A new antenna selection scheme for correlated MIMO channels

To reduce the severe performance degradation of the traditional antenna selection schemes in correlated channels, this paper proposes a new antenna selection scheme via the self-organizing feature map (SOFM) algorithm which exploits spatial local related statistical information in fully correlated channels to improve the spatial adaptability. SOFM algorithm classifies N available antennas into L classes: antennas in each class are strongly correlated but antennas between different classes are weak correlated or uncorrelated. Thus, one antenna in each class offers the possibility of almost-optimum selection and increases the rank of the correlated fading channel matrix. These increments, directly, contribute to the Effective Degree Of Freedom (EDOF) of the channel and hence the performance. Through simulations, it was demonstrated that the proposed scheme provides excellent performance in correlated MIMO channels.