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Abstrak :
ABSTRAK
Orthogonal Frequency Division Multiplexing adalah sistem komunikasi saat ini mulai banyak digunakan secara luas karena tingginya kecepatan transfer data. Kecepatan transfer data OFDM bisa mencapai 100 Mbps. Namun, tingginya kecepatan transmit data sistem OFDM membuatnya rentan terhadap fading dan noise yang dihasilkan oleh kanal. Fading dan noise ini dapat mengakibatkan terjadinya eror pada transmisi bit. Oleh karena itu, diperlukan suatu teknik yang dapat mengurangi error yang terjadi. Salah satu teknik yang banyak digunakan adalah estimasi kanal. Estimasi kanal berguna untuk mengurangi perubahan bit yang terjadi saat ditransmisikan. Pada skripsi ini, akan dijelaskan salah satu metode estimasi kanal least square dengan meggunakan pilot symbol. Estimator ini akan mengestimasi kanal yang mengandung Rayleigh fading dan AWGN terhadap penerima yang diam dan bergerak dengan kecepatan tertentu.

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ABSTRACT
Orthogonal Frequency Division Multiplexing communication system is now starting to be widely used because of the high-speed data transfer. OFDM data transfer speeds can reach 100 Mbps. However, the high speed transmits data OFDM system makes it susceptible to fading and noise generated by the channel. Fading and noise can result errors in the transmission of bits. Therefore, we need a technique that can reduce the error that occurred. One technique widely used is the estimated channel. Channel estimation is useful to reduce the error that occur when the bits transmitted. In this thesis, will be explained one of the least square method of channel estimation using pilot symbol. This estimator will estimate the channel containing the Rayleigh fading and AWGN to the fixed and moving receiver at certain speeds.

Abstrak :
Mobile VIMAX system is espexted to be an base for wireless ubiquitous products all over the world. This high mobilety communication systems need efficient channel estimation to cope high requency selectivity and time variation channel effect....

Abstrak :
Channel estimation memiliki definisi untuk memperkirakan koefisien filter melalui sinyal yang diterima dan informasi lain yang dikenal. Ada beberapa metode channel estimation yang dapat diguanakan seperti minimum mean square error, least square, zero-force, maximum likelihood. Dalam penelitian ini, least square dan zero-force akan dibahas lebih lanjut. Kedua jenis ini dikenal umum sebagai jenis yang paling sederhana dan paling mudah untuk diterapkan di dalam komunikasi nirkabel. Meskipun metode lain seperti minimum mean square error atau maximum likelihood telah dikenal secara luas untuk memperkirakan kanal, metode tersebut terbukti sangat kompleks untuk diimplementasikan. Penelitian ini bertujuan untuk memahami efek dan membandingkan kinerja channel estimation dengan menggunakan kapasitas multi antenna seperti Single-Input Single Output (SISO), Multiple-Input Single-Output (MISO), Single-Input Multiple-Output (SIMO) dan Multiple-Input Multiple-Output (MIMO). Least square dan metode estimasi zero-force telah digunakan dengan memakai modulasi Binary Phase Shift Keying (BPSK), hal ini dikarenakan BPSK adalah metode phase shift keying yang paling sederhana untuk di implementasikan di dalam penelitian ini. Pertama-tama, segala parameter perlu dikonfigurasi terlebih dahulu untuk digunakan di dalam simulasi. Kemudian, data dalam sistem pilot dikirim ke penerima menggunakan modulasi BPSK di setiap sistem multi antenna dengan menggunakan saluran nirkabel yang berbeda. Lalu, Alamouti encoder dieksekusi khusus untuk sistem MIMO dan MISO. Setelah itu, least square dan zero-force diterapkan dan tingkat kesalahan bit atau dengan nama lain bit error rate (BER) dapat dicapai dengan menyamakan sinyal yang ditransmisikan. Kemudian, analisa hasil data dengan membandingkan kinerja least square dan zero-force dapat dicapai. Pada akhirnya, hasil yang telah ditemukan menunjukkan bahwa least square melakukan performa lebih baik daripada metode estimasi zero force yang berlaku pada kinerja tingkat kesalahan bit dengan sinyal terhadap noise atau dengan nama lain signal to noise ratio (SNR). ......Channel estimation has a definition to estimate the filter coefficient through received signal and other known information. There are many methods that channel estimation can be used such as minimum mean square error, least square, zero-force, maximum likelihood. In this research, least square and zero force will be discussed further. These two types are commonly known as the simplest and easiest type to implement in the wireless communication. Even though other methods like minimum mean square error or maximum likelihood have been widely known to estimate channel, such methods are proven very complex to implement. The aimed of this research is to understand the effect and compare the performance of the channel estimation method with the capacity of multiple antennas such as Single-Input Single-Output (SISO), Multiple-Input Single-Output (MISO), Single-Input Multiple-Output (SIMO) and Multiple-Input Multiple-Output (MIMO). Least square and zero force estimation method were being used with BPSK modulation, this is due to BPSK is the simplest phase shift keying. First, the parameters need to be configured in simulation software. Then, the data within pilots system transmitted to receiver using BPSK modulation in each of the wireless antenna systems with different wireless channels. Space time block coding of Alamouti encoder were executed for MIMO and MISO system. After that, least square and zero force method were implemented and bit error rate (BER) performance can be achieved by equalizing the transmitted signal. Analysing the result by comparing the performance of least square and zero force were accomplished. In the recent result, it was shown that the least square performs better than zero force estimation method for the performance of bit error rate with signal to noise ratio.

