Spectrum occupancy of Malaysia radio environment for cognitive radio application

Dzulkifli, Muhammad Rajaei; Kamarudin, M. R.; Rahman, Tharek Abdul

doi:10.1049/cp.2012.2071

Cited by 8 publications

(3 citation statements)

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“…When visualizing the spectrum occupation from the measured data with the conventional model, it is found that the number of the spectrums are being used more than licensed users. This is in contrast to our expectation that the spectrum occupation is underutilized, like in other countries [1][2][3][4][5][6][7][8][9][10]. Thus, we propose a new model to achieve the more reliable spectrum utilization visualization.…”

Section: Introductionmentioning

confidence: 64%

“…Mainly, the spectra for radio broadcasting and mobile communication are more extensive than other activities due to their utilization. Many campaigns have been monitoring the broadcasting spectrum [1][2][3][4][5][6][7][8][9][10] to investigate the vacant range and reuse it for other applications. Their results point out that those spectra are underutilized, and other users should be allowed to access those spectra while they are unused.…”

Section: Introductionmentioning

confidence: 99%

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Spectrum Occupancy Model Based on Empirical Data for FM Radio Broadcasting in Suburban Environments

Chantaveerod

Woradit

Pochaiya

2021

Sensors

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It is well-known that the analog FM radio channels in suburban areas are underutilized. Before reallocating the unused channels for other applications, a regulator must analyze the spectrum occupancy. Many researchers proposed the spectrum occupancy models to find vacant spectrum. However, the existing models do not analyze each channel individually. This paper proposes an approach consisting (i) a spectrum measurement strategy, (ii) an appropriate decision threshold, and (iii) criteria for channel classification, to find the unused channels. The measurement strategy monitors each channel’s activity by capturing the power levels of the passband and the guardband separately. The decision threshold is selected depending on the monitored channel’s activity. The criteria classifies the channels based on the passband’s and guardband’s duty cycles. The results show that the proposed channel classification can identify 42 unused channels. If the power levels of wholebands (existing model) were analyzed instead of passband’s and guardband’s duty cycles, only 24 unoccupied channels were found. Furthermore, we propose the interference criteria, based on relative duty cycles across channels, to classify the abnormally used channels into interference sources and interference sinks, which have 16 and 15 channels, respectively. This information helps the dynamic spectrum sharing avoid or mitigate the interferences.

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Section: Introductionmentioning

confidence: 64%

Section: Introductionmentioning

confidence: 99%

Spectrum Occupancy Model Based on Empirical Data for FM Radio Broadcasting in Suburban Environments

Chantaveerod

Woradit

Pochaiya

2021

Sensors

View full text Add to dashboard Cite

show abstract

“…This growth is primarily due to the advent of fifth‐generation (5G) of communication systems [1] and the internet of things [2], which predicts spectrum allocation to a large number of transceivers. Spectrum allocation regulatory bodies, however, found that, although scarce, the spectrum bands are underused [3] due to the currently adopted allocation policy. In current policy, the spectrum access is given exclusively to the so‐called primary user (PU), which negotiates its access in some geographical area during some time slot.…”

Section: Introductionmentioning

confidence: 99%