An eigenvalue approach to enhance energy detection in a mobile spectrum monitoring network

Bloem, Jan-Willem van; Hendrikse, Anne; Schiphorst, Roel; Slump, Cornelis H.

doi:10.1109/icspcs.2011.6140867

Cited by 4 publications

(2 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In line with this, recently in [52] the initial results on spectrum occupancy for different types of areas were presented with the aid of SVD processing (applied to the UMTS band). Building upon this idea, we aim to enhance blind spectrum sensing for mobile spectrum monitoring by application of matrix factorization techniques for AGC noise removal.…”

Section: Research Objectivesmentioning

confidence: 82%

Removing non-stationary noise in spectrum sensing using matrix factorization

Bloem

Schiphorst

Slump

2013

EURASIP J. Adv. Signal Process.

Self Cite

View full text Add to dashboard Cite

Spectrum sensing is key to many applications like dynamic spectrum access (DSA) systems or telecom regulators who need to measure utilization of frequency bands. The International Telecommunication Union (ITU) recommends a 10 dB threshold above the noise to decide whether a channel is occupied or not. However, radio frequency (RF) receiver front-ends are non-ideal. This means that the obtained data is distorted with noise and imperfections from the analog front-end. As part of the front-end the automatic gain control (AGC) circuitry mainly affects the sensing performance as strong adjacent signals lift the noise level. To enhance the performance of spectrum sensing significantly we focus in this article on techniques to remove the noise caused by the AGC from the sensing data. In order to do this we have applied matrix factorization techniques, i.e., SVD (singular value decomposition) and NMF (non-negative matrix factorization), which enables signal space analysis. In addition, we use live measurement results to verify the performance and to remove the effects of the AGC from the sensing data using above mentioned techniques, i.e., applied on block-wise available spectrum data. In this article it is shown that the occupancy in the industrial, scientific and medical (ISM) band, obtained by using energy detection (ITU recommended threshold), can be an overestimation of spectrum usage by 60%.

show abstract

Section: Research Objectivesmentioning

confidence: 82%

Removing non-stationary noise in spectrum sensing using matrix factorization

Bloem

Schiphorst

Slump

2013

EURASIP J. Adv. Signal Process.

Self Cite

View full text Add to dashboard Cite

show abstract

“…In line with this, recently in [72] the initial results on spectrum occupancy for different types of areas were presented by using solely SVD processing (for the UMTS band). Building upon this idea, we aim to enhance the research on AGC noise removal by using and comparing different matrix factorization techniques for the 2.4 GHz ISM band in conjunction with an experimental verification.…”

Section: Research Objectivesmentioning

confidence: 79%

Coexistence of spectrum sensing of IEEE 802.11 systems for cognitive radio applications

Bloem¹

View full text Add to dashboard Cite

Most of today's short range wireless communication is based on the IEEE 802.11 standard, also referred to as Wi-Fi, which has been developed to exchange data using a certain portion of radio spectrum. However, many of today's new technologies, such as Wi-Fi, have been allocated to unlicensed spectrum bands while spectrum is scarcely available and therefore needs to be used efficiently. Nowadays, a vast majority of the Wi-Fi systems operates in the license-exempt 2.4 GHz ISM band that becomes more and more crowded due to the growing usage of Wi-Fi. On top of that, a growing number of non Wi-Fi technologies become active in this band as well. In this thesis the coexistence of Wi-Fi systems with other technologies is addressed to deal with congestion and interference issues. The focus is on spectrum sensing and detection techniques, that can be used by cognitive radio applications, to enhance the coexistence of Wi-Fi systems in the ISM band. The improvement in coexistence can be achieved through the detection of both interference sources and congestion mechanisms which in turn can assist in a more efficient usage of the radio spectrum. In addition, improvements can be made on the monitoring side to assess the spectrum usage better and thus more precisely by minimizing the influences of the measurement equipment on the observation data.First, we investigate spectrum sensing for monitoring short-range wireless technologies. We show the value of using mobile spectrum monitoring equipment and results are presented concordantly. Additionally the impact of Automatic Gain Control (AGC), an essential building block in spectrum monitoring receivers, is investigated in order to enhance spectrum sensing performance. By doing so, techniques are developed and applied to remove the AGC influences from the monitoring spectrum data. The results show that interference due to the AGC could lead to an overestimation of the actual spectrum usage by 60% in the 2.4 GHz ISM band.Secondly, the influence of interference on Wi-Fi systems has been investigated. This entails respectively interference due to non Wi-Fi technologies and co-channel interference due to overlapping Wi-Fi systems.A measurement tool has been developed to assess spectrum utilization and to measure the congestion simultaneously. The obtained results show the inefficient use of the wireless medium due to a large amount of transmission overhead which may lead to only 21% of actual data content transmitted in highly congested areas.Thirdly, the alternative use of Wi-Fi communication in the licensed UHF/VHF bands has been investigated to alleviate the congestion and interference issues in the ISM band and to access the large amount of additional available bandwidth. The operation of Wi-Fi systems in these bands is considered to be allowed under iv the condition of secondary use, i.e. avoiding interference to users with the primary rights (e.g. TV-broadcasting stations). Recently the IEEE 802.11af standard has been set up, based on cognitive radio, to provide Wi-Fi access by...

show abstract

The exploitation of Fourth Industrial Revolution technologies toward efficient spectrum management in South Africa

Moshweunyane,

Pretorius

2023

2023 IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC)

View full text Add to dashboard Cite

An eigenvalue approach to enhance energy detection in a mobile spectrum monitoring network

Cited by 4 publications

References 13 publications

Removing non-stationary noise in spectrum sensing using matrix factorization

Removing non-stationary noise in spectrum sensing using matrix factorization

Coexistence of spectrum sensing of IEEE 802.11 systems for cognitive radio applications

The exploitation of Fourth Industrial Revolution technologies toward efficient spectrum management in South Africa

Contact Info

Product

Resources

About