In the paper, we demonstrate an application of the wireless earbud - an acoustic ruler. Approaches are proposed to improve the robustness of the design in the low signal-to-noise ratio environment. We also share our solution to several engineering challenges, which aims at facilitating the transformation of earbuds to into acoustic sensing research platforms without any hardware modification.
{"title":"Acoustic ruler using wireless earbud","authors":"Ruofeng Liu, Wenjun Jiang, Xun Chen","doi":"10.1145/3458864.3466905","DOIUrl":"https://doi.org/10.1145/3458864.3466905","url":null,"abstract":"In the paper, we demonstrate an application of the wireless earbud - an acoustic ruler. Approaches are proposed to improve the robustness of the design in the low signal-to-noise ratio environment. We also share our solution to several engineering challenges, which aims at facilitating the transformation of earbuds to into acoustic sensing research platforms without any hardware modification.","PeriodicalId":153361,"journal":{"name":"Proceedings of the 19th Annual International Conference on Mobile Systems, Applications, and Services","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116024329","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}
{"title":"SOS","authors":"S. Narayana, R. Prasad, T. Prabhakar","doi":"10.4414/saez.2016.04440","DOIUrl":"https://doi.org/10.4414/saez.2016.04440","url":null,"abstract":"","PeriodicalId":153361,"journal":{"name":"Proceedings of the 19th Annual International Conference on Mobile Systems, Applications, and Services","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124286161","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}
Zhihao Gu, Taiwei He, Junwei Yin, Yuedong Xu, Jun Wu
This work presents the design and implementation of TyrLoc, an accurate multi-technology switching MIMO localization system that can be deployed on low-cost SDRs. TyrLoc only uses a single RF Chain to switch on each antenna in an antenna array within the coherence time asynchronously, thus mimicking a MIMO platform to pinpoint the positions of WIFI, Bluetooth Low Energy (BLE) and LoRa devices. TyrLoc makes three key technical contributions. First, TyrLoc modifies the firmware of inexpensive PlutoSDR that controls the antenna switching pattern and tags the signal associated with each antenna. Second, it develops a two-stage fine-grained carrier frequency offset (CFO) calibration algorithm that harnesses the agile antenna switching pattern and is 10× more accurate than the baseline method. Third, TyrLoc employs an interpolated transform approach to facilitate angle-of-arrival (AoA) estimation in the presence of missing antennas. The AoA-based localization experiments in a multipath-rich indoor environment show that TyrLoc with eight antennas achieves the median errors of 63cm for WIFI, 39cm for BLE and 32cm for LoRa, respectively.
{"title":"TyrLoc","authors":"Zhihao Gu, Taiwei He, Junwei Yin, Yuedong Xu, Jun Wu","doi":"10.1145/3458864.3467677","DOIUrl":"https://doi.org/10.1145/3458864.3467677","url":null,"abstract":"This work presents the design and implementation of TyrLoc, an accurate multi-technology switching MIMO localization system that can be deployed on low-cost SDRs. TyrLoc only uses a single RF Chain to switch on each antenna in an antenna array within the coherence time asynchronously, thus mimicking a MIMO platform to pinpoint the positions of WIFI, Bluetooth Low Energy (BLE) and LoRa devices. TyrLoc makes three key technical contributions. First, TyrLoc modifies the firmware of inexpensive PlutoSDR that controls the antenna switching pattern and tags the signal associated with each antenna. Second, it develops a two-stage fine-grained carrier frequency offset (CFO) calibration algorithm that harnesses the agile antenna switching pattern and is 10× more accurate than the baseline method. Third, TyrLoc employs an interpolated transform approach to facilitate angle-of-arrival (AoA) estimation in the presence of missing antennas. The AoA-based localization experiments in a multipath-rich indoor environment show that TyrLoc with eight antennas achieves the median errors of 63cm for WIFI, 39cm for BLE and 32cm for LoRa, respectively.","PeriodicalId":153361,"journal":{"name":"Proceedings of the 19th Annual International Conference on Mobile Systems, Applications, and Services","volume":"130 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122073269","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}
Availability and security problems in cellular emergency call systems can cost people their lives, yet this topic has not been thoroughly researched. Based on our proposed Seed-Assisted Specification method, we start to investigate this topic by looking closely into one emergency call failure case in China. Using what we learned from the case as prior knowledge, we build a formal model of emergency call systems with proper granularity. By running model checking, four public-unaware scenarios where emergency calls cannot be correctly routed are discovered. Additionally, we extract configurations of two major U.S. carriers and incorporate them as model constraints into the model. Based on the augmented model, we find two new attacks leveraging the privileges of emergency calls. Finally, we present a solution with marginal overhead to resolve issues we can foresee.
