A Low-Power Multi Resolution Spectrum Sensing Architecture for a Wireless Sensor Network with Cognitive Radio

被引:1
|
作者
Konishi, Toshihiro [1 ]
Izumi, Shintaro [1 ]
Tsuruda, Koh [1 ]
Lee, Hyeokjong [1 ]
Takeuchi, Takashi [1 ]
Yoshimoto, Masahiko [1 ]
Kawaguchi, Hiroshi [1 ]
机构
[1] Kobe Univ, Dept Comp & Syst Engn, Kobe, Hyogo 6578501, Japan
关键词
MRSS; multi-resolution spectrum sensing; cognitive radio; wireless sensor network; low power;
D O I
10.1587/transfun.E94.A.2287
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Concomitantly with the progress of wireless communications, cognitive radio has attracted attention as a solution for depleted frequency bands. Cognitive radio is suitable for wireless sensor networks because it reduces collisions and thereby achieves energy-efficient communication. To make cognitive radio practical, we propose a low-power multi-resolution spectrum sensing (MRSS) architecture that has flexibility in sensing frequency bands. The conventional MRSS scheme consumes much power and can be adapted only slightly to process scaling because it comprises analog circuits. In contrast, the proposed architecture carries out signal processing in a digital domain and can detect occupied frequency bands at multiple resolutions and with low power. Our digital MRSS module can be implemented in 180-nm and 65-nm CMOS processes using Verilog-HDL. We confirmed that the processes respectively dissipate 9.97 mW and 3.45 mW
引用
收藏
页码:2287 / 2294
页数:8
相关论文
共 50 条
  • [31] Spectrum Sensing Time Optimization Algorithm for Spectrum Efficiency Maximization in the Low-power Cognitive Radio Ultra Wideband System
    Zeng, Liaoyuan
    McGrath, Sean
    2013 INTERNATIONAL CONFERENCE ON ELECTRONIC ENGINEERING AND COMPUTER SCIENCE (EECS 2013), 2013, 4 : 68 - 73
  • [32] A LOW-POWER WIRELESS SENSOR NETWORK FOR STRUCTURAL HEALTH MONITORING
    Meyer, Jonas
    Feltrin, Glauco
    Bischoff, Reinhard
    Motavalli, Masoud
    PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON STRUCTURE HEALTH MONITORING & INTELLIGENT INFRASTRUCTURE: STRUCTURAL HEALTH MONITORING & INTELLIGENT INFRASTRUCTURE, 2007,
  • [33] A Star Low-power Wireless Sensor Network Design and Analysis
    Zhang, Yanan
    Dai, Yongshou
    Niu, Hui
    Xie, Tengteng
    2011 IET 4TH INTERNATIONAL CONFERENCE ON WIRELESS, MOBILE & MULTIMEDIA NETWORKS (ICWMMN 2011), 2011, : 18 - 21
  • [34] Design of Low-Power Wireless Sensor Network with Simplified Protocol
    Rozman, Robert
    IPSI BGD TRANSACTIONS ON INTERNET RESEARCH, 2019, 15 (01):
  • [35] Energy Optimization in Spectrum Sensing Using Cognitive Radio Wireless Sensor Networks
    Raghavendra, Y. M.
    Mahadevaswamy, U. B.
    Asha, M.
    Manjula, G.
    WIRELESS PERSONAL COMMUNICATIONS, 2023, 133 (03) : 1675 - 1691
  • [36] Energy Optimization in Spectrum Sensing Using Cognitive Radio Wireless Sensor Networks
    Y. M. Raghavendra
    U. B. Mahadevaswamy
    M. Asha
    G. Manjula
    Wireless Personal Communications, 2023, 133 : 1675 - 1691
  • [37] Design and optimization of low-power processor for wireless sensor network
    Zhao, Gang
    Hou, Ligang
    Luo, Rengui
    Liu, Yuan
    Wu, Wuchen
    Pan Tao Ti Hsueh Pao/Chinese Journal of Semiconductors, 2006, 27 (SUPPL.): : 370 - 373
  • [38] Low-power periodic task scheduling in wireless sensor network
    School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China
    Yi Qi Yi Biao Xue Bao, 2007, SUPPL. 5 (109-112):
  • [39] Low-power device for wireless sensor network for Smart Cities
    Ramirez, Cesar A.
    Barragan, R. C.
    Garcia-Torales, G.
    Larios, Victor M.
    2016 IEEE MTT-S LATIN AMERICA MICROWAVE CONFERENCE (LAMC), 2016,
  • [40] Low-Power Digital Signal Processor Architecture for Wireless Sensor Nodes
    Walravens, Cedric
    Dehaene, Wim
    IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS, 2014, 22 (02) : 313 - 321