Pub Date : 2023-07-04DOI: 10.1109/ICUFN57995.2023.10199866
Junghoon Lee, Seungah Jang, Eunjung Park
This paper designs a FHIR (Fast Healthcare Interoperable Resources) interface to provide a standard clinical data exchange for personal wearable healthcare devices, aiming at taking them as a part of remote medical services. In uploading, the agent converts the series of sensor readings, such as electrocardiogram, to the JSON-based standard format, divides it into several subparts if necessary, finds the references to relevant resources, and submits the request via RESTful API. For download, a Python client specifies the set of search parameters, gets the target resources from the server, converts them to the language-specific data structure, and hands over to the analysis module. Our testbed is implemented, making use of diverse FHIR tools including the FRED resource editor and the HAPI server.
{"title":"Design of a FHIR interface for wearable healthcare devices","authors":"Junghoon Lee, Seungah Jang, Eunjung Park","doi":"10.1109/ICUFN57995.2023.10199866","DOIUrl":"https://doi.org/10.1109/ICUFN57995.2023.10199866","url":null,"abstract":"This paper designs a FHIR (Fast Healthcare Interoperable Resources) interface to provide a standard clinical data exchange for personal wearable healthcare devices, aiming at taking them as a part of remote medical services. In uploading, the agent converts the series of sensor readings, such as electrocardiogram, to the JSON-based standard format, divides it into several subparts if necessary, finds the references to relevant resources, and submits the request via RESTful API. For download, a Python client specifies the set of search parameters, gets the target resources from the server, converts them to the language-specific data structure, and hands over to the analysis module. Our testbed is implemented, making use of diverse FHIR tools including the FRED resource editor and the HAPI server.","PeriodicalId":341881,"journal":{"name":"2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128905460","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}
Pub Date : 2023-07-04DOI: 10.1109/ICUFN57995.2023.10199608
Q. V. Toan, Min Young Kim
Semantic segmentation is a complex topic where they assign each pixel of an image with a corresponding class and demand accuracy at objective boundaries. The method plays a vital role in scene-understanding scenarios. For self-driving applications, the input source includes various types of objects such as trucks, people, or traffic signs. One receptive field is only effective in capturing a short range of sizes. Feature pyramid network (FPN) utilizes different fields of view to extract information from the input. The FPN approach obtains the spatial information from the high-resolution feature map and the semantic information from the lower scales. The final feature representation contains coarse and fine details, but it has some drawbacks. They burden the system with extensive computation and reduce the semantic information. In this paper, we devise an effective multiscale predictions network (MPNet) to address these issues. A multiscale pyramid of predictions effectively processes the prominent characteristics of each feature. A pair of adjacent features is combined together to predict the output separately. A lower-scale feature of each prediction is assigned as the contextual contributor, and the other provides coarser information. The contextual branch is passed through the atrous spatial pyramid pooling to improve performance. The segmentation scores are fused to obtain advantages from all predictions. The model is validated by a series of experiments on open data sets. We have achieved good results 76.5% mIoU at 50 FPS on Cityscapes and 43.9% mIoU on Mapillary Vistas.
