2022 20th International Symposium on Modeling and Optimization in Mobile, Ad hoc, and Wireless Networks (WiOpt)最新文献_第4页

Cooperative Video Quality Adaptation for Delay-Sensitive Dynamic Streaming using Adaptive Super-Resolution 基于自适应超分辨率的延迟敏感动态流媒体协同视频质量自适应

2022 20th International Symposium on Modeling and Optimization in Mobile, Ad hoc, and Wireless Networks (WiOpt) Pub Date : 2022-09-19 DOI: 10.23919/WiOpt56218.2022.9930547

Minseok Choi, Won Joon Yun, Joongheon Kim

引用次数: 0

Intelligent RAN Power Saving using Balanced Model Training in Cellular Networks 基于平衡模型训练的蜂窝网络智能无线局域网省电

2022 20th International Symposium on Modeling and Optimization in Mobile, Ad hoc, and Wireless Networks (WiOpt) Pub Date : 2022-09-19 DOI: 10.23919/WiOpt56218.2022.9930603

V. Singh, M. Gupta, C. Maciocco

{"title":"Intelligent RAN Power Saving using Balanced Model Training in Cellular Networks","authors":"V. Singh, M. Gupta, C. Maciocco","doi":"10.23919/WiOpt56218.2022.9930603","DOIUrl":"https://doi.org/10.23919/WiOpt56218.2022.9930603","url":null,"abstract":"optimizing power consumption of 5G systems and next generation technology deployments is a critical problem. It is essential that the solution for optimizing power consumption takes into account the tradeoffs with maintaining service level agreement (SLA). Mobile network operator (MNO) may have different priorities for the objectives of saving power and for maintaining SLA, which depends on factors, such as customer contract, location, time of day, type of traffic, etc. In this paper, we design an intelligent solution using switching cells on-off action to save power, using machine learning (ML)/ deep learning (DL) methods to forecast future traffic load. We firstly identify the problem of training imbalance in traffic load prediction due to data imbalance in real cellular networks, and MNO preferences for the competing objectives of saving power and SLA maintenance. We then propose a novel solution that incorporates Balancing Loss Function, which addresses the training imbalance problem. Compared with the performance of previous approaches such as Mean Square Error (MSE) minimization traffic forecast based methods, we demonstrate using network field data that our method is able to achieve upto 3X improvement in service quality outage, with fairly similar power savings.","PeriodicalId":228040,"journal":{"name":"2022 20th International Symposium on Modeling and Optimization in Mobile, Ad hoc, and Wireless Networks (WiOpt)","volume":"513 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134063646","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}

引用次数: 1

Bandit Learning-based Online User Clustering and Selection for Cellular Networks 基于Bandit学习的蜂窝网络在线用户聚类与选择

2022 20th International Symposium on Modeling and Optimization in Mobile, Ad hoc, and Wireless Networks (WiOpt) Pub Date : 2022-09-19 DOI: 10.23919/WiOpt56218.2022.9930562

Isfar Tariq, Kartik Patel, T. Novlan, S. Akoum, M. Majmundar, G. Veciana, S. Shakkottai

{"title":"Bandit Learning-based Online User Clustering and Selection for Cellular Networks","authors":"Isfar Tariq, Kartik Patel, T. Novlan, S. Akoum, M. Majmundar, G. Veciana, S. Shakkottai","doi":"10.23919/WiOpt56218.2022.9930562","DOIUrl":"https://doi.org/10.23919/WiOpt56218.2022.9930562","url":null,"abstract":"Current wireless networks employ sophisticated multi-user transmission techniques to fully utilize the physical layer resources for data transmission. At the MAC layer, these techniques rely on a semi-static map that translates the channel quality of users to the potential transmission rate (more precisely, a map from the Channel Quality Index to the Modulation and Coding Scheme) for user selection and scheduling decisions. However, such a static map does not adapt to the actual deployment scenario and can lead to large performance losses. Furthermore, adaptively learning this map can be inefficient, particularly when there are a large number of users. In this work, we make this learning efficient by clustering users. Specifically, we develop an online learning approach that jointly clusters users and channel-states, and learns the associated rate regions of each cluster. This approach generates a scenario-specific map that replaces the static map that is currently used in practice. Furthermore, we show that our learning algorithm achieves sub-linear regret when compared to an omniscient genie. Next, we develop a user selection algorithm for multi-user scheduling using the learned user-clusters and associated rate regions. Our algorithms are validated on the WiNGS simulator from AT&T Labs, that implements the PHY/MAC stack and simulates the channel. We show that our algorithm can efficiently learn user clusters and the rate regions associated with the user sets for any observed channel state. Moreover, our simulations show that a deployment-scenario-specific map significantly outperforms the current static map approach for resource allocation at the MAC layer.","PeriodicalId":228040,"journal":{"name":"2022 20th International Symposium on Modeling and Optimization in Mobile, Ad hoc, and Wireless Networks (WiOpt)","volume":"142 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133685037","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}

引用次数: 0

Goal-Oriented Quantization: Applications to Convex Cost Functions with Polyhedral Decision Space 面向目标的量化:在多面体决策空间凸代价函数中的应用

