Open AccessTime‐variant beam selection for lens‐based millimetre‐wave massive MIMO systems
Author(s) -
Guo Zhenduo,
Li Jianjun
Publication year - 2017
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/el.2017.2259
Subject(s) - mimo , millimetre wave , neighbourhood (mathematics) , computer science , selection (genetic algorithm) , channel (broadcasting) , extremely high frequency , electronic engineering , telecommunications , optics , physics , artificial intelligence , engineering , mathematics , mathematical analysis
Lens‐based millimetre‐wave (mmWave) massive multiple‐input multiple‐output (MIMO) can utilise beam selection to reduce the number of radio‐frequency (RF) chains. However, most of the existing beam selection schemes involve high complexity, especially with the fast time‐variant mmWave channels. In this Letter, by exploiting the mmWave channel property that the angles of departure of channel paths are slowly varying, the authors propose an adaptive neighbourhood search (ANS) beam selection. The key idea is to utilise the concept of neighbourhood search developed from machine learning to select the beams with significantly reduced complexity, where the neighbourhood range is adaptively adjusted to avoid the local optimum. Simulation results show that the authors’ scheme can achieve the performance close to the conventional real‐time beam selection schemes.