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Conference Paper
Low Complexity Beam Searching Algorithm Using Asymptotic Property of Massive MIMO Systems
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- Authors
- Heeyoung Kim, Jaemin Jung, Seongbae Han, Seokki Kim, Seungkwon Baek, Sooyong Choi
- Issue Date
- 2018-07
- Citation
- International Conference on Ubiquitous and Future Networks (ICUFN) 2018, pp.589-591
- Publisher
- IEEE
- Language
- English
- Type
- Conference Paper
- Abstract
- This paper considers a low complexity codebook-based beam searching algorithm for massive MIMO (Multiple Input Multiple Output) systems in limited scattering environments. Based on the asymptotic property of the massive MIMO systems that the channel array response vector converges to the optimal precoding vector derived from channel singular value decomposition (SVD), we propose a independent selection method for the transmitter (TX) and receiver (RX) beam vectors. Due to the independent selection of the Tx and Rx beam vectors from the asymptotic property, the proposed algorithm has a much lower complexity compared to the full search beam selection method. Furthermore, the proposed algorithm shows the similar data rates to the full search beam selection method at low signal to noise ratio regions in a 6-bit codebook system with 64×64 antennas and 2 RF chains at each TX and RX.
- KSP Keywords
- Full search, Massive MIMO system, Multiple input multiple output(MIMO), Precoding Vector, RF chain, Searching algorithm, Selection method, Signal noise ratio(SNR), Signal-to-Noise, beam selection, data rate