2022 20th International Symposium on Modeling and Optimization in Mobile, Ad hoc, and Wireless Networks (WiOpt) Pub Date : 2022-09-19 DOI: 10.23919/WiOpt56218.2022.9930620

Hang Zou, Yifei Sun, Chao Zhang, S. Lasaulce, M. Kieffer, L. Saludjian

引用次数: 0

A timing game approach for the roll-out of new mobile technologies 新移动技术推出的计时游戏方法

2022 20th International Symposium on Modeling and Optimization in Mobile, Ad hoc, and Wireless Networks (WiOpt) Pub Date : 2022-09-19 DOI: 10.23919/WiOpt56218.2022.9930538

P. Zappalà, Amal Benhamiche, Matthieu Chardy, F. Pellegrini, Rosa Figueiredo

引用次数: 0

Parallel Retransmissions in Orthogonal Multiple Access Multiple Relay Networks 正交多址多中继网络中的并行重传

2022 20th International Symposium on Modeling and Optimization in Mobile, Ad hoc, and Wireless Networks (WiOpt) Pub Date : 2022-09-19 DOI: 10.23919/WiOpt56218.2022.9930609

Ali Al Khansa, R. Visoz, Y. Hayel, S. Lasaulce, Rasha Alkhansa

引用次数: 1

Energy-Efficient and Radio Resource Control State Aware Resource Allocation with Fairness Guarantees 具有公平保证的节能无线资源控制状态感知资源分配

2022 20th International Symposium on Modeling and Optimization in Mobile, Ad hoc, and Wireless Networks (WiOpt) Pub Date : 2022-09-19 DOI: 10.23919/WiOpt56218.2022.9930553

Alba Jano, R. S. Ganesan, Fidan Mehmeti, Serkut Ayvaşık, W. Kellerer

{"title":"Energy-Efficient and Radio Resource Control State Aware Resource Allocation with Fairness Guarantees","authors":"Alba Jano, R. S. Ganesan, Fidan Mehmeti, Serkut Ayvaşık, W. Kellerer","doi":"10.23919/WiOpt56218.2022.9930553","DOIUrl":"https://doi.org/10.23919/WiOpt56218.2022.9930553","url":null,"abstract":"In the next-generation wireless networks, energy efficiency (EE) is a fundamental requirement due to the limited battery power and the deployment of various devices in hardly accessible areas. While a plethora of approaches have been proposed to increase users’ EE, there are still many unresolved issues stemming mainly from the limited wireless resources. In this paper, we investigate the energy-efficient resource allocation, taking into account users’ radio resource control (RRC) state. We aim to achieve max-min fairness among users in an uplink orthogonal frequency-division multiple access (OFDMA) system while fulfilling data rate requirements and transmit power constraints. In particular, we avoid waste of the energy through unnecessary state transitions when no network resources are available. We study the impact of the RRC Resume procedure on users’ EE and propose allocating resources while users are in their current RRC Connected or RRC Inactive state. The solution is obtained from a constrained optimization problem, whose output is max-min fair and energy-efficient. To that end, we use generalized fractional programming and the Lagrangian dual decomposition approach to allocate the radio resources and transmission power iteratively. Using extensive realistic simulations with input parameters from measurement data, we compare the results of our approach against benchmark models and show the performance improvements RRC state awareness brings. Specifically, using our approach, the users’ EE increases by at least 10% on average.","PeriodicalId":228040,"journal":{"name":"2022 20th International Symposium on Modeling and Optimization in Mobile, Ad hoc, and Wireless Networks (WiOpt)","volume":"485 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116193312","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}

引用次数: 0

Content Caching with Personalized and Incumbent-aware Recommendation: An optimization Approach 内容缓存与个性化和现有意识的建议:一种优化方法

2022 20th International Symposium on Modeling and Optimization in Mobile, Ad hoc, and Wireless Networks (WiOpt) Pub Date : 2022-09-19 DOI: 10.23919/WiOpt56218.2022.9930536

Yi Zhao, Zhanwei Yu, Qing He, Di Yuan

引用次数: 0

Multi-User Frequency Assignment for Ultra-Reliable mmWave Two-Ray Channels 超可靠毫米波双射线信道的多用户频率分配

2022 20th International Symposium on Modeling and Optimization in Mobile, Ad hoc, and Wireless Networks (WiOpt) Pub Date : 2022-09-19 DOI: 10.23919/WiOpt56218.2022.9930571

Karl-Ludwig Besser, Eduard Axel Jorswieck, J. Coon

引用次数: 2

Beam Tracking for Dynamic mmWave Channels: A New Training Beam Sequence Design Approach 动态毫米波通道的波束跟踪:一种新的训练波束序列设计方法

2022 20th International Symposium on Modeling and Optimization in Mobile, Ad hoc, and Wireless Networks (WiOpt) Pub Date : 2022-09-16 DOI: 10.23919/WiOpt56218.2022.9930586

Deyou Zhang, Ming Xiao, M. Skoglund

引用次数: 0