Prediction and Modeling for the Time-Evolving Ultra-Wideband Channel

被引:19
|
作者
Tsao, Jonathan [1 ]
Porrat, Dana [2 ]
Tse, David [1 ]
机构
[1] Univ Calif Berkeley, Dept Elect Engn & Comp Sci, Berkeley, CA 94720 USA
[2] Hebrew Univ Jerusalem, Selim & Rachel Benin Sch Engn & Comp Sci, Engn & Comp Sci Sch, IL-91904 Jerusalem, Israel
基金
美国国家科学基金会;
关键词
Angle of arrival estimation; channel measurements; channel modeling; channel prediction; multipath channel; ultra-wideband communications;
D O I
10.1109/JSTSP.2007.906662
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
W e conduct a feasibility study of ultra-wideband (UWB) channel prediction to answer the following two questions: Is the UWB channel predictable? Is UWB channel prediction useful? We setup the problem in the following way: A receiver travels along a linear trajectory at a constant velocity. The transmitter and environment are stationary. Using past channel measurements, the receiver predicts future measurements of the channel, assuming its direction of movement and velocity remain constant. Our approach is to decompose the time evolution of the channel, which is jointly correlated in time and delay, in terms of the time evolution of individual paths, which are independent across delay. A measurement campaign was conducted in the Berkeley Wireless Research Center, where measurements were taken with line-of-sight (LOS) and non-line-of-sight (NLOS) conditions. We develop a channel prediction algorithm, and evaluate results in terms of the matched filter output energy (MFOE). Iterating through the six strongest paths, our prediction algorithm achieves more than 70% (40%) of the possible MFOE over a prediction distance of 34 cm for the LOS (NLOS) conditions. These results are good since the coherence distance, being the distance for which the channel is approximately constant, is less than 1 cm.
引用
收藏
页码:340 / 356
页数:17
相关论文
共 50 条
  • [41] Modeling and Identification of Ultra-Wideband Analog Multipliers
    Pedross-Engel, Andreas
    Schumacher, Hermann
    Witrisal, Klaus
    IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS, 2018, 65 (01) : 283 - 292
  • [42] Modeling of ultra-wideband channels within vehicles
    Richardson, PC
    Xiang, WD
    Stark, W
    IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, 2006, 24 (04) : 906 - 912
  • [43] Prediction of time-evolving sand ripples in shelf seas
    Soulsby, R. L.
    Whitehouse, R. J. S.
    Marten, K. V.
    CONTINENTAL SHELF RESEARCH, 2012, 38 : 47 - 62
  • [44] Dynamic Modeling and Forecasting of Time-evolving Data Streams
    Matsubara, Yasuko
    Sakurai, Yasushi
    KDD'19: PROCEEDINGS OF THE 25TH ACM SIGKDD INTERNATIONAL CONFERENCCE ON KNOWLEDGE DISCOVERY AND DATA MINING, 2019, : 458 - 468
  • [45] Clustered ML channel estimation for ultra-wideband signals
    Carbonelli, Cecilia
    Mitra, Urbashi
    IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2007, 6 (07) : 2412 - 2416
  • [46] Modeling and optimization of ultra-wideband intelligent reflecting surface based on time reversal
    Ge X.
    Yu K.
    Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition), 2023, 51 (03): : 7 - 16
  • [47] Bayesian Compressive Sensing for Ultra-Wideband Channel Models
    Ozgor, Mehmet
    Erkucuk, Serhat
    Cirpan, Hakan Ali
    2012 35TH INTERNATIONAL CONFERENCE ON TELECOMMUNICATIONS AND SIGNAL PROCESSING (TSP), 2012, : 320 - 324
  • [48] Directional channel model for ultra-wideband indoor applications
    Janson, Malgorzata
    Fuegen, Thomas
    Zwick, Thomas
    Wiesbeck, Werner
    2009 IEEE INTERNATIONAL CONFERENCE ON ULTRA-WIDEBAND (ICUWB 2009), 2009, : 235 - 239
  • [49] Joint Timing and Channel Estimation for Ultra-Wideband Signals
    Liu, Tao
    Zhu, Shihua
    IEICE TRANSACTIONS ON COMMUNICATIONS, 2009, E92B (02) : 499 - 506
  • [50] Ultra-Wideband Channel Sounder for Measurements at 70 GHz
    Mueller, Robert
    Haefner, Stephan
    Dupleich, Diego
    Herrmann, Ralf
    Schneider, Christian
    Thomae, Reiner S.
    Luo, Jian
    Schulz, Egon
    Lu, Xiaofeng
    Wang, Tianxiang
    2015 IEEE 81ST VEHICULAR TECHNOLOGY CONFERENCE (VTC SPRING), 2015,