Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  introduces adaptive filters that are effective to suppress multiple access interference (MAI) in orthogonal space-time block coded/ multiple-input multiple-output (OSTBC-MIMO) systems.  define an optimal linear filter that minimizes the mean-square error beten the filter output and a scaled version of the desired output under a constraint defined by the available channel state information (CSI). The adaptive filters refine a given estimate of the optimal filter by suppressing a sequence of closed convex functions with the adaptive projected subgradient method (APSM) at each iteration. To provide robustness against imperfect CSI, the adaptive filters use not only the available CSI but also estimates of previously transmitted symbols, which usually belong to a small finite set in digital communication systems. The resulting algorithms employ computationally efficient projections onto hyperplanes or hyperslabs and do not require any matrix inversion. An efficient recursive scheme based on such an algorithm is also presented. Convergence analysis and simulation results show the excellent performance of the proposed schemes.
['Renato L. G. Cavalcante', 'Isao Yamada']
I am writing a research paper on a idea Multiaccess Interference Suppression in Orthogonal Space–Time Block Coded MIMO Systems by Adaptive Projected Subgradient Method
[{"from": "human", "value": "I am writing a research paper on a idea Multiaccess Interference Suppression in Orthogonal Space\u2013Time Block Coded MIMO Systems by Adaptive Projected Subgradient Method"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  introduces adaptive filters that are effective to suppress multiple access interference (MAI) in orthogonal space-time block coded/ multiple-input multiple-output (OSTBC-MIMO) systems.  define an optimal linear filter that minimizes the mean-square error beten the filter output and a scaled version of the desired output under a constraint defined by the available channel state information (CSI). The adaptive filters refine a given estimate of the optimal filter by suppressing a sequence of closed convex functions with the adaptive projected subgradient method (APSM) at each iteration. To provide robustness against imperfect CSI, the adaptive filters use not only the available CSI but also estimates of previously transmitted symbols, which usually belong to a small finite set in digital communication systems. The resulting algorithms employ computationally efficient projections onto hyperplanes or hyperslabs and do not require any matrix inversion. An efficient recursive scheme based on such an algorithm is also presented. Convergence analysis and simulation results show the excellent performance of the proposed schemes."}]