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Access type: UnknownAuthor: search.filters.author.Mueadkhunthod, Krittiyaporn

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    5G Channel Coding Tool: Learning and Performance Evaluation
    (2023-01-01)
    Mueadkhunthod, Krittiyaporn
    ;
    Wongsa, Anusorn
    ;
    Srisupha, Thanat
    ;
    Duangthong, Chatuporn
    ;
    Puntsri, Kidsanapong
    The 5G channel coding tool is presented to explain channel coding in 5G New Radio (NR). Our tool consists of six modules such as information generator, channel encoder, modulator, noise generator, demodulator, and channel decoder. The channel encoder and modulator are developed according to 3GPP TS 38.212 and 3GPP TS 38.211 technical specifications, respectively. The 5G channel coding tool provides a graphical user interface (GUI) in which users can study the block diagrams of downlink and uplink process. In addition, our 5G channel coding tool can be used to evaluate the bit error rate performance of 5G channel coding in additive white Gaussian noise (AWGN) and fading channels.
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    Development of 5G Polar Experimental Kit
    (2022-01-01)
    Wongsa, Anusorn
    ;
    Mueadkhunthod, Krittiyaporn
    ;
    Phakphisut, Watid
    ;
    Duangthong, Chatuporn
    ;
    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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    Design of Transmission Lengths for IR-HARQ Scheme Using Q-Learning
    (2022-01-01)
    Mueadkhunthod, Krittiyaporn
    ;
    Phakphisut, Watid
    In this paper, we apply the Q-learning algorithm to design the transmission lengths of incremental redundancy hybrid automatic repeat request (IR-HARQ). The incremental redundancy (IR) bits are generated by polar codes with the polarizing matrix extension. The IR-HARQ scheme is considered as an environment, where the number of transmissions, the number of information bits, code rates, and signal-to-noise ratio (SNR) are the state of Q-learning. The reward is obtained by calculating the throughput of the successful transmission. The simulation results show that our Q-learning-based transmission lengths outperforms the fixed transmission lengths in the IR-HARO scheme.
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    Development of 5G LDPC Experimental Kit
    (2022-01-01)
    Srisupha, Thanat
    ;
    Mueadkhunthod, Krittiyaporn
    ;
    Phakphisut, Watid
    ;
    Khittiwitchayakul, Sirawit
    ;
    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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    Construction of punctured polar codes based on genetic algorithm
    (2021-05-19)
    Mueadkhunthod, Krittiyaporn
    ;
    Min Myint, Lin Min
    ;
    Supnithi, Pornchai
    ;
    Phakphisut, Watid
    In this work, we propose a new construction of punctured polar codes, which provides a good error-correcting performance at arbitrary code lengths and code rates. We exploit the density evolution to evaluate the error probability of punctured polar codes. Then, the puncturing pattern and frozen bit positions are selected by genetic algorithm to construct a punctured polar code with low error probability. The results show that the proposed technique provides superior block error rate performance than the quasi-uniform puncturing technique at a high code rate. At a low code rate, the proposed technique can show the better performance than the shortening technique.
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    An early termination technique of polar codes for IR-HARQ scheme
    (2020-10-08)
    Mueadkhunthod, Krittiyaporn
    ;
    Phakphisut, Watid
    ;
    Myint, Lin Min Min
    ;
    Supnithi, Pornchai
    In this work, we focus on polar codes in mobile communication systems where a retransmission strategy, namely, the incremental redundancy hybrid automatic repeat request (IR-HARQ) scheme, is performed. We propose an early termination (ET) of polar codes using the interleaved cyclic redundancy check (CRC) codes and the parity check (PC) codes. The parity-check equations of CRC and PC codes are used to detect the incorrectly decoded bits during the polar decoding. The simulation results verify that the proposed ET techniques can detect the erroneous bits in initial transmission and retransmission. The proposed technique provides the ET rate about 4-90%, and the block error rate (BLER) performance degradation is less than 2 dB.
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    Stock Analysis System for the Stock Exchange of Thailand
    (2019-06-01)
    Mueadkhunthod, Krittiyaporn
    ;
    Khunmood, Natchaya
    ;
    Khittiwichayakul, Sirawit
    ;
    Phakphisut, Watid
    ;
    Supnithi, Pornchai
    In this work, we develop the stock analysis system which consists of data collection, data analytic, database and android application which guides the investors to buy, sell or hold a stock. Herein, we propose the analysis of stock data in Stock Exchange of Thailand (SET) using the economic information, historical stock prices, financial statement and exchange rate. The normalized-cross correlation is used to analyze the tendencies of gross profit. Furthermore, we apply the Artificial Neural Network (ANN) to predict the net profit of a public company in SET Our prediction can provide that the prediction errors are less than 15%.