Massive multiple input multiple output(MIMO)systems can increase capacity and reliability greatly.However,extremely high hardware costs and computational complexity lead to the demand for reasonable antenna selection....Massive multiple input multiple output(MIMO)systems can increase capacity and reliability greatly.However,extremely high hardware costs and computational complexity lead to the demand for reasonable antenna selection.Aiming at the problem that the traditional antenna selection algorithm based on maximizing sum capacity has large complexity and worse bit error rate(BER)performance,a two-step selection algorithm is proposed,which selects a part of the antennas based on the norm-based antenna selection(NBS)firstly,and then selects the antenna based on maximizing capacity via convex optimization.The simulation results show that the improved algorithm has better BER performance than the traditional algorithms.At the same time,it reduces computational complexity greatly.展开更多
基金the National Natural Science Foundation of China(61801371)。
文摘Massive multiple input multiple output(MIMO)systems can increase capacity and reliability greatly.However,extremely high hardware costs and computational complexity lead to the demand for reasonable antenna selection.Aiming at the problem that the traditional antenna selection algorithm based on maximizing sum capacity has large complexity and worse bit error rate(BER)performance,a two-step selection algorithm is proposed,which selects a part of the antennas based on the norm-based antenna selection(NBS)firstly,and then selects the antenna based on maximizing capacity via convex optimization.The simulation results show that the improved algorithm has better BER performance than the traditional algorithms.At the same time,it reduces computational complexity greatly.