{"title":"Discovering emergency call pitfalls for cellular networks with formal methods","authors":"Kaiyu Hou, You Li, Yinbo Yu, Yan Chen, Hai Zhou","doi":"10.1145/3458864.3466625","DOIUrl":"https://doi.org/10.1145/3458864.3466625","url":null,"abstract":"Availability and security problems in cellular emergency call systems can cost people their lives, yet this topic has not been thoroughly researched. Based on our proposed Seed-Assisted Specification method, we start to investigate this topic by looking closely into one emergency call failure case in China. Using what we learned from the case as prior knowledge, we build a formal model of emergency call systems with proper granularity. By running model checking, four public-unaware scenarios where emergency calls cannot be correctly routed are discovered. Additionally, we extract configurations of two major U.S. carriers and incorporate them as model constraints into the model. Based on the augmented model, we find two new attacks leveraging the privileges of emergency calls. Finally, we present a solution with marginal overhead to resolve issues we can foresee.","PeriodicalId":153361,"journal":{"name":"Proceedings of the 19th Annual International Conference on Mobile Systems, Applications, and Services","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130210635","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}
Connected autonomous vehicles have boosted a high demand on communication throughput in order to timely share the information collected by in-car sensors (e.g., LiDAR). While visible light communication (VLC) has shown its capability to offer Gigabit-level throughput for applications with high demand for data rate, most are performed indoors and the throughput of outdoor VLC drops to a few Mbps. To fill this performance gap, this paper presents RayTrack, an interference-free outdoor mobile VLC system. The key idea of RayTrack is to use a small but real-time adjustable FOV according to the transmitter location, which can effectively repel interference from the environment and from other transmitters and boost the system throughput. The idea also realizes virtual point-to-point links, and eliminates the need of link access control. To be able to minimize the transmitter detection time to only 20 ms, RayTrack leverages a high-compression-ratio compressive sensing scheme, incorporating a dual-photodiode architecture, optimized measurement matrix and Gaussian-based basis to increase sparsity. Real-world driving experiments show that RayTrack is able to achieve a data rate of 607.9 kbps with over 90% detection accuracy and lower than 15% bit error rate at 35 m, with 70 - 100 km/hr driving speed. To the best of our knowledge, this is the first working outdoor VLC system which can offer such range, throughput and error performance while accommodating freeway mobility.
{"title":"RayTrack","authors":"Wen-Hsuan Shen, Hsin-Mu Tsai","doi":"10.1145/3458864.3466867","DOIUrl":"https://doi.org/10.1145/3458864.3466867","url":null,"abstract":"Connected autonomous vehicles have boosted a high demand on communication throughput in order to timely share the information collected by in-car sensors (e.g., LiDAR). While visible light communication (VLC) has shown its capability to offer Gigabit-level throughput for applications with high demand for data rate, most are performed indoors and the throughput of outdoor VLC drops to a few Mbps. To fill this performance gap, this paper presents RayTrack, an interference-free outdoor mobile VLC system. The key idea of RayTrack is to use a small but real-time adjustable FOV according to the transmitter location, which can effectively repel interference from the environment and from other transmitters and boost the system throughput. The idea also realizes virtual point-to-point links, and eliminates the need of link access control. To be able to minimize the transmitter detection time to only 20 ms, RayTrack leverages a high-compression-ratio compressive sensing scheme, incorporating a dual-photodiode architecture, optimized measurement matrix and Gaussian-based basis to increase sparsity. Real-world driving experiments show that RayTrack is able to achieve a data rate of 607.9 kbps with over 90% detection accuracy and lower than 15% bit error rate at 35 m, with 70 - 100 km/hr driving speed. To the best of our knowledge, this is the first working outdoor VLC system which can offer such range, throughput and error performance while accommodating freeway mobility.","PeriodicalId":153361,"journal":{"name":"Proceedings of the 19th Annual International Conference on Mobile Systems, Applications, and Services","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128439755","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}
With the advent of Space-IoTs, the rate of launch of satellites has grown significantly. Alongside, the failure rate of satellites has also surged increased tremendously. Satellites are non-repairable systems in orbit, and the financial loss incurred when the satellites fail before their expected mission time is substantial. If the source of a failure is known while the satellite is in orbit, then there is a possibility to revive it by sending appropriate commands from ground stations. In this work, we present a simple, independent satellite health monitoring system called Chirper. The Chirper is equipped with multiple modules such as IMU, isolated voltage and current measurement probes, and an onboard communication channel. We present a new approach to measure low DC voltages in an isolated way, providing a resolution and accuracy of around 1 V. We evaluated the design and performance of the Chirper through simulation, testing it in space systems test facility, and by mounting it on a helium balloon. With extensive experiments we show that 90% of the time the dc voltage measurement error is within 0.8 V, and the maximum error is 0.9 V. We expect to launch the Chirper soon on a space system.
