• 제목/요약/키워드: time-varying channel

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Performance Investigation of Space-Time Block Coded Multicarrier DS-CDMA in Time-Varying Channels

  • Narzullaev, Anvar;Ryu, Kwan-Woong;Park, Yong-Wan
    • ETRI Journal
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    • 제28권5호
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    • pp.684-687
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    • 2006
  • In this letter, we evaluate the system performance of a space-time block coded (STBC) multicarrier (MC) DS-CDMA system over a time selective fading channel, with imperfect channel knowledge. The average bit error rate impairment due to imperfect channel information is investigated by taking into account the effect of the STBC position. We consider two schemes: STBC after spreading and STBC before spreading in the MC DS-CDMA system. In the scheme with STBC after spreading, STBC is performed at the chip level; in the scheme with STBC before spreading, STBC is performed at the symbol level. We found that these two schemes have various channel estimation errors, and that the system with STBC before spreading is more sensitive to channel estimation than the system with STBC after spreading. Furthermore, derived results prove that a high spreading factor (SF) in the MC DS-CDMA system with STBC before spreading leads to high channel estimation error, whereas for a system with STBC after spreading this statement is not true.

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Independent Component Analysis Based MIMO Transceiver With Improved Performance In Time Varying Wireless Channels

  • Uddin, Zahoor;Ahmad, Ayaz;Iqbal, Muhammad;Shah, Nadir
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제9권7호
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    • pp.2435-2453
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    • 2015
  • Independent component analysis (ICA) is a signal processing technique used for un-mixing of the mixed recorded signals. In wireless communication, ICA is mainly used in multiple input multiple output (MIMO) systems. Most of the existing work regarding the ICA applications in MIMO systems assumed static or quasi static wireless channels. Performance of the ICA algorithms degrades in case of time varying wireless channels and is further degraded if the data block lengths are reduced to get the quasi stationarity. In this paper, we propose an ICA based MIMO transceiver that performs well in time varying wireless channels, even for smaller data blocks. Simulation is performed over quadrature amplitude modulated (QAM) signals. Results show that the proposed transceiver system outperforms the existing MIMO system utilizing the FastICA and the OBAICA algorithms in both the transceiver systems for time varying wireless channels. Performance improvement is observed for different data blocks lengths and signal to noise ratios (SNRs).

Optimization for Relay-Assisted Broadband Power Line Communication Systems with QoS Requirements Under Time-varying Channel Conditions

  • Wu, Xiaolin;Zhu, Bin;Wang, Yang;Rong, Yue
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제11권10호
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    • pp.4865-4886
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    • 2017
  • The user experience of practical indoor power line communication (PLC) applications is greatly affected by the system quality-of-service (QoS) criteria. With a general broadcast-and-multi-access (BMA) relay scheme, in this work we investigate the joint source and relay power optimization of the amplify-and-forward (AF) relay systems used under indoor broad-band PLC environments. To achieve both time diversity and spatial diversity from the relay-involved PLC channel, which is time-varying in nature, the source node has been configured to transmit an identical message twice in the first and second signalling phase, respectively. The QoS constrained power allocation problem is not convex, which makes the global optimal solution is computationally intractable. To solve this problem, an alternating optimization (AO) method has been adopted and decomposes this problem into three convex/quasi-convex sub-problems. Simulation results show the fast convergence and short delay of the proposed algorithm under realistic relay-involved PLC channels. Compared with the two-hop and broadcast-and-forward (BF) relay systems, the proposed general relay system meets the same QoS requirement with less network power assumption.

시그마 포인트를 이용한 채널 등화용 순환신경망 훈련 알고리즘 (Training Algorithm of Recurrent Neural Network Using a Sigma Point for Equalization of Channels)

  • 권오신
    • 한국정보통신학회논문지
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    • 제11권4호
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    • pp.826-832
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    • 2007
  • 고속 통신 시스템의 채널 등화에 순환 신경망이 자주 이용되고 있다. 기존의 등화방법은 대부분 시불변 채널을 주로 다루었다. 그러나 이동통신과 같은 현대의 통신환경은 페이딩으로 인하여 시변특성을 갖는다. 본 논문에서는 비선형 시변 시스템에 적용하여 성능이 우수한 결정 피드백 순환신경망을 채널등화기로 이용하며, 또한 채널 등화에 빠른 수렴속도와 우수한 추적성능을 지니는 확장된 칼만필터와 시그마 포인트 칼만필터를 이용한 두 종류의 훈련 알고리즘을 제안한다. 확장된 칼만필터를 이용한 경우 비선형 시스템의 1차 선형화 과정에서 커다란 오차를 유발할 수도 있으며, 이에 대한 대안으로 시그마 포인트 칼만필터를 이용하여 이러한 문제점을 극복할 수 있다.

