• Journal of electromagnetic engineering and science
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• 제11권2호
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• pp.128-132
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• 2011

In interference tolerance based spectrum sharing systems, primary receivers (PRs) are protected by a predefined peak or average interference power constraint. To implement such systems, cognitive radio (CR) transmitters are required to adjust their transmit power so that the interference power received at the PR receivers is kept below the threshold value. Hence, a CR-transmitter requires knowledge of its channel and the primary receiver in order to allocate the transmit power. In practice, it is impossible or very difficult for a CR transmitter to have perfect knowledge of this channel state information (CSI). In this paper, we investigate the impact of imperfect knowledge of this CSI on the performances of both a primary and cognitive radio network. For fixed transmit power, average interference power (AIP) constraint can be maintained through knowledge of the channel distribution information. To maintain the peak interference power (PIP) constraint, on the other hand, the CR-transmitter requires the instantaneous CSI of its channel with the primary receiver. First, we show that, compared to the PIP constraint with perfect CSI, the AIP constraint is advantageous for primary users but not for CR users. Then, we consider a PIP constraint with imperfect CSI at the CR-transmitter. We show that inaccuracy in CSI reduces the interference at the PR-receivers that is caused by the CR-transmitter. Consequently the proposed schemes improve the capacity of the primary links. Contrarily, the capacities of the CR links significantly degrade due to the inaccuracy in CSI.

• Journal of Communications and Networks
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• 제15권4호
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• pp.352-361
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• 2013

Combining multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) with a massive number of transmit antennas (massive MIMO-OFDM) is an attractive way of increasing the spectrum efficiency or reducing the transmission energy per bit. The effectiveness of Massive MIMO-OFDM is strongly affected by the channel state information (CSI) estimation method used. The overheads of training frame transmission and CSI feedback decrease multiple access channel (MAC) efficiency and increase the CSI estimation cost at a user station (STA). This paper proposes a CSI estimation scheme that reduces the training frame length by using a novel pilot design and a novel unitary matrix feedback method. The proposed pilot design and unitary matrix feedback enable the access point (AP) to estimate the CSI of the signal space of all transmit antennas using a small number of training frames. Simulations in an IEEE 802.11n channel verify the attractive transmission performance of the proposed methods.

• ETRI Journal
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• 제45권6호
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• pp.929-938
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• 2023

The detection of all the symbols transmitted simultaneously in multiuser systems using limited wireless resources is challenging. Traditional model-based methods show high performance with perfect channel state information (CSI); however, severe performance degradation will occur if perfect CSI cannot be acquired. In contrast, data-driven methods perform slightly worse than model-based methods in terms of symbol error ratio performance in perfect CSI states; however, they are also able to overcome extreme performance degradation in imperfect CSI states. This study proposes a novel deep learning-based method by improving a state-of-the-art data-driven technique called deep soft interference cancellation (DSIC). The enhanced DSIC (EDSIC) method detects multiuser symbols in a fully sequential manner and uses an efficient neural network structure to ensure high performance. Additionally, error-propagation mitigation techniques are used to ensure robustness against channel uncertainty. The EDSIC guarantees a performance that is very close to the optimal performance of the existing model-based methods in perfect CSI environments and the best performance in imperfect CSI environments.

• 한국산학기술학회논문지
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• 제12권2호
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• pp.872-877
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• 2011

본 본 논문에서는 블록터보코드를 사용하는 OFDM 시스템에서 오류정정 능력을 향상시키기 위하여 블록터보코드를 디코딩하는데 있어 채널상태정보(CSI)를 이용하는 새로운 알고리듬을 제안한다. 새로운 디코딩 알고리듬은 레일레이 페이딩 환경에서 채널정보를 사용하지 않는 기존의 디코딩 알고리듬과 비교를 하였으며 실험결과 새롭게 제안된 시스템의 경우 1회의 같은 반복 횟수를 가지는 경우에 BER 성능이 신호의 변조방식에 따라 5.0dB~9.0dB 정도의 뛰어난 성능 향상을 보였다. 또한 CSI 값을 적용하고 1회 반복 복호한 시스템이 CSI값을 적용하지 않은 기존의 복호 시스템의 4회 반복 복호한 경우보다도 3.5dB~5dB의 성능 향상을 보임을 알 수 있었다. 따라서 블록터보코드를 반복 복호하는 경우에 CSI 값을 적용한 시스템이 뛰어난 성능 향상과 더불어 반복 복호 시간을 줄임을 알 수 있었다.

• Journal of Electrical Engineering and Technology
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• 제12권3호
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• pp.1286-1291
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• 2017

In this paper, we propose an indoor positioning system that makes use of the attenuation model for IEEE 802.11 Channel State Information (CSI) in order to determine its distance from an Access Point (AP) at a fixed position. With the use of CSI, we can mitigate the problems present in the use of Received Signal Strength Indicator (RSSI) data and increase the accuracy of the estimated mobile device's location. For the experiments we performed, we made use of the Intel 5300 Series Network Interface Card (NIC) in order to receive the channel frequency response. The Intel 5300 NIC differs from its counterparts in that it can obtain not only the RSSI but also the CSI between an access point and a mobile device. We can obtain the signal strengths and phases from subcarriers of a system which in turn means making use of this data in the estimation of a mobile device's position.