{"title":"SOS: isolated health monitoring system to save our satellites","authors":"S. Narayana, R. V. Prasad, T. V. Prabhakar","doi":"10.1145/3458864.3466862","DOIUrl":"https://doi.org/10.1145/3458864.3466862","url":null,"abstract":"With the advent of Space-IoTs, the rate of launch of satellites has grown significantly. Alongside, the failure rate of satellites has also surged increased tremendously. Satellites are non-repairable systems in orbit, and the financial loss incurred when the satellites fail before their expected mission time is substantial. If the source of a failure is known while the satellite is in orbit, then there is a possibility to revive it by sending appropriate commands from ground stations. In this work, we present a simple, independent satellite health monitoring system called Chirper. The Chirper is equipped with multiple modules such as IMU, isolated voltage and current measurement probes, and an onboard communication channel. We present a new approach to measure low DC voltages in an isolated way, providing a resolution and accuracy of around 1 V. We evaluated the design and performance of the Chirper through simulation, testing it in space systems test facility, and by mounting it on a helium balloon. With extensive experiments we show that 90% of the time the dc voltage measurement error is within 0.8 V, and the maximum error is 0.9 V. We expect to launch the Chirper soon on a space system.","PeriodicalId":153361,"journal":{"name":"Proceedings of the 19th Annual International Conference on Mobile Systems, Applications, and Services","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115684902","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}
Many apps performing security-sensitive tasks (e.g., online banking) attempt to verify the integrity of the device they are running in and the integrity of their own code. To ease this goal, Android provides an API, called the SafetyNet Attestation API, that can be used to detect if the device an app is running in is in a "safe" state (e.g., non-rooted) and if the app's code has not been modified (using, for instance, app repackaging). In this paper, we perform the first large-scale systematic analysis of the usage of the SafetyNet API. Our study identifies many common mistakes that app developers make when attempting to use this API. Specifically, we provide a systematic categorization of the possible misusages of this API, and we analyze how frequent each misuse is. Our results show that, for instance, more than half of the analyzed apps check SafetyNet results locally (as opposed to using a remote trusted server), rendering their checks trivially bypassable. Even more surprisingly, we found that none of the analyzed apps invoking the SafetyNet API uses it in a fully correct way.
{"title":"SafetyNOT","authors":"Muhammad Ibrahim, A. Imran, Antonio Bianchi","doi":"10.1145/3458864.3466627","DOIUrl":"https://doi.org/10.1145/3458864.3466627","url":null,"abstract":"Many apps performing security-sensitive tasks (e.g., online banking) attempt to verify the integrity of the device they are running in and the integrity of their own code. To ease this goal, Android provides an API, called the SafetyNet Attestation API, that can be used to detect if the device an app is running in is in a \"safe\" state (e.g., non-rooted) and if the app's code has not been modified (using, for instance, app repackaging). In this paper, we perform the first large-scale systematic analysis of the usage of the SafetyNet API. Our study identifies many common mistakes that app developers make when attempting to use this API. Specifically, we provide a systematic categorization of the possible misusages of this API, and we analyze how frequent each misuse is. Our results show that, for instance, more than half of the analyzed apps check SafetyNet results locally (as opposed to using a remote trusted server), rendering their checks trivially bypassable. Even more surprisingly, we found that none of the analyzed apps invoking the SafetyNet API uses it in a fully correct way.","PeriodicalId":153361,"journal":{"name":"Proceedings of the 19th Annual International Conference on Mobile Systems, Applications, and Services","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121644116","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}
Existing smartphone-based Augmented Reality (AR) systems are able to render virtual effects on static anchors. However, today's solutions lack the ability to render follow-up effects attached to moving anchors since they fail to track the 6 degrees of freedom (6-DoF) poses of them. We find an opportunity to accomplish the task by leveraging sensors capable of generating sparse point clouds on smartphones and fusing them with vision-based technologies. However, realizing this vision is non-trivial due to challenges in modeling radar error distributions and fusing heterogeneous sensor data. This study proposes FollowUpAR, a framework that integrates vision and sparse measurements to track object 6-DoF pose on smartphones. We derive a physical-level theoretical radar error distribution model based on an in-depth understanding of its hardware-level working principles and design a novel factor graph competent in fusing heterogeneous data. By doing so, FollowUpAR enables mobile devices to track anchor's pose accurately. We implement FollowUpAR on commodity smartphones and validate its performance with 800,000 frames in a total duration of 15 hours. The results show that FollowUpAR achieves a remarkable rotation tracking accuracy of 2.3° with a translation accuracy of 2.9mm, outperforming most existing tracking systems and comparable to state-of-the-art learning-based solutions. FollowUpAR can be integrated into ARCore and enable smartphones to render follow-up AR effects to moving objects.
