Optimized FFT and filter bank based spectrum sensing for Bluetooth signal
Wireless Local Area Networks (WLAN) and Wireless Personal Area Networks (WPAN) such as the Bluetooth are designed to operate in 2.4 GHz ISM band. Since both IEEE 802.15 based Bluetooth and IEEE 802.11 WLAN devices, among various others, use the same frequency band, interference may lead to significa...
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creator | Dikmese, S. Renfors, M. |
description | Wireless Local Area Networks (WLAN) and Wireless Personal Area Networks (WPAN) such as the Bluetooth are designed to operate in 2.4 GHz ISM band. Since both IEEE 802.15 based Bluetooth and IEEE 802.11 WLAN devices, among various others, use the same frequency band, interference may lead to significant performance degradation. Hence, Cognitive Radio (CR) technology has been considered for coordinating better the spectrum use in this band. Spectrum sensing is one of the most important functions in a CR. In this study, energy detector based spectrum sensing techniques are optimized for detecting Bluetooth signals, considering both the effect of non-flat power spectrum and frequency hopping characteristics. To reduce complexity and required number of samples for effective spectrum sensing, optimum weighting process is proposed for subband based spectrum sensing. Bluetooth sensing is analyzed also in the presence of WLANs at nearby frequencies. |
doi_str_mv | 10.1109/WCNC.2012.6214479 |
format | Conference Proceeding |
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Since both IEEE 802.15 based Bluetooth and IEEE 802.11 WLAN devices, among various others, use the same frequency band, interference may lead to significant performance degradation. Hence, Cognitive Radio (CR) technology has been considered for coordinating better the spectrum use in this band. Spectrum sensing is one of the most important functions in a CR. In this study, energy detector based spectrum sensing techniques are optimized for detecting Bluetooth signals, considering both the effect of non-flat power spectrum and frequency hopping characteristics. To reduce complexity and required number of samples for effective spectrum sensing, optimum weighting process is proposed for subband based spectrum sensing. Bluetooth sensing is analyzed also in the presence of WLANs at nearby frequencies.</description><identifier>ISSN: 1525-3511</identifier><identifier>ISBN: 9781467304368</identifier><identifier>ISBN: 1467304360</identifier><identifier>EISSN: 1558-2612</identifier><identifier>EISBN: 1467304352</identifier><identifier>EISBN: 9781467304351</identifier><identifier>EISBN: 9781467304375</identifier><identifier>EISBN: 1467304379</identifier><identifier>DOI: 10.1109/WCNC.2012.6214479</identifier><language>eng</language><publisher>IEEE</publisher><subject>Approximation methods ; Bluetooth ; Cognitive Radio ; filter bank ; multicarrier modulation ; OFDM ; Sensors ; Signal to noise ratio ; Spectrum sensing ; Wireless LAN</subject><ispartof>2012 IEEE Wireless Communications and Networking Conference (WCNC), 2012, p.792-797</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6214479$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>310,311,781,785,790,791,2059,27930,54925</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/6214479$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Dikmese, S.</creatorcontrib><creatorcontrib>Renfors, M.</creatorcontrib><title>Optimized FFT and filter bank based spectrum sensing for Bluetooth signal</title><title>2012 IEEE Wireless Communications and Networking Conference (WCNC)</title><addtitle>WCNC</addtitle><description>Wireless Local Area Networks (WLAN) and Wireless Personal Area Networks (WPAN) such as the Bluetooth are designed to operate in 2.4 GHz ISM band. Since both IEEE 802.15 based Bluetooth and IEEE 802.11 WLAN devices, among various others, use the same frequency band, interference may lead to significant performance degradation. Hence, Cognitive Radio (CR) technology has been considered for coordinating better the spectrum use in this band. Spectrum sensing is one of the most important functions in a CR. In this study, energy detector based spectrum sensing techniques are optimized for detecting Bluetooth signals, considering both the effect of non-flat power spectrum and frequency hopping characteristics. To reduce complexity and required number of samples for effective spectrum sensing, optimum weighting process is proposed for subband based spectrum sensing. Bluetooth sensing is analyzed also in the presence of WLANs at nearby frequencies.