This material is aimed to attract attention to the “incoherent approach for power NOMA-RIS-MIMO transmission in wireless channels”. Such kind of approach might be successfully applied in future dense networks formed...This material is aimed to attract attention to the “incoherent approach for power NOMA-RIS-MIMO transmission in wireless channels”. Such kind of approach might be successfully applied in future dense networks formed by High-Speed Vehicles (HSV networks, etc.). Those scenarios take place in doubly selective communication channels typical for such kind of radio networks. The proposal for the presented hereafter incoherent view (“paradigm”) is based on several basic principles: 1) Shift from the “coherent “ideology”, i.e. rejection of the application of any type of Channel State Information (CSI, CSIT);2) Application of the so-called “invariant” to the communication channel’s features (distortions) modulation technique together with its incoherent demodulation;3) Orthogonal channel decomposition by means of “universal” eigen basis (in the form of Prolate Spheroidal Wave Functions, PSWF) as “artificial trajectories” of wave propagation;4) Chaotic filtering (chaos parameter settings as UE signatures) together with sequential multiuser parallel detection algorithms for users’ identification (classification). It is shown that the proposed approach might provide an effective use of the radio resource and it is relatively simple for implementation.展开更多
文摘This material is aimed to attract attention to the “incoherent approach for power NOMA-RIS-MIMO transmission in wireless channels”. Such kind of approach might be successfully applied in future dense networks formed by High-Speed Vehicles (HSV networks, etc.). Those scenarios take place in doubly selective communication channels typical for such kind of radio networks. The proposal for the presented hereafter incoherent view (“paradigm”) is based on several basic principles: 1) Shift from the “coherent “ideology”, i.e. rejection of the application of any type of Channel State Information (CSI, CSIT);2) Application of the so-called “invariant” to the communication channel’s features (distortions) modulation technique together with its incoherent demodulation;3) Orthogonal channel decomposition by means of “universal” eigen basis (in the form of Prolate Spheroidal Wave Functions, PSWF) as “artificial trajectories” of wave propagation;4) Chaotic filtering (chaos parameter settings as UE signatures) together with sequential multiuser parallel detection algorithms for users’ identification (classification). It is shown that the proposed approach might provide an effective use of the radio resource and it is relatively simple for implementation.
