A novel spectrum sensing method using multi-antennas without channel state information

2009 ◽  
Author(s):  
Abdul Rahman Al-Abbasi ◽  
Takeo Fujii
Keyword(s):  
Spectrum Sensing ◽  
Channel State Information ◽  
Channel State ◽  
State Information

scholarly journals Subcarrier-Sniffer：CSI-based Subcarrier-Level Spectrum Sensing Algorithm

2019 ◽  
Author(s):  
Zhenjiang Tan ◽  
Zheng Lu ◽  
Hongyu Sun
Keyword(s):  
Spectrum Sensing ◽  
Channel State Information ◽  
Spectrum Sharing ◽  
Smart Homes ◽  
Experimental Results ◽  
Spectrum Utilization ◽  
Channel State ◽  
State Information ◽  
Level Spectrum ◽  
Iot Devices

Abstract: As the massive deployment of the heterogeneous IoT devices in the coexisting environment such as smart homes，Traditional channel-based spectrum sharing algorithms such as CSMA has great limitations to further optimize spectrum utilization. Therefore, exploring more efficient spectrum sensing algorithm becomes hot topic these years. This paper proposes Subcarrier-Sniffer, which utilizes Channel State Information (CSI) to sense the subcarrier-level detailed status of the spectrum. In order to evaluate the performance of Subcarrier-Sniffer, we implemented Subcarrier-Sniffer by USRP B200min, and the experimental results show that when the distance between Subcarrier-Sniffer and the monitored devices is not great than 7 m, the accuracy of subcarrier-level spectrum sensing could achieve 100% in our settings.

scholarly journals A Novel Subcarrier-Level Spectrum Sensing Method by Utilizing Fine-Grained Channel State Information in Wireless Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Zheng Lu ◽  
Handong Wang ◽  
Hongyu Sun ◽  
Chin-Ling Chen ◽  
Zhenjiang Tan
Keyword(s):  
Spectrum Sensing ◽  
Channel State Information ◽  
Utilization Efficiency ◽  
Spectrum Utilization ◽  
Channel State ◽  
State Information ◽  
Wireless Technologies ◽  
Ism Band ◽  
Fine Grained ◽  
Level Spectrum

Traditionally, the channelization structures of wireless technologies (802.11/ZigBee/BLE) have been fixed. Each node content for the spectrum is assigned one channel with a specific bandwidth. However, classical channel-based spectrum sensing and sharing algorithms have great limitations to further optimize spectrum utilization when multiple IoT with different wireless technologies coexisting in the same environment. Therefore, exploring the fine-grained spectrum sensing algorithm becomes an essential work to further improve the spectrum utilization efficiency, especially in the Industrial Scientific Medical (ISM) band. This paper proposes Subcarrier-Sniffer, a novel subcarrier-level spectrum sensing and sharing method, which utilizes channel state information (CSI) to sense the fine-grained status of each subcarrier of the traditional channel. To evaluate the performance of Subcarrier-Sniffer, we implemented Subcarrier-Sniffer by USRP B200min, and the experimental results show that the accuracy of subcarrier-level spectrum sensing could achieve 100% in our settings that the distance between Subcarrier-Sniffer and the monitor is not greater than 7 m. Subcarrier-Sniffer could be applied in WiFi and ZigBee, WiFi and BLE, and WiFi and LTE-U coexisted environments for better spectrum utilization.

scholarly journals A Novel Spectrum Sensing Without Channel State Information Using Estimated Parameters

2010 ◽  
Author(s):  
Pham Duy Phong ◽  
Dang Trung Chinh ◽  
Vu Van Yem
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Channel State Information ◽  
Multiple Antennas ◽  
The Other ◽  
Multiple Antenna ◽  
Channel State ◽  
State Information ◽  
Estimated Parameters ◽  
A New Technique

this  paper  develops  a  spectrum  sensing technique using multiple antenna and energy detector in cognitive  radio.  The  conventional  spectrum  sensing techniques  using  multiple  antennas  such  as  maximum ratio  processing  (MRP),  Equal  Gain  Combining (EGC)…  require  channel  state  information  (CSI)  to combine  received signal at each antenna. In practice, it is complicate and requires time to obtain CSI. Recently, some  methods  performing  spectrum  sensing  without CSI  have  been  proposed.  However,  these  methods  do not  bring  desired  results  compared  with  the conventional techniques using CSI. In our research, we propose  a  new  technique  without  requiring  CSI  to combine  signals from  multiple  antennas.  The  proposed technique  brings  good  results  compared  to  the  other conventional  techniques  requiring  CSI  like  EGC.  In addition,  we  do  not  assume  exact  parameters  of  signal and noise in our simulation. The samples at the receiver are used for two purposes: estimating these parameters of noise and signal and performing spectrum sensing

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