시변 페이딩 채널에서 상향 직교 주파수 분할 다중 접속을 위한 혼합 간섭 제거 기법 (Hybrid Interference Cancellation for OFDMA Uplink in Time-Varying Fading Channels)

  • 송형준;홍대식
    • 대한전자공학회논문지TC
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    • 제46권6호
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    • pp.78-85
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    • 2009
  • 시변 채널에서 상향 직교 주파수 분할 다중 접속 (OFDMA uplink : Orthogonal Frequency Division Multiple Access uplink) 시스템은 도플러 현상 (Doppler Effect)과 시간 비동기에 의한 부반송파 간의 간섭 (ICI : Inter-Channel Interference)으로 인해 치명적인 성능 열화가 발생한다. 본 논문에서는 OFDM uplink 시스템에서 부반송파 간의 간섭으로 인한 열화를 줄이기 위해 혼합 간섭 제거 기법 (HIC : Hybrid Interference Cancellation)을 제안한다. 제안된 혼합 간섭 제거 기법은 직렬 간섭 제거 기법 (SIC : Successive Interference Cancellation)의 강인한 간섭 제거 효과와 병렬 간섭 제거 기법 (PIC : Parallel Interference Cancellation)의 복잡도 감소 효과를 동시에 얻을 수 있도록 설계되었다. 이것은 신호 대 간섭 및 잡음 비 (SINR : Signal-to-Interference and Noise Ratio)에 따라 정렬된 수신 신호의 효과적인 군(Group) 선택과 위너 여파기 (WF : Wiener Filter), 그리고 시변 채널 특성을 고려한 신호 선택 기준을 통해 구현된다. 모의 실험 결과에서는 기존 OFDMA 기법의 등화기가 시변 페이딩 채널의 영향이 커짐에 따라 성능 열화가 심해지는 것에 반해 제안된 간섭 제거 기법은 간섭 제거를 위한 신호 선택 기준에 의해 저복잡도에서도 비트 오류 확률 성능이 더욱 향상되며, 또한 성능과 복잡도의 교환이 가능한 유연한 시스템인 것을 보여 준다.

WAVE 시스템에서 선택 다이버시티를 위한 선택 기준에 대한 연구 (A Study on Selection Criterions for Selection Diversity in WAVE Systems)

  • 홍대기
    • 반도체디스플레이기술학회지
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    • 제14권2호
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    • pp.9-16
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    • 2015
  • In this paper, selection criterions on selection diversity are researched. The diversity is applied to the multiple antenna system based on wireless access in vehicular environment (WAVE) standard for rapid varying channel. Least squares (LS) based decision feedback equalizer (DFE) are used for channel equalization. Received signal is regenerated by means of the decision feedback path. In the selection diversity, the regenerated signal as well as the received signal is selected according to selection criterion. The decision feedback algorithm can follow the fast speed of WAVE fading channel. To control the tracking speed of the time-varying channel, simple low pass filter is used. Finally, the estimated channel value recovers the distorted payloads. Signal power before automatic gain control (AGC) in analog stage can be used as a selection criterion. In the digital stage, signal power after AGC, noise power after AGC, signal to noise ratio after AGC and cross-correlation method can be used as selection criterions. According to the simulation results, the performance of the selection diversity is improved in comparison with that of the combining diversity for the WAVE fading channel.

Beamforming for Downlink Multiuser MIMO Time-Varying Channels Based on Generalized Eigenvector Perturbation

  • Yu, Heejung;Lee, Sok-Kyu
    • ETRI Journal
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    • 제34권6호
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    • pp.869-878
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    • 2012
  • A beam design method based on signal-to-leakage-plus-noise ratio (SLNR) has been recently proposed as an effective scheme for multiuser multiple-input multiple-output downlink channels. It is shown that its solution, which maximizes the SLNR at a transmitter, can be simply obtained by the generalized eigenvectors corresponding to the dominant generalized eigenvalues of a pair of covariance matrices of a desired signal and interference leakage plus noise. Under time-varying channels, however, generalized eigendecomposition is required at each time step to design the optimal beam, and its level of complexity is too high to implement in practical systems. To overcome this problem, a predictive beam design method updating the beams according to channel variation is proposed. To this end, the perturbed generalized eigenvectors, which can be obtained by a perturbation theory without any iteration, are used. The performance of the method in terms of SLNR is analyzed and verified using numerical results.

Block-Mode Lattice Reduction for Low-Complexity MIMO Detection

  • Choi, Kwon-Hue;Kim, Han-Nah;Kim, Soo-Young;Kim, Young-Il
    • ETRI Journal
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    • 제34권1호
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    • pp.110-113
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    • 2012
  • We propose a very-low-complexity lattice-reduction (LR) algorithm for multi-input multi-output detection in time-varying channels. The proposed scheme reduces the complexity by performing LR in a block-wise manner. The proposed scheme takes advantage of the temporal correlation of the channel matrices in a block and its impact on the lattice transformation matrices during the LR process. From this, the proposed scheme can skip a number of redundant LR processes for consecutive channel matrices and performs a single LR in a block. As the Doppler frequency decreases, the complexity reduction efficiency becomes more significant.

Computation Offloading with Resource Allocation Based on DDPG in MEC

  • Sungwon Moon;Yujin Lim
    • Journal of Information Processing Systems
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    • 제20권2호
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    • pp.226-238
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    • 2024
  • Recently, multi-access edge computing (MEC) has emerged as a promising technology to alleviate the computing burden of vehicular terminals and efficiently facilitate vehicular applications. The vehicle can improve the quality of experience of applications by offloading their tasks to MEC servers. However, channel conditions are time-varying due to channel interference among vehicles, and path loss is time-varying due to the mobility of vehicles. The task arrival of vehicles is also stochastic. Therefore, it is difficult to determine an optimal offloading with resource allocation decision in the dynamic MEC system because offloading is affected by wireless data transmission. In this paper, we study computation offloading with resource allocation in the dynamic MEC system. The objective is to minimize power consumption and maximize throughput while meeting the delay constraints of tasks. Therefore, it allocates resources for local execution and transmission power for offloading. We define the problem as a Markov decision process, and propose an offloading method using deep reinforcement learning named deep deterministic policy gradient. Simulation shows that, compared with existing methods, the proposed method outperforms in terms of throughput and satisfaction of delay constraints.