Pub Date : 2023-01-01DOI: 10.1587/transcom.2022ebp3101
Ryusuke Igarashi, Ryo Nakagawa, Daniel Okochi, Yukio Ogawa, M. Dong, K. Ota
{"title":"Field Evaluation of Adaptive Path Selection for Platoon-Based V2N Communications","authors":"Ryusuke Igarashi, Ryo Nakagawa, Daniel Okochi, Yukio Ogawa, M. Dong, K. Ota","doi":"10.1587/transcom.2022ebp3101","DOIUrl":"https://doi.org/10.1587/transcom.2022ebp3101","url":null,"abstract":"","PeriodicalId":48825,"journal":{"name":"IEICE Transactions on Communications","volume":"20 1","pages":"448-458"},"PeriodicalIF":0.7,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75362053","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Analysis of Field Uniformity in a TEM Cell Based on Finite Difference Method and Measured Field Strength","authors":"Yixing Gu, Zhongyuan Zhou, Yunfen Chang, Mingjie Sheng, Qi Zhou","doi":"10.1587/transcom.2022ebp3138","DOIUrl":"https://doi.org/10.1587/transcom.2022ebp3138","url":null,"abstract":"","PeriodicalId":48825,"journal":{"name":"IEICE Transactions on Communications","volume":"15 1","pages":"509-517"},"PeriodicalIF":0.7,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78818611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1587/transcom.2022ebt0003
Kundjanasith Thonglek, Koheix Ichikawa, Keichi Takahashi, Chawanat Nakasan, K. Yuasa, T. Babasaki, Hajimu Iida
SUMMARY Solar power is the most widely used renewable energy source, which reduces pollution consequences from using conventional fossil fuels. However, supplying stable power from solar power generation remains challenging because it is difficult to forecast power generation. Accurate prediction of solar power generation would allow effective control of the amount of electricity stored in batteries, leading in a stable supply of electricity. Although the number of power plants is increasing, building a solar power prediction model for a newly constructed power plant usually requires collecting a new training dataset for the new power plant, which takes time to collect a sufficient amount of data. This paper aims to develop a highly accurate solar power prediction model for multiple power plants available for both new and existing power plants. The proposed method trains the model on existing multiple power plants to generate a general prediction model, and then uses it for a new power plant while waiting for the data to be collected. In addition, the proposed method tunes the general prediction model on the newly collected dataset and improves the accuracy for the new power plant. We evaluated the proposed method on 55 power plants in Japan with the dataset collected for two and a half years. As a result, the pre-trained models of our proposed method significantly reduces theaverageRMSEofthebaselinemethodby73.19%. Thisindicatesthatthe modelcangeneralizeovermultiplepowerplants, andtrainingusingdatasets from other power plants is effective in reducing the RMSE. Fine-tuning the pre-trained model further reduces the RMSE by 8.12%.
{"title":"Toward Predictive Modeling of Solar Power Generation for Multiple Power Plants","authors":"Kundjanasith Thonglek, Koheix Ichikawa, Keichi Takahashi, Chawanat Nakasan, K. Yuasa, T. Babasaki, Hajimu Iida","doi":"10.1587/transcom.2022ebt0003","DOIUrl":"https://doi.org/10.1587/transcom.2022ebt0003","url":null,"abstract":"SUMMARY Solar power is the most widely used renewable energy source, which reduces pollution consequences from using conventional fossil fuels. However, supplying stable power from solar power generation remains challenging because it is difficult to forecast power generation. Accurate prediction of solar power generation would allow effective control of the amount of electricity stored in batteries, leading in a stable supply of electricity. Although the number of power plants is increasing, building a solar power prediction model for a newly constructed power plant usually requires collecting a new training dataset for the new power plant, which takes time to collect a sufficient amount of data. This paper aims to develop a highly accurate solar power prediction model for multiple power plants available for both new and existing power plants. The proposed method trains the model on existing multiple power plants to generate a general prediction model, and then uses it for a new power plant while waiting for the data to be collected. In addition, the proposed method tunes the general prediction model on the newly collected dataset and improves the accuracy for the new power plant. We evaluated the proposed method on 55 power plants in Japan with the dataset collected for two and a half years. As a result, the pre-trained models of our proposed method significantly reduces theaverageRMSEofthebaselinemethodby73.19%. Thisindicatesthatthe modelcangeneralizeovermultiplepowerplants, andtrainingusingdatasets from other power plants is effective in reducing the RMSE. Fine-tuning the pre-trained model further reduces the RMSE by 8.12%.","PeriodicalId":48825,"journal":{"name":"IEICE Transactions on Communications","volume":"23 1","pages":"547-556"},"PeriodicalIF":0.7,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85311129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1587/transcom.2022ebp3106
Takafumi Tanaka, H. Hasegawa
