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Sub-Optimum Training Design for Spatially Correlated Doubly-Selective MIMO-OFDM Channels
Qinghai Yang,Shaoyi Xu,Kyung Sup Kwak 대한전자공학회 2007 ITC-CSCC :International Technical Conference on Ci Vol.2007 No.7
We design a sub-optimal training scheme for MIMO-OFDM systems under spatially correlated time- and frequency- (doubly) selective fading channels. We first develop the optimal pilot symbols and placement of pilot clusters with respect to the minimum mean square error (MMSE) of the linear channel estimate. We then derive the sub-optimal power allocation for pilot symbols in a twowater- level way: By maximizing the averaged capacity lower bound, how much power to be allocated to training is determined subject to the global water level (or the constraint of total transmit power); Subsequently, pouring power to the pilot symbols with an approximately optimal water filling scheme subject to the local water level (or the constraint of assigned power for training). In addition, for a particular OFDM size, the optimal number of pilot clusters is derived by maximizing the capacity lower bound and by minimizing the channel estimate's MMSE.
Outage Probability of Opportunistic Amplify-and- Forward Relaying in Nakagami-m Fading Channels
Qinghai Yang,Yingji Zhong,곽경섭,Fenglin Fu 한국전자통신연구원 2008 ETRI Journal Vol.30 No.4
We address the outage performance for the opportunistic amplify-and-forward relaying strategies under Nakagami-m fading channels. A closed-form expression for the outage probability is derived. Simulation results verify our theoretical solutions.
Time-Varying Multipath Channel Estimation with Superimposed Training in CP-OFDM Systems
Qinghai Yang,곽경섭 한국전자통신연구원 2006 ETRI Journal Vol.28 No.6
Based on superimposed training methods, a novel time-varying multipath channel estimation scheme is proposed for orthogonal frequency division multiplexing systems. We first develop a linear least square channel estimator, and meanwhile find the optimal superimposed sequences with respect to the channel estimates’ mean square error. Next, a low-rank approximated channel estimator is obtained by using the singular value decomposition. As demonstrated in simulations, the proposed scheme achieves not only better performance but also higher bandwidth efficiency than the conventional pilot-aided approach.
Superimposed Pilot Aided Multiuser Channel Estimation for MIMO-OFDM Uplinks
Qinghai Yang,곽경섭 한국전자통신연구원 2006 ETRI Journal Vol.28 No.5
This letter addresses the superimposed pilot aided multiuser channel estimation for the uplinks of multiinput multi-output orthogonal frequency-division multiplexing systems. To mitigate the embedded-data effects on the performance of channel estimation, a novel combining algorithm is proposed. Optimal pilot symbols are developed with respect to the least square channel estimate’s mean square error. The averaged sum-capacity lower bound is derived and simulated. Simulation results show that on a low signal-tonoise ratio regime, our proposed scheme achieves better performance and higher capacity than the conventional pilot aided approach.
Optimum Superimposed Training for Mobile OFDM Systems
Qinghai Yang,곽경섭 한국통신학회 2009 Journal of communications and networks Vol.11 No.1
Superimposed training (SIT) design for estimating of time-varying multipath channels is investigated for mobile orthogonal frequency division multiplexing (OFDM) systems. The design of optimum SIT consists of two parts: The optimal SIT sequence is derived by minimizing the channel estimates’ mean square error (MSE); the optimal power allocation between training and information data is developed by maximizing the averaged signal to interference plus noise ratio (SINR) under the condition of equal powered paths. The theoretical analysis is verified by simulations. For the metric of the averaged SINR against signal to noise ratio (SNR), the theoretical result matches the simulation result perfectly. In contrast to an interpolated frequency-multiplexing training (FMT) scheme or an SIT scheme with random pilot sequence, the SIT scheme with proposed optimal sequence achieves higher SINR. The analytical solution of the optimal power allocation is demonstrated by the simulation as well.
Qinghai Wang,Qi Chen,Zhongyuan Wang 제어로봇시스템학회 2021 제어로봇시스템학회 국제학술대회 논문집 Vol.2021 No.10
Taking the general control energy optimal trajectory programming model as the research object, the Radau pseudo-spectral method is used to discretize the continuous variables and then linearly convexify the nonlinear dynamic equation to establish the standard convex optimization model. In order to solve the problems of large amount of redundant computation and slow convergence speed of the traditional L1 penalty successive convex programming algorithm (LPSCP), an improved L1 penalty successive convex programming algorithm (ILPSCP) is proposed in this paper. The algorithm introduces the feasibility judgment process to avoid solving the more complex L1 subproblem PL1 when the original problem P0 is feasible. Taking the gliding trajectory model of the guided projectile in the longitudinal plane as an example, the traditional LPSCP algorithm, the ILPSCP algorithm proposed in this paper and GPOPS2 are used to simulate and compare. The simulation results of ILPSCP algorithm are highly consistent with those of GPOPS2, which proves the effectiveness of the proposed ILPSCP algorithm for solving trajectory programming problems, and the convergence rate of ILPSCP algorithm is improved by 46.36% compared with traditional LPSCP algorithm.