2013/06/22 by Yuan Wang, Haonan Wang, Wang, Yuan +4
Computer Science · Engineering · Mathematics · #Advanced Multi-Objective Optimization Algorithms #Antenna Design and Optimization #FOS: Computer and information sciences #Information Theory (cs.IT) #Sparse and Compressive Sensing Techniques #cs.IT #math.IT
paper · pdf · doi:10.48550/arxiv.1306.5323
Manuscript has been submitted to Signal Processing
arxiv created 2013/06/22 · openalex publication_date 2013/06/22 · arxiv updated 2013/06/25 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01
This paper is motivated by the problem of integrating multiple sources of measurements. We consider two multiple-input-multiple-output (MIMO) channels, a primary channel and a secondary channel, with dependent input signals. The primary channel carries the signal of interest, and the secondary channel carries a signal that shares a joint distribution with the primary signal. The problem of particular interest is designing the secondary channel matrix, when the primary channel matrix is fixed. We formulate the problem as an optimization problem, in which the optimal secondary channel matrix maximizes an information-based criterion. An analytical solution is provided in a special case. Two fast-to-compute algorithms, one extrinsic and the other intrinsic, are proposed to approximate the optimal solutions in general cases. In particular, the intrinsic algorithm exploits the geometry of the unit sphere, a manifold embedded in Euclidean space. The performances of the proposed algorithms are examined through a simulation study. A discussion of the choice of dimension for the secondary channel is given.