{"title":"MPNet: Multiscale predictions based on feature pyramid network for semantic segmentation","authors":"Q. V. Toan, Min Young Kim","doi":"10.1109/ICUFN57995.2023.10199608","DOIUrl":"https://doi.org/10.1109/ICUFN57995.2023.10199608","url":null,"abstract":"Semantic segmentation is a complex topic where they assign each pixel of an image with a corresponding class and demand accuracy at objective boundaries. The method plays a vital role in scene-understanding scenarios. For self-driving applications, the input source includes various types of objects such as trucks, people, or traffic signs. One receptive field is only effective in capturing a short range of sizes. Feature pyramid network (FPN) utilizes different fields of view to extract information from the input. The FPN approach obtains the spatial information from the high-resolution feature map and the semantic information from the lower scales. The final feature representation contains coarse and fine details, but it has some drawbacks. They burden the system with extensive computation and reduce the semantic information. In this paper, we devise an effective multiscale predictions network (MPNet) to address these issues. A multiscale pyramid of predictions effectively processes the prominent characteristics of each feature. A pair of adjacent features is combined together to predict the output separately. A lower-scale feature of each prediction is assigned as the contextual contributor, and the other provides coarser information. The contextual branch is passed through the atrous spatial pyramid pooling to improve performance. The segmentation scores are fused to obtain advantages from all predictions. The model is validated by a series of experiments on open data sets. We have achieved good results 76.5% mIoU at 50 FPS on Cityscapes and 43.9% mIoU on Mapillary Vistas.","PeriodicalId":341881,"journal":{"name":"2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)","volume":"130 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132525119","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}
Pub Date : 2023-07-04DOI: 10.1109/ICUFN57995.2023.10199969
Jinheng Shao, Chao Zhang
In this paper, a real-time visible light communication (VLC) based on blue laser diode is implemented on field programmable gate array (FPGA) platform. To reduce requirements for signal processing speed, we propose a parallel scheme for modulation and demodulation with simple hardware implementation and low performance loss. Finally, we successfully constructed a VLC system prototype with 600 MHz transmission bandwidth and 2.4 Gbps communication rate over 1 m link distance. Actual measurements shows that $10 -^{5}$ magnitude bit error rate (BER) is achieved without forward error correction (FEC), which demonstrates excellent performance in reported single-source VLC system.
{"title":"2.4 Gbps Real-Time Visible Light Communication System Based on Blue Laser Diode","authors":"Jinheng Shao, Chao Zhang","doi":"10.1109/ICUFN57995.2023.10199969","DOIUrl":"https://doi.org/10.1109/ICUFN57995.2023.10199969","url":null,"abstract":"In this paper, a real-time visible light communication (VLC) based on blue laser diode is implemented on field programmable gate array (FPGA) platform. To reduce requirements for signal processing speed, we propose a parallel scheme for modulation and demodulation with simple hardware implementation and low performance loss. Finally, we successfully constructed a VLC system prototype with 600 MHz transmission bandwidth and 2.4 Gbps communication rate over 1 m link distance. Actual measurements shows that $10 -^{5}$ magnitude bit error rate (BER) is achieved without forward error correction (FEC), which demonstrates excellent performance in reported single-source VLC system.","PeriodicalId":341881,"journal":{"name":"2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126832423","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}
Pub Date : 2023-07-04DOI: 10.1109/ICUFN57995.2023.10200998
Geun-Hyeong Kim, Minuk Yang, Geun-Hyeong Kim, Seong-Hwan Eom, Tae-Soo Lee, Seung Park
Although heart failure (HF) diagnosis and treatment techniques have advanced, more than 50% of HF patients are readmitted. Readmission worsens the life quality of patients due to economic and psychological burdens. Therefore, readmission prediction for patients is important to prevent unnecessary readmissions. We used a feature tokenizer transformer (FT-transformer) to predict readmission by embedding all features and analyzing via transformer encoder. Our experiment with 615 HF patients outperformed conventional machine learning models, achieving an area under the curve of 0.7434 within 28 days, 0.7063 within 3 months, and 0.7039 within 6 months. FT-transformer can potentially improve patient outcomes by enabling early interventions to prevent readmissions.
{"title":"Predicting heart failure prognosis using deep learning based on FT-transformer","authors":"Geun-Hyeong Kim, Minuk Yang, Geun-Hyeong Kim, Seong-Hwan Eom, Tae-Soo Lee, Seung Park","doi":"10.1109/ICUFN57995.2023.10200998","DOIUrl":"https://doi.org/10.1109/ICUFN57995.2023.10200998","url":null,"abstract":"Although heart failure (HF) diagnosis and treatment techniques have advanced, more than 50% of HF patients are readmitted. Readmission worsens the life quality of patients due to economic and psychological burdens. Therefore, readmission prediction for patients is important to prevent unnecessary readmissions. We used a feature tokenizer transformer (FT-transformer) to predict readmission by embedding all features and analyzing via transformer encoder. Our experiment with 615 HF patients outperformed conventional machine learning models, achieving an area under the curve of 0.7434 within 28 days, 0.7063 within 3 months, and 0.7039 within 6 months. FT-transformer can potentially improve patient outcomes by enabling early interventions to prevent readmissions.","PeriodicalId":341881,"journal":{"name":"2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124902466","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}
Pub Date : 2023-07-04DOI: 10.1109/ICUFN57995.2023.10200723
Saud Alhajaj Aldossari, Abdullah Aldosary, Kwang-Cheng Chen
Wireless technology has faced technical challenges that have been unresolved or only partially addressed. Issues such as modeling the wireless channel and selecting the optimum signal This paper proposes using Artificial Intelligence (AI) to tackle these concerns. Machine Learning (ML) can estimate wireless channel states based on available data. Regression and classification techniques have been used to improve communication and meet 5G standards. The effectiveness of ML and Deep Learning techniques were compared to achieve the best accuracy. This paper shows how AI can revolutionize the design of 5G-NR and future generations with an accurate prediction of 99.99%.