Abstrak :
Implementasi non-orthogonal multiple access (NOMA) pada komunikasi cahaya tampak atau visible light communication (VLC) memberikan akses jamak dengan membagi daya sinyal tanpa pemisahan frekuensi ataupun spektrum warna LED pemancar. Dengan konsep umum fair power, alokasi daya perlu dirancang dengan baik agar semua pengakses memiliki probabilitas kesalahan rendah dalam penerimaan sinyal. Penelitian ini memberikan kebaruan secara khusus yaitu model alokasi daya optimal dan adaptif untuk transmisi multi level downlink sistem NOMA VLC. Kontribusi keseluruhan dibagi atas tiga kategori yaitu formulasi batasan, model alokasi daya optimal, dan model dinamik untuk daya adaptif. Digunakan unilateral M-ary pulse amplitude modulation (PAM) untuk memberikan modulasi orde tinggi dengan sinyal non riil non imajiner yang cocok bagi VLC. Pada kelompok kontribusi pertama, penelitian mendefinisikan batasan penerimaan sinyal dan kapasitas sistem berbasis successive interference cancellation (SIC), menggunakan sensitivitas komponen dan orde PAM. Batasan error diberikan untuk deteksi bertahap SIC sebagai fungsi pengkode konvolusi, modulasi, dan rasio daya. Batasan dasar berbasis orde modulasi diberikan untuk alokasi daya akses jamak SIC. Selanjutnya penelitian mengajukan kontribusi penentuan daya optimal melalui optimasi rasio daya berbasis throughput dengan model Lagrange. Secara analitik solusi optimal diperoleh melalui kondisi Karush-kuhn-Tucker (KKT) untuk dua tipe sistem, yaitu pada best-effort-service, dan quality of service (QoS), dalam bentuk persamaan tertutup dengan kompleksitas rendah. Dalam kontribusi ketiga, penelitian mengajukan model dinamik berbasis sudut dan jarak pengakses sesuai model kanal VLC Lambertian. Model dinamik ini menjadi dasar untuk alokasi daya adaptif dengan estimasi kanal menggunakan extended Kalman filter (EKF). Kinerja setiap skenario dan strategi dianalisis dengan parameter observasi utama adalah error rate (ER) pada simulasi Monte Carlo. Simulasi akhir dilakukan untuk 2, 4, dan 8-PAM, dengan 2-5 pengakses. ER rata-rata 3 pengakses di bawah 10-6 dicapai oleh skema 2-PAM pada SNR di atas 35, oleh skema 4-PAM pada SNR di atas 60, dan oleh skema 8-PAM pada SNR 84. Alokasi dinamik menggunakan EKF dengan parameter sudut membutuhkan waktu proses 1:5 dibandingkan model EKF referensi. ......Implementation of non-orthogonal multiple access (NOMA) on visible light communication (VLC) permits multiple access by rationing power among the signals for multiple users without splitting frequency or color spectrum on the LED transmitter. On regards to the fair power concept, power allocation needs to be carefully designed so that all users have a low probability of error. This research contributes specifically in proposing models optimal and adaptive power allocation in downlink VLC NOMA with higher order modulation. Contributions are categorized in three, the bounds of VLC NOMA, optimal power model, and dynamic model for adaptive power. Unilateral M-ary pulse amplitude modulation (PAM) is used to produce real and nonnegative signals which suits the system. On the first cathegory, the research defined the bounds of signal discernibility on receiver and system capacity based on successive interference cancellation (SIC), containing components sensitivity and PAM order. Error bounds were defined for the system based on SIC, containing the convolutional code design, modulation order, and the power ratio. The bounds of power ratio allocation based on PAM order is defined. Secondly the research contributed the proposed the optimal power allocation, using Lagrangian optimization on the power ratio of throughput. Solutions are defined by using Karush-kuhn-Tucker (KKT) condition in closed form low-complexity solutions for two cases, that of best effort service and that of quality of service (QoS). For the third contribution, the research proposed a dynamic model based on user angle and distance, which were parameters of Lambertian VLC channel model. The model served as the core for adaptive power allocation with channel estimation using extended Kalman filter (EKF). Completing the discussion, the research also provided an adaptive power allocation scheme by channel estimation using extended Kalman filter (EKF), based on parameters of user’s angle and distance. With error rate (ER) as the main observed parameter, Monte Carlo simulation was conducted for each observation. End simulations involved systems with 2-, 4-, and 8-PAM, serving 2-5 users. On 3 users, average ER below 10-6 was reached on 2-PAM at SNR above 35, on 4-PAM at SNR above 60, and on 8-PAM at SNR 84. Dynamic allocation using EKF with angle parameters has reduced the calculating time of 1:5 in comparison to the refered EKF.

