Beam Alignment Using Trajectory Information in Mobile Millimeter-wave Networks

被引:0
作者
Khosravi, Sara [1 ]
Ghadikolaei, Hossein S. [3 ]
Zander, Jens [1 ]
Petrova, Marina [1 ,2 ]
机构
[1] KTH Royal Inst Technol, Sch EECS, Stockholm, Sweden
[2] Rhein Westfal TH Aachen, Mobile Commun & Comp, Aachen, Germany
[3] Ericsson Res, Stockholm, Sweden
来源
ICC 2023-IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS | 2023年
关键词
Millimeter-wave systems; terahertz systems; beamforming codebook; beam alignment;
D O I
10.1109/ICC45041.2023.10279741
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
Millimeter-wave and terahertz systems rely on beamforming/combining codebooks to determine the best beam directions during the initial access and data transmission. Existing approaches suffer from large codebook sizes and high beam searching overhead in the presence of mobile devices. To address this issue, we utilize the similarity of the channel in adjacent locations to divide the user trajectory into a set of separate regions and maintain a set of candidate beams for each region in a database. Due to the tradeoff between the number of regions and the signalling overhead, i.e., the greater number of regions results in a higher signal-to-noise ratio (SNR) but also a larger signalling overhead for the database, we propose an optimization framework to find the minimum number of regions based on the trajectory of a mobile device. Using a ray tracing tool, we demonstrate that the proposed method provides high SNR while being more robust to the location information accuracy in comparison to the lookup table baseline and fixed size region baseline.
引用
收藏
页码:1850 / 1855
页数:6
相关论文
共 13 条
  • [1] Millimeter Wave Channel Modeling and Cellular Capacity Evaluation
    Akdeniz, Mustafa Riza
    Liu, Yuanpeng
    Samimi, Mathew K.
    Sun, Shu
    Rangan, Sundeep
    Rappaport, Theodore S.
    Erkip, Elza
    [J]. IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, 2014, 32 (06) : 1164 - 1179
  • [2] [Anonymous], 2021, 3GPP TR 38.808
  • [3] Millimeter-Wave Vehicular Communication to Support Massive Automotive Sensing
    Choi, Junil
    Va, Vutha
    Gonzalez-Prelcic, Nuria
    Daniels, Robert
    Bhat, Chandra R.
    Heath, Robert W., Jr.
    [J]. IEEE COMMUNICATIONS MAGAZINE, 2016, 54 (12) : 160 - 167
  • [4] Heng Y., 2021, LEARNING PROBING BEA, P1
  • [5] Machine Learning-Assisted Beam Alignment for mmWave Systems
    Heng, Yuqiang
    Andrews, Jeffrey G.
    [J]. IEEE TRANSACTIONS ON COGNITIVE COMMUNICATIONS AND NETWORKING, 2021, 7 (04) : 1142 - 1155
  • [6] Six Key Challenges for Beam Management in 5.5G and 6G Systems
    Heng, Yuqiang
    Andrews, Jeffrey G.
    Mo, Jianhua
    Va, Vutha
    Ali, Anum
    Ng, Boon Loong
    Zhang, Jianzhong Charlie
    [J]. IEEE COMMUNICATIONS MAGAZINE, 2021, 59 (07) : 74 - 79
  • [7] Beam Management in Millimeter-Wave Communications for 5G and Beyond
    Li, Yu-Ngok Ruyue
    Gao, Bo
    Zhang, Xiaodan
    Huang, Kaibin
    [J]. IEEE ACCESS, 2020, 8 : 13282 - 13293
  • [8] Millimeter-Wave Cellular Wireless Networks: Potentials and Challenges
    Rangan, Sundeep
    Rappaport, Theodore S.
    Erkip, Elza
    [J]. PROCEEDINGS OF THE IEEE, 2014, 102 (03) : 366 - 385
  • [9] Millimeter Wave Mobile Communications for 5G Cellular: It Will Work!
    Rappaport, Theodore S.
    Sun, Shu
    Mayzus, Rimma
    Zhao, Hang
    Azar, Yaniv
    Wang, Kevin
    Wong, George N.
    Schulz, Jocelyn K.
    Samimi, Mathew
    Gutierrez, Felix
    [J]. IEEE ACCESS, 2013, 1 : 335 - 349
  • [10] Sur S., USENIX NSDI