Pub Date : 2022-09-01DOI: 10.1109/VTC2022-Fall57202.2022.10012988
Kaizhen Liu, Xiangning Li, Haiyang Zhao, Guoping Fan
We study the question of phase retrieval aided Millimeter wave (mmWave) channel estimation and propose a sparse phase retrieval-aided mmWave channel estimation technique which can estimate the sparse mmWave channel parameters from quadratic measurements. The proposed scheme has low-cost hardware implementation compared with traditional compressed sensing-based methods and robust to carrier frequency offset caused by high-frequency hardware imperfections. Based on the proposed sparse phase retrieval-aided model, we introduce a two-stage algorithm to estimate the mmWave channel parameters (up to a global phase) and then compute the exact solution via the anchor measurements. Simulation results are provided to illustrate the effectiveness of the proposed method.
{"title":"Structured Phase Retrieval-aided Channel Estimation for Millimeter-Wave/Sub-Terahertz MIMO Systems","authors":"Kaizhen Liu, Xiangning Li, Haiyang Zhao, Guoping Fan","doi":"10.1109/VTC2022-Fall57202.2022.10012988","DOIUrl":"https://doi.org/10.1109/VTC2022-Fall57202.2022.10012988","url":null,"abstract":"We study the question of phase retrieval aided Millimeter wave (mmWave) channel estimation and propose a sparse phase retrieval-aided mmWave channel estimation technique which can estimate the sparse mmWave channel parameters from quadratic measurements. The proposed scheme has low-cost hardware implementation compared with traditional compressed sensing-based methods and robust to carrier frequency offset caused by high-frequency hardware imperfections. Based on the proposed sparse phase retrieval-aided model, we introduce a two-stage algorithm to estimate the mmWave channel parameters (up to a global phase) and then compute the exact solution via the anchor measurements. Simulation results are provided to illustrate the effectiveness of the proposed method.","PeriodicalId":326047,"journal":{"name":"2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)","volume":"39 1-4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129676010","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 : 2022-09-01DOI: 10.1109/VTC2022-Fall57202.2022.10012836
Mourad Raif, El Mehdi Ouafiq, Abdessamad El Rharras, A. Chehri, Rachid Saadane
Smart city applications are using extensively artificial intelligence for decision-making. Among the fields of application are facial recognition and intrusion detection. The subject is old, but processing techniques and hardware are constantly evolving. This paper will review the most widely known practices and apply them to a smart parking and intrusion detection system using the “JetsonNano” board. Nowadays, quality assurance for machine learning systems is becoming increasingly important. This article focuses on detecting bugs in implementing two classical face recognition algorithms: Eigenface (EF) and Local binary pattern histogram (LBPH). We tested the efficiency of our system using metamorphic testing depending on many factors: weather conditions, pixel noise, and distortion.
