Temporal and three-dimensional(3 D) spatial information is important for the characterization of wireless channels. In this paper, the commonly used array signal processing(ASP) methods to estimate channel parameters ...Temporal and three-dimensional(3 D) spatial information is important for the characterization of wireless channels. In this paper, the commonly used array signal processing(ASP) methods to estimate channel parameters are summarized. Firstly, algorithms that can be used to estimate azimuth angle of arrival(AAo A) and elevation Ao A(EAo A) are introduced. They include multiple signal classification(MUSIC), estimation of signal parameter via rotational invariance techniques(ESPRIT), and Unitary ESPRIT algorithms. Secondly, algorithms that can be used to jointly estimate delay, AAo A, and EAo A are given. They include joint angle and delay estimation(JADE) MUSIC, JADE ESPRIT, shift-invariance(SI) JADE, and space-alternating generalized expectation-maximization(SAGE) algorithms. We also propose an improved SIJADE algorithm to further reduce computation complexity by incorporating with the Unitary ESPRIT algorithm. Performance of the above algorithms to extract only spatial information and to jointly extract temporal and spatial information is compared in both synthetic and 60 GHz real channel environments. Simulation results show that with the inclusion of delay estimation, the joint temporal and spatial estimation algorithms can provide better resolution than algorithms estimating only angles.Measurement data processing results show that MUSIC algorithm can provide comparable results with SAGE algorithm in estimating AAoA and EAoA. SI-JADE and the improved SI-JADE algorithms are also applicable to process 60 GHz channel measurement data.However, MUSIC, SI-JADE, and the improved SI-JADE algorithms can greatly reduce computational burden compared with SAGE algorithm. At last, some future directions are pointed out.展开更多
In this paper,the conventional method of establishing spatial channel models(SCMs)based on measurements is extended by including clusters-of-scatterers(CoSs)that exist along propagation paths.The channel models result...In this paper,the conventional method of establishing spatial channel models(SCMs)based on measurements is extended by including clusters-of-scatterers(CoSs)that exist along propagation paths.The channel models resulted utilizing this new method are applicable for generating channel realizations of reasonable spatial consistency,which is required for designing techniques and systems of the fifth generation wireless communications.The scatterers’locations are estimated from channel measurement data obtained using large-scale antenna arrays through the Space-Alternating Generalized Expectation-Maximization(SAGE)algorithm derived under a spherical wavefront assumption.The stochastic properties of CoSs extracted from real measurement data in an indoor environment are presented.展开更多
基金support from the Natural Science Foundation of China (Grant No. 61210002, 61371110)EU H2020 ITN 5G Wireless project (No. 641985)+1 种基金EU H2020 RISE TESTBED project (No. 734325)EPSRC TOUCAN project (Grant No. EP/L020009/1)
文摘Temporal and three-dimensional(3 D) spatial information is important for the characterization of wireless channels. In this paper, the commonly used array signal processing(ASP) methods to estimate channel parameters are summarized. Firstly, algorithms that can be used to estimate azimuth angle of arrival(AAo A) and elevation Ao A(EAo A) are introduced. They include multiple signal classification(MUSIC), estimation of signal parameter via rotational invariance techniques(ESPRIT), and Unitary ESPRIT algorithms. Secondly, algorithms that can be used to jointly estimate delay, AAo A, and EAo A are given. They include joint angle and delay estimation(JADE) MUSIC, JADE ESPRIT, shift-invariance(SI) JADE, and space-alternating generalized expectation-maximization(SAGE) algorithms. We also propose an improved SIJADE algorithm to further reduce computation complexity by incorporating with the Unitary ESPRIT algorithm. Performance of the above algorithms to extract only spatial information and to jointly extract temporal and spatial information is compared in both synthetic and 60 GHz real channel environments. Simulation results show that with the inclusion of delay estimation, the joint temporal and spatial estimation algorithms can provide better resolution than algorithms estimating only angles.Measurement data processing results show that MUSIC algorithm can provide comparable results with SAGE algorithm in estimating AAoA and EAoA. SI-JADE and the improved SI-JADE algorithms are also applicable to process 60 GHz channel measurement data.However, MUSIC, SI-JADE, and the improved SI-JADE algorithms can greatly reduce computational burden compared with SAGE algorithm. At last, some future directions are pointed out.
基金jointly supported by the key project “5G Ka frequency bands and higher and lower frequency band cooperative trail system research and development” of China Ministry of Industry and Information Technology under Grant number 2016ZX03001015the Hong Kong,Macao and Taiwan Science&Technology Cooperation Program of China under Grant No.2014DFT10290.
文摘In this paper,the conventional method of establishing spatial channel models(SCMs)based on measurements is extended by including clusters-of-scatterers(CoSs)that exist along propagation paths.The channel models resulted utilizing this new method are applicable for generating channel realizations of reasonable spatial consistency,which is required for designing techniques and systems of the fifth generation wireless communications.The scatterers’locations are estimated from channel measurement data obtained using large-scale antenna arrays through the Space-Alternating Generalized Expectation-Maximization(SAGE)algorithm derived under a spherical wavefront assumption.The stochastic properties of CoSs extracted from real measurement data in an indoor environment are presented.