{"title":"FollowUpAR","authors":"Jingao Xu, Guoxuan Chi, Zheng Yang, Danyang Li, Qian Zhang, Q. Ma, Xin Miao","doi":"10.1145/3458864.3467675","DOIUrl":"https://doi.org/10.1145/3458864.3467675","url":null,"abstract":"Existing smartphone-based Augmented Reality (AR) systems are able to render virtual effects on static anchors. However, today's solutions lack the ability to render follow-up effects attached to moving anchors since they fail to track the 6 degrees of freedom (6-DoF) poses of them. We find an opportunity to accomplish the task by leveraging sensors capable of generating sparse point clouds on smartphones and fusing them with vision-based technologies. However, realizing this vision is non-trivial due to challenges in modeling radar error distributions and fusing heterogeneous sensor data. This study proposes FollowUpAR, a framework that integrates vision and sparse measurements to track object 6-DoF pose on smartphones. We derive a physical-level theoretical radar error distribution model based on an in-depth understanding of its hardware-level working principles and design a novel factor graph competent in fusing heterogeneous data. By doing so, FollowUpAR enables mobile devices to track anchor's pose accurately. We implement FollowUpAR on commodity smartphones and validate its performance with 800,000 frames in a total duration of 15 hours. The results show that FollowUpAR achieves a remarkable rotation tracking accuracy of 2.3° with a translation accuracy of 2.9mm, outperforming most existing tracking systems and comparable to state-of-the-art learning-based solutions. FollowUpAR can be integrated into ARCore and enable smartphones to render follow-up AR effects to moving objects.","PeriodicalId":153361,"journal":{"name":"Proceedings of the 19th Annual International Conference on Mobile Systems, Applications, and Services","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121859031","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}
Billions of smoke detectors are in use worldwide to provide early warning of fires. Despite this, they frequently fail to operate in an ongoing fire, risking death and property damage. A significant fraction of faults result from drift, or reduced sensitivity, and other faults in smoke detectors' phototransistors (PTs). Existing approaches attempt to detect drift from the PT output in normal conditions (without smoke). However, we find that drifted PTs mimic the output of working PTs in normal conditions, but diverge in the presence of smoke, making this approach ineffective. This paper presents two novel approaches to systematically detect faults and measure and compensate for drift in smoke detectors' PTs. Our first approach, called FallTime, measures a PT "fingerprint," a unique electrical characteristic with distinct behavior for working, drifted, and faulty components. FallTime can be added to many existing smoke detector models in software alone, with no/minimal hardware modifications. Our second approach, DriftTestButton, is a mechanical test button that simulates the behavior of smoke when pressed. It offers a robust, straightforward approach to detect faults, and can measure and compensate for drift across the entire smoke detector system. We empirically evaluate both approaches and present extensive experimental results from actual smoke detectors deployed in a commercial building, along with custom-built smoke detectors. By conducting tests with live smoke, we show that both FallTime and DriftTestButton perform more effectively than existing fault tolerance techniques and stand to substantially reduce the risk that a smoke detector fails to alarm in the presence of smoke.
