Interference Alignment in Two-Way Relay Networks via Rank Constraints Rank Minimization

摘要

Interference alignment (IA) is one of the promising measures for the multi-user network to manage interference. The rank con-straints rank minimization means that interfer-ence spans the lowest dimensional subspace and the useful signal spans all available spatial dimensions. In order to improve the perfor-mance of two-way relay network, we can use rank constrained rank minimization (RCRM) to solve the IA problem. This paper proposes left reweighted nuclear norm minimization-γalgorithm and selective coupling reweighted nuclear norm minimization algorithm to im-plement interference alignment in two-way relay networks. The left reweighted nuclear norm minimization-γ algorithm is based on reweighted nuclear norm minimization algo-rithm and has a novel γ choosing rule. The selective coupling reweighted nuclear norm minimization algorithm weighting methods choose according to singular value of interfer-ence matrixes. Simulation results show that the proposed algorithms considerably improve the sum rate performance and achieve the higher average achievable multiplexing gain in two-way relay interference networks.