Title :
A Quadratically Convergent Method for Interference Alignment in MIMO Interference Channels
Author :
Gonzalez, O. ; Lameiro, C. ; Santamaria, Ignacio
Author_Institution :
Dept. of Commun. Eng., Univ. of Cantabria, Santander, Spain
Abstract :
Alternating minimization and steepest descent are commonly used strategies to obtain interference alignment (IA) solutions in the K-user multiple-input multiple-output (MIMO) interference channel (IC). Although these algorithms are shown to converge monotonically, they experience a poor convergence rate, requiring an enormous amount of iterations which substantially increases with the size of the scenario. To alleviate this drawback, in this letter we resort to the Gauss-Newton (GN) method, which is well-known to experience quadratic convergence when the iterates are sufficiently close to the optimum. We discuss the convergence properties of the proposed GN algorithm and provide several numerical examples showing that it always converges to the optimum with quadratic rate, reducing dramatically the required computation time in comparison to other algorithms, hence paving a new way for the design of IA algorithms.
Keywords :
MIMO communication; Newton method; gradient methods; minimisation; radiofrequency interference; wireless channels; GN method; Gauss-Newton method; IA; IC; K-user multiple-input multiple-output interference channel; MIMO interference channel; interference alignment; iteration method; minimization; quadratically convergent method; steepest descent; Convergence; Interference channels; MIMO; Minimization; Optimization; Signal processing algorithms; Alternating minimization; Gauss-Newton; interference alignment; interference channel; steepest descent;
Journal_Title :
Signal Processing Letters, IEEE
DOI :
10.1109/LSP.2014.2338132