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A new antenna selection algorithm for multiple input multiple output (MIMO) wireless systems is proposed. The modified Tanimoto coeffcient is used to compare the similarity of the rows/columns of the channel matrix. Based on the calculated similarity, the proposed algorithm chooses the antenna subset, which has the maximum product of dissimilarity and Frobenius norm. The proposed algorithm requires low computational com-plexity as to the optimal selection but with comparative outage capacity and average signal to noise ratio (SNR) performance. It can improve both the outage capacity and the average SNR as compared to random selection. The simulation results are shown to validate our algorithm.
The new algorithm for multiple input multiple output (MIMO) wireless systems is proposed. The modified Tanimoto coeffcient is used to compare the similarity of the rows / columns of the channel matrix. Based on the calculated similarity, the proposed algorithm chooses the antenna subset, which has the maximum product of dissimilarity and Frobenius norm. The proposed algorithm requires low computational com-plexity as to the optimal selection but with comparative outage capacity and average signal to noise ratio (SNR) performance. It can improve both the outage capacity and the average SNR as compared to random selection. The simulation results are shown validate our algorithm.