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A Combination Approach for 2-D Interference Channel Based on Factor Graph in BPMR System
(2025-02-01)
Sopon, Thanomsak
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Supnithi, Pornchai
High areal density in bit-patterned media recording (BPMR) systems encounters several challenges, such as two-dimensional (2-D) interference channels and media noises in the presence of severe fluctuations. To combat the effects of the 2-D interference channel, a factor graph-based detector (FGB) is one of the promising detectors for the 2-D detection that can mitigate the channel impairment. In this paper, we propose an improvement of factor graph decoding for 2-D interference channels of the BPMR system. The 2-D interference channel is separated into the two targets that are the upper triangular target and the lower triangular target. After that, the joint outputs are averaged for each detector. The simulation results show that the proposed FGB detector method achieves lower bit error rate (BER) performances than both the conventional FGB detector and the 2-D FGB detector on the BPMR system with an areal density of 3 and 4 Tb/in2.
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Instrumental Receiver Bias Estimation for Ionospheric Total Electron Content by Neural Network Model
(2023-10-01)
Thu, Phyo C.
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Supnithi, Pornchai
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Budtho, Jirapoom
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Saekow, Apitep
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Sopon, Thanomsak
Total Electron Content (TEC) is one of the most important parameters in the study of the ionosphere, especially for determining ionospheric disturbances. The TEC levels are typically estimated from dual-frequency GPS observation data. Since the measured TEC contains discrepancies such as satellite and receiver biases, they need to be removed to obtain more accurate TEC values. In this work, we estimate the receiver bias using a neural network technique. Based on the exhaustive evaluation, we design a neural network (NN) model with two-hidden layers, and it is trained with datasets from three GNSS observation stations in Thailand. The prediction from the proposed neural network deviates from the baseline reference using the minimum standard deviation method with significantly faster computational time. The trained NN model is also tested for estimating the receiver bias values at other untrained stations in Thailand.
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Development of 5G Polar Experimental Kit
(2022-01-01)
Wongsa, Anusorn
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Mueadkhunthod, Krittiyaporn
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Phakphisut, Watid
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Duangthong, Chatuporn
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Puntsri, Kidsanapong
The 5G polar experimental kit is presented for learning polar codes in 5G new radio. The experimental kit is developed to demonstrate the eleven encoding processes of polar codes described in 3GPP TS 38.212 technical specification. The experimental kit provides a graphical user interface (GUI) which a user can provide any the input parameters defined in the 5G new radio. The experimental kit provides a software and a hardware for a 5G polar encoder. After the polar encoder in the software or the hardware are done, the encoding results will be displayed on the GUI along with their processes details.
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Development of 5G LDPC Experimental Kit
(2022-01-01)
Srisupha, Thanat
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Mueadkhunthod, Krittiyaporn
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Phakphisut, Watid
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Khittiwitchayakul, Sirawit
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Puntsri, Kidsanapong
In this work, we develop the 5G LDPC experimental kit to demonstrate the encoding processes of LDPC codes in 5G new radio. The experimental kit consists of a graphical user interface (GUI) and an FPGA development board. Any parameters defined in the 5G new radio can be configured and their encoding results are presented in the GUI. We also develop the 5G LDPC encoder as the software module integrated within the GUI. The user can select the software or hardware for the 5G LDPC encoder. The experimental kit is simple to use and no need any complicated setups. We believe that the experimental kit would be useful to anyone interested in the LDPC 5G NR standard.
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Ionograms Scaling by Using the Convolutional Neural Network
(2021-03-10)
Thanakulketsarat, Thananphat
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Sopon, Thanomsak
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Phakphisut, Watid
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Hozumi, Kornyanat
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Wongtrairat, Wannaree
Ionosphere in F layer has the most irregularity for phenomenon occurrence of amplitude scintillation which leads to the problem in the satellite signals. Ionosphere can be observed by Ionosonde to study F2 layer critical frequency (foF2) parameter and height of F layer (h'F) parameter from the ionogram. This paper presents the convolutional neural network (CNN) to determine foF2 and h'F parameters. The simulation start from passing the ionogram images to the proposed CNN model with 2,000 epoch training. The simulated accuracies of both foF2 and h'F parameters are equal to 92.8% and 98.4%, respectively.