{"title":"Overcoming Wireless Channel modeling and Relay Signal Selection Via Artificial Intelligence Techniques in the 5G and Beyond","authors":"Saud Alhajaj Aldossari, Abdullah Aldosary, Kwang-Cheng Chen","doi":"10.1109/ICUFN57995.2023.10200723","DOIUrl":"https://doi.org/10.1109/ICUFN57995.2023.10200723","url":null,"abstract":"Wireless technology has faced technical challenges that have been unresolved or only partially addressed. Issues such as modeling the wireless channel and selecting the optimum signal This paper proposes using Artificial Intelligence (AI) to tackle these concerns. Machine Learning (ML) can estimate wireless channel states based on available data. Regression and classification techniques have been used to improve communication and meet 5G standards. The effectiveness of ML and Deep Learning techniques were compared to achieve the best accuracy. This paper shows how AI can revolutionize the design of 5G-NR and future generations with an accurate prediction of 99.99%.","PeriodicalId":341881,"journal":{"name":"2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)","volume":"199 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124929333","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}
Pub Date : 2023-07-04DOI: 10.1109/ICUFN57995.2023.10200399
Chaeyeon Cha, Hyunggon Park
With the increasing development of the Internet of Things (IoT), there is a growing need for efficient resource allocation to the many devices in the IoT system. This need is particularly acute in the case of time-sensitive applications, where fast resource allocation is essential. However, the resource allocation based on the Nash bargaining solution (NBS) necessitates exponentially increasing computational complexity for user dynamic systems. We propose an approach that makes groups based on the requested services and predicts a disagreement point whenever the group size changes, with the aim of reducing the computational complexity to find the NBS. Through simulation results, we demonstrate that our proposed approach outperforms the existing method in terms of execution time to find the NBS, maintaining the optimality in finding NBS.
{"title":"Service-Based Optimal Group Resource Allocation Strategy","authors":"Chaeyeon Cha, Hyunggon Park","doi":"10.1109/ICUFN57995.2023.10200399","DOIUrl":"https://doi.org/10.1109/ICUFN57995.2023.10200399","url":null,"abstract":"With the increasing development of the Internet of Things (IoT), there is a growing need for efficient resource allocation to the many devices in the IoT system. This need is particularly acute in the case of time-sensitive applications, where fast resource allocation is essential. However, the resource allocation based on the Nash bargaining solution (NBS) necessitates exponentially increasing computational complexity for user dynamic systems. We propose an approach that makes groups based on the requested services and predicts a disagreement point whenever the group size changes, with the aim of reducing the computational complexity to find the NBS. Through simulation results, we demonstrate that our proposed approach outperforms the existing method in terms of execution time to find the NBS, maintaining the optimality in finding NBS.","PeriodicalId":341881,"journal":{"name":"2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127724335","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}
Pub Date : 2023-07-04DOI: 10.1109/ICUFN57995.2023.10200250
P. Srivastav, Hoon Lee
Millimeter wave (mmWave) communication techniques have been regarded as promising solutions for wireless communication networks. However, short wavelength of mmWave signals poses fundamental challenges in estimating wireless channels. This paper tackles the channel estimation problems for frequency selective mmWave imposed on a multiple-input and multiple-output (MIMO) systems. In particular, we leverage the low-rank and sparse properties of mmWave channel matrices. The alternating direction method of multipliers (ADMM) with a relaxation parameter in a symmetrical order is employed. The numerical results exhibit the superiority of proposed methodology in terms of mean-squared-error and spectral efficiency.
