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Perencanaan dan Simulasi Jaringan Small Cell Indoor Hotspots Studi Kasus di Gedung Vokasi Universitas Telkom Nugraha, Toha Ardi
Semesta Teknika Vol 20, No 1 (2017): MEI 2017
Publisher : Semesta Teknika

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Poor signal in indoor celluler network is caused by attentuation of the building  partition. In indoor areas, signal from base station transmitter cannot received perfectly in the receiver part. Therefore, this study discusses about planning of Indoor Hotspot (InH) using Small Cells technology case studi in Vocational Building Telkom University. From the network simulation, the  transmit power of the entire antennas can cover each floor as well with received signal level greater than -80 dBm with SIR level has positive value above 0dB. The lowest floor, the average received signal power values is the best value compare with the others with  received power about -40 dBm using 6 InHs. SIR best quality on the first floor of the building with the average received signal quality value of about -50 dBm using 7 InHs.
Block diagonalization precoding and power allocation for clustering small-cell networks Toha Ardi Nugraha; Indar Surahmat; Firdaus Firdaus
Bulletin of Electrical Engineering and Informatics Vol 9, No 6: December 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v9i6.2580

Abstract

The clustering network is a solution to improve data-rate transmission in small-cells. In this case, clustering small-cells (CSCs) adopt a multiple antennas concept. The multiple antennas are used to maximize the downlink data-rate transmission at the users, but it requires precoding techniques to minimize interference among CSC users. This paper proposes a block diagonalization (BD) as a precoding technique for minimizing interference among CSC users. The performance of the BD precoding implemented on the clustering network under various numbers of small-cells. The CSC also implements a water-filling power allocation (PA-CoopWF) to distribute the available transmission power along with the CSCs antennas. To show the performance, our paper simulates two types of precoding techniques; those are the proposed BD and minimum mean square error (MMSE) in CSCs. Based on the receiver user parts under the overlapping coordination of CSCs, our method based on the BD precoding achieves considerably higher data-rate transmission compared to the MMSE precoding, especially on larger clusters. The simulation also shows that by implementing CSC with the BD in short-range distances and higher numbers of antennas, it promotes better data-rate performances compared to the MMSE precoding by 2.75 times at distance 100m and 67% at 50 antennas.
Perencanaan dan Simulasi Jaringan Small Cell Indoor Hotspots Studi Kasus di Gedung Vokasi Universitas Telkom Toha Ardi Nugraha
Semesta Teknika Vol 20, No 1 (2017): MEI 2017
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/st.v20i1.2354

Abstract

Poor signal in indoor celluler network is caused by attentuation of the building  partition. In indoor areas, signal from base station transmitter cannot received perfectly in the receiver part. Therefore, this study discusses about planning of Indoor Hotspot (InH) using Small Cells technology case studi in Vocational Building Telkom University. From the network simulation, the  transmit power of the entire antennas can cover each floor as well with received signal level greater than -80 dBm with SIR level has positive value above 0dB. The lowest floor, the average received signal power values is the best value compare with the others with  received power about -40 dBm using 6 InHs. SIR best quality on the first floor of the building with the average received signal quality value of about -50 dBm using 7 InHs.
University Course Timetabling with Genetic Algorithm: A Case Study Toha Ardi Nugraha; Karisma Trinanda Putra; Nur Hayati
Journal of Electrical Technology UMY Vol 1, No 2 (2017)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jet.1213

Abstract

University Course Timetabling Problems is a scheduling problem to allocate some lectures with some constraint, such as the availability of lecturers, number of classrooms and time slot in each day. The schedule of courses is one of important factors before start the semester in order to manage the study process. Generally, the university course scheduling in some universities are usually created manually through administration office. It needs to synchronize for all schedules from all departments in faculty of the university. In addition, the limitations of classroom and timeslot can make collision of the courses, lecturers and also incompatibility between the room capacity and the number of students whom take the course in the class. This paper proposes the university course time tabling systems. Based on some simulations with 93 courses, 18 lecturers and up to six classrooms, the result is that the system will get the best violation if the system adds more number of iteration. This situation also happens in the result of the scheduling lectures, the system will get the best percentage when the number of iteration sets as maximum.
Interference Coordination Using Precoding Schemes for Indoor Hotspots Toha Ardi Nugraha
Journal of Electrical Technology UMY Vol 1, No 1 (2017)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jet.1105

