• 제목/요약/키워드: Gaussian channel

검색결과 513건 처리시간 0.036초

Channel Capacity for NOMA Weak Channel User and Capacity Region for NOMA with Gaussian Mixture Interference

  • Chung, Kyuhyuk
    • 전기전자학회논문지
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    • 제23권1호
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    • pp.302-305
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    • 2019
  • Non-orthogonal multiple access (NOMA) has been considered for the fifth generation (5G) mobile networks to provide high system capacity and low latency. We calculate the channel capacity for the weak channel user in NOMA and the channel capacity region for NOMA. In this paper, Gaussian mixture channel is compared to the additive white Gaussian noise (AWGN) channel. Gaussian mixture channel is modeled when we assume the practical signal modulation for the inter user interference, such as the binary phase shift keying (BPSK) modulation. It is shown that the channel capacity with BPSK inter user interference is better than that with Gaussian inter user interference. We also show that the channel capacity region with BPSK inter user interference is larger than that with Gaussian inter user interference. As a result, NOMA could perform better in the practical environments.

Gaussian Weighted CFCM for Blind Equalization of Linear/Nonlinear Channel

  • Han, Soo-Whan
    • 융합신호처리학회논문지
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    • 제14권3호
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    • pp.169-180
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    • 2013
  • The modification of conditional Fuzzy C-Means (CFCM) with Gaussian weights (CFCM_GW) is accomplished for blind equalization of channels in this paper. The proposed CFCM_GW can deal with both of linear and nonlinear channels, because it searches for the optimal desired states of an unknown channel in a direct manner, which is not dependent on the type of channel structure. In the search procedure of CFCM_GW, the Bayesian likelihood fitness function, the Gaussian weighted partition matrix and the conditional constraint are exploited. Especially, in contrast to the common Euclidean distance in conventional Fuzzy C-Means(FCM), the Gaussian weighted partition matrix and the conditional constraint in the proposed CFCM_GW make it more robust to the heavy noise communication environment. The selected channel states by CFCM_GW are always close to the optimal set of a channel even when the additive white Gaussian noise (AWGN) is heavily corrupted. These given channel states are utilized as the input of the Bayesian equalizer to reconstruct transmitted symbols. The simulation studies demonstrate that the performance of the proposed method is relatively superior to those of the existing conventional FCM based approaches in terms of accuracy and speed.

트래픽별 특성 규명을 통한 인터넷 부하 측정에 관한 연구 (A New Traffic Model for Internet Load Estimation)

  • 김후곤
    • 경영과학
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    • 제26권1호
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    • pp.161-169
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    • 2009
  • A traffic analysis on the Internet has an advantage for obtaining the characteristics of transferred packets. There were many studies to understand the characteristics of the Internet traffic with mathematical statistical approach. The approach of this study is different from previous studies. We first introduced a virtual network concept to present the Internet as a simplified mathematical model. It also represents each traffic flowing on the Internet as a parallel Gaussian channel on the virtual network. We suggest the optimal capacity of each parallel Gaussian channel using some related studies on the Gaussian channel model.

Control of Short-Channel Effects in Nano DG MOSFET Using Gaussian-Channel Doping Profile

  • Charmi, Morteza
    • Transactions on Electrical and Electronic Materials
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    • 제17권5호
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    • pp.270-274
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    • 2016
  • This article investigates the use of the Gaussian-channel doping profile for the control of the short-channel effects in the double-gate MOSFET whereby a two-dimensional (2D) quantum simulation was used. The simulations were completed through a self-consistent solving of the 2D Poisson equation and the Schrodinger equation within the non-equilibrium Green’s function (NEGF) formalism. The impacts of the p-type-channel Gaussian-doping profile parameters such as the peak doping concentration and the straggle parameter were studied in terms of the drain current, on-current, off-current, sub-threshold swing (SS), and drain-induced barrier lowering (DIBL). The simulation results show that the short-channel effects were improved in correspondence with incremental changes of the straggle parameter and the peak doping concentration.