{"title":"Policy-Based Grooming, Route, Spectrum, and Operational Mode Planning in Dynamic Multilayer Networks","authors":"Takafumi Tanaka, H. Hasegawa","doi":"10.1587/transcom.2022ebp3106","DOIUrl":"https://doi.org/10.1587/transcom.2022ebp3106","url":null,"abstract":"","PeriodicalId":48825,"journal":{"name":"IEICE Transactions on Communications","volume":"16 1","pages":"489-499"},"PeriodicalIF":0.7,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76881630","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1587/transcom.2022ebp3098
Keisuke Asano, Mamoru Okumura, T. Abe, E. Okamoto, Tetsuya Yamamoto
SUMMARY In recent years, physical layer security (PLS), which is based on information theory and whose strength does not depend on the eavesdropper’s computing capability, has attracted much attention. We have proposed a chaos modulation method as one PLS method that o ff ers channel coding gain. One alternative is based on polar codes. They are robust error-correcting codes, have a nested structure in the encoder, and the application of this mechanism to PLS encryption (PLS-polar) has been actively studied. However, most conventional studies assume the application of conventional linear modulation such as BPSK, do not use encryption modulation, and the channel coding gain in the modulation is not achieved. In this paper, we propose a PLS-polar method that can realize high-quality transmission and encryption of a modulated signal by applying chaos modulation to a polar-coding system. Numerical results show that the proposed method improves the performance compared to the conventional PLS-polar method by 0.7dB at a block error rate of 10 − 5 . In addition, we show that the proposed method is superior to conventional chaos modulation concatenated with low-density parity-check codes, indicating that the polar code is more suitable for chaos modulation. Finally, it is demonstrated that the proposed method is secure in terms of information theoretical and computational security.
{"title":"High-Quality Secure Wireless Transmission Scheme Using Polar Codes and Radio-Wave Encrypted Modulation","authors":"Keisuke Asano, Mamoru Okumura, T. Abe, E. Okamoto, Tetsuya Yamamoto","doi":"10.1587/transcom.2022ebp3098","DOIUrl":"https://doi.org/10.1587/transcom.2022ebp3098","url":null,"abstract":"SUMMARY In recent years, physical layer security (PLS), which is based on information theory and whose strength does not depend on the eavesdropper’s computing capability, has attracted much attention. We have proposed a chaos modulation method as one PLS method that o ff ers channel coding gain. One alternative is based on polar codes. They are robust error-correcting codes, have a nested structure in the encoder, and the application of this mechanism to PLS encryption (PLS-polar) has been actively studied. However, most conventional studies assume the application of conventional linear modulation such as BPSK, do not use encryption modulation, and the channel coding gain in the modulation is not achieved. In this paper, we propose a PLS-polar method that can realize high-quality transmission and encryption of a modulated signal by applying chaos modulation to a polar-coding system. Numerical results show that the proposed method improves the performance compared to the conventional PLS-polar method by 0.7dB at a block error rate of 10 − 5 . In addition, we show that the proposed method is superior to conventional chaos modulation concatenated with low-density parity-check codes, indicating that the polar code is more suitable for chaos modulation. Finally, it is demonstrated that the proposed method is secure in terms of information theoretical and computational security.","PeriodicalId":48825,"journal":{"name":"IEICE Transactions on Communications","volume":"37 1","pages":"374-383"},"PeriodicalIF":0.7,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78412727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1587/transcom.2023ebp3060
Shota AKIYOSHI, Yuzo TAENAKA, Kazuya TSUKAMOTO, Myung LEE
Cross-domain data fusion is becoming a key driver in the growth of numerous and diverse applications in the Internet of Things (IoT) era. We have proposed the concept of a new information platform, Geo-Centric Information Platform (GCIP), that enables IoT data fusion based on geolocation, i.e., produces spatio-temporal content (STC), and then provides the STC to users. In this environment, users cannot know in advance ”when,” ”where,” or ”what type” of STC is being generated because the type and timing of STC generation vary dynamically with the diversity of IoT data generated in each geographical area. This makes it difficult to directly search for a specific STC requested by the user using the content identifier (domain name of URI or content name). To solve this problem, a new content discovery method that does not directly specify content identifiers is needed while taking into account (1) spatial and (2) temporal constraints. In our previous study, we proposed a content discovery method that considers only spatial constraints and did not consider temporal constraints. This paper proposes a new content discovery method that matches user requests with content metadata (topic) characteristics while taking into account spatial and temporal constraints. Simulation results show that the proposed method successfully discovers appropriate STC in response to a user request.
