{"title":"IEEE Microwave and Wireless Technology Letters Information for Authors","authors":"","doi":"10.1109/LMWT.2025.3582102","DOIUrl":"https://doi.org/10.1109/LMWT.2025.3582102","url":null,"abstract":"","PeriodicalId":73297,"journal":{"name":"IEEE microwave and wireless technology letters","volume":"35 7","pages":"C3-C3"},"PeriodicalIF":0.0,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11073538","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144581593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"IEEE Microwave and Wireless Technology Letters Information for Authors","authors":"","doi":"10.1109/LMWT.2025.3576687","DOIUrl":"https://doi.org/10.1109/LMWT.2025.3576687","url":null,"abstract":"","PeriodicalId":73297,"journal":{"name":"IEEE microwave and wireless technology letters","volume":"35 6","pages":"C3-C3"},"PeriodicalIF":0.0,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11036842","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144299217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"IEEE Microwave and Wireless Technology Letters Information for Authors","authors":"","doi":"10.1109/LMWT.2025.3576706","DOIUrl":"https://doi.org/10.1109/LMWT.2025.3576706","url":null,"abstract":"","PeriodicalId":73297,"journal":{"name":"IEEE microwave and wireless technology letters","volume":"35 6","pages":"C3-C3"},"PeriodicalIF":0.0,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11036846","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144299069","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"150 GHz-Band Compact Phased-Array AiP Module for XR Applications Toward 6G","authors":"Yohei Morishita;Ken Takahashi;Ryosuke Hasaba;Akihiro Egami;Tomoki Abe;Masatoshi Suzuki;Tomohiro Murata;Yoichi Nakagawa;Yudai Yamazaki;Sunghwan Park;Takaya Uchino;Chenxin Liu;Jun Sakamaki;Takashi Tomura;Hiroyuki Sakai;Hiroshi Taneda;Kei Murayama;Yoko Nakabayashi;Shinsuke Hara;Issei Watanabe;Akifumi Kasamatsu;Kenichi Okada;Koji Takinami","doi":"10.1109/LMWT.2025.3565729","DOIUrl":"https://doi.org/10.1109/LMWT.2025.3565729","url":null,"abstract":"To realize the practical application of sub-THz band wireless communication toward 6G, it is necessary to develop AiP modules with compact size and low cost. This letter discusses the design of a miniaturized AiP module for high-speed wireless communication targeting extended reality (XR) applications in medical operating rooms as an example of 6G use cases. By integrating waveguide antenna array along with a compact divider/combiner within the multilayer substrates, the module achieves a small form factor of <inline-formula> <tex-math>$8.42times 20.0times 1.37$ </tex-math></inline-formula> mm while integrating radio frequency integrated circuit (RFIC) and peripheral surface mount components. The measurement shows a data rate of 40 Gb/s at a 3 m distance in the 150 GHz band with an excellent transmission energy efficiency of 35.7 pJ/bit.","PeriodicalId":73297,"journal":{"name":"IEEE microwave and wireless technology letters","volume":"35 6","pages":"920-923"},"PeriodicalIF":0.0,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11023526","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144299278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Knowledge-Based Extrapolation of Neural Network Model for Transistor Modeling","authors":"Jinyuan Cui;Lei Zhang;Humayun Kabir;Zhihao Zhao;Rick Sweeney;Qi-Jun Zhang","doi":"10.1109/LMWT.2025.3562538","DOIUrl":"https://doi.org/10.1109/LMWT.2025.3562538","url":null,"abstract":"Artificial neural network (ANN) is a useful technique for active device modeling. However, it shows limitations in the extrapolation region. To address this issue, we propose a novel knowledge-based neural network (KBNN) method. The KBNN technique consists of three submodels and their transition mechanisms. One submodel is a pure ANN model which is used for training data region. Two additional submodels are used for the extrapolation region. The proposed method ensures that the output and derivatives of ANN and extrapolation models match at the boundary of the measurement data. This keeps the KBNN model smooth and consistent, making it suitable for transistor design over a broad range. The precision, smoothness, and consistency of the proposed method are verified with a <inline-formula> <tex-math>$2times 250~mu $ </tex-math></inline-formula>m GaN HEMT device modeling. The results show that the KBNN model provides physically reasonable predictions over a wide extrapolation region.","PeriodicalId":73297,"journal":{"name":"IEEE microwave and wireless technology letters","volume":"35 6","pages":"812-815"},"PeriodicalIF":0.0,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144299315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Arne Fischer-Bühner;Lauri Anttila;Alberto Brihuega;Manil Dev Gomony;Mikko Valkama
{"title":"Predistortion of GaN Power Amplifier Transient Responses in Time-Division Duplex Using Machine Learning","authors":"Arne Fischer-Bühner;Lauri Anttila;Alberto Brihuega;Manil Dev Gomony;Mikko Valkama","doi":"10.1109/LMWT.2025.3561227","DOIUrl":"https://doi.org/10.1109/LMWT.2025.3561227","url":null,"abstract":"The extensive use of time-division duplexing in 5G and 6G poses a challenge to the linear operation of the power amplifiers (PAs) in radio base stations. Particularly with gallium nitride (GaN) technology, the PAs can produce strong transient behavior when resuming from an idle state, which degrades the first few transmitted symbols. This article proposes a novel machine learning technique to model and compensate the PA gain transient, based on a lightweight, low-rate recurrent model. Our RF measurements at 3.6 GHz examine the joint application of transient compensation and predistortion of short-term effects and show a successful mitigation of both types of distortion.","PeriodicalId":73297,"journal":{"name":"IEEE microwave and wireless technology letters","volume":"35 6","pages":"924-927"},"PeriodicalIF":0.0,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10980633","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144299155","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Patrick Boe;Dominik Brouczek;Lisa Mikiss;Marc Hofbauer;Daniel Miek;Michael Höft
{"title":"Compact Ku-Band Diplexer With Additive Manufactured Multimaterial Dielectric Resonator Insets","authors":"Patrick Boe;Dominik Brouczek;Lisa Mikiss;Marc Hofbauer;Daniel Miek;Michael Höft","doi":"10.1109/LMWT.2025.3562691","DOIUrl":"https://doi.org/10.1109/LMWT.2025.3562691","url":null,"abstract":"This letter presents the design and electrical measurement results of a novel compact diplexer design in Ku-band. The proposed diplexer is based on <inline-formula> <tex-math>$text {TM}_{01delta }$ </tex-math></inline-formula> mode dielectric resonators (DRs). A fourth-order filter with one triplet section for each channel is used. An additively manufactured inset is used for each filter, which contains the resonators and the required support structure and is printed from two materials in one piece. The chosen arrangement enables a compact design and simple assembly. To validate the concept, the design, fabrication, and measurement of the fourth-order dielectric diplexer are presented.","PeriodicalId":73297,"journal":{"name":"IEEE microwave and wireless technology letters","volume":"35 6","pages":"800-803"},"PeriodicalIF":0.0,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144299262","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}