Pub Date : 2023-06-06DOI: 10.1109/EuCNC/6GSummit58263.2023.10188365
Zi Ye, Faryal Junaid, R. Nilsson, Jaap van de Beek
Single antenna sensors in the rapidly emerging Internet-of- Things (IoT) are attractive due to their simplicity and low cost. However, determining their own positions autonomously using only a single antenna is challenging. This paper presents a novel approach for autonomous downlink localization of single-antenna receivers using Reconfigurable Intelligent Surfaces (RIS) and a tracking process using the complex extended Kalman filter (EKF). Simulation results show that the considered RIS-aided wireless radio system can provide accurate localization and continuous fast tracking down to the centimeter level, especially when multiple RISs are deployed. Furthermore, various factors affecting the system performance are analyzed in detail.
{"title":"Autonomous Single Antenna Receiver Localization and Tracking with RIS and EKF","authors":"Zi Ye, Faryal Junaid, R. Nilsson, Jaap van de Beek","doi":"10.1109/EuCNC/6GSummit58263.2023.10188365","DOIUrl":"https://doi.org/10.1109/EuCNC/6GSummit58263.2023.10188365","url":null,"abstract":"Single antenna sensors in the rapidly emerging Internet-of- Things (IoT) are attractive due to their simplicity and low cost. However, determining their own positions autonomously using only a single antenna is challenging. This paper presents a novel approach for autonomous downlink localization of single-antenna receivers using Reconfigurable Intelligent Surfaces (RIS) and a tracking process using the complex extended Kalman filter (EKF). Simulation results show that the considered RIS-aided wireless radio system can provide accurate localization and continuous fast tracking down to the centimeter level, especially when multiple RISs are deployed. Furthermore, various factors affecting the system performance are analyzed in detail.","PeriodicalId":65870,"journal":{"name":"公共管理高层论坛","volume":"219 1","pages":"216-221"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79798935","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 : 2023-06-06DOI: 10.1109/EuCNC/6GSummit58263.2023.10188372
I. Ajayi, Y. Medjahdi, L. Mroueh, Olumide Okubadejo, F. Kaddour
Channel adaptation physical layer security (PLS) schemes are degraded when the channel state information (CSI) is imperfect. Imperfect CSI is due to factors such as noisy feedback, outdated CSI, etc. In this paper, we propose a low-complexity noisy CSI denoising scheme based on the autoencoder architecture of deep neural networks referred to as DenoiseSec-Net. To further reduce complexity, we then propose a hybrid version (HybDenoiseSecNet) that combines a legacy denoising scheme and a shallow neural network to achieve a similar performance as DenoiseSecNet. Simulation results, in terms of bit error rate (BER), secrecy capacity, and normalized mean squared error (NMSE), show the performance improvement of our proposed scheme compared to conventional denoising schemes. Finally, we study the significant reduction in computational complexity of the proposed scheme compared to another neural network scheme.
{"title":"Low-Complexity Neural Networks for Denoising Imperfect CSI in Physical Layer Security","authors":"I. Ajayi, Y. Medjahdi, L. Mroueh, Olumide Okubadejo, F. Kaddour","doi":"10.1109/EuCNC/6GSummit58263.2023.10188372","DOIUrl":"https://doi.org/10.1109/EuCNC/6GSummit58263.2023.10188372","url":null,"abstract":"Channel adaptation physical layer security (PLS) schemes are degraded when the channel state information (CSI) is imperfect. Imperfect CSI is due to factors such as noisy feedback, outdated CSI, etc. In this paper, we propose a low-complexity noisy CSI denoising scheme based on the autoencoder architecture of deep neural networks referred to as DenoiseSec-Net. To further reduce complexity, we then propose a hybrid version (HybDenoiseSecNet) that combines a legacy denoising scheme and a shallow neural network to achieve a similar performance as DenoiseSecNet. Simulation results, in terms of bit error rate (BER), secrecy capacity, and normalized mean squared error (NMSE), show the performance improvement of our proposed scheme compared to conventional denoising schemes. Finally, we study the significant reduction in computational complexity of the proposed scheme compared to another neural network scheme.","PeriodicalId":65870,"journal":{"name":"公共管理高层论坛","volume":"182 1","pages":"48-53"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80302027","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 : 2023-06-06DOI: 10.1109/EuCNC/6GSummit58263.2023.10188233