{"title":"ADMM-Based Channel Estimation Methods for Millimeter Wave MIMO System","authors":"P. Srivastav, Hoon Lee","doi":"10.1109/ICUFN57995.2023.10200250","DOIUrl":"https://doi.org/10.1109/ICUFN57995.2023.10200250","url":null,"abstract":"Millimeter wave (mmWave) communication techniques have been regarded as promising solutions for wireless communication networks. However, short wavelength of mmWave signals poses fundamental challenges in estimating wireless channels. This paper tackles the channel estimation problems for frequency selective mmWave imposed on a multiple-input and multiple-output (MIMO) systems. In particular, we leverage the low-rank and sparse properties of mmWave channel matrices. The alternating direction method of multipliers (ADMM) with a relaxation parameter in a symmetrical order is employed. The numerical results exhibit the superiority of proposed methodology in terms of mean-squared-error and spectral efficiency.","PeriodicalId":341881,"journal":{"name":"2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132278501","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}
Pub Date : 2023-07-04DOI: 10.1109/ICUFN57995.2023.10200804
F. Tseng, Tsang-Yi Wang, Chun-Tao Lin, Chun-Cheng Su
The paper studies the estimation of phase noise (PHN) in a full-duplex (FD) orthogonal frequency division multiplexing (OFDM) system. Unlike the conventional half-duplex OFDM system, the receiver faces the challenge of estimating the PHN of the intended signals and self-interference (SI). To address this issue, the PHN estimation problem is transformed into a sparse signal detection problem, which can be solved using compressive sensing techniques. However, the performance of these techniques is limited by linear approximation, improper prior information, or improper structure of the sensing matrix. To overcome these limitations, the extended Kalman filter (EKF) is introduced for PHN estimation. The EKF utilizes the maximum a posteriori probability (MAP) criterion with an approximated linear observation model. Furthermore, a novel MAP estimator is developed that employs the original nonlinear observations. Numerical results validate the effectiveness of the proposed estimators and demonstrate that the proposed MAP estimator outperforms existing compressive sensing approaches due to the utilization of accurate posterior distribution.
{"title":"Phase Noise Estimation in Full-Duplex Orthogonal Frequency Division Multiplexing Systems","authors":"F. Tseng, Tsang-Yi Wang, Chun-Tao Lin, Chun-Cheng Su","doi":"10.1109/ICUFN57995.2023.10200804","DOIUrl":"https://doi.org/10.1109/ICUFN57995.2023.10200804","url":null,"abstract":"The paper studies the estimation of phase noise (PHN) in a full-duplex (FD) orthogonal frequency division multiplexing (OFDM) system. Unlike the conventional half-duplex OFDM system, the receiver faces the challenge of estimating the PHN of the intended signals and self-interference (SI). To address this issue, the PHN estimation problem is transformed into a sparse signal detection problem, which can be solved using compressive sensing techniques. However, the performance of these techniques is limited by linear approximation, improper prior information, or improper structure of the sensing matrix. To overcome these limitations, the extended Kalman filter (EKF) is introduced for PHN estimation. The EKF utilizes the maximum a posteriori probability (MAP) criterion with an approximated linear observation model. Furthermore, a novel MAP estimator is developed that employs the original nonlinear observations. Numerical results validate the effectiveness of the proposed estimators and demonstrate that the proposed MAP estimator outperforms existing compressive sensing approaches due to the utilization of accurate posterior distribution.","PeriodicalId":341881,"journal":{"name":"2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115088553","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}
Pub Date : 2023-07-04DOI: 10.1109/ICUFN57995.2023.10200944
Hitoshi Yamasaki, Hiroki Matsuura, M. Ohta, M. Taromaru
LoRaWAN is focused as one of standards for LPWA (Low Power Wide Area) that is employed in IoT (Internet of Things) system. In order to realize a packet-level index modulation (PLIM), this paper implements the sensor nodes with LoRaWAN. In this paper, a differential PLIM (DPLIM) which is based on PLIM without a time frame synchronization is studied. The use of DPLIM implemented in LoRaWAN requires the design of a new time frame to transmit at any given time. The new time frame design is based on the specification of LoRaWAN that the sensor node has to open two receive windows after transmits a packet. This paper uses the implemented wireless sensor node and confirms the performance of DPLIM that is better than that of conventional PLIM.
