fault tolerance. Finally, the experiments are carried out in a linear test bench, verifying the theoretical analysis.
Design and Analysis of Linear Primary Permanent Magnet Vernier Machines with Different Winding Configurations
2024-12-11
PIER C
Vol. 151, 25-31, 2025
download: 11
A Novel Proof-of-Concept AI-Driven Approach for Advanced Electromagnetic Imaging
Ali Ghaffarpour , Tahereh Vasei , Mahindra Ganesh , Reza K. Amineh and Maryam Ravan
This paper introduces an artificial intelligence (AI) methodology designed to enhance the output of two-dimensional (2D) electromagnetic imaging systems, specifically tailored for the imaging of conductive objects utilizing inductive sensors. The core of our imaging system comprises a commercial data acquisition board, alongside custom-made multilayer planar coils developed by conventional printed circuit board technology. By leveraging recent advances in AI and machine learning, our approach significantly improves the resolution and clarity of electromagnetic images. The paper uses a multi-layer perceptron (MLP) classifier to process the raw electromagnetic data captured by the imaging system. These algorithms are trained to recognize patterns and anomalies in electromagnetic field data, which are often indicative of conductive objects. The enhanced imaging capability is demonstrated through a series of experiments that compare the AI-enhanced outputs with the ground truth.
A Novel Proof-of-Concept AI-Driven Approach for Advanced Electromagnetic Imaging
2024-12-11
PIER C
Vol. 151, 13-24, 2025
download: 9
Application of Attention Mechanism-Enhanced BiLSTM-CNN in Power Amplifier Behavioral Modeling and Predistortion
Jingchang Nan , Shize Liu and Jiadong Yu
Power amplifiers in wireless communication systems can introduce nonlinear distortion, degrade signal transmission quality, and increase power consumption. The paper presents a BiLSTM-CNN-based model for modelling power amplifier behaviour to address this issue. The model uses BiLSTM layers to capture temporal information from the signal data and incorporates a multi-head attention mechanism to focus on different temporal features. Additionally, convolutional layers process global features and reduce model parameters through weight sharing. Using this model, a digital pre-distortion (DPD) model is proposed to linearise the power amplifier through an indirect learning approach. The results show that the BiLSTM-CNN model achieves a normalised mean square error (NMSE) of -40.3dB, and the DPD model enhances the adjacent channel power ratio (ACPR) of the communication system by 18dB, demonstrating the model's feasibility. Comparative analysis with other network models indicates that BiLSTM-CNN outperforms traditional methods of fitting performance and convergence speed, showcasing its superiority.
Application of Attention Mechanism-enhanced BiLSTM-CNN in Power Amplifier Behavioral Modeling and Predistortion
2024-12-08
PIER C
Vol. 151, 1-12, 2025
download: 31
AI-Tuned Metantenna Antenna for Fifth Generation & Beyond Communication Applications
Bikash Ranjan Behera and Harikkrishna Paik
For the purpose of fifth-generation and beyond communication applications, broadband circularly polarized (CP) & high gain AI-tuned metantenna operating in the 5 GHz band is presented in this article. So, an linearly polarized (LP) printed monopole antenna is being taken into consideration in the initial stage. To initiate CP from LP, a metallic strip that functions as a dynamic switching mechanism is utilized to short one of the parasitic conducting strips (PCS) with partial ground plane. The objective is to enhance the impedance (IBW) and axial bandwidths (ARBWs) as well as the antenna gain in order to make it a suitable candidate for ambient RF energy harvesting/wireless energy harvesting application. To achieve this, AI-tuned metasurface is placed below the monopole radiator at a height of 0.33λo. With a measured 49.84% IBW, 22.36% ARBW, CP gain > 8 dBic, antenna efficiency > 70%, fabricated on an FR-4 substrate with 1.3λo x 0.9λo x 0.02λo, it is suitable for the technological deployments in a current wireless technology, assuring resilience in networks. To meet the ever-increasing requirements of the current scenario, wireless communication landscape is on a paradigm shift. This transformation is brought by the utilization of metasurfaces offering customized, effective, and typical control of electromagnetic waves keeping with the desired frequency conditions.
AI-tuned Metantenna Antenna for Fifth Generation & Beyond Communication Applications