Open AccessLow complexity Massive MIMO detection algorithm based on improved LAS
Author(s) -
Quan Yuan,
Juan Zhang
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1861/1/012019
Subject(s) - algorithm , mimo , computer science , key (lock) , set (abstract data type) , wireless , channel (broadcasting) , telecommunications , computer security , programming language
Massive multiple-input multiple-output (M-MIMO) technology is a key technology for 5G communications and future mobile wireless networks. Although the likelihood ascent search (LAS) algorithm in the existing detection algorithms is relatively low in complexity, the algorithm is easy to fall into the local optimum, resulting in poor global performance. Therefore, based on this algorithm, this paper proposes an improved detection scheme based on the LAS algorithm in the reduced neighborhood. This algorithm combines the idea of a reduced neighborhood and iteratively improves the LAS algorithm. The algorithm is designed by reducing the size of the neighborhood and increasing the number of iterations. The algorithm compares the BER performance of different neighborhood parameters, and obtains a set of parameters to significantly reduce BER through simulation comparison.