H. Haile, Karl-Johan Grinnemo, Simone Ferlin Oliveira, Per Hurtig, A. Brunström
The lack of consideration for application delay requirements in standard loss-based congestion control algorithms (CCAs) has motivated the proposal of several alternative CCAs. Among these new CCAs, Copa is one of the promising few CCAs that have attracted attention from both academia and industry. The delay performance of Copa is governed by a mostly static latency-throughput tradeoff parameter, $delta$. However, a static $delta$ parameter makes it difficult for Copa to achieve consistent delay and throughput over a range of bottleneck bandwidths. In particular, the coexistence of 4G and 5G networks and the wide range of bandwidths experienced in NG-RANs can result in inconsistent CCA performance. To this end, we propose Copa-D, a modification to Copa that dynamically tunes $delta$ to achieve a consistent delay performance. We evaluate the modification over fixed, 4G, and 5G emulated bottlenecks. Our results show that Copa-D achieves consistent delay with minimal impact on throughput in fixed capacity bottlenecks. Copa-D also allows a more intuitive way of specifying the latency-throughput tradeoff and achieves more accurate and predictable delay in variable cellular bottlenecks.
{"title":"Copa-D: Delay Consistent Copa for Dynamic Cellular Networks","authors":"H. Haile, Karl-Johan Grinnemo, Simone Ferlin Oliveira, Per Hurtig, A. Brunström","doi":"10.1109/EuCNC/6GSummit58263.2023.10188233","DOIUrl":"https://doi.org/10.1109/EuCNC/6GSummit58263.2023.10188233","url":null,"abstract":"The lack of consideration for application delay requirements in standard loss-based congestion control algorithms (CCAs) has motivated the proposal of several alternative CCAs. Among these new CCAs, Copa is one of the promising few CCAs that have attracted attention from both academia and industry. The delay performance of Copa is governed by a mostly static latency-throughput tradeoff parameter, $delta$. However, a static $delta$ parameter makes it difficult for Copa to achieve consistent delay and throughput over a range of bottleneck bandwidths. In particular, the coexistence of 4G and 5G networks and the wide range of bandwidths experienced in NG-RANs can result in inconsistent CCA performance. To this end, we propose Copa-D, a modification to Copa that dynamically tunes $delta$ to achieve a consistent delay performance. We evaluate the modification over fixed, 4G, and 5G emulated bottlenecks. Our results show that Copa-D achieves consistent delay with minimal impact on throughput in fixed capacity bottlenecks. Copa-D also allows a more intuitive way of specifying the latency-throughput tradeoff and achieves more accurate and predictable delay in variable cellular bottlenecks.","PeriodicalId":65870,"journal":{"name":"公共管理高层论坛","volume":"1 1","pages":"508-513"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87400424","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 : 2023-06-06DOI: 10.1109/EuCNC/6GSummit58263.2023.10188377
Norbert Reider, G. Németh, Sándor Rácz, Marcell Balogh, A. Vidács, G. Fehér, D. Harutyunyan, P. Buseck, A. Hohner
This paper gives a detailed outline of the trial and the validation of cloud-controlled collaborative mobile robots applied in a real semiconductor factory of Bosch in Reutlin-gen, Germany. Two Autonomous Mobile Robots (AMRs) are controlled from the cloud over a 5G Standalone (SA) private network deployed inside the plant. We describe the methodology adopted to validate and evaluate this use case, using the industry goals set by the factory management to understand how much each industry goal is affected by the usage of 5G and cloud technologies. We then present the test results of the Key Performance Indicators (KPIs) in various validation scenarios executed in the operational factory. Finally, we demonstrate that 5G technology is ready to be used for the considered industrial application.
