Location-Based Greedy Pilot Assignment for Cell-Free Massive MIMO Systems

In recent years cell-free massive multiple-input multiple-output system has attracted considerable attention for promising large spectral and power efficiency. However, pilot contamination, a well-known challenge in cell-free massive MIMO, limits these aspired gains. Alongside, and since 2000, Locat...

Full description

Saved in:
Bibliographic Details
Published in2018 IEEE 4th International Conference on Computer and Communications (ICCC) pp. 392 - 396
Main Authors Zhang, Yao, Cao, Haotong, Zhong, Peng, Qi, Chang, Yang, Longxiang
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2018
Subjects
Online AccessGet full text
DOI10.1109/CompComm.2018.8780756

Cover

More Information
Summary:In recent years cell-free massive multiple-input multiple-output system has attracted considerable attention for promising large spectral and power efficiency. However, pilot contamination, a well-known challenge in cell-free massive MIMO, limits these aspired gains. Alongside, and since 2000, Location Based Services (LBS) have rapidly emerged and enabled users to know their current location information for various purposes. In order to reduce pilot contamination and improve system performance in cell-free massive MIMO, this paper proposes an efficient location-based greedy pilot assignment (LBGPA) algorithm. Specifically, by following the principle that two users in close vicinity of each other are not assigned the same pilot sequence and utilizing the advantage of greedy pilot assignment (GPA), the pilot contamination can be reduced significantly. Numerical experiments show that the proposed algorithm outperforms other conventional pilot assignment schemes in typical cell-free massive MIMO systems.
DOI:10.1109/CompComm.2018.8780756