• Title/Summary/Keyword: 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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    • v.28 no.5
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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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    • v.9 no.7
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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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    • v.11 no.10
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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.

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

  • Kwon, Oh-Shin
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.11 no.4
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    • pp.826-832
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    • 2007
  • A recurrent neural network has been frequently used in equalizing the channel for fast communication systems. The existing techniques, however, have mainly dealt with time-invariant chamois. The modern environments of communication systems such as mobile ones have the time-varying feature due to fading. In this paper, powerful decision feedback - recurrent neural network is used as channel equalizer for nonlinear and time-varying system, and two kinds of algorithms, such as extended Kalman filter (EKF) and sigma-point Kalman filter (SPKF), are proposed; EKF is for fast convergence and good tracing function, and SPKF for overcoming the problems which can be developed during the process of first linearization for nonlinear system EKF.

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

  • Song, Hyung-Joon;Hong, Dae-Sik
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.46 no.6
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    • pp.78-85
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    • 2009
  • In time-varying multipath fading channels, orthogonal frequency division multiple access (OFDMA) uplink systems suffer severe performance degradation caused by inter-channel interference (ICI). In this paper, we propose a hybrid interference cancellation (HIC) for suppressing the degradation effect of ICI. The proposed HIC can achieve both exact interference cancellation and low detection complexity through efficient combination of parallel detection and serial cancellation. Simulation results show that, as the effect of Doppler increases, the proposed HIC achieves bit error rate (BER) performance enhancement in compared with severe performance degradation of conventional OFDMA receivers. In addition, both the computational complexity and total detection time are reduced.

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

  • Hong, Dae-Ki
    • Journal of the Semiconductor & Display Technology
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    • v.14 no.2
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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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    • v.34 no.6
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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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    • v.34 no.1
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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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    • v.20 no.2
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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.