{"title":"Metamorphic Testing for Edge Real-Time Face Recognition and Intrusion Detection Solution","authors":"Mourad Raif, El Mehdi Ouafiq, Abdessamad El Rharras, A. Chehri, Rachid Saadane","doi":"10.1109/VTC2022-Fall57202.2022.10012836","DOIUrl":"https://doi.org/10.1109/VTC2022-Fall57202.2022.10012836","url":null,"abstract":"Smart city applications are using extensively artificial intelligence for decision-making. Among the fields of application are facial recognition and intrusion detection. The subject is old, but processing techniques and hardware are constantly evolving. This paper will review the most widely known practices and apply them to a smart parking and intrusion detection system using the “JetsonNano” board. Nowadays, quality assurance for machine learning systems is becoming increasingly important. This article focuses on detecting bugs in implementing two classical face recognition algorithms: Eigenface (EF) and Local binary pattern histogram (LBPH). We tested the efficiency of our system using metamorphic testing depending on many factors: weather conditions, pixel noise, and distortion.","PeriodicalId":326047,"journal":{"name":"2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130901766","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 : 2022-09-01DOI: 10.1109/VTC2022-Fall57202.2022.10013077
M. Mahmood, Asil Koç, T. Le-Ngoc
This work studies the joint design of hybrid pre-coding (HP) and optimal positioning of unmanned aerial vehicle (UAV) relay in a millimeter-wave (mmWave) multi-user massive multiple-input multiple-output (MU-mMIMO) systems to maximize the spectral and energy efficiencies. The UAV operates as a flying wireless relay, expanding a base station’s coverage and delivering capacity boost to a group of users/devices that are obscured by obstructions. We explore the geometry-based mmWave channel model for the UAV-User link and propose joint HP and UAV positioning scheme (JHPP). In particular, the RF beamformer is designed using singular value decomposition (SVD) of channel matrix by incorporating users’ angle-of-departure (AoD) information to reduce the number of radio frequency (RF) chains, and the baseband (BB) precoder is designed using regularized zero-forcing (RZF) technique to mitigate MU interference. Then, using a particle swarm optimization-based location algorithm (PSO-L), a constrained optimization problem with the goal of maximizing the achievable sum-rate (ASR) is constructed for the optimal UAV placement in the given search space. Illustrative results show that the integration of a UAV relay considerably enhances the performance of mmWave MU-mMIMO systems when the BS is remote. Moreover, compared to UAV random placement in the given flying span, PSO-L based UAV positioning has higher spectral/energy efficiency. Finally, the use of a hemispherical array (HSA) configuration at UAV relay can further increase the performance when compared to uniform rectangular array (URA).
{"title":"PSO-Based Joint UAV Positioning and Hybrid Precoding in UAV-Assisted Massive MIMO Systems","authors":"M. Mahmood, Asil Koç, T. Le-Ngoc","doi":"10.1109/VTC2022-Fall57202.2022.10013077","DOIUrl":"https://doi.org/10.1109/VTC2022-Fall57202.2022.10013077","url":null,"abstract":"This work studies the joint design of hybrid pre-coding (HP) and optimal positioning of unmanned aerial vehicle (UAV) relay in a millimeter-wave (mmWave) multi-user massive multiple-input multiple-output (MU-mMIMO) systems to maximize the spectral and energy efficiencies. The UAV operates as a flying wireless relay, expanding a base station’s coverage and delivering capacity boost to a group of users/devices that are obscured by obstructions. We explore the geometry-based mmWave channel model for the UAV-User link and propose joint HP and UAV positioning scheme (JHPP). In particular, the RF beamformer is designed using singular value decomposition (SVD) of channel matrix by incorporating users’ angle-of-departure (AoD) information to reduce the number of radio frequency (RF) chains, and the baseband (BB) precoder is designed using regularized zero-forcing (RZF) technique to mitigate MU interference. Then, using a particle swarm optimization-based location algorithm (PSO-L), a constrained optimization problem with the goal of maximizing the achievable sum-rate (ASR) is constructed for the optimal UAV placement in the given search space. Illustrative results show that the integration of a UAV relay considerably enhances the performance of mmWave MU-mMIMO systems when the BS is remote. Moreover, compared to UAV random placement in the given flying span, PSO-L based UAV positioning has higher spectral/energy efficiency. Finally, the use of a hemispherical array (HSA) configuration at UAV relay can further increase the performance when compared to uniform rectangular array (URA).","PeriodicalId":326047,"journal":{"name":"2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131040413","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}
Age of information (AoI) is proposed to characterize the freshness of information. Since it describes the time elapsed since the information is generated, it can accurately characterize the freshness of the information. Most of the existing studies have focused on the average AoI of systems, but time-sensitive applications such as industrial control systems and sensing networks have strict requirements for information freshness. We consider the scenario of multi-terminal wireless uplink with random packet arrivals and study the system average peak AoI (PAoI) minimization and maximum PAoI minimization problem. First we derive a closed expression of the system average PAoI and sufficient and necessary conditions of the optimal policy, from which an optimal ratio based no butter policy (OR-NB) is developed. We further generalize it to a system design method to make the average PAoI of all terminals satisfy the corresponding hard constraints. In addition, a maximum expected peak AoI (EPAoI) increasing probability minimization policy is proposed to minimize the maximum PAoI, which is proved to be near-optimal.
