Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Interference alignment (IA) is a technique recently shown to achieve the maximum degrees of freedom (DoF) of $K$-user interference channel. ,  focus on the precoder designs on manifolds for IA. By restricting the optimization only at the transmitters' side, it will alleviate the overhead induced by alternation beten the forward and reverse links significantly. Firstly a classical steepest descent (SD) algorithm in multi-dimensional complex space is proposed to achieve feasible IA. Then  reform the optimization problem on Stiefel manifold, and propose a novel SD algorithm based on this manifold with lor dimensions. Moreover, aiming at further reducing the complexity, Grassmann manifold is introduced to derive corresponding algorithm for reaching the perfect IA. Numerical simulations show that the proposed algorithms on manifolds have better convergence performance and higher system capacity than previous methods, also achieve the maximum DoF.
['Chen Zhang', 'Huarui Yin', 'Guo Wei']
I am writing a research paper on a idea One-sided Precoder Designs on Manifolds for Interference Alignment
[{"from": "human", "value": "I am writing a research paper on a idea One-sided Precoder Designs on Manifolds for Interference Alignment"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Interference alignment (IA) is a technique recently shown to achieve the maximum degrees of freedom (DoF) of $K$-user interference channel. ,  focus on the precoder designs on manifolds for IA. By restricting the optimization only at the transmitters' side, it will alleviate the overhead induced by alternation beten the forward and reverse links significantly. Firstly a classical steepest descent (SD) algorithm in multi-dimensional complex space is proposed to achieve feasible IA. Then  reform the optimization problem on Stiefel manifold, and propose a novel SD algorithm based on this manifold with lor dimensions. Moreover, aiming at further reducing the complexity, Grassmann manifold is introduced to derive corresponding algorithm for reaching the perfect IA. Numerical simulations show that the proposed algorithms on manifolds have better convergence performance and higher system capacity than previous methods, also achieve the maximum DoF."}]