To decrease the complexity of MAP algorithm, reduced state or reduced search techniques can be applied. In this paper we propose a reduced search soft output detection algorithm fully based on the principle of M a...To decrease the complexity of MAP algorithm, reduced state or reduced search techniques can be applied. In this paper we propose a reduced search soft output detection algorithm fully based on the principle of M algorithm for turbo equalization, which is a suboptimum version of the Lee algorithm. This algorithm is called soft output M algorithm (denoted as SO M algorithm), which applies the M strategy to both the forward recursion and the extended forward recursion of the Lee algorithm. Computer simulation results show that, by properly selecting and adjusting the breadth parameter and depth parameter during the iteration of turbo equalization, this algorithm can obtain good performance and complexity trade off.展开更多
In order to fully utilize the soft decision ability of the outer decoder in a concatenated system, reliability information (called soft output) from the inner decoder or equalizer is required. In this paper, based on...In order to fully utilize the soft decision ability of the outer decoder in a concatenated system, reliability information (called soft output) from the inner decoder or equalizer is required. In this paper, based on the analysis of typical implementations of soft output VA, a novel algorithm is proposed by utilizing the property of Viterbi algorithm. Compared with the typical implementations, less processing expense is required by the new algorithm for weighting the hard decisions of VA. Meanwhile, simulation results show that, deterioration in performance of this algorithm is usually small for decoding of convolutional code and negligible for equalization.展开更多
A computationally efficient soft-output detector with lattice-reduction （LR） for the multiple-input multiple-output （MIMO） systems is proposed. In the proposed scheme, the sorted QR de- composition is applied on t...A computationally efficient soft-output detector with lattice-reduction （LR） for the multiple-input multiple-output （MIMO） systems is proposed. In the proposed scheme, the sorted QR de- composition is applied on the lattice-reduced equivalent channel to obtain the tree structure. With the aid of the boundary control, the stack algorithm searches a small part of the whole search tree to generate a handful of candidate lists in the reduced lattice. The proposed soft-output algorithm achieves near-optimal perfor- mance in a coded MIMO system and the associated computational complexity is substantially lower than that of previously proposed methods.展开更多
准确预测风电低出力是保障高比例新能源电力系统供电安全的关键。为此,提出了一种基于门控循环单元-降噪自编码器(gate recurrent unit-denoising auto encoder,GRU-DAE)-DLinear的风电低出力并行预测方法,采用无监督学习方法刻画低出...准确预测风电低出力是保障高比例新能源电力系统供电安全的关键。为此,提出了一种基于门控循环单元-降噪自编码器(gate recurrent unit-denoising auto encoder,GRU-DAE)-DLinear的风电低出力并行预测方法,采用无监督学习方法刻画低出力典型波动特性,并通过针对性建模提升预测准确性。首先,提出了基于GRU-DAE的低出力事件分类方法,利用时序神经网络的序列数据降噪归纳和重构能力辨识典型低出力事件。然后,建立了基于DLinear的低出力事件并行预测模型,对不同类型低出力的时序特性独立建模,从而提升整体预测准确性。最后,基于中国北方某风电场的实际运行数据验证了所提方法的有效性。展开更多
文摘To decrease the complexity of MAP algorithm, reduced state or reduced search techniques can be applied. In this paper we propose a reduced search soft output detection algorithm fully based on the principle of M algorithm for turbo equalization, which is a suboptimum version of the Lee algorithm. This algorithm is called soft output M algorithm (denoted as SO M algorithm), which applies the M strategy to both the forward recursion and the extended forward recursion of the Lee algorithm. Computer simulation results show that, by properly selecting and adjusting the breadth parameter and depth parameter during the iteration of turbo equalization, this algorithm can obtain good performance and complexity trade off.
文摘In order to fully utilize the soft decision ability of the outer decoder in a concatenated system, reliability information (called soft output) from the inner decoder or equalizer is required. In this paper, based on the analysis of typical implementations of soft output VA, a novel algorithm is proposed by utilizing the property of Viterbi algorithm. Compared with the typical implementations, less processing expense is required by the new algorithm for weighting the hard decisions of VA. Meanwhile, simulation results show that, deterioration in performance of this algorithm is usually small for decoding of convolutional code and negligible for equalization.
文摘A computationally efficient soft-output detector with lattice-reduction （LR） for the multiple-input multiple-output （MIMO） systems is proposed. In the proposed scheme, the sorted QR de- composition is applied on the lattice-reduced equivalent channel to obtain the tree structure. With the aid of the boundary control, the stack algorithm searches a small part of the whole search tree to generate a handful of candidate lists in the reduced lattice. The proposed soft-output algorithm achieves near-optimal perfor- mance in a coded MIMO system and the associated computational complexity is substantially lower than that of previously proposed methods.
文摘准确预测风电低出力是保障高比例新能源电力系统供电安全的关键。为此,提出了一种基于门控循环单元-降噪自编码器(gate recurrent unit-denoising auto encoder,GRU-DAE)-DLinear的风电低出力并行预测方法,采用无监督学习方法刻画低出力典型波动特性,并通过针对性建模提升预测准确性。首先,提出了基于GRU-DAE的低出力事件分类方法,利用时序神经网络的序列数据降噪归纳和重构能力辨识典型低出力事件。然后,建立了基于DLinear的低出力事件并行预测模型,对不同类型低出力的时序特性独立建模,从而提升整体预测准确性。最后,基于中国北方某风电场的实际运行数据验证了所提方法的有效性。
文摘针对新能源不确定性,文中基于深度确定性策略梯度(deep deterministic policy gradient,DDPG)算法,提出了考虑新能源承载能力的交直流电网鲁棒扩展规划方法。首先,建立了交直流电网的扩展规划模型。其次,构建了考虑新能源接入的交直流电网鲁棒扩展规划模型,提出了基于极限场景集的新能源不确定性处理方法。进一步,提出了基于改进DDPG的扩展规划模型求解方法。最后,通过IEEE RTS 24系统、IEEE New England 39系统以及中国西南电网的算例分析,验证了所提方法能够有效降低弃风弃光量和切负荷量,且在不增加额外投资的前提下显著降低规划成本。