跨域数据融合正在成为物联网(IoT)时代众多不同应用增长的关键驱动力。我们提出了一种新的信息平台概念——以地理为中心的信息平台(Geo-Centric information platform, GCIP)，它可以实现基于地理位置的物联网数据融合，即产生时空内容(spatial -temporal content, STC)，然后将STC提供给用户。在这种环境下，用户无法提前知道“何时”、“何地”或“何种类型”的STC正在生成，因为STC生成的类型和时间会随着各个地理区域物联网数据的多样性而动态变化。这使得使用内容标识符(URI的域名或内容名)直接搜索用户请求的特定STC变得困难。为了解决这个问题，需要一种新的内容发现方法，它不直接指定内容标识符，同时考虑到(1)空间和(2)时间约束。在我们之前的研究中，我们提出了一种只考虑空间约束而不考虑时间约束的内容发现方法。本文提出了一种新的内容发现方法，在考虑空间和时间约束的情况下，将用户请求与内容元数据(主题)特征相匹配。仿真结果表明，该方法能够根据用户请求成功发现合适的STC。
{"title":"Content search method utilizing the metadata matching characteristics of both Spatio-temporal content and user request in the IoT era","authors":"Shota AKIYOSHI, Yuzo TAENAKA, Kazuya TSUKAMOTO, Myung LEE","doi":"10.1587/transcom.2023ebp3060","DOIUrl":"https://doi.org/10.1587/transcom.2023ebp3060","url":null,"abstract":"Cross-domain data fusion is becoming a key driver in the growth of numerous and diverse applications in the Internet of Things (IoT) era. We have proposed the concept of a new information platform, Geo-Centric Information Platform (GCIP), that enables IoT data fusion based on geolocation, i.e., produces spatio-temporal content (STC), and then provides the STC to users. In this environment, users cannot know in advance ”when,” ”where,” or ”what type” of STC is being generated because the type and timing of STC generation vary dynamically with the diversity of IoT data generated in each geographical area. This makes it difficult to directly search for a specific STC requested by the user using the content identifier (domain name of URI or content name). To solve this problem, a new content discovery method that does not directly specify content identifiers is needed while taking into account (1) spatial and (2) temporal constraints. In our previous study, we proposed a content discovery method that considers only spatial constraints and did not consider temporal constraints. This paper proposes a new content discovery method that matches user requests with content metadata (topic) characteristics while taking into account spatial and temporal constraints. Simulation results show that the proposed method successfully discovers appropriate STC in response to a user request.","PeriodicalId":48825,"journal":{"name":"IEICE Transactions on Communications","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135953568","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We have developed an all-optical fiber link antenna measurement system for a millimeter wave 5th generation mobile communication frequency band around 28 GHz. Our developed system consists of an optical fiber link an electrical signal transmission system, an antenna-coupled-electrode electric-field (EO) sensor system for 28 GHz-band as an electrical signal receiving system, and a 6-axis vertically articulated robot with an arm length of 1 m. Our developed optical fiber link electrical signal transmission system can transmit the electrical signal of more than 40 GHz with more than -30 dBm output level. Our developed EO sensor can receive the electrical signal from 27 GHz to 30 GHz. In addition, we have estimated a far field antenna factor of the EO sensor system for the 28 GHz-band using an amplitude center modified antenna factor estimation equation. The estimated far field antenna factor of the sensor system is 83.2 dB/m at 28 GHz.
