Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: After reviewing the information geometric channel identification algorithm (IGID) (A. Zia et al., 2003), the application of the algorithm for semi-blind identification of the MIMO channel with Gaussian input sources is discussed. The method is developed based on the results from information geometry; specifically, the alternating projections theorem first proved by Csiszar and G. Tusnady (1984) which provides an iterative method for minimizing the distance beten two sets of probability distributions. Also, an EM-type identification algorithm (EM-MCMC) for which the necessary expectation computations are performed using Markov-chain Monte-Carlo (MCMC) method is introduced. The comparative analysis of channel identification using two methods for MIMO systems with ISI-free flat-fading channels is given. It is shown that the IGID method has a similar performance while benefiting from an analytical solution. Thus, complex multidimensional integrations usually necessary in similar EM-type methods are avoided. This characteristic provides very fast computation times relative to previous EM-type algorithms.
['Amin Zia', 'James P. Reilly', 'Shahram Shirani']
I am writing a research paper on a idea Information geometric approach to channel identification: a comparison with EM-MCMC algorithm
[{"from": "human", "value": "I am writing a research paper on a idea Information geometric approach to channel identification: a comparison with EM-MCMC algorithm"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: After reviewing the information geometric channel identification algorithm (IGID) (A. Zia et al., 2003), the application of the algorithm for semi-blind identification of the MIMO channel with Gaussian input sources is discussed. The method is developed based on the results from information geometry; specifically, the alternating projections theorem first proved by Csiszar and G. Tusnady (1984) which provides an iterative method for minimizing the distance beten two sets of probability distributions. Also, an EM-type identification algorithm (EM-MCMC) for which the necessary expectation computations are performed using Markov-chain Monte-Carlo (MCMC) method is introduced. The comparative analysis of channel identification using two methods for MIMO systems with ISI-free flat-fading channels is given. It is shown that the IGID method has a similar performance while benefiting from an analytical solution. Thus, complex multidimensional integrations usually necessary in similar EM-type methods are avoided. This characteristic provides very fast computation times relative to previous EM-type algorithms."}]