Abstract: A Kernel-power-density based method for wireless channel multipath components (MPCs) clustering. Signals get to the receiver from a transmitter via multipath propagation. MIMO channels can be modeled as double-directional, which contains the information of power, delay, direction of departure (DOD) and direction of arrival (DOA) of MPCs. The MPCs tend to appear in clusters. All the parameters of MPCs can be estimated by using high-resolution algorithms, such as MUSIC, CLEAN, SAGE, and RiMAX. Considering a data snapshot for a certain time with several clusters, which include a number of MPCs, where each MPC is represented by its power, delay, DOD and DOA. This invention adopts a novel clustering framework by using a density based method, which can better identify the local density variations of MPCs and requires no prior knowledge about clusters. It can work for the cluster oriented channel processing technology in future wireless communication field.

Abstract: A Kernel-power-density based method for wireless channel multipath components (MPCs) clustering. Signals get to the receiver from a transmitter via multipath propagation. MIMO channels can be modeled as double-directional, which contains the information of power, delay, direction of departure (DOD) and direction of arrival (DOA) of MPCs. The MPCs tend to appear in clusters. All the parameters of MPCs can be estimated by using high-resolution algorithms, such as MUSIC, CLEAN, SAGE, and RiMAX. Considering a data snapshot for a certain time with several clusters, which include a number of MPCs, where each MPC is represented by its power, delay, DOD and DOA. This invention adopts a novel clustering framework by using a density based method, which can better identify the local density variations of MPCs and requires no prior knowledge about clusters. It can work for the cluster oriented channel processing technology in future wireless communication field.

Abstract: A power amplifying device with linear corrector utilizing the polynomial format to realize pre-distortion is disclosed. Its effective order estimation technique for polynomial based pre-distorter includes the following steps. Firstly, it receives the polynomial of the described pre-distorter and then, the polynomial is transformed into the matrix expression, obtaining the pre-distorter consisted of K pre-distortion functions, where K denotes the maximum order of the described polynomials. Secondly, singular value decomposition is performed for the pre-distortion matrix, obtaining singular value matrix. Thirdly, on the basis of the singular value matrix, effective rank of the pre-distortion matrix is obtained. Such effective rank of the pre-distortion matrix is determined as the effective order of the polynomial.