{"title":"Frame Design for Differential Packet-Level Index Modulation implemented by LoRaWAN","authors":"Hitoshi Yamasaki, Hiroki Matsuura, M. Ohta, M. Taromaru","doi":"10.1109/ICUFN57995.2023.10200944","DOIUrl":"https://doi.org/10.1109/ICUFN57995.2023.10200944","url":null,"abstract":"LoRaWAN is focused as one of standards for LPWA (Low Power Wide Area) that is employed in IoT (Internet of Things) system. In order to realize a packet-level index modulation (PLIM), this paper implements the sensor nodes with LoRaWAN. In this paper, a differential PLIM (DPLIM) which is based on PLIM without a time frame synchronization is studied. The use of DPLIM implemented in LoRaWAN requires the design of a new time frame to transmit at any given time. The new time frame design is based on the specification of LoRaWAN that the sensor node has to open two receive windows after transmits a packet. This paper uses the implemented wireless sensor node and confirms the performance of DPLIM that is better than that of conventional PLIM.","PeriodicalId":341881,"journal":{"name":"2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115202551","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}
Pub Date : 2023-07-04DOI: 10.1109/ICUFN57995.2023.10200160
Serena Akasaka, Suguru Kameda, S. Yasuda, N. Shiga
Synchronized spread spectrum code division multiple access (SS-CDMA) is very effective for increasing the capacity and reducing the interference with a rapid spread of Internet of things (IoT) devices. Since the synchronized SS-CDMA requires receiving timing synchronization, it is essential to realize transmission timing control of each node using space-time synchronization. In this paper, we investigate precise time synchronization between nodes using Wireless Two-Way Interferometry (Wi-Wi). The measurement results show that the standard deviation of offset ($sigma$) was less than 30ns. Furthermore, we implement a synchronized SS-CDMA communication function on Universal Software Radio Peripheral (USRP). The bit error rate (BER) characteristics are evaluated with different offsets of initial timing synchronization of the Wi-Wi module. It is found that BER characteristics when two signals are transmitted simultaneously become smaller as the Wi-Wi offset becomes smaller. For an offset of around 12 ns, the degradation of BER compared to the case with 1 transmission signal is negligibly small. As a result, we reveal that simultaneous communication between two terminals is possible without large degradation.
{"title":"Implementation and Evaluation of Synchronized SS-CDMA Using Wireless Two-Way Interferometry (Wi-Wi)","authors":"Serena Akasaka, Suguru Kameda, S. Yasuda, N. Shiga","doi":"10.1109/ICUFN57995.2023.10200160","DOIUrl":"https://doi.org/10.1109/ICUFN57995.2023.10200160","url":null,"abstract":"Synchronized spread spectrum code division multiple access (SS-CDMA) is very effective for increasing the capacity and reducing the interference with a rapid spread of Internet of things (IoT) devices. Since the synchronized SS-CDMA requires receiving timing synchronization, it is essential to realize transmission timing control of each node using space-time synchronization. In this paper, we investigate precise time synchronization between nodes using Wireless Two-Way Interferometry (Wi-Wi). The measurement results show that the standard deviation of offset ($sigma$) was less than 30ns. Furthermore, we implement a synchronized SS-CDMA communication function on Universal Software Radio Peripheral (USRP). The bit error rate (BER) characteristics are evaluated with different offsets of initial timing synchronization of the Wi-Wi module. It is found that BER characteristics when two signals are transmitted simultaneously become smaller as the Wi-Wi offset becomes smaller. For an offset of around 12 ns, the degradation of BER compared to the case with 1 transmission signal is negligibly small. As a result, we reveal that simultaneous communication between two terminals is possible without large degradation.","PeriodicalId":341881,"journal":{"name":"2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115921461","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}
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