{"title":"Validation of Cloud-Controlled Autonomous Mobile Robots in a Real Semiconductor Plant","authors":"Norbert Reider, G. Németh, Sándor Rácz, Marcell Balogh, A. Vidács, G. Fehér, D. Harutyunyan, P. Buseck, A. Hohner","doi":"10.1109/EuCNC/6GSummit58263.2023.10188377","DOIUrl":"https://doi.org/10.1109/EuCNC/6GSummit58263.2023.10188377","url":null,"abstract":"This paper gives a detailed outline of the trial and the validation of cloud-controlled collaborative mobile robots applied in a real semiconductor factory of Bosch in Reutlin-gen, Germany. Two Autonomous Mobile Robots (AMRs) are controlled from the cloud over a 5G Standalone (SA) private network deployed inside the plant. We describe the methodology adopted to validate and evaluate this use case, using the industry goals set by the factory management to understand how much each industry goal is affected by the usage of 5G and cloud technologies. We then present the test results of the Key Performance Indicators (KPIs) in various validation scenarios executed in the operational factory. Finally, we demonstrate that 5G technology is ready to be used for the considered industrial application.","PeriodicalId":65870,"journal":{"name":"公共管理高层论坛","volume":"69 1","pages":"681-686"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87669488","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 : 2023-06-06DOI: 10.1109/EuCNC/6GSummit58263.2023.10188273
Atiquzzaman Mondal, Aparajita Dutta, S. Biswas
We investigate a two-tier distributed spectrum sharing framework between a multi-cell multi-user mobile broadband network (MBN) and a multiple-input multiple-output (MIMO) radar. While multi-agent reinforcement learning (RL) is used for transmit power allocation at MBN's base-stations to improve the quality of service of its users subject to the constraint of the probability of detection of the radar, the interference from the radar towards the MBN is mitigated via null-space based waveform projection. In the RL framework, the multiple cells in the MBN operate as agents, and the average signal-to-noise ratio value is the reward. Accordingly, we propose a deep RL network called dueling deep Q-network (DDQN) to enable co-existence by taking into account the physical layer parameters of the MBN and radar communication. The DDQN is compared to two other baseline RL algorithms, namely Q- learning and deep Q-network (DQN). Numerical results show that DDQN learns to obtain the best power allocation policies for distributed spectrum access without needing a centralized controller to control interference towards the radar. In particular, over time, the advantage network of DDQN allows the agent to take actions having higher advantage value, thus leading to faster convergence and a more stable spectrum sharing framework.
我们研究了多小区多用户移动宽带网络(MBN)和多输入多输出(MIMO)雷达之间的两层分布式频谱共享框架。多智能体强化学习(RL)用于MBN基站的发射功率分配，在受雷达检测概率约束的情况下提高用户的服务质量，通过基于零空间的波形投影来减轻雷达对MBN的干扰。在RL框架中，MBN中的多个单元作为代理运行，平均信噪比值是奖励。因此，我们提出了一种称为dueling deep Q-network (DDQN)的深度RL网络，通过考虑MBN和雷达通信的物理层参数来实现共存。DDQN与另外两种基线RL算法，即Q-学习和深度Q-网络(DQN)进行了比较。数值结果表明，DDQN在不需要集中控制器控制对雷达干扰的情况下，学习得到分布式频谱接入的最佳功率分配策略。特别是随着时间的推移，DDQN的优势网络允许agent采取具有更高优势价值的动作，从而使收敛速度更快，频谱共享框架更加稳定。
{"title":"Dueling-DQN Based Spectrum Sharing Between MIMO Radar and Cellular Networks","authors":"Atiquzzaman Mondal, Aparajita Dutta, S. Biswas","doi":"10.1109/EuCNC/6GSummit58263.2023.10188273","DOIUrl":"https://doi.org/10.1109/EuCNC/6GSummit58263.2023.10188273","url":null,"abstract":"We investigate a two-tier distributed spectrum sharing framework between a multi-cell multi-user mobile broadband network (MBN) and a multiple-input multiple-output (MIMO) radar. While multi-agent reinforcement learning (RL) is used for transmit power allocation at MBN's base-stations to improve the quality of service of its users subject to the constraint of the probability of detection of the radar, the interference from the radar towards the MBN is mitigated via null-space based waveform projection. In the RL framework, the multiple cells in the MBN operate as agents, and the average signal-to-noise ratio value is the reward. Accordingly, we propose a deep RL network called dueling deep Q-network (DDQN) to enable co-existence by taking into account the physical layer parameters of the MBN and radar communication. The DDQN is compared to two other baseline RL algorithms, namely Q- learning and deep Q-network (DQN). Numerical results show that DDQN learns to obtain the best power allocation policies for distributed spectrum access without needing a centralized controller to control interference towards the radar. In particular, over time, the advantage network of DDQN allows the agent to take actions having higher advantage value, thus leading to faster convergence and a more stable spectrum sharing framework.","PeriodicalId":65870,"journal":{"name":"公共管理高层论坛","volume":"54 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84829654","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 : 2023-06-06DOI: 10.1109/EuCNC/6GSummit58263.2023.10188319
Riccardo Rusca, Francesco Raviglione, C. Casetti, P. Giaccone, Francesco Restuccia
