Channel Estimation Overhead Reduction for Downlink FDD Massive MIMO Systems

<p>Massive multiple-input multiple-output (MIMO) is the concept of deploying a very large number of antennas at the base stations (BS) of cellular networks. Frequency-division duplexing (FDD) massive MIMO systems in the downlink (DL) suffer significantly from the channel estimation overhead. In this thesis, we propose a minimum