<xml> </xml><![endif]--><!--[if gte mso 9]><xml> Normal 0 false false false EN-ID X-NONE X-NONE </xml><![endif]--><!--[if gte mso 9]><xml> </xml><![endif]--><!--[if gte mso 10]> <style> /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin-top:0cm; mso-para-margin-right:0cm; mso-para-margin-bottom:8.0pt; mso-para-margin-left:0cm; line-height:107%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri",sans-serif; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi; mso-font-kerning:1.0pt; mso-ligatures:standardcontextual; mso-fareast-language:EN-US;} </style> <![endif]-->The performance evaluation indicator for spectrum sensing results uses a receiver operating characteristic (ROC) curve based on the results of the Probability of Detection (PD) and Probability of False Alarm (PFA) calculations. The research carried out can detect the presence of LU in DoA and frequency bands that match the initial input. The use of K-means and DBSCAN as adaptive thresholds has good detection performance based on the obtained ROC curve."> <xml> </xml><![endif]--><!--[if gte mso 9]><xml> Normal 0 false false false EN-ID X-NONE X-NONE </xml><![endif]--><!--[if gte mso 9]><xml> </xml><![endif]--><!--[if gte mso 10]> <style> /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin-top:0cm; mso-para-margin-right:0cm; mso-para-margin-bottom:8.0pt; mso-para-margin-left:0cm; line-height:107%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri",sans-serif; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi; mso-font-kerning:1.0pt; mso-ligatures:standardcontextual; mso-fareast-language:EN-US;} </style> <![endif]-->The performance evaluation indicator for spectrum sensing results uses a receiver operating characteristic (ROC) curve based on the results of the Probability of Detection (PD) and Probability of False Alarm (PFA) calculations. The research carried out can detect the presence of LU in DoA and frequency bands that match the initial input. The use of K-means and DBSCAN as adaptive thresholds has good detection performance based on the obtained ROC curve.">
Laporkan Masalah

Penginderaan Spektral Daya pada Domain Sudut dan Frekeunsi

AHMAD NUGROHO JATI, Ir. Sigit Basuki Wibowo, S.T., M.Eng., Ph.D., IPM.; Dr. Dyonisius Dony Ariananda, S.T., M.Sc.

2023 | Tesis | S2 Teknik Elektro

Perkembangan teknologi nirkabel yang semakin pesat membutuhkan efisiensi pada alokasi pita frekuensi. Pemanfaatan pita frekuensi yang dilakukan secara tradisional dianggap tidak efisien sehingga menimbulkan masalah pada kelangkaan pita frekeunsi. Sistem cognitive radio (CR) dikembangkan untuk menjawab permasalahan tersebut. Sistem CR memiliki kemampuan melakukan spectrum sensing (SS) dan menemukan spektrum yang sedang kosong untuk ditempati. Cognitive radio bekerja dengan melakukan sensing pada domain frekuensi didasarkan pada estimasi Power Spectral Density (PSD). Interferensi dengan sinyal lain masih dapat terjadi saat hanya menggunakan informasi frekuensi saja sehingga sistem CR dapat mempertimbangkan Direction of Arrival (DoA) sinyal yang dikirim oleh licensed user (LU) dari perspektif secondary user (SU) untuk lebih meningkatkan utilitas spektrum. Sistem CR juga memiliki proses untuk deteksi spektrum frekuensi yang kosong berdasarkan nilai threshold. Keputusan nilai threshold didasarkan pada statistik noise pada pita tersebut secara analitik.

Penelitian ini bertujuan untuk mengurangi kemungkinan terjadinya interferensi keputusan CR dengan menambahkan informasi DoA pada estimasi PSD cognitive radio. Penentuan nilai threshold deteksi secara manual sulit untuk dilakukan pada kanal pita lebar dan tidak diketahui nilai statistik dari noise. Penelitian ini menggunakan nilai threshold adaptif menggunakan K-means clustering dan Density-based Spatial Clustering of Applications with Noise (DBDSCAN) untuk mengatasi hal tersebut. Peneliti menggunakan uniform linear array (ULA), kemudian melakukan pencuplikan sinyal yang diterima oleh setiap elemen, menghitung korelasi antara sampel, menerapkan classical beamforming, dan menghitung transformasi Fourier diskrit untuk merekonstruksi spektrum daya angular-frekuensi dua dimensi yang lengkap.