Bayesian Nonlinear Blind Channel Equalizer based on Gaussian Weighted MFCM

  • Han, Soo-Whan;Park, Sung-Dae;Lee, Jong-Keuk
    • 한국멀티미디어학회논문지
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    • 제11권12호
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    • pp.1625-1634
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    • 2008
  • In this study, a modified Fuzzy C-Means algorithm with Gaussian weights (MFCM_GW) is presented for the problem of nonlinear blind channel equalization. The proposed algorithm searches for the optimal channel output states of a nonlinear channel based on received symbols. In contrast to conventional Euclidean distance in Fuzzy C-Means (FCM), the use of the Bayesian likelihood fitness function and the Gaussian weighted partition matrix is exploited in this method. In the search procedure, all possible sets of desired channel states are constructed by considering the combinations of estimated channel output states. The set of desired states characterized by the maxima] value of the Bayesian fitness is selected and updated by using the Gaussian weights. After this procedure, the Bayesian equalizer with the final desired states is implemented to reconstruct transmitted symbols. The performance of the proposed method is compared with those of a simplex genetic algorithm (GA), a hybrid genetic algorithm (GA merged with simulated annealing (SA):GASA), and a previously developed version of MFCM. In particular, a relative]y high accuracy and a fast search speed have been observed.

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Blind linear/nonlinear equalization for heavy noise-corrupted channels

  • Han, Soo- Whan;Park, Sung-Dae
    • Journal of information and communication convergence engineering
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    • 제7권3호
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    • pp.383-391
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    • 2009
  • In this paper, blind equalization using a modified Fuzzy C-Means algorithm with Gaussian Weights (MFCM_GW) is attempted to the heavy noise-corrupted channels. The proposed algorithm can deal with both of linear and nonlinear channels, because it searches for the optimal channel output states of a channel instead of estimating the channel parameters in a direct manner. In contrast to the common Euclidean distance in Fuzzy C-Means (FCM), the use of the Bayesian likelihood fitness function and the Gaussian weighted partition matrix is exploited in its search procedure. The selected channel states by MFCM_GW are always close to the optimal set of a channel even the additive white Gaussian noise (AWGN) is heavily corrupted in it. Simulation studies demonstrate that the performance of the proposed method is relatively superior to existing genetic algorithm (GA) and conventional FCM based methods in terms of accuracy and speed.

The Analysis of Breakdown Voltage for the Double-gate MOSFET Using the Gaussian Doping Distribution

  • Jung, Hak-Kee
    • Journal of information and communication convergence engineering
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    • 제10권2호
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    • pp.200-204
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    • 2012
  • This study has presented the analysis of breakdown voltage for a double-gate metal-oxide semiconductor field-effect transistor (MOSFET) based on the doping distribution of the Gaussian function. The double-gate MOSFET is a next generation transistor that shrinks the short channel effects of the nano-scaled CMOSFET. The degradation of breakdown voltage is a highly important short channel effect with threshold voltage roll-off and an increase in subthreshold swings. The analytical potential distribution derived from Poisson's equation and the Fulop's avalanche breakdown condition have been used to calculate the breakdown voltage of a double-gate MOSFET for the shape of the Gaussian doping distribution. This analytical potential model is in good agreement with the numerical model. Using this model, the breakdown voltage has been analyzed for channel length and doping concentration with parameters such as projected range and standard projected deviation of Gaussian function. As a result, since the breakdown voltage is greatly changed for the shape of the Gaussian function, the channel doping distribution of a double-gate MOSFET has to be carefully designed.

