Efficient low-overhead channel estimation for 5g lens based millimeter-wave massive MIMO systems
Автор: Imran Khan
Журнал: International Journal of Wireless and Microwave Technologies @ijwmt
Статья в выпуске: 3 Vol.8, 2018 года.
Бесплатный доступ
Beamspace MIMO performs beam-selection which can substantially reduce the number of power-consuming radio frequency (RF) chains without perceptible performance deterioration. However, for capacity-approaching performance, accurate information of the beamspace-channel of large-size is required for beam-selection, which is contesting in case of little number of RF-chains. To overcome such problem, I proposed an efficient support-detection (SD) algorithm for channel-estimation with low pilot-overhead and short number of RF chains. The key idea of SD-algorithm is to divide the whole issue of beamspace channel-estimation into a series of sub-issues, where each of them considers only one sparse channel-component. The support of each channel component is detected reliably by deploying the sparse structure attributes of the beamspace-channel. The effect of this channel-component is eliminated from the whole channel-estimation issue. Thus, the sparse beamspace-channel can be estimated with low pilot-overhead. Simulation Results shows that the proposed schemes perform much better than the conventional compressed-sensing (CS) schemes.
MmWave, Beamspace, SD, Pilot, RF chain
Короткий адрес: https://sciup.org/15016931
IDR: 15016931 | DOI: 10.5815/ijwmt.2018.03.05
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