Cyclostationary Approaches to Signal Detection and Classification in Cognitive Radio

Regulatory bodies have predicted an impending shortage in commercial radio frequency spectrum in the near future.However, due to outdated regulatory practices, many of these bands are in fact inefficiently underutilised. Spectrum measurement campaigns have be carried out around the world to determine the extent to which this is true. However, there still seems to be a lack of knowledge regarding spectrum occupancy in South Africa. A spectrum measurement system was thus designed and employed to measure the spectrum occupancy of the ultra-high frequency (UHF), global system for mobile communications (GSM) 900 MHz and GSM 1800 MHz bands through a measurement campaign in the Hatfield area of Pretoria, South Africa. A method for determining spectrum occupancy, from raw spectrum measurements, has been described and used to calculate the average spectrum occupancy of these bands. Occupancy in the UHF band was found to be fairly constant at approximately only 20%. While the maximum occupancy of the GSM 900 MHz band was calculated to be much higher at approximately 92% and that of the GSM 1800 band to be approximately 40%. However, the GSM 900 MHz and 1800 MHz bands did exhibit fluctuations in occupancy of between 10% and 20% respectively according to the time of day. Slight variations in occupancy of between 1% and 3% were also evident over the days of the week. These results are placed into context by a comparison with the findings of various other measurement campaigns from around the world. When compared, occupancy was generally found to be lower in the UHF bands but higher in the mobile bands.

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“…A decision metric Y may then be compared against this threshold to determine channel occupancy [18].…”

Section: Signal Detectionmentioning

confidence: 99%

Spectrum occupancy investigation: Measurements in South Africa

2013

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“…Cyclostationary properties are often used when little can be assumed about the signal or noise environment, such as with modulation identification [6], spectrum sensing [7], and blind channel identification [8], [9]. A cyclostationary process is one whose statistics vary periodically in time.…”

Section: Cyclostationaritymentioning

confidence: 99%

Using Higher Order Cyclostationarity to Identify Space-Time Block Codes

DeYoung

Heath

Evans

2008

IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference

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Abstract-Research in cognitive radios has renewed interest in tools, such as spectrum estimation and modulation identification, to characterize the radio frequency (RF) environment. The use of multiple antennas for multiple-input multiple-output (MIMO) communications presents a new challenge in detecting and classifying signals. In this paper, we propose a cyclostationarity-based statistical test to detect space-time block codes, focusing on the two transmitter Alamouti space-time block code (STBC). Our test exploits a new characterization of the Alamouti code using fourth order cyclic frequencies. The test requires only a single receive antenna, and does not require any symbol synchronization.

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“…The standard deviation of the instantaneous frequency and the maximum duration of a signal are extracted using time-frequency analysis in [22], [23], [36], [37] and neural networks are used for identification of active transmissions using these features. Cycle frequencies of the incoming signal are used for detection and signal classification in [30]. Signal identification is performed by processing the (cyclostationary) signal features using hidden Markov model (HMM).…”

Section: Radio Identification Based Sensingmentioning

confidence: 99%

Performance Analysis and Comparative Study of Cognitive Radio Spectrum Sensing Schemes

Singh¹

2013

IOSR-JECE

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Cyclostationary Approaches to Signal Detection and Classification in Cognitive Radio

Cited by 346 publications

References 6 publications

Spectrum occupancy investigation: Measurements in South Africa

Spectrum occupancy investigation: Measurements in South Africa

Using Higher Order Cyclostationarity to Identify Space-Time Block Codes

Performance Analysis and Comparative Study of Cognitive Radio Spectrum Sensing Schemes

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