• Title/Summary/Keyword: Soft Decision Detection

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Channel Estimation Using Virtual Pilot Signal for MIMO-OFDM Systems (MIMO-OFDM 시스템을 위한 가상 기준 신호를 이용한 채널 추정 기법)

  • Seo, Heejin;Park, Sunho;Kim, Jinhong;Shim, Byonghyo
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.27 no.1
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    • pp.27-32
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    • 2016
  • In this paper, we proposed a soft decision-directed channel estimation based on MMSE estimation for MIMO-OFDM system. While the conventional method employs only pilot signals for channel estimation, the proposed algorithm performs channel estimation using pilot and reliable data signals. We also proposed selection criterion among reliable data signal for channel estimation. From numerical simulations, we show that the proposed channel estimator achieves 1 dB performance gain over conventional channel estimators.

Monte Carlo Simulation based Optimal Aiming Point Computation Against Multiple Soft Targets on Ground (몬테칼로 시뮬레이션 기반의 다수 지상 연성표적에 대한 최적 조준점 산출)

  • Kim, Jong-Hwan;Ahn, Nam-Su
    • Journal of the Korea Society for Simulation
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    • v.29 no.1
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    • pp.47-55
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    • 2020
  • This paper presents a real-time autonomous computation of shot numbers and aiming points against multiple soft targets on grounds by applying an unsupervised learning, k-mean clustering and Monte carlo simulation. For this computation, a 100 × 200 square meters size of virtual battlefield is created where an augmented enemy infantry platoon unit attacks, defences, and is scatted, and a virtual weapon with a lethal range of 15m is modeled. In order to determine damage types of the enemy unit: no damage, light wound, heavy wound and death, Monte carlo simulation is performed to apply the Carlton damage function for the damage effect of the soft targets. In addition, in order to achieve the damage effectiveness of the enemy units in line with the commander's intention, the optimal shot numbers and aiming point locations are calculated in less than 0.4 seconds by applying the k-mean clustering and repetitive Monte carlo simulation. It is hoped that this study will help to develop a system that reduces the decision time for 'detection-decision-shoot' process in battalion-scaled combat units operating Dronebot combat system.

Soft-Decision Algorithm with Low Complexity for MIMO Systems Using High-Order Modulations (고차 변조 방식을 사용하는 MIMO 시스템을 위한 낮은 복잡도를 갖는 연판정 알고리즘)

  • Lee, Jaeyoon;Kim, Kyoungtaek
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.40 no.6
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    • pp.981-989
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    • 2015
  • In a log likelihood ratio(LLR) calculation of the detected symbol, multiple-input multiple-output(MIMO) system applying an optimal or suboptimal algorithm such as a maximum likelihood(ML) detection, sphere decoding(SD), and QR decomposition with M-algorithm Maximum Likelihood Detection(QRM-MLD) suffers from exponential complexity growth with number of spatial streams and modulation order. In this paper, we propose a LLR calculation method with very low complexity in the QRM-MLD based symbol detector for a high order modulation based $N_T{\times}N_R$ MIMO system. It is able to approach bit error rate(BER) performance of full maximum likelihood detector to within 1 dB. We also analyze the BER performance through computer simulation to verify the validity of the proposed method.

Experimental Performance Analysis of BCJR-Based Turbo Equalizer in Underwater Acoustic Communication (수중음향통신에서 BCJR 기반의 터보 등화기 실험 성능 분석)

  • Ahn, Tae-Seok;Jung, Ji-Won
    • Journal of Navigation and Port Research
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    • v.39 no.4
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    • pp.293-297
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    • 2015
  • Underwater acoustic communications has been limited use for military purposes in the past. However, the fields of underwater applications expend to detection, submarine and communication in recent. The excessive multipath encountered in underwater acoustic communication channel is creating inter symbol interference, which is limiting factor to achieve a high data rate and bit error rate performance. To improve the performance of a received signal in underwater communication, many researchers have been studied for channel coding scheme with excellent performance at low SNR. In this paper, we applied BCJR decoder based ( 2,1,7 ) convolution codes and to compensate for the distorted data induced by the multipath, we applying the turbo equalization method. Through the underwater experiment on the Gyeungcheun lake located in Mungyeng city, we confirmed that turbo equalization structure of BCJR has better performance than hard decision and soft decision of Viterbi decoding. We also confirmed that the error rate of decoder input is less than error rate of $10^{-1}$, all the data is decoded. We achieved sucess rate of 83% through the experiment.

