简单线性模型的时间序列预测质量通常超过Transformer等深度模型;而在具有大量通道的数据集上,深度模型尤其是多层感知器(MLP)的性能反而可超过简单线性模型。针对简单线性模型和MLP在时间序列预测中的误差功率谱差异,提出一种基于MLP...简单线性模型的时间序列预测质量通常超过Transformer等深度模型;而在具有大量通道的数据集上,深度模型尤其是多层感知器(MLP)的性能反而可超过简单线性模型。针对简单线性模型和MLP在时间序列预测中的误差功率谱差异,提出一种基于MLP的高频增强型时间序列预测模型HiFNet(High-Frequency Network)。首先,利用MLP在低频段的拟合能力;其次,通过自适应序列分解(ASD)模块及分组线性层解决MLP高频段易过拟合以及通道独立策略不能有效应对通道冗余的问题,从而增强MLP在高频段的鲁棒性;最后,对HiFNet在气象、电力和交通等领域的标准数据集上进行实验。结果表明:HiFNet的均方误差(MSE)在最佳情况下相较于NLinear、RLinear、SegRNN(Segment Recurrent Neural Network)和PatchTST(Patch Time Series Transformer)分别降低了23.6%、10.0%、35.1%和6.5%,而分组线性层通过学习通道相关性的低秩表达减轻了通道冗余的影响。展开更多
Cognitive radio （CR） is a promising technology deemed to improve the efficiency of spectrum utilization. This paper considers a spectrum underlay cognitive radio network, in which the cognitive users （CUs） are all...Cognitive radio （CR） is a promising technology deemed to improve the efficiency of spectrum utilization. This paper considers a spectrum underlay cognitive radio network, in which the cognitive users （CUs） are allowed to use the radio spectrum concurrently with the primary users （PUs） under the interference temperature constraint. We investigate the system performance by using the proposed joint channel and power allocation scheme under two transmit strategies to achieve higher data rates and performance diversity gain respectively. Simulation results show that the proposed scheme provides a significant improvement on the bit error rate （BER） performance and spectrum efficiency of a cognitive wireless network.展开更多
文摘简单线性模型的时间序列预测质量通常超过Transformer等深度模型;而在具有大量通道的数据集上,深度模型尤其是多层感知器(MLP)的性能反而可超过简单线性模型。针对简单线性模型和MLP在时间序列预测中的误差功率谱差异,提出一种基于MLP的高频增强型时间序列预测模型HiFNet(High-Frequency Network)。首先,利用MLP在低频段的拟合能力;其次,通过自适应序列分解(ASD)模块及分组线性层解决MLP高频段易过拟合以及通道独立策略不能有效应对通道冗余的问题,从而增强MLP在高频段的鲁棒性;最后,对HiFNet在气象、电力和交通等领域的标准数据集上进行实验。结果表明:HiFNet的均方误差(MSE)在最佳情况下相较于NLinear、RLinear、SegRNN(Segment Recurrent Neural Network)和PatchTST(Patch Time Series Transformer)分别降低了23.6%、10.0%、35.1%和6.5%,而分组线性层通过学习通道相关性的低秩表达减轻了通道冗余的影响。
基金Project supported by the Shanghai Pujiang Program (Grant No.08PJ14057)the Science and Technology Commission of Shanghai Municipality (Grant No.08220510900)+1 种基金the Innovation Foundation of Shanghai University (Grant No.SHUCX102153)the Cognitive Communications Consortium of the Worldwide Universities' Network
文摘Cognitive radio （CR） is a promising technology deemed to improve the efficiency of spectrum utilization. This paper considers a spectrum underlay cognitive radio network, in which the cognitive users （CUs） are allowed to use the radio spectrum concurrently with the primary users （PUs） under the interference temperature constraint. We investigate the system performance by using the proposed joint channel and power allocation scheme under two transmit strategies to achieve higher data rates and performance diversity gain respectively. Simulation results show that the proposed scheme provides a significant improvement on the bit error rate （BER） performance and spectrum efficiency of a cognitive wireless network.