Large-scale wireless emulation is gaining momen-tum nowadays, thanks to its potential in the development and deployment of advanced use cases for next-generation wireless networks. Several novel use cases are indeed emerging, including massive MIMO, millimeter wave beamforming and AI-based Vehicle-to-Everything (V2X) optimized communication. The de-velopment and testing of a wireless application, especially at a large scale and when dealing with mobile nodes, faces several challenges that cannot be solved by simulation frameworks alone. Thus, massive-scale channel emulators are emerging, enabling the emulation of realistic scenarios which leverage real hardware and radio signals. However, this is a complex task due to the lack of realistic scenarios based on real datasets. We thus propose a novel framework for the design and generation of channel emulation scenarios starting from real mobility traces, either generated by means of dedicated tools, or collected on the field. Our framework provides a practical way of generating mobility scenarios with vehicles, pedestrians, drones and other mobile entities. We detail all the steps foreseen by our framework, from the provision of the traces and radio parameters, to the generation of a matrix describing the delay and IQ samples for each time instant and node in the scenario. We also showcase the potentiality of our proposal by designing and creating a vehicular 5G scenario with 13 vehicles, starting from a recently-disclosed open dataset. This scenario is then validated on the Colosseum channel emulator, proving how our framework can provide an effective tool for large-scale wireless networking evaluation.
{"title":"Mobile RF Scenario Design for Massive-Scale Wireless Channel Emulators","authors":"Riccardo Rusca, Francesco Raviglione, C. Casetti, P. Giaccone, Francesco Restuccia","doi":"10.1109/EuCNC/6GSummit58263.2023.10188319","DOIUrl":"https://doi.org/10.1109/EuCNC/6GSummit58263.2023.10188319","url":null,"abstract":"Large-scale wireless emulation is gaining momen-tum nowadays, thanks to its potential in the development and deployment of advanced use cases for next-generation wireless networks. Several novel use cases are indeed emerging, including massive MIMO, millimeter wave beamforming and AI-based Vehicle-to-Everything (V2X) optimized communication. The de-velopment and testing of a wireless application, especially at a large scale and when dealing with mobile nodes, faces several challenges that cannot be solved by simulation frameworks alone. Thus, massive-scale channel emulators are emerging, enabling the emulation of realistic scenarios which leverage real hardware and radio signals. However, this is a complex task due to the lack of realistic scenarios based on real datasets. We thus propose a novel framework for the design and generation of channel emulation scenarios starting from real mobility traces, either generated by means of dedicated tools, or collected on the field. Our framework provides a practical way of generating mobility scenarios with vehicles, pedestrians, drones and other mobile entities. We detail all the steps foreseen by our framework, from the provision of the traces and radio parameters, to the generation of a matrix describing the delay and IQ samples for each time instant and node in the scenario. We also showcase the potentiality of our proposal by designing and creating a vehicular 5G scenario with 13 vehicles, starting from a recently-disclosed open dataset. This scenario is then validated on the Colosseum channel emulator, proving how our framework can provide an effective tool for large-scale wireless networking evaluation.","PeriodicalId":65870,"journal":{"name":"公共管理高层论坛","volume":"100 1","pages":"675-680"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76993907","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 : 2023-06-06DOI: 10.1109/EuCNC/6GSummit58263.2023.10188293
Dimitris Giannopoulos, George P. Katsikas, Kostis Trantzas, D. Klonidis, C. Tranoris, S. Denazis, L. Gifre, R. Vilalta, P. Alemany, R. Muñoz, A. Bosneag, A. Mozo, Amit Karamchandani, Luis De La Cal, D. López, Antonio Pastor, Ángela Burgaleta
As the demand for advanced and efficient network and service deployment continues to rise, the integration of multiple domains and the incorporation of AI technology are becoming essential. The ACROSS project is a Horizon Europe project, that aims to address this need by proposing an innovative end-to-end service deployment and management platform. This platform is designed to deliver unprecedented levels of automation, performance, scalability, and energy efficiency in the next-gen networks and services landscape. The platform will be built as a highly-distributed grid of domain-level orchestrators, spread across multiple geo-dispersed and potentially heterogeneous edge environments, all overseen by a cloud-managed multi-domain orchestrator. The use of standardised communication interfaces will promote separation of concerns and ensure compliance with ongoing standardization efforts, some of which include ETSI ZSM, ETSI NFV-OSM, TMF, ETSI TFS and ONF. The platform will also be enhanced with deep end-to-end telemetry, AI-driven intelligence, full-stack cross-domain zero-touch provisioning, and secure and trusted orchestration mechanisms.