提出了信息时代(Age of information, AoI)来表征信息的新鲜度。由于它描述了自信息生成以来经过的时间，因此它可以准确地表征信息的新鲜度。现有的研究大多集中在系统的平均AoI上，但工业控制系统和传感网络等时间敏感应用对信息新鲜度有严格的要求。考虑随机分组到达的多终端无线上行场景，研究了系统平均峰值AoI (PAoI)最小化和最大PAoI最小化问题。首先导出了系统平均PAoI的封闭表达式和最优策略的充要条件，并由此导出了基于最优比率的无黄油策略(OR-NB)。我们进一步将其推广为一种系统设计方法，使所有终端的平均pai满足相应的硬约束。此外，提出了一种最大期望峰值AoI (EPAoI)增加概率最小化策略来最小化最大期望峰值AoI，并证明该策略是接近最优的。
{"title":"Optimal Scheduling for Minimizing Peak Age of Information in Uplink Systems","authors":"Ridong Li, Junwei Lei, Qianying Zhou, Zhengchuan Chen, Min Wang, Zhong Tian","doi":"10.1109/VTC2022-Fall57202.2022.10012764","DOIUrl":"https://doi.org/10.1109/VTC2022-Fall57202.2022.10012764","url":null,"abstract":"Age of information (AoI) is proposed to characterize the freshness of information. Since it describes the time elapsed since the information is generated, it can accurately characterize the freshness of the information. Most of the existing studies have focused on the average AoI of systems, but time-sensitive applications such as industrial control systems and sensing networks have strict requirements for information freshness. We consider the scenario of multi-terminal wireless uplink with random packet arrivals and study the system average peak AoI (PAoI) minimization and maximum PAoI minimization problem. First we derive a closed expression of the system average PAoI and sufficient and necessary conditions of the optimal policy, from which an optimal ratio based no butter policy (OR-NB) is developed. We further generalize it to a system design method to make the average PAoI of all terminals satisfy the corresponding hard constraints. In addition, a maximum expected peak AoI (EPAoI) increasing probability minimization policy is proposed to minimize the maximum PAoI, which is proved to be near-optimal.","PeriodicalId":326047,"journal":{"name":"2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130330644","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 : 2022-09-01DOI: 10.1109/VTC2022-Fall57202.2022.10013072
Hongchao Chen, Simeng Xu, Jiajia Wang, Meifang Jing, Yuhan Hu, Yi Zhao, Xiaohui Yang
This paper investigates the optimization of phase shifts at intelligent reflecting surface (IRS)-assisted multiple input single output (MISO) systems with imperfect channel state information (CSI). By utilizing the channel statistical expressions, a closed-form ergodic achievable rate expression is derived by considering channel estimation errors of the base station (BS)-user channel, BS-IRS channel and IRS-user channel for semi-passive IRS systems in which only a portion of all IRS elements has been equipped with active sensors. We further propose to apply the genetic algorithm to tackle the system ergodic achievable rate maximization problem. Simulation results show the effectiveness of our proposed scheme.
