The Hidden Fine-grained State Machine in Cellular Network for Simultaneous Voice and Data Services

被引:1
|
作者
Fu, Wenshan [1 ]
Bian, Kaigui [1 ]
Zhao, Tong [1 ]
Yan, Wei [1 ]
机构
[1] Peking Univ, Sch EECS, Beijing, Peoples R China
来源
2015 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM) | 2015年
关键词
D O I
10.1109/GLOCOM.2015.7417329
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The Radio Resource Control (RRC) state machine has been widely studied to improve application performance and reduce the energy consumption of smart phones. We observe that even a smart phone remains in the RRC state, there may still exist some significant performance change if it simultaneously carry on voice and data services. For example, the Round Trip Time (RTT) will get larger when a voice call comes upon, and may get even larger after finishing the voice call. We conduct in-depth study and find out the primary cause of those phenomena - smart phones may get different physical channels even in the same RRC state. In this paper, we define new states according to which physical channel is allocated to smart phones, then discover a fine-grained state machine which is hidden in the physical layer of user plane, which can explain those phenomena very well. We construct the hidden fine-grained state machine for two carriers, one only supports 3G network in most area and the other supports 4G network. The state machine can help us analyze the interference of voice to data. Using the fine-grained state machine, we also offer some suggestions on how to avoid those performance loss both from the perspective of carriers and users.
引用
收藏
页数:6
相关论文
共 50 条
  • [41] Taming the IDE with Fine-grained Interaction Data
    Minelli, Roberto
    Mocci, Andrea
    Robbes, Romain
    Lanza, Michele
    2016 IEEE 24TH INTERNATIONAL CONFERENCE ON PROGRAM COMPREHENSION (ICPC), 2016,
  • [42] Commonsense Oriented Fine-Grained Data Augmentation
    Li, Huachao
    Kang, Bin
    Wang, Lei
    Computer Engineering and Applications, 2024, 60 (06) : 214 - 221
  • [43] Fine-grained Partitioning for Aggressive Data Skipping
    Sun, Liwen
    Franklin, Michael J.
    Krishnan, Sanjay
    Xin, Reynold S.
    SIGMOD'14: PROCEEDINGS OF THE 2014 ACM SIGMOD INTERNATIONAL CONFERENCE ON MANAGEMENT OF DATA, 2014, : 1115 - 1126
  • [44] Fine-Grained Data Committing for Persistent Memory
    Lu, Tianyue
    Liu, Yuhang
    Chen, Mingyu
    2017 15TH IEEE INTERNATIONAL SYMPOSIUM ON PARALLEL AND DISTRIBUTED PROCESSING WITH APPLICATIONS AND 2017 16TH IEEE INTERNATIONAL CONFERENCE ON UBIQUITOUS COMPUTING AND COMMUNICATIONS (ISPA/IUCC 2017), 2017, : 438 - 443
  • [45] Authenticated Data Redaction with Fine-Grained Control
    Ma, Jinhua
    Liu, Jianghua
    Huang, Xinyi
    Xiang, Yang
    Wu, Wei
    IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTING, 2020, 8 (02) : 291 - 302
  • [46] A data augment method for fine-grained recognition
    Zhang Y.
    Hu Z.
    Tian S.
    Zhang, Yin (yinzh@zju.edu.cn), 2018, Computer Society of the Republic of China (29) : 12 - 18
  • [47] Fine-Tuning BERT on Coarse-Grained Labels: Exploring Hidden States for Fine-Grained Classification
    Anjum, Aftab
    Krestel, Ralf
    NATURAL LANGUAGE PROCESSING AND INFORMATION SYSTEMS, PT I, NLDB 2024, 2024, 14762 : 1 - 15
  • [48] Fine-Grained End-to-End Network Model via Vector Quantization and Hidden Markov Processes
    Ghorbanzadeh, Mo
    Chen, Yang
    Clancy, Charles
    McGwier, Robert
    2013 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC), 2013,
  • [49] Network Endpoint Congestion Control for Fine-Grained Communication
    Jiang, Nan
    Dennison, Larry
    Dally, William J.
    PROCEEDINGS OF SC15: THE INTERNATIONAL CONFERENCE FOR HIGH PERFORMANCE COMPUTING, NETWORKING, STORAGE AND ANALYSIS, 2015,
  • [50] Alignment Enhancement Network for Fine-grained Visual Categorization
    Hu, Yutao
    Liu, Xuhui
    Zhang, Baochang
    Han, Jungong
    Cao, Xianbin
    ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS, 2021, 17 (01)