{"title":"Antennas Measurement for Millimeter Wave 5G Wireless Applications using Radio over Fiber Technologies","authors":"Satoru Kurokawa, Michitaka Ameya, Yui Otagaki, Hiroshi Murata, Masatoshi Onizawa, Masahiro Sato, Masanobu Hirose","doi":"10.1587/transcom.2023cei0001","DOIUrl":"https://doi.org/10.1587/transcom.2023cei0001","url":null,"abstract":"We have developed an all-optical fiber link antenna measurement system for a millimeter wave 5th generation mobile communication frequency band around 28 GHz. Our developed system consists of an optical fiber link an electrical signal transmission system, an antenna-coupled-electrode electric-field (EO) sensor system for 28 GHz-band as an electrical signal receiving system, and a 6-axis vertically articulated robot with an arm length of 1 m. Our developed optical fiber link electrical signal transmission system can transmit the electrical signal of more than 40 GHz with more than -30 dBm output level. Our developed EO sensor can receive the electrical signal from 27 GHz to 30 GHz. In addition, we have estimated a far field antenna factor of the EO sensor system for the 28 GHz-band using an amplitude center modified antenna factor estimation equation. The estimated far field antenna factor of the sensor system is 83.2 dB/m at 28 GHz.","PeriodicalId":48825,"journal":{"name":"IEICE Transactions on Communications","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135501455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In the beyond 5G and 6G networks, the number of connected devices and their types will greatly increase including not only user devices such as smartphones but also the Internet of Things (IoT). Moreover, Non-terrestrial networks (NTN) introduce dynamic changes in the types of connected devices as base stations or access points are moving objects. Therefore, continuous network capacity design is required to fulfill the network requirements of each device. However, continuous optimization of network capacity design for each device within a short time span becomes difficult because of the heavy calculation amount. We introduce device types as groups of devices whose traffic characteristics resemble and optimize network capacity per device type for efficient network capacity design. This paper proposes a method to classify device types by analyzing only encrypted traffic behavior without using payload and packets of specific protocols. In the first stage, general device types, such as IoT and non-IoT, are classified by analyzing packet header statistics using machine learning. Then, in the second stage, connected devices classified as IoT in the first stage are classified into IoT device types, by analyzing a time series of traffic behavior using deep learning. We demonstrate that the proposed method classifies device types by analyzing traffic datasets and outperforms the existing IoT-only device classification methods in terms of the number of types and the accuracy. In addition, the proposed model performs comparable as a state-of-the-art model of traffic classification, ResNet 1D model. The proposed method is suitable to grasp device types in terms of traffic characteristics toward efficient network capacity design in networks where massive devices for various services are connected and the connected devices continuously change.
{"title":"Device Type Classification based on Two-stage Traffic Behavior Analysis","authors":"Chikako TAKASAKI, Tomohiro KORIKAWA, Kyota HATTORI, Hidenari OHWADA","doi":"10.1587/transcom.2023wwp0004","DOIUrl":"https://doi.org/10.1587/transcom.2023wwp0004","url":null,"abstract":"In the beyond 5G and 6G networks, the number of connected devices and their types will greatly increase including not only user devices such as smartphones but also the Internet of Things (IoT). Moreover, Non-terrestrial networks (NTN) introduce dynamic changes in the types of connected devices as base stations or access points are moving objects. Therefore, continuous network capacity design is required to fulfill the network requirements of each device. However, continuous optimization of network capacity design for each device within a short time span becomes difficult because of the heavy calculation amount. We introduce device types as groups of devices whose traffic characteristics resemble and optimize network capacity per device type for efficient network capacity design. This paper proposes a method to classify device types by analyzing only encrypted traffic behavior without using payload and packets of specific protocols. In the first stage, general device types, such as IoT and non-IoT, are classified by analyzing packet header statistics using machine learning. Then, in the second stage, connected devices classified as IoT in the first stage are classified into IoT device types, by analyzing a time series of traffic behavior using deep learning. We demonstrate that the proposed method classifies device types by analyzing traffic datasets and outperforms the existing IoT-only device classification methods in terms of the number of types and the accuracy. In addition, the proposed model performs comparable as a state-of-the-art model of traffic classification, ResNet 1D model. The proposed method is suitable to grasp device types in terms of traffic characteristics toward efficient network capacity design in networks where massive devices for various services are connected and the connected devices continuously change.","PeriodicalId":48825,"journal":{"name":"IEICE Transactions on Communications","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136374336","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1587/transcom.2022ebn0001
T. Tachibana, Y. Hirota, Keijiro Suzuki, T. Tsuritani, H. Hasegawa
SUMMARY To accelerate research on Beyond 5G (B5G) technologies in Japan, we propose an algorithm that designs mesh-type metropolitan area network (MAN) models based on a priori Japanese regional railway information, because ground-truth communication network information is unavailable. Instead, we use the information of regional railways, which is expected to express the necessary geometric structure of our metropolitan cities while remaining strongly correlated with their population densities and demographic variations. We provide an additional compression algo-rithm for use in reducing a small-scale network model from the original MAN model designed using the proposed algorithm. Two Tokyo MAN models are created, and we provide day and night variants for each while highlighting the number of passengers alighting/boarding at each station and the respective population densities. The validity of the proposed al-gorithm is verified through comparisons with the Japan Photonic Network model and another model designed using the communication network information, which is not ground-truth. Comparison results show that our proposed algorithm is effective for designing MAN models and that our result provides a valid Tokyo MAN model.
