Wang Qin-Min, Zhang Zhong-Pei, Jie Feng-Ke, Dang Zhi-Jun. Research on Diversity Detection Algorithm for Interference Alignment[J]. Journal of Electronics & Information Technology, 2012, 34(6): 1393-1397. doi: 10.3724/SP.J.1146.2011.01039
Citation:
Wang Qin-Min, Zhang Zhong-Pei, Jie Feng-Ke, Dang Zhi-Jun. Research on Diversity Detection Algorithm for Interference Alignment[J]. Journal of Electronics & Information Technology, 2012, 34(6): 1393-1397. doi: 10.3724/SP.J.1146.2011.01039
Wang Qin-Min, Zhang Zhong-Pei, Jie Feng-Ke, Dang Zhi-Jun. Research on Diversity Detection Algorithm for Interference Alignment[J]. Journal of Electronics & Information Technology, 2012, 34(6): 1393-1397. doi: 10.3724/SP.J.1146.2011.01039
Citation:
Wang Qin-Min, Zhang Zhong-Pei, Jie Feng-Ke, Dang Zhi-Jun. Research on Diversity Detection Algorithm for Interference Alignment[J]. Journal of Electronics & Information Technology, 2012, 34(6): 1393-1397. doi: 10.3724/SP.J.1146.2011.01039
In order to achieve the optimal detection algorithm for interference alignment, a diversity detection algorithm is proposed based on analyzing the feature of signal subspace. In this algorithm, the projection of desired signal onto signal subspace is served as detection vector to maximize received signal-to-noise-ratio. Numerical results show that the proposed algorithm outperforms existing schemes when the interference alignment conditions are satisfied strictly. Furthermore, with the increasing of diversity degree, the benefit of the algorithm becomes more and more obvious.