A Practical and Efficient Algorithm for Distributed Interference Alignment Based on Cognitive Radio

The authors propose a practical and efficient Minor Subspace Tracking (MST) algorithm to implement Distributed Interference Alignment (IA) based on Cognitive Radio (CR) that employs Interference Subspace Tracking (IST). The proposed MST algorithm utilizes the parallelizable matrix-vector products instead of the back and forward substitution in the existing MST algorithm for IST-IA, which is an inherent serial process unsuitable for the parallel implementation. Thus the proposed MST algorithm is more suitable for the practical parallel implementation than the existing MST algorithm for IST-IA. The proposed MST algorithm also requires less computational complexity than the existing MST algorithm for IST-IA.