{"title":"ACROSS: Automated zero-touch cross-layer provisioning framework for 5G and beyond vertical services","authors":"Dimitris Giannopoulos, George P. Katsikas, Kostis Trantzas, D. Klonidis, C. Tranoris, S. Denazis, L. Gifre, R. Vilalta, P. Alemany, R. Muñoz, A. Bosneag, A. Mozo, Amit Karamchandani, Luis De La Cal, D. López, Antonio Pastor, Ángela Burgaleta","doi":"10.1109/EuCNC/6GSummit58263.2023.10188293","DOIUrl":"https://doi.org/10.1109/EuCNC/6GSummit58263.2023.10188293","url":null,"abstract":"As the demand for advanced and efficient network and service deployment continues to rise, the integration of multiple domains and the incorporation of AI technology are becoming essential. The ACROSS project is a Horizon Europe project, that aims to address this need by proposing an innovative end-to-end service deployment and management platform. This platform is designed to deliver unprecedented levels of automation, performance, scalability, and energy efficiency in the next-gen networks and services landscape. The platform will be built as a highly-distributed grid of domain-level orchestrators, spread across multiple geo-dispersed and potentially heterogeneous edge environments, all overseen by a cloud-managed multi-domain orchestrator. The use of standardised communication interfaces will promote separation of concerns and ensure compliance with ongoing standardization efforts, some of which include ETSI ZSM, ETSI NFV-OSM, TMF, ETSI TFS and ONF. The platform will also be enhanced with deep end-to-end telemetry, AI-driven intelligence, full-stack cross-domain zero-touch provisioning, and secure and trusted orchestration mechanisms.","PeriodicalId":65870,"journal":{"name":"公共管理高层论坛","volume":"185 3 1","pages":"735-740"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81065001","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 : 2023-06-06DOI: 10.1109/EuCNC/6GSummit58263.2023.10188375
José Quevedo, André Perdigão, David Santos, Rui Silva, Rui L. Aguiar
Every new mobile communication generation comes with the emergence of novel applications and services. The fifth-generation (5G) is not an exception, its increased performance and flexibility are expected to provide support for a plethora of utilization scenarios, where the network can be tailored, in runtime, to the particular requirements of each use case. In particular, 5G is gaining the attention of different vertical industries as an enabler of Industry 4.0. However, adopting these technologies requires novel business models for delivering communication services. Moreover, 5G deployments are still in early stages, with novel functionalities expected to gradually emerge over the next few years. The 5GAIner laboratory provides a 5G experimentation en-vironment for the different stakeholders taking part in the 5G ecosystem. The goal is to facilitate vertical markets' digital transition to 5G by providing an environment for easy inno-vation, development, and experimentation. In this context, the paper describes the existing infrastructure, provides some initial performance results, summarises the learned lessons, and outlines the expected evolution path.