{"title":"Imperfect CSI Based Design for Intelligent Reflecting Surface Assisted MISO Systems","authors":"Hongchao Chen, Simeng Xu, Jiajia Wang, Meifang Jing, Yuhan Hu, Yi Zhao, Xiaohui Yang","doi":"10.1109/VTC2022-Fall57202.2022.10013072","DOIUrl":"https://doi.org/10.1109/VTC2022-Fall57202.2022.10013072","url":null,"abstract":"This paper investigates the optimization of phase shifts at intelligent reflecting surface (IRS)-assisted multiple input single output (MISO) systems with imperfect channel state information (CSI). By utilizing the channel statistical expressions, a closed-form ergodic achievable rate expression is derived by considering channel estimation errors of the base station (BS)-user channel, BS-IRS channel and IRS-user channel for semi-passive IRS systems in which only a portion of all IRS elements has been equipped with active sensors. We further propose to apply the genetic algorithm to tackle the system ergodic achievable rate maximization problem. Simulation results show the effectiveness of our proposed scheme.","PeriodicalId":326047,"journal":{"name":"2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129383858","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 : 2022-09-01DOI: 10.1109/VTC2022-Fall57202.2022.10012928
Yang Li, Shuyi Chen, W. Meng
Massive multiple-input-multiple-output (MIMO) and millimeter-wave (mmWave) have been adopted as the enabling technologies for the 5G and beyond 5G (B5G) systems. However, due to the large number of antennas, it is hard to obtain the channel state information (CSI) which is essential for obtaining desirable beamforming gains. Off-grid error is one of the main limiting factors of the channel estimation (CE) performance, which presents when the true angle does not lie on the discretized angle grid of mmWave channel. To address this problem, we propose a joint algorithm named off-grid approximate message passing (OG-AMP) to achieve both angular domain CE and off-grid errors eliminationin in this paper. Specially, we formulate CE issue as a Bayesian inference problem to compute the posterior of the channel coefficients and adopt the Gaussian approximation to simplify the sum-product algorithm. Our simulation results show that the proposed algorithm shows the superiority over a state-of-art benchmark method.
{"title":"Bilinear Approximate Message Passing Based Off-grid Channel Estimation for Multi-user Millimeter-Wave MIMO System","authors":"Yang Li, Shuyi Chen, W. Meng","doi":"10.1109/VTC2022-Fall57202.2022.10012928","DOIUrl":"https://doi.org/10.1109/VTC2022-Fall57202.2022.10012928","url":null,"abstract":"Massive multiple-input-multiple-output (MIMO) and millimeter-wave (mmWave) have been adopted as the enabling technologies for the 5G and beyond 5G (B5G) systems. However, due to the large number of antennas, it is hard to obtain the channel state information (CSI) which is essential for obtaining desirable beamforming gains. Off-grid error is one of the main limiting factors of the channel estimation (CE) performance, which presents when the true angle does not lie on the discretized angle grid of mmWave channel. To address this problem, we propose a joint algorithm named off-grid approximate message passing (OG-AMP) to achieve both angular domain CE and off-grid errors eliminationin in this paper. Specially, we formulate CE issue as a Bayesian inference problem to compute the posterior of the channel coefficients and adopt the Gaussian approximation to simplify the sum-product algorithm. Our simulation results show that the proposed algorithm shows the superiority over a state-of-art benchmark method.","PeriodicalId":326047,"journal":{"name":"2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126469731","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 : 2022-09-01DOI: 10.1109/VTC2022-Fall57202.2022.10012750
A. Asif, C. Liaskos, A. Pitsillides, H. K. Qureshi, M. Lestas
Metasurfaces constitute a revolutionary technology for the realization of intelligent reflecting surfaces (IRS) which can alleviate the blockage problem in mmWave and Thz communications in the absence of Line of Sight (LOS). In this work, we consider the use of multiple IRSs to provide LOS paths between a sender and a receiver via reflection. Unlike previous work, we use the directivity as a means to incorporate the metasurface reflection behavior in the channel model and parameterize with respect to the design parameters. The design problem considered is the choice of the “best” IRSs for consecutive reflection of the transmitted signal to optimize the communication channel. The problem is formulated as an optimization problem which is challenging to solve due to the dependence of each link cost on the previous link. We consider a relaxation which decouples the link costs, we apply Dijkstra’s algorithm for the solution and we show that the performance degradation as compared to the original problem which is solved using exhaustive search is not significant.