Abstrak :
This Springerbreif introduces a threshold-based channel sparsification approach, and then, the sparsity is exploited for scalable channel training. Last but not least, this brief introduces two scalable cooperative signal detection algorithms in C-RANs. The authors wish to spur new research activities in the following important question: how to leverage the revolutionary architecture of C-RAN to attain unprecedented system capacity at an affordable cost and complexity. Cloud radio access network (C-RAN) is a novel mobile network architecture that has a lot of significance in future wireless networks like 5G. the high density of remote radio heads in C-RANs leads to severe scalability issues in terms of computational and implementation complexities. This Springerbrief undertakes a comprehensive study on scalable signal processing for C-RANs, where scalable means that the computational and implementation complexities do not grow rapidly with the network size.

Abstrak :
[ABSTRAK Pemodelan kanal propagasi menjadi isu penting di dalam sistem komunikasi nirkabel body-centric (BWCS) yang efektif dan efisien. Prediksi karakteristik path loss dapat membantu estimasi kekuatan sinyal yang diterima, optimasi dan analisis interferensi, perancangan dan analisis link budget, serta estimasi ukuran coverage. Model path loss terdiri dari tiga klasifikasi, yaitu model deterministik, empiris dan semi-empiris. Tujuan dari skripsi ini ialah mengestimasi model path loss berdasarkan hasil pengukuran pada komunikasi off-body dan on-body dengan menggunakan antena tekstil yang bekerja di frekuensi ISM 2,45 GHz di Anechoic Chamber, serta menganalisis karakteristik kanal propagasinya. Pada skripsi ini digunakan model path loss semi-empiris. Dari berbagai model yang digunakan untuk memodelkan path loss hasil pengukuran komunikasi off-body dan on-body, menunjukkan nilai root mean square error (RMSE) jauh di bawah 6 dB. Dalam skripsi ini juga dilakukan estimasi model kanal propagasi dari tiap skenario pengukuran komunikasi off-body dan on-body yang dilakukan. Pendekatan model kanal dilakukan dengan melihat kesesuaian distribusi path loss hasil pengukuran dengan jenis model kanal yang diuji. Model kanal uji yang dipakai meliputi model distribusi log-normal, Nakagami, Rayleigh, dan Ricean. Hasil analisis menunjukkan bahwa pada komunikasi off-body, model distribusi Ricean dan Nakagami sama baiknya dalam merepresentasikan data pengukuran. Selain itu, pada komunikasi on-body, fungsi distribusi kumulatif (CDF) pada model Ricean lebih mendekati hasil pengukuran daripada distribusi Nakagami.

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ABSTRACT , Channel propagation modeling is very essential for effective and efficient performance in body-centric wireless communications system (BWCS). Path loss characteristics prediction plays an important role in estimation of received signal strength, interference optimization and analysis, link budget design and analysis, and coverage area estimation. The Path loss models are commonly classified as deterministic, empirical, or semi-empirical model. This bachelor thesis is aimed to estimate path loss model based on off-body and on-body communications measurement results in Anechoic Chamber by using a textile antenna at 2,45 GHz of ISM band, and to analyze propagation channel characteristics. In this study, semi-empirical path loss model is adopted. From various path loss models that are used to estimate the propagation channel model from the measurement results in off-body and on-body communications, each root mean square errors (RMSE) of the predicted model is less than 6 dB. This thesis also estimates propagation channel model of several off-body and on-body measurement scenarios. The approached channel model is conducted by comparing the measured path loss data with some theoretical channel distribution models. Those models are log-normal, Nakagami, Rayleigh, and Ricean distribution model. The data analysis showed that as for off-body communication, either Nakagami or Ricean distribution model is equally well suited for representing the measured data. Moreover, as for on-body communication, the Ricean distribution model is suited to the measured data rather than the Nakagami model in terms of its cumulative distribution function (CDF).]