{"title":"5GAIner: Taking the verticals into the 5G road","authors":"José Quevedo, André Perdigão, David Santos, Rui Silva, Rui L. Aguiar","doi":"10.1109/EuCNC/6GSummit58263.2023.10188375","DOIUrl":"https://doi.org/10.1109/EuCNC/6GSummit58263.2023.10188375","url":null,"abstract":"Every new mobile communication generation comes with the emergence of novel applications and services. The fifth-generation (5G) is not an exception, its increased performance and flexibility are expected to provide support for a plethora of utilization scenarios, where the network can be tailored, in runtime, to the particular requirements of each use case. In particular, 5G is gaining the attention of different vertical industries as an enabler of Industry 4.0. However, adopting these technologies requires novel business models for delivering communication services. Moreover, 5G deployments are still in early stages, with novel functionalities expected to gradually emerge over the next few years. The 5GAIner laboratory provides a 5G experimentation en-vironment for the different stakeholders taking part in the 5G ecosystem. The goal is to facilitate vertical markets' digital transition to 5G by providing an environment for easy inno-vation, development, and experimentation. In this context, the paper describes the existing infrastructure, provides some initial performance results, summarises the learned lessons, and outlines the expected evolution path.","PeriodicalId":65870,"journal":{"name":"公共管理高层论坛","volume":"23 1","pages":"514-519"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83195148","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}
In this paper, we investigate the downlink (DL) precoder design in coordinated multi-point joint transmission massive multiple-input multiple-output systems. The DL precoder design problem is formulate to maximize the sum-rate under the per base station transmit power constraint. Utilizing the first-order condition, the structure of the optimal precoder is derived, involving the generalized eigenvectors of a pair of matrices. In accordance with this, the largest generalized eigenvector (LGEV) precoder is proposed to solve the first-order condition in an iterative manner, which involves solving the complicated generalized eigenvalue problem in each iteration. Specifically, we propose to solve the eigenvalue problem numerically for low-complexity implementation based on the inverse free Krylov subspace method. Simulation results demonstrate that the proposed LGEV precoder achieves satisfactory performances with fast convergences within a couple of iterations.
{"title":"Largest Generalized Eigenvector Precoder for CoMP-JT Massive MIMO Systems","authors":"Xianglong Yu, Hanqing Wang, Yiling Yuan, Xiaohan Wang, Hao Chen","doi":"10.1109/EuCNC/6GSummit58263.2023.10188356","DOIUrl":"https://doi.org/10.1109/EuCNC/6GSummit58263.2023.10188356","url":null,"abstract":"In this paper, we investigate the downlink (DL) precoder design in coordinated multi-point joint transmission massive multiple-input multiple-output systems. The DL precoder design problem is formulate to maximize the sum-rate under the per base station transmit power constraint. Utilizing the first-order condition, the structure of the optimal precoder is derived, involving the generalized eigenvectors of a pair of matrices. In accordance with this, the largest generalized eigenvector (LGEV) precoder is proposed to solve the first-order condition in an iterative manner, which involves solving the complicated generalized eigenvalue problem in each iteration. Specifically, we propose to solve the eigenvalue problem numerically for low-complexity implementation based on the inverse free Krylov subspace method. Simulation results demonstrate that the proposed LGEV precoder achieves satisfactory performances with fast convergences within a couple of iterations.","PeriodicalId":65870,"journal":{"name":"公共管理高层论坛","volume":"78 1","pages":"114-119"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79738819","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 : 2023-06-06DOI: 10.1109/EuCNC/6GSummit58263.2023.10188281
C. Stan, S. Rommel, I. Miguel, J. Olmos, R. Durán, I. Monroy
Edge computing is envisioned as a key enabler in future cellular networks by bringing the computing, networking and storage resources closer to the end users and enabling offloading for computation-intensive or latency-critical tasks coming from the emerging 5G/6G applications. Such technology also introduces additional challenges when it comes to deciding when to offload or not since the dynamic wireless environment plays a significant role in the overall communication and computation costs when offloading workload to the nearby edge nodes. In this paper, we focus on the communication cost in computation offloading via wireless channels, by formulating an $alpha$-fair utility-based radio resource allocation (RRA) problem tailored for offloading in a multi-user urban scenario where the uplink connection is the main focus. We begin by modeling the wireless channel with large- and small-scale fading at both lower and millimetre-wave frequencies, followed by data rate calculation based on 3GPP for a more realistic approach. Then, while assessing the fairness of the RRA, we simulate the resource allocation framework while taking into account both users who need to offload and users who are only interested in high downlink data rates. Simulation results show that the weighted proportional fairness method adapted for computation offloading can provide a good trade-off between fairness and performance compared to other benchmark schemes.
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