{"title":"Optimal Path Selection in Cascaded Intelligent Reflecting Surfaces","authors":"A. Asif, C. Liaskos, A. Pitsillides, H. K. Qureshi, M. Lestas","doi":"10.1109/VTC2022-Fall57202.2022.10012750","DOIUrl":"https://doi.org/10.1109/VTC2022-Fall57202.2022.10012750","url":null,"abstract":"Metasurfaces constitute a revolutionary technology for the realization of intelligent reflecting surfaces (IRS) which can alleviate the blockage problem in mmWave and Thz communications in the absence of Line of Sight (LOS). In this work, we consider the use of multiple IRSs to provide LOS paths between a sender and a receiver via reflection. Unlike previous work, we use the directivity as a means to incorporate the metasurface reflection behavior in the channel model and parameterize with respect to the design parameters. The design problem considered is the choice of the “best” IRSs for consecutive reflection of the transmitted signal to optimize the communication channel. The problem is formulated as an optimization problem which is challenging to solve due to the dependence of each link cost on the previous link. We consider a relaxation which decouples the link costs, we apply Dijkstra’s algorithm for the solution and we show that the performance degradation as compared to the original problem which is solved using exhaustive search is not significant.","PeriodicalId":326047,"journal":{"name":"2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125608040","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 : 2022-09-01DOI: 10.1109/VTC2022-Fall57202.2022.10012876
Yu Yao, Junhui Zhao, Zeqing Li, Xu Cheng, Lenan Wu, Xuan Li
Vehicle-to-vehicle (V2V) communication applications face significant challenges to security and privacy since all types of possible breaches are common in connected and autonomous vehicles (CAVs) networks. As an inheritance from conventional wireless services, illegal eavesdropping is one of the main threats to Vehicle-to-vehicle (V2V) communications. In our work, the anti-eavesdropping scheme in CAVs networks is developed through the use of cognitive risk control (CRC)-based vehicular joint radar-communication (JRC) system. In particular, the supplement of off-board measurements acquired using V2V links to the perceptual information has presented the potential to enhance the traffic target positioning precision. Then, transmission power control is performed utilizing reinforcement learning, the result of which is determined by a task switcher. Based on the threat evaluation, a multi-armed bandit (MAB) problem is designed to implement the secret key selection procedure when it is needed. Numerical experiments have presented that the developed approach has anticipated performance in terms of some risk assessment indicators.
{"title":"Cognitive Risk Control for Anti-Eavesdropping in Connected and Autonomous Vehicles Network","authors":"Yu Yao, Junhui Zhao, Zeqing Li, Xu Cheng, Lenan Wu, Xuan Li","doi":"10.1109/VTC2022-Fall57202.2022.10012876","DOIUrl":"https://doi.org/10.1109/VTC2022-Fall57202.2022.10012876","url":null,"abstract":"Vehicle-to-vehicle (V2V) communication applications face significant challenges to security and privacy since all types of possible breaches are common in connected and autonomous vehicles (CAVs) networks. As an inheritance from conventional wireless services, illegal eavesdropping is one of the main threats to Vehicle-to-vehicle (V2V) communications. In our work, the anti-eavesdropping scheme in CAVs networks is developed through the use of cognitive risk control (CRC)-based vehicular joint radar-communication (JRC) system. In particular, the supplement of off-board measurements acquired using V2V links to the perceptual information has presented the potential to enhance the traffic target positioning precision. Then, transmission power control is performed utilizing reinforcement learning, the result of which is determined by a task switcher. Based on the threat evaluation, a multi-armed bandit (MAB) problem is designed to implement the secret key selection procedure when it is needed. Numerical experiments have presented that the developed approach has anticipated performance in terms of some risk assessment indicators.","PeriodicalId":326047,"journal":{"name":"2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126042758","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 : 2022-09-01DOI: 10.1109/VTC2022-Fall57202.2022.10013059
Liang Guo, Jie Jia, Jian Chen, An Du, Xingwei Wang
In this paper, the joint task offloading and resource allocation are investigated for the semi-grant-free (SGF) non-orthogonal multiple access (NOMA) assisted mobile edge computing (MEC) system. Moreover, simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RIS) are deployed to improve the quality of wireless communications under the mode switching protocol. Each MU can partially or fully offload its task to the base station (BS) based on its differentiated channel conditions and computing capacity in the proposed MEC system. We formulate the joint task offloading, channel assignment, power allocation, and the RIS coefficients design problem to save energy consumption. The formulated problem is modeled from a long-term optimization perspective as a multi-agent Markov game (MG). Then, a multi-agent deep reinforcement learning (MADRL) based joint task offloading and resource allocation (JTORA) algorithm is proposed to solve the problem. The simulation results confirm that the applied SGF-NOMA scheme can significantly reduce energy consumption under a stringent latency constraint. Moreover, the effectiveness of the STAR-RIS and the proposed algorithm are confirmed.
