Baghdad Hadji, A. Aïssa-El-Bey, L. Fergani, M. Djeddou
{"title":"Alternating Hybrid Beamforming Design using GMD Decomposition for mmWave MIMO-OFDM Systems","authors":"Baghdad Hadji, A. Aïssa-El-Bey, L. Fergani, M. Djeddou","doi":"10.1109/ICATEEE57445.2022.10093704","DOIUrl":null,"url":null,"abstract":"Since millimeter wave (mmWave) communications have wideband channels, mmWave signal corruptions increase due to radio-channel frequency selectivity. In this case, the combination of the orthogonal frequency division multiplexing (OFDM) with the mmWave MIMO system is envisioned as a candidate technique to address the degradation of communication. As hybrid analog/digital architecture offers potential energy and spectral efficiency for the mmWave MIMO device. Matrix factorization formulation with singular value decomposition (SVD) is the most used method for designing the hybrid precoder/combiner. However, using SVD decomposition in pre- coding/combining designing requires power allocation schemes due to the different signal-to-noise ratios (SNRs) of different sub- channels. To achieve a high wireless communications capacity, we propose in this work, a manifold optimization-based alternating minimization algorithm using the geometric mean decomposition (GMD) (called MO-AltMin-GMD) to derive unconstrained optimal precoders and combiners from the channel state information (CSI). The principal objective is that the proposed hybrid design avoids any allocation schemes to maintain the hybrid architecture complexity low. According to the obtained numecal results, the proposed hybrid design provides high results compared to existing methods in terms of spectral efficiency.","PeriodicalId":150519,"journal":{"name":"2022 International Conference of Advanced Technology in Electronic and Electrical Engineering (ICATEEE)","volume":"6 5","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference of Advanced Technology in Electronic and Electrical Engineering (ICATEEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICATEEE57445.2022.10093704","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Since millimeter wave (mmWave) communications have wideband channels, mmWave signal corruptions increase due to radio-channel frequency selectivity. In this case, the combination of the orthogonal frequency division multiplexing (OFDM) with the mmWave MIMO system is envisioned as a candidate technique to address the degradation of communication. As hybrid analog/digital architecture offers potential energy and spectral efficiency for the mmWave MIMO device. Matrix factorization formulation with singular value decomposition (SVD) is the most used method for designing the hybrid precoder/combiner. However, using SVD decomposition in pre- coding/combining designing requires power allocation schemes due to the different signal-to-noise ratios (SNRs) of different sub- channels. To achieve a high wireless communications capacity, we propose in this work, a manifold optimization-based alternating minimization algorithm using the geometric mean decomposition (GMD) (called MO-AltMin-GMD) to derive unconstrained optimal precoders and combiners from the channel state information (CSI). The principal objective is that the proposed hybrid design avoids any allocation schemes to maintain the hybrid architecture complexity low. According to the obtained numecal results, the proposed hybrid design provides high results compared to existing methods in terms of spectral efficiency.