{"title":"Is your smoke detector working properly?: robust fault tolerance approaches for smoke detectors","authors":"Arjun Tambe, A. Nambi, Sumukh Marathe","doi":"10.1145/3458864.3466869","DOIUrl":"https://doi.org/10.1145/3458864.3466869","url":null,"abstract":"Billions of smoke detectors are in use worldwide to provide early warning of fires. Despite this, they frequently fail to operate in an ongoing fire, risking death and property damage. A significant fraction of faults result from drift, or reduced sensitivity, and other faults in smoke detectors' phototransistors (PTs). Existing approaches attempt to detect drift from the PT output in normal conditions (without smoke). However, we find that drifted PTs mimic the output of working PTs in normal conditions, but diverge in the presence of smoke, making this approach ineffective. This paper presents two novel approaches to systematically detect faults and measure and compensate for drift in smoke detectors' PTs. Our first approach, called FallTime, measures a PT \"fingerprint,\" a unique electrical characteristic with distinct behavior for working, drifted, and faulty components. FallTime can be added to many existing smoke detector models in software alone, with no/minimal hardware modifications. Our second approach, DriftTestButton, is a mechanical test button that simulates the behavior of smoke when pressed. It offers a robust, straightforward approach to detect faults, and can measure and compensate for drift across the entire smoke detector system. We empirically evaluate both approaches and present extensive experimental results from actual smoke detectors deployed in a commercial building, along with custom-built smoke detectors. By conducting tests with live smoke, we show that both FallTime and DriftTestButton perform more effectively than existing fault tolerance techniques and stand to substantially reduce the risk that a smoke detector fails to alarm in the presence of smoke.","PeriodicalId":153361,"journal":{"name":"Proceedings of the 19th Annual International Conference on Mobile Systems, Applications, and Services","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129026461","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}
The performance of wireless communication systems is evolving rapidly, making it difficult to build experimentation platforms that meet the hardware requirements of new standards. The bandwidth of current systems ranges from 160 MHz for IEEE 802.11ac/ax to 2 GHz for Millimeter-Wave (mm-wave) IEEE 802.11ad/ay, and they support up to 8 spatial MIMO streams. Mobile 5G and beyond systems have a similarly diverse set of requirements. To address this, we propose a highly configurable wireless platform that meets such requirements and is both affordable and scalable. It is implemented on a single state-of-the-art FPGA board that can be configured from 4x4 mm-wave MIMO with 2 GHz channels to 8x8 MIMO with 160 MHz channels in sub-6 GHz bands. In addition, multi-band operation will play an important role in future wireless networks and our platform supports mixed configurations with simultaneous use of mm-wave and sub-6 GHz. Finally, the platform supports real-time operation, e.g., for closed-loop MIMO beam training with low-latency, by implementing suitable hardware/software accelerators. We demonstrate the platform's performance in a wide range of experiments. The platform is provided as open-source to build a community to use and extend it.
{"title":"A real-time experimentation platform for sub-6 GHz and millimeter-wave MIMO systems","authors":"J. O. Lacruz, R. Ortiz, Joerg Widmer","doi":"10.1145/3458864.3466868","DOIUrl":"https://doi.org/10.1145/3458864.3466868","url":null,"abstract":"The performance of wireless communication systems is evolving rapidly, making it difficult to build experimentation platforms that meet the hardware requirements of new standards. The bandwidth of current systems ranges from 160 MHz for IEEE 802.11ac/ax to 2 GHz for Millimeter-Wave (mm-wave) IEEE 802.11ad/ay, and they support up to 8 spatial MIMO streams. Mobile 5G and beyond systems have a similarly diverse set of requirements. To address this, we propose a highly configurable wireless platform that meets such requirements and is both affordable and scalable. It is implemented on a single state-of-the-art FPGA board that can be configured from 4x4 mm-wave MIMO with 2 GHz channels to 8x8 MIMO with 160 MHz channels in sub-6 GHz bands. In addition, multi-band operation will play an important role in future wireless networks and our platform supports mixed configurations with simultaneous use of mm-wave and sub-6 GHz. Finally, the platform supports real-time operation, e.g., for closed-loop MIMO beam training with low-latency, by implementing suitable hardware/software accelerators. We demonstrate the platform's performance in a wide range of experiments. The platform is provided as open-source to build a community to use and extend it.","PeriodicalId":153361,"journal":{"name":"Proceedings of the 19th Annual International Conference on Mobile Systems, Applications, and Services","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133933418","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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