• 전기전자학회논문지
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• 제26권3호
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• pp.341-348
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• 2022

Wi-Fi가 거의 모든 곳에서 사용이 가능한 환경이 도래하면서 Wi-Fi 기반의 센싱 시스템의 활용가능성에 대한 학계의 주목과 함께 활발한 연구가 진행되고 있다. 최근에는 채널 상태 정보(CSI)를 활용한 딥러닝 기술의 비약적 발달로 높은 감지 성능을 달성하고 있다. 하지만, 새로운 대상 도메인에 적용하기 위해서는 명시적인 데이터 수집 및 모델 재학습 과정의 값비싼 적응 노력 없이는 여전히 실질적으로는 사용하기가 어렵다. 본 연구에서는 딥러닝 기반의 Wi-Fi 센싱 시스템을 위한 훈련데이터 수집 및 레이블링을 자동으로 진행하는 CSI 자동 레이블링 시스템(CALS)를 제안한다. 제안 시스템은 CSI 데이터 수집 과정에서 컴퓨터 비전 기술을 함께 활용하여, 지도학습용으로 수집된 CSI 데이터에 대한 레이블링을 자동으로 수행토록 하였다. CALS의 효율성을 보이기 위해 라즈베리파이를 이용하여 프로토타입 시스템을 구현하고, 실내 환경에서의 사람 존재 감지를 수행하는 3가지 모델에 대해 학습과 평가를 진행하였다. 자동 수집된 데이터를 진행하여 학습을 활용하는 방식으로 실시간 데이터에 대해 평가를 진행했을 때 90% 이상의 높은 정확도를 달성하였다.

• 한국통신학회논문지
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• 제32권7A호
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• pp.762-769
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• 2007

적응 전송 MIMO(multiple input multiple output)-OFDM(orthogonal frequency division multiplexing) 시스템은 CSI(channel state information)의 되먹임을 이용하여 각 부반송파의 채널 상황에 따라 변조 방식을 다르게 전송하는 시스템이다. CSI 되먹임 채널인 상향링크 채널에는 송수신기 처리지연, 전송 지연, 프레임 지연 등 다중 지연 요소가 존재한다. 이러한 다중 지연요소로 인한 CSI 불일치는 채널 상황에 따라 적절한 변조 방식을 결정하는데 오류를 발생시키게 되어 시스템 성능을 떨어트린다. 본 논문에서는 적응 시스템에 내장되는 다중 지연 채널 예측 방식인 CTSBP(comb type samples based prediction)와 BTSBP(block type samples based prediction)에 대해 전송 지연 및 채널 신호 대 잡음비에 따른 MSE (mean square error), 데이터 율 등 성능을 비교한다. 이를 통하여 악조건 다중경로 채널환경에 강건한 적응 전송 SISO(single input single output)-OFDM/MIMO-OFDM을 설계한다. 또한 CSI 되먹임 오버헤드를 줄이기 위한 방안으로 선형보간 방법을 제안하고 선형 보간 간격에 따른 MSE를 도출한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권1호
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• pp.253-271
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• 2017

In this paper, considering that perfect channel state information (CSI) is hard to achieve in practice, the downlink capacity of distributed antenna systems (DAS) with imperfect CSI and multiple receive antennas is investigated over composite Rayleigh fading channel. According to the performance analysis, using the numerical calculation, the probability density function (PDF) of the effective output SNR is derived. With this PDF, accurate closed-form expressions of ergodic capacity and outage probability of DAS with imperfect CSI are, respectively, obtained, and they include the ones under perfect CSI as special cases. Besides, the outage capacity of DAS in the presence of imperfect CSI is also derived, and a Newton's method based practical iterative algorithm is proposed to find the accurate outage capacity. By utilizing the Gaussian distribution approximation, another approximate closed-form expression of outage capacity is also derived, and it may simplify the calculation of accurate outage capacity. These theoretical expressions can provide good performance evaluation for downlink DAS for both perfect and imperfect CSI. Simulation results verify the effectiveness of the theoretical analysis, and the system capacity can be improved by increasing the receive antennas, and decreasing the estimation error or path loss. Moreover, the system can tolerate the estimation error variance up to about 0.01 with a slight degradation in the capacity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권11호
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• pp.5305-5321
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• 2016

In wireless communication, the multiple-input multiple-output (MIMO) system is a well-known approach to improve the reliability as well as the data rate. In MIMO systems, channel state information (CSI) is typically required at the receiver to detect transmitted signals; however, in practical systems, the CSI is imperfect and contains errors, which affect the overall system performance. In this paper, we propose a novel maximum likelihood (ML) scheme for MIMO systems that is robust to the CSI errors. We apply an optimization method to estimate an instantaneous covariance matrix of the CSI errors in order to improve the detection performance. Furthermore, we propose the employment of the list sphere decoding (LSD) scheme to reduce the computational complexity, which is capable of efficiently finding a reduced set of the candidate symbol vectors for the computation of the covariance matrix of the CSI errors. An iterative detection scheme is also proposed to further improve the detection performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권11호
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• pp.2616-2635
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• 2013

In this paper, we propose an iterative transceiver design in a multi-relay multi-user multiple-input multiple-output (MIMO) system. The design criterion is to minimize sum mean squared error (SMSE) under relay sum power constraint (RSPC) where only local channel state information (CSI)s are available at relays. Local CSI at a relay is defined as the CSI of the channel between BS and the relay in the $1^{st}$ hop link, and the CSI of the channel between the relay and all users in the $2^{nd}$ hop link. Exploiting BS transmitter structure which is concatenated with block diagonalization (BD) precoder, each relay's precoder can be determined using local CSI at the relay. The proposed scheme is based on sequential iteration of two stages; stage 1 determines BS transmitter and relay precoders jointly with SMSE duality, and stage 2 determines user receivers. We verify that the proposed scheme outperforms simple amplify-and-forward (SAF), minimum mean squared error (MMSE) relay, and an existing good scheme of [13] in terms of both SMSE and sum-rate performances.