</description><subject>Approximation methods</subject><subject>Bluetooth</subject><subject>Cognitive Radio</subject><subject>filter bank</subject><subject>multicarrier modulation</subject><subject>OFDM</subject><subject>Sensors</subject><subject>Signal to noise ratio</subject><subject>Spectrum sensing</subject><subject>Wireless LAN</subject><issn>1525-3511</issn><issn>1558-2612</issn><isbn>9781467304368</isbn><isbn>1467304360</isbn><isbn>1467304352</isbn><isbn>9781467304351</isbn><isbn>9781467304375</isbn><isbn>1467304379</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2012</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNo10L1OwzAUBWDzJ9GWPgBi8Qsk-F7bsT1C1EKlii5FjJWT3BRDmlRxOsDTU0RZzhk-6QyHsVsQKYBw92_5S56iAEwzBKWMO2NjUJmRQkmN52wEWtsEM8ALNnXG_ltmL38NdSI1wDUbx_ghBAqt1IgtVvsh7MI3VXw-X3PfVrwOzUA9L3z7eYx4lLincugPOx6pjaHd8rrr-WNzoKHrhncew7b1zQ27qn0TaXrqCXudz9b5c7JcPS3yh2USwOghUWVVSwuVLaUha6kqkLQrAMmAMIQIBXg0QNaLCmVd1g619iJThctcSXLC7v52AxFt9n3Y-f5rc7pE_gBOu1CZ</recordid><startdate>201204</startdate><enddate>201204</enddate><creator>Dikmese, S.</creator><creator>Renfors, M.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201204</creationdate><title>Optimized FFT and filter bank based spectrum sensing for Bluetooth signal</title><author>Dikmese, S. ; Renfors, M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-4cdf381d8c37e88edb2e59b12e7107e221b1a271e8a0d23fcf9255a064b969ce3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Approximation methods</topic><topic>Bluetooth</topic><topic>Cognitive Radio</topic><topic>filter bank</topic><topic>multicarrier modulation</topic><topic>OFDM</topic><topic>Sensors</topic><topic>Signal to noise ratio</topic><topic>Spectrum sensing</topic><topic>Wireless LAN</topic><toplevel>online_resources</toplevel><creatorcontrib>Dikmese, S.</creatorcontrib><creatorcontrib>Renfors, M.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Dikmese, S.</au><au>Renfors, M.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Optimized FFT and filter bank based spectrum sensing for Bluetooth signal</atitle><btitle>2012 IEEE Wireless Communications and Networking Conference (WCNC)</btitle><stitle>WCNC</stitle><date>2012-04</date><risdate>2012</risdate><spage>792</spage><epage>797</epage><pages>792-797</pages><issn>1525-3511</issn><eissn>1558-2612</eissn><isbn>9781467304368</isbn><isbn>1467304360</isbn><eisbn>1467304352</eisbn><eisbn>9781467304351</eisbn><eisbn>9781467304375</eisbn><eisbn>1467304379</eisbn><abstract>Wireless Local Area Networks (WLAN) and Wireless Personal Area Networks (WPAN) such as the Bluetooth are designed to operate in 2.4 GHz ISM band. Since both IEEE 802.15 based Bluetooth and IEEE 802.11 WLAN devices, among various others, use the same frequency band, interference may lead to significant performance degradation. Hence, Cognitive Radio (CR) technology has been considered for coordinating better the spectrum use in this band. Spectrum sensing is one of the most important functions in a CR. In this study, energy detector based spectrum sensing techniques are optimized for detecting Bluetooth signals, considering both the effect of non-flat power spectrum and frequency hopping characteristics. To reduce complexity and required number of samples for effective spectrum sensing, optimum weighting process is proposed for subband based spectrum sensing. Bluetooth sensing is analyzed also in the presence of WLANs at nearby frequencies.</abstract><pub>IEEE</pub><doi>10.1109/WCNC.2012.6214479</doi><tpages>6</tpages></addata></record> |
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source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | Approximation methods Bluetooth Cognitive Radio filter bank multicarrier modulation OFDM Sensors Signal to noise ratio Spectrum sensing Wireless LAN |
title | Optimized FFT and filter bank based spectrum sensing for Bluetooth signal |
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