MFCM의 성능개선을 통한 블라인드 비선형 채널 등화 (Blind Nonlinear Channel Equalization by Performance Improvement on MFCM)

  • 박성대;우영운;한수환
    • 한국정보통신학회논문지
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    • 제11권11호
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    • pp.2158-2165
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    • 2007
  • 본 논문에서는 비선형 블라인드 채널등화기의 구현을 위하여 가우시안 가중치(gaussian weights)를 이용한 개선된 퍼지 클러스터(Modified Fuzzy C-Means with Gaussian Weights: MFCM_GW) 알고리즘을 제안한다. 제안된 알고리즘은 기존 FCM 알고리즘의 유클리디언 거리(Euclidean distance) 값 대신 Bayesian Likelihood 목적 함수(fitness function)와 가우시안 가중치가 적용된 멤버십 매트릭스(partition matrix)를 이용하여, 비선형 채널의 출력으로 수신된 데이터들로부터 최적의 채널 출력 상태 값(optimal channel output states)들을 직접 추정한다. 이렇게 추정된 채널 출력 상태 값들로 비선형 채널의 이상적 채널 상태(desired channel states) 백터들을 구성하고, 이를 Radial Basis Function(RBF) 등화기의 중심(center)으로 활용함으로써 송신된 데이터 심볼을 찾아낸다. 실험에서는 무작위 이진 신호에 가우시안 잡음이 추가된 데이터를 사용하여 기존의 Simplex Genetic Algorithm(GA), 하이브리드 형태의 GASA(GA merged with simulated annealing(SA)), 그리고 과거에 발표되었던 MFCM 등과 그 성능을 비교 분석하였으며, 가우시안 가중치가 적용된 MFCM_GW를 이용한 채널등화기가 상대적으로 정확도와 속도 면에서 우수함을 보였다.

이중게이트 MOSFET의 채널도핑에 다른 문턱전압이하 전류 변화 분석 (Analysis of Subthreshold Current Deviation for Channel Doping of Double Gate MOSFET)

  • 정학기
    • 한국정보통신학회논문지
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    • 제17권6호
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    • pp.1409-1413
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    • 2013
  • 본 연구에서는 이중게이트 MOSFET의 채널도핑농도의 변화에 따른 문턱전압이하 전류의 변화를 분석하였다. 이를 위하여 이중게이트 MOSFET의 채널 내 전위분포를 구하기 위하여 포아송방정식을 이용하였으며 이때 전하분포함수에 대하여 가우시안 함수를 사용하였다. 전위분포는 경계조건을 이용하여 채널크기에 따른 해석학적인 함수로 구하였다. 가우시안 함수의 변수인 이온주입범위 및 분포편차 그리고 채널도핑농도 등에 대하여 문턱전압 이하 전류 특성의 변화를 관찰하였다. 본 연구의 전위모델에 대한 타당성은 이미 기존에 발표된 논문에서 입증하였으며 본 연구에서는 이 모델을 이용하여 문턱전압이하 전류 특성을 분석하였다. 분석결과, 문턱전압이하 전류는 채널도핑농도 및 가우시안 분포함수의 변수 등에 크게 영향을 받는 것을 관찰할 수 있었다.

On Additive Signal Dependent Gaussian Noise Channel Capacity for NOMA in 5G Mobile Communication

  • Chung, Kyuhyuk
    • International Journal of Internet, Broadcasting and Communication
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    • 제12권2호
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    • pp.37-44
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    • 2020
  • The fifth generation (5G) mobile communication has been commercialized and the 5G applications, such as the artificial intelligence (AI) and the internet of things (IoT), are deployed all over the world. The 5G new radio (NR) wireless networks are characterized by 100 times more traffic, 1000 times higher system capacity, and 1 ms latency. One of the promising 5G technologies is non-orthogonal multiple access (NOMA). In order for the NOMA performance to be improved, sometimes the additive signal-dependent Gaussian noise (ASDGN) channel model is required. However, the channel capacity calculation of such channels is so difficult, that only lower and upper bounds on the capacity of ASDGN channels have been presented. Such difficulties are due to the specific constraints on the dependency. Herein, we provide the capacity of ASDGN channels, by removing the constraints except the dependency. Then we obtain the ASDGN channel capacity, not lower and upper bounds, so that the clear impact of ASDGN can be clarified, compared to additive white Gaussian noise (AWGN). It is shown that the ASDGN channel capacity is greater than the AWGN channel capacity, for the high signal-to-noise ratio (SNR). We also apply the analytical results to the NOMA scheme to verify the superiority of ASDGN channels.