Iterative Phase estimation based on Turbo code (터보부호를 이용한 반복 위상 추정기법)

  • Ryu, Joong-Gon;Heo, Jun
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.43 no.12 s.354
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    • pp.1-8
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    • 2006
  • In this paper, we propose carrier phase synchronization algorithm which are base on turbo coded system for DVB-RCS. There have been two categories of phase estimator, single estimator outside turbo code decoder and multiple estimators inside turbo code decoder. In single estimator, we use the estimation algorithm that ML(Maximum Likelihood) and LMS(Least Mean Square), also three different soft decision methods are proposed. Multiple estimator apply PSP(Per Survivor Processing) algorithm additionally. We compared performance between single estimator and Multiple estimator in AWGN channel. We presented the two methods of PSP algorithm for performance elevation. First is the Bi-directional channel estimation and second is binding method.

Clinical Usefulness of PET-MRI in Lymph Node Metastasis Evaluation of Head and Neck Cancer (두경부암 림프절 전이 평가에서 PET-MRI의 임상적 유용성)

  • Kim, Jung-Soo;Lee, Hong-Jae;Kim, Jin-Eui
    • The Korean Journal of Nuclear Medicine Technology
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    • v.18 no.1
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    • pp.26-32
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    • 2014
  • Purpose: As PET-MRI which has excellent soft tissue contrast is developed as integration system, many researches about clinical application are being conducted by comparing with existing display equipments. Because PET-MRI is actively used for head and neck cancer diagnosis in our hospital, lymph node metastasis before the patient's surgery was diagnosed and clinical usefulness of head and neck cancer PET-MRI scan was evaluated using pathological opinions and idiopathy surrounding tissue metastasis evaluation method. Materials and Methods: Targeting 100 head and neck cancer patients in SNUH from January to August in 2013. $^{18}F-FDG$ (5.18 MBq/kg) was intravenous injected and after 60 min of rest, torso (body TIM coil, Vibe-Dixon) and dedication (head-neck TIM coil, UTE, Dotarem injection) scans were conducted using $Bio-graph^{TM}$ mMR 3T (SIEMENS, Munich). Data were reorganized using iterative reconstruction and lymph node metastasis was read with Syngo.Via workstation. Subsequently, pathological observations and diagnosis before-and-after surgery were examined with integrated medical information system (EMR, best-care) in SNUH. Patient's diagnostic information was entered in each category of $2{\times}2$ decision matrix and was classified into true positive (TP), true negative (TN), false positive (FP) and false negative (FN). Based on these classified test results, sensitivity, specificity, accuracy, false negative and false positive rate were calculated. Results: In PET-MRI scan results of head and neck cancer patients, positive and negative cases of lymph node metastasis were 49 and 51 cases respectively and positive and negative lymph node metastasis through before-and-after surgery pathological results were 46 and 54 cases respectively. In both tests, TP which received positive lymph node metastasis were analyzed as 34 cases, FP which received positive lymph node metastasis in PET-MRI scan but received negative lymph node metastasis in pathological test were 4 cases, FN which received negative lymph node metastasis but received positive lymph node metastasis in pathological test was 1 case, and TN which received negative lymph node metastasis in both two tests were 50 cases. Based on these data, sensitivity in PET-MRI scan of head and neck cancer patient was identified to be 97.8%, specificity was 92.5%, accuracy was 95%, FN rate was 2.1% and FP rate was 7.00% respectively. Conclusion: PET-MRI which can apply the acquired functional information using high tissue contrast and various sequences was considered to be useful in determining the weapons before-and-after surgery in head and neck cancer diagnosis or in the evaluation of recurrence and remote detection of metastasis and uncertain idiopathy cervical lymph node metastasis. Additionally, clinical usefulness of PET-MRI through pathological test and integrated diagnosis and follow-up scan was considered to be sufficient as a standard diagnosis scan of head and neck cancer, and additional researches about the development of optimum MR sequence and clinical application are required.

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