Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Higher order statistics-based inverse filter criteria (IFC) have been effectively used for blind equalization of single-input multiple-output (SIMO) systems. Recently, Chi and Chen reported a relationship beten the unknown SIMO system and the optimum equalizer designed by the IFC for finite signal-to-noise ratio (SNR). , based on this relationship, an iterative fast Fourier transform (FFT)-based nonparametric blind system identification (BSI) algorithm and an FFT-based multiple-time-delay estimation (MTDE) algorithm are proposed with a given set of non-Gaussian measurements. The proposed BSI algorithm allows the unknown SIMO system to have common subchannel zeros, and its performance (estimation accuracy) is superior to that of the conventional IFC-based methods. The proposed MTDE algorithm can simultaneously estimate all the (P-1) time delays (with respect to a reference sensor) with space diversity of sensors exploited; therefore, its performance (estimation accuracy) is robust to the nonuniform distribution of SNRs of P /spl ges/ 2 sensors (due to channel fading). Some simulation results are presented to support the efficacy of the proposed BSI algorithm and MTDE algorithm.
['Chong-Yung Chi', 'Ching-Yung Chen', 'Chii-Horng Chen', 'Chih-Chun Feng', 'Chun-Hsien Peng']
I am writing a research paper on a idea Blind identification of SIMO systems and simultaneous estimation of multiple time delays from HOS-based inverse filter criteria
[{"from": "human", "value": "I am writing a research paper on a idea Blind identification of SIMO systems and simultaneous estimation of multiple time delays from HOS-based inverse filter criteria"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Higher order statistics-based inverse filter criteria (IFC) have been effectively used for blind equalization of single-input multiple-output (SIMO) systems. Recently, Chi and Chen reported a relationship beten the unknown SIMO system and the optimum equalizer designed by the IFC for finite signal-to-noise ratio (SNR). , based on this relationship, an iterative fast Fourier transform (FFT)-based nonparametric blind system identification (BSI) algorithm and an FFT-based multiple-time-delay estimation (MTDE) algorithm are proposed with a given set of non-Gaussian measurements. The proposed BSI algorithm allows the unknown SIMO system to have common subchannel zeros, and its performance (estimation accuracy) is superior to that of the conventional IFC-based methods. The proposed MTDE algorithm can simultaneously estimate all the (P-1) time delays (with respect to a reference sensor) with space diversity of sensors exploited; therefore, its performance (estimation accuracy) is robust to the nonuniform distribution of SNRs of P /spl ges/ 2 sensors (due to channel fading). Some simulation results are presented to support the efficacy of the proposed BSI algorithm and MTDE algorithm."}]