{"title":"Metropolitan Area Network Model Design Using Regional Railways Information for Beyond 5G Research","authors":"T. Tachibana, Y. Hirota, Keijiro Suzuki, T. Tsuritani, H. Hasegawa","doi":"10.1587/transcom.2022ebn0001","DOIUrl":"https://doi.org/10.1587/transcom.2022ebn0001","url":null,"abstract":"SUMMARY To accelerate research on Beyond 5G (B5G) technologies in Japan, we propose an algorithm that designs mesh-type metropolitan area network (MAN) models based on a priori Japanese regional railway information, because ground-truth communication network information is unavailable. Instead, we use the information of regional railways, which is expected to express the necessary geometric structure of our metropolitan cities while remaining strongly correlated with their population densities and demographic variations. We provide an additional compression algo-rithm for use in reducing a small-scale network model from the original MAN model designed using the proposed algorithm. Two Tokyo MAN models are created, and we provide day and night variants for each while highlighting the number of passengers alighting/boarding at each station and the respective population densities. The validity of the proposed al-gorithm is verified through comparisons with the Japan Photonic Network model and another model designed using the communication network information, which is not ground-truth. Comparison results show that our proposed algorithm is effective for designing MAN models and that our result provides a valid Tokyo MAN model.","PeriodicalId":48825,"journal":{"name":"IEICE Transactions on Communications","volume":"11 1","pages":"296-306"},"PeriodicalIF":0.7,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84332894","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1587/transcom.2022ebp3051
S. Denno, Koki Kashihara, Yafei Hou
SUMMARY This paper proposes a novel approach to low complexity soft input decoding for lattice reduction-aided MIMO receivers. The proposed approach feeds a soft input decoder with soft signals made from hard decision signals generated by using a lattice reduction-aided linear detector. The soft signal is a weighted-sum of some candidate vectors that are near by the hard decision signal coming out from the lattice reduction-aided linear detector. This paper proposes a technique to adjust the weight adapt to the channel for the higher transmission performance. Furthermore, we propose to introduce a coe ffi cient that is used for the weights in order to enhance the transmission performance. The transmission performance is evaluated in a 4 × 4 MIMO channel. When a linear MMSE filter or a serial interference canceller is used as the linear detector, the proposed technique achieves about 1 . 0dB better transmission performance at the BER of 10 − 5 than the decoder fed with the hard decision signals. In addition, the low computational complexity of the proposed technique is quantitatively evaluated.
{"title":"Superposition Signal Input Decoding for Lattice Reduction-Aided MIMO Receivers","authors":"S. Denno, Koki Kashihara, Yafei Hou","doi":"10.1587/transcom.2022ebp3051","DOIUrl":"https://doi.org/10.1587/transcom.2022ebp3051","url":null,"abstract":"SUMMARY This paper proposes a novel approach to low complexity soft input decoding for lattice reduction-aided MIMO receivers. The proposed approach feeds a soft input decoder with soft signals made from hard decision signals generated by using a lattice reduction-aided linear detector. The soft signal is a weighted-sum of some candidate vectors that are near by the hard decision signal coming out from the lattice reduction-aided linear detector. This paper proposes a technique to adjust the weight adapt to the channel for the higher transmission performance. Furthermore, we propose to introduce a coe ffi cient that is used for the weights in order to enhance the transmission performance. The transmission performance is evaluated in a 4 × 4 MIMO channel. When a linear MMSE filter or a serial interference canceller is used as the linear detector, the proposed technique achieves about 1 . 0dB better transmission performance at the BER of 10 − 5 than the decoder fed with the hard decision signals. In addition, the low computational complexity of the proposed technique is quantitatively evaluated.","PeriodicalId":48825,"journal":{"name":"IEICE Transactions on Communications","volume":"55 1","pages":"184-192"},"PeriodicalIF":0.7,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76276479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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