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Improved 2-D graph-based detectors for 2-D interference channels
(2014-11-01)
Sopon, Thanomsak
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Supnithi, Pornchai
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Vichienchom, Kasin
The 2-D interference channels, which consist of intersymbol interference as well as intertrack interference (ITI), appear in highdensity recording channels. A graph-based detector has received much attention since it is a real 2-D detector, which can recover data from multiple tracks or each 2-D page simultaneously. In this paper, we propose two approaches to improve the performances of graph-based detectors. For the first method (M1), which processes data on a 2-D page, the system equalizes 2-D interference channel into two 1-D targets, horizontal and vertical directions followed by two corresponding graph detectors. The second method (M2) is similar to the first one, but the 2-D channel is equalized into two 2-D targets with and without cornered ITIs, respectively, in order to better handle the effects of cornered ITIs. Compared with the full-graph detector, the method M1 offers reduced-complexity due the fewer number of edges from the factor nodes. The simulation results on the 3 × 3 channel matrix with 2% cornered ITI show that the proposed methods achieve the gains of about 1.0 and 1.7 dB, respectively, at the BER of 10-5 over the full graph detector. As the cornered ITI levels increase, the method M2 gives the larger gains over the others. When the media noise is accounted for, the method M2 still gives the best performances. Finally, the mutual information of the three graph detectors for the 2-D channels is computed and compared.
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Performance of Log-MAP algorithm for graph-based detections on the 2-D interference channel
(2014-01-01)
Sopon, Thanomsak
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Supnithi, Pornchai
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Vichienchom, Kasin
The read channel of magnetic recording system is affected by two-dimensional interference channel that is a combination of inter-symbol interference and inter-track interference. Inter-track interference is one of the biggest challenges in the high density magnetic recording systems and it can degrade the performance of the channels. In this work, we compare three variations of log-MAP algorithms for graph-based detectors in two-dimensional interference channels. The simulation results show the performance of the graph-based detector with the full log-MAP and extended log-MAP algorithms achieve the gains of about 0.1 and 0.05 dB at BER = 10-5, over the max approximation on bit patterned media recording system with the areal density 2.5 Tbits/in2. © 2014 IEEE.
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Modified graph-based detection methods for two-dimensional interference channels
(2012-10-29)
Sopon, Thanomsak
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Myint, Lin Min Min
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Supnithi, Pornchai
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Vichienchom, Kasin
Two-dimensional (2-D) interference channels with inter-symbol interference (ISI) and inter-track interference (ITI) exist in the magnetic recording systems at high areal density. A number of 2-D detection methods have recently been proposed for the multi-track processing of the 2-D channels. Graph-based detector with the belief propagation algorithm appears as an alternative method, but at a degraded performance and high complexity level. In this work, we propose two methods to modify the graph-based (GB) detector. One applies a serial scheduling to the GB detector, while the other modifies the GB detection by ignoring some connections during one direction of the reliability updates in the factor graph leading to the reduction of short cycles. The simulation results show that the proposed GB detectors give better bit error rate performances than the other GB detectors. © 2012 IEEE.
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Serial belief propagation for the high-rate LDPC decoders and performances in the bit patterned media systems with media noise
(2011-01-01)
Phakphisut, Watid
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Supnithi, Pornchai
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Sopon, Thanomsak
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Myint, Lin M.M.
In this work, we propose to use the serial belief propagation or serial scheduling in the 2-D bit patterned media (BPM) system with media noise. The serial scheduling methods are applied to the random LDPC codes and quasi-cyclic LDPC (QC-LDPC) codes of high code rates. Both are constructed from the progress-edge growth (PEG) algorithm. We compare the performance of the LDPC codes using the serial belief propagation and the conventional belief propagation (BP) decoding. The simulation results show that the serial scheduling provides a faster convergence speed and a better bit error rate performance than the conventional BP in an AWGN channel. The serial belief propagation is also shown to offer the performance gains over the BP decoding for the BPM system with various media noise levels. © 2011 IEEE.

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