{"title":"Joint Task Offloading and Resource Allocation in STAR-RIS assisted NOMA System","authors":"Liang Guo, Jie Jia, Jian Chen, An Du, Xingwei Wang","doi":"10.1109/VTC2022-Fall57202.2022.10013059","DOIUrl":"https://doi.org/10.1109/VTC2022-Fall57202.2022.10013059","url":null,"abstract":"In this paper, the joint task offloading and resource allocation are investigated for the semi-grant-free (SGF) non-orthogonal multiple access (NOMA) assisted mobile edge computing (MEC) system. Moreover, simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RIS) are deployed to improve the quality of wireless communications under the mode switching protocol. Each MU can partially or fully offload its task to the base station (BS) based on its differentiated channel conditions and computing capacity in the proposed MEC system. We formulate the joint task offloading, channel assignment, power allocation, and the RIS coefficients design problem to save energy consumption. The formulated problem is modeled from a long-term optimization perspective as a multi-agent Markov game (MG). Then, a multi-agent deep reinforcement learning (MADRL) based joint task offloading and resource allocation (JTORA) algorithm is proposed to solve the problem. The simulation results confirm that the applied SGF-NOMA scheme can significantly reduce energy consumption under a stringent latency constraint. Moreover, the effectiveness of the STAR-RIS and the proposed algorithm are confirmed.","PeriodicalId":326047,"journal":{"name":"2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)","volume":"138 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126014970","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 : 2022-09-01DOI: 10.1109/VTC2022-Fall57202.2022.10012719
Tianyi Zhou, C. Liang, Qianbin Chen
With the development of satellite communications, satellites have been equipped with edge computing capability and edge caching capability, and these advancements can further drive the development of video transmission mechanisms. In this paper, we propose to utilize in-network caching and computing of software-defined space-air-ground integrated networks to improve the quality of video experience for users. The optimization problem can be viewed as a coupling of three parts, namely, the video resolution adaptation problem, the computing resource scheduling problem, and the bandwidth provision problem. To achieve the solution of the problem effectively in practice, we deploy the alternating direction method of multipliers to decouple the three sets of variables. Numerical results demonstrate the effectiveness of the proposed scheme.
{"title":"Joint Caching and Computing of Software-Defined Space-Air-Ground Integrated Networks for Video Streaming Service Improvement","authors":"Tianyi Zhou, C. Liang, Qianbin Chen","doi":"10.1109/VTC2022-Fall57202.2022.10012719","DOIUrl":"https://doi.org/10.1109/VTC2022-Fall57202.2022.10012719","url":null,"abstract":"With the development of satellite communications, satellites have been equipped with edge computing capability and edge caching capability, and these advancements can further drive the development of video transmission mechanisms. In this paper, we propose to utilize in-network caching and computing of software-defined space-air-ground integrated networks to improve the quality of video experience for users. The optimization problem can be viewed as a coupling of three parts, namely, the video resolution adaptation problem, the computing resource scheduling problem, and the bandwidth provision problem. To achieve the solution of the problem effectively in practice, we deploy the alternating direction method of multipliers to decouple the three sets of variables. Numerical results demonstrate the effectiveness of the proposed scheme.","PeriodicalId":326047,"journal":{"name":"2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126171683","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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