Sampled-data $H^{\infty}$ Optimization for Self-interference Suppression in Baseband Signal Subspaces
It addresses self-interference cancellation for wireless relay stations, but the contribution appears incremental as it extends existing H∞ control techniques to a specific implementation structure.
The paper proposes a sampled-data H∞ optimization method for self-interference suppression in wireless relay stations, formulated as a control problem with generalized sampler and hold structures, and demonstrates effectiveness via simulation.
In this article, we propose a design method of selfinterference cancelers for wireless relay stations taking account of the baseband signal subspace. The problem is first formulated as a sampled-data $H^{\infty}$ control problem with a generalized sampler and a generalized hold, which can be reduced to a discretetime $\ell^2$-induced norm minimization problem. Taking account of the implementation of the generalized sampler and hold, we adopt the filter-sampler structure for the generalized sampler, and the uspampler-filter-hold structure for the generalized hold. Under these implementation constraints, we reformulate the problem as a standard discrete-time $H^{\infty}$ control problem by using the discrete-time lifting technique. A simulation result is shown to illustrate the effectiveness of the proposed method.