Mimo Fading(Mimo 褪色)研究综述
Mimo Fading Mimo 褪色 - We derive the space–time correlation functions for the scattering environments in terms of the different system parameters of the MIMO fading channel. [1] However, due to the complexity of modeling and solving the optimization problems over mmWave m-MIMO fading channels in the non-asymptotic error-control regime, it is challenging to derive an optimal resource allocation policy for maximizing $\epsilon$ -effective capacity to guarantee statistical delay/error-rate bounded QoS. [2] Our simulation results show that the proposed NOMA-PSM scheme is capable of achieving considerable performance gains over conventional orthogonal multiple access aid PSM and antenna-grouping-based PSM in wireless MIMO fading channels. [3] We train two DNNs which learn the real and imaginary parts of the MIMO fading channels over a wide range of Doppler rates. [4] To fully capture the spatial correlation effects, the MIMO fading channel matrix is modelled according to three types of Kronecker correlation structure, i. [5] We demonstrate that the linear threshold-based detection methods, which were designed for AWGN channels, are suboptimal in the context of MIMO fading channels. [6]我们根据 MIMO 衰落信道的不同系统参数推导出散射环境的时空相关函数。 [1] 然而，由于在非渐近误差控制机制下对 mmWave m-MIMO 衰落信道进行建模和解决优化问题的复杂性，推导最优资源分配策略以最大化保证统计延迟/错误率有界的 QoS。 [2] 我们的仿真结果表明，所提出的 NOMA-PSM 方案能够在无线 MIMO 衰落信道中比传统的正交多址辅助 PSM 和基于天线分组的 PSM 实现可观的性能提升。 [3] 我们训练了两个 DNN，它们在很宽的多普勒速率范围内学习 MIMO 衰落信道的实部和虚部。 [4] 为了充分捕捉空间相关效应，根据三种类型的克罗内克相关结构对 MIMO 衰落信道矩阵进行建模，即。 [5] 我们证明了为 AWGN 信道设计的基于线性阈值的检测方法在 MIMO 衰落信道的情况下是次优的。 [6]
mimo fading channel Mimo 衰落频道
We derive the space–time correlation functions for the scattering environments in terms of the different system parameters of the MIMO fading channel. [1] However, due to the complexity of modeling and solving the optimization problems over mmWave m-MIMO fading channels in the non-asymptotic error-control regime, it is challenging to derive an optimal resource allocation policy for maximizing $\epsilon$ -effective capacity to guarantee statistical delay/error-rate bounded QoS. [2] Our simulation results show that the proposed NOMA-PSM scheme is capable of achieving considerable performance gains over conventional orthogonal multiple access aid PSM and antenna-grouping-based PSM in wireless MIMO fading channels. [3] We train two DNNs which learn the real and imaginary parts of the MIMO fading channels over a wide range of Doppler rates. [4] To fully capture the spatial correlation effects, the MIMO fading channel matrix is modelled according to three types of Kronecker correlation structure, i. [5] We demonstrate that the linear threshold-based detection methods, which were designed for AWGN channels, are suboptimal in the context of MIMO fading channels. [6]我们根据 MIMO 衰落信道的不同系统参数推导出散射环境的时空相关函数。 [1] 然而，由于在非渐近误差控制机制下对 mmWave m-MIMO 衰落信道进行建模和解决优化问题的复杂性，推导最优资源分配策略以最大化保证统计延迟/错误率有界的 QoS。 [2] 我们的仿真结果表明，所提出的 NOMA-PSM 方案能够在无线 MIMO 衰落信道中比传统的正交多址辅助 PSM 和基于天线分组的 PSM 实现可观的性能提升。 [3] 我们训练了两个 DNN，它们在很宽的多普勒速率范围内学习 MIMO 衰落信道的实部和虚部。 [4] 为了充分捕捉空间相关效应，根据三种类型的克罗内克相关结构对 MIMO 衰落信道矩阵进行建模，即。 [5] 我们证明了为 AWGN 信道设计的基于线性阈值的检测方法在 MIMO 衰落信道的情况下是次优的。 [6]