NDLI: Optimal and Sub-Optimal Spectrum Sensing of OFDM Signals in Known and Unknown Noise Variance

Content Provider	IEEE Xplore Digital Library
Author	Axell, E. Larsson, E.G.
Copyright Year	1983
Abstract	We consider spectrum sensing of OFDM signals in an AWGN channel. For the case of completely known noise and signal powers, we set up a vector-matrix model for an OFDM signal with a cyclic prefix and derive the optimal Neyman-Pearson detector from first principles. The optimal detector exploits the inherent correlation of the OFDM signal incurred by the repetition of data in the cyclic prefix, using knowledge of the length of the cyclic prefix and the length of the OFDM symbol. We compare the optimal detector to the energy detector numerically. We show that the energy detector is near-optimal (within 1 dB SNR) when the noise variance is known. Thus, when the noise power is known, no substantial gain can be achieved by using any other detector than the energy detector. For the case of completely unknown noise and signal powers, we derive a generalized likelihood ratio test (GLRT) based on empirical second-order statistics of the received data. The proposed GLRT detector exploits the non-stationary correlation structure of the OFDM signal and does not require any knowledge of the noise power or the signal power. The GLRT detector is compared to state-of-the-art OFDM signal detectors, and shown to improve the detection performance with 5 dB SNR in relevant cases.
Starting Page	290
Ending Page	304
Page Count	15
File Size	468826
File Format	PDF
ISSN	07338716
Volume Number	29
Issue Number	2
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-02-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Detectors OFDM Neodymium Synchronization Signal to noise ratio second-order statistics spectrum sensing signal detection cyclic prefix subspace detection
Content Type	Text
Resource Type	Article
Subject	Computer Networks and Communications Electrical and Electronic Engineering

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Optimal and near-optimal spectrum sensing of OFDM signals in AWGN channels

Autocorrelation-Based Decentralized Sequential Detection of OFDM Signals in Cognitive Radios

Iterative Synchronization-Assisted Detection of OFDM Signals in Cognitive Radio Systems

Advanced Spectrum Sensing for OFDM-Based Cognitive Radio Networks Using Cyclic Prefix

Multiantenna detection of constant-envelope signals in noise of unknown variance

Spectrum sensing using adaptive threshold based energy detection for OFDM signals

A random matrix approach to wide band spectrum sensing: Unknown noise variance case

Spectrum Sensing of Unsynchronized OFDM Signals for Cognitive Radio Communications

2nd Order Cyclostationarity of OFDM Signals: Impact of Pilot Tones and Cyclic Prefix

Optimal and Sub-Optimal Spectrum Sensing of OFDM Signals in Known and Unknown Noise Variance

Similar Documents

Optimal and near-optimal spectrum sensing of OFDM signals in AWGN channels

Autocorrelation-Based Decentralized Sequential Detection of OFDM Signals in Cognitive Radios

Iterative Synchronization-Assisted Detection of OFDM Signals in Cognitive Radio Systems

Advanced Spectrum Sensing for OFDM-Based Cognitive Radio Networks Using Cyclic Prefix

Multiantenna detection of constant-envelope signals in noise of unknown variance

Spectrum sensing using adaptive threshold based energy detection for OFDM signals

A random matrix approach to wide band spectrum sensing: Unknown noise variance case

Spectrum Sensing of Unsynchronized OFDM Signals for Cognitive Radio Communications

2nd Order Cyclostationarity of OFDM Signals: Impact of Pilot Tones and Cyclic Prefix

Optimal and Sub-Optimal Spectrum Sensing of OFDM Signals in Known and Unknown Noise Variance