<!--[if gte mso 9]><xml> </xml><![endif]--><!--[if gte mso 9]><xml> Normal 0 false false false EN-ID X-NONE X-NONE </xml><![endif]--><!--[if gte mso 9]><xml> </xml><![endif]--><!--[if gte mso 10]> <style> /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin-top:0cm; mso-para-margin-right:0cm; mso-para-margin-bottom:8.0pt; mso-para-margin-left:0cm; line-height:107%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri",sans-serif; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi; mso-font-kerning:1.0pt; mso-ligatures:standardcontextual; mso-fareast-language:EN-US;} </style> <![endif]-->Indikator evaluasi unjuk kerja deteksi hasil spectrum sensing menggunakan kurva receiver operating characteristic (ROC) berdasarkan hasil perhitungan Probability of Detection (Pd) dan Probability of False Alarm (Pfa). Penelitian yang dilakukan dapat mendeteksi keberadaan LU pada DoA dan pita frekuensi yang sesuai dengan masukan awal. Penggunaan K-means dan DBSCAN sebagai threshold adaptif memiliki kinerja deteksi yang baik berdasarkan dari kurva ROC yang didapatkan.

The rapid development of wireless technology requires efficiency in frequency band allocation. Traditional use of frequency bands is considered inefficient, causing problems with scarcity of frequency bands. Cognitive radio (CR) systems were developed to answer these problems. The CR system has the ability to perform spectrum sensing (SS) and find an empty spectrum to occupy. Cognitive radio works by sensing in the frequency domain based on the estimated Power Spectral Density (PSD). Interference with other signals can still occur when only using frequency information so that the CR system can consider the Direction of Arrival (DoA) signal sent by the licensed user (LU) from the perspective of the secondary user (SU) to further increase spectrum utility. The CR system also has a process to determine the empty frequency spectrum detected by spectrum sensing based on a threshold value. The threshold value decision is based on the noise statistics in that band analytically.

This study aims to reduce the possibility of CR decision interference by adding DoA information to the PSD estimation. Determining the detection threshold value manually is difficult to do on wide band channels and the statistical value of noise is not known. This study uses adaptive threshold values using K-means clustering and DBDSCAN to overcome this. The researcher uses a uniform linear array (ULA), then samples the signal received by each element, calculates the correlation between the samples, applies classical beamforming, and calculates the discrete Fourier transform to reconstruct a complete two-dimensional angular-frequency power spectrum.

<!--[if gte mso 9]><xml> </xml><![endif]--><!--[if gte mso 9]><xml> Normal 0 false false false EN-ID X-NONE X-NONE </xml><![endif]--><!--[if gte mso 9]><xml> </xml><![endif]--><!--[if gte mso 10]> <style> /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin-top:0cm; mso-para-margin-right:0cm; mso-para-margin-bottom:8.0pt; mso-para-margin-left:0cm; line-height:107%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri",sans-serif; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi; mso-font-kerning:1.0pt; mso-ligatures:standardcontextual; mso-fareast-language:EN-US;} </style> <![endif]-->The performance evaluation indicator for spectrum sensing results uses a receiver operating characteristic (ROC) curve based on the results of the Probability of Detection (PD) and Probability of False Alarm (PFA) calculations. The research carried out can detect the presence of LU in DoA and frequency bands that match the initial input. The use of K-means and DBSCAN as adaptive thresholds has good detection performance based on the obtained ROC curve.

Kata Kunci : spectrum sensing, direction-of-arrival, cognitive radio, K-means, DBSCAN.

  1. S2-2023-467314-abstract.pdf  
  2. S2-2023-467314-bibliography.pdf  
  3. S2-2023-467314-tableofcontent.pdf  
  4. S2-2023-467314-title.pdf