Abstract

This paper investigates an interference coordination method for indoor hotspot deployment which includes cooperative communication between access points. Coordination between indoor hotspots access point with a method of coordination strategy is used by using of multiple-input multiple-output (MIMO) antennas technique. In order to achieve the capacity, some preceding technique is implemented in MIMO such as Minimum Mean Square Error (MMSE) and Block Diagonalization (BD). MMSE and BD precoding is used to coordinate the transmissions across multiple antenna in transmitter and receiver in case of multiple antenna transmissions. Water-Filling (WF) power allocation is also implemented in this scheme. This schemes is proposed to mitigate inter user interference. Based on the simulation, the results show that coordination scheme in indoor hotspots deployment using BD pre-coding demonstrates a higher data rate than MMSE. The achievable sum rate of hotspot with coordination three access points using BD better around 5 Bps/Hz compared to MMSE method in the same cases. 
Simulasi Penggunaan Frekuensi Milimeter Wave Untuk Akses Komunikasi Jaringan 5G Indoor Toha Ardi Nugraha; Alfin Hikmaturokhman
JURNAL INFOTEL Vol 9 No 1 (2017): February 2017
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v9i1.144

Abstract

Millimeter Wave (mmWave) is a solution to overcome of frequency limitations in 5G technology implementations using high frequency domain. This research discusses about mmWave frequency selection for 5G technology using empirical models in indoor propagation model. Several MmWave frequencies are simulated on indoor office environment. Based on simulation with InH placed in each room 5x5 meter size, it will be more effective using 60GHz, compared to 38Ghz, 28GHz, and 5GHz and also unlicenced 2.4. The average SIR will better at mmWave frequencies in the 60GHz with 33.97 dB and the average received signal is -73.87 dBm. Overall, it can also be concluded that the InH device with low frequency is not suitable applied indoors with massive deployement, it can be interference, for exampe using unlicenced 2.4GHz and 5GHz, receiver only gets average SIR of approximately 5dB. Keywords-5G, Indoor, Milimeter Wave, Indoor Hotspot
Tree-based Filtering in Pulse-Line Intersection Method Outputs for An Outlier-tolerant Data Processing Damarjati, Cahya; Trinanda Putra, Karisma; Wijayanto, Heri; Chen, Hsing-Chung; Nugraha, Toha Ardi
JOIV : International Journal on Informatics Visualization Vol 6, No 1 (2022)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.6.1.861

Abstract

Pulse palpation is one of the non-invasive patient observations that identify patient conditions based on the shape of the human pulse. The observations have been practiced by Traditional Chinese Medicine (TCM) practitioners since thousands of years ago. The practitioners measure the patient’s arterial pulses in three points of both patient wrists called chun, guan, and chy, then diagnose based on their knowledge and experience. Pulse-Line Intersection (PLI) method extract features of each pulse from the observed pulse wave sequence. PLI is performed by summing the number of intersections between the artificial line and the pulse wave. The method is proven in differentiating between hesitant with moderate pulse waves. As the method implemented in Clinical Decision Support System (CDSS) related to pulse palpation, some outlier data might emerge and affect the measurement result. Thus, outlier filtering is needed to prevent unnecessary prediction processes by machine learning (ML) models inside CDSS. This study proposed an outlier filtering model using a decision tree algorithm. This concept is designed by analyzing pulse features values and the chance of odd values combination. Then inappropriate values are excepted using several rules. Every pulse feature list that did not pass the filtering rule is categorized as outliers and were not included for further process. The proposed model works more efficiently than ML models dealing with outliers since this procedure is unsupervised learning with a small number of parameters. Overall, the proposed filtering method can be used in pulse measurement applications by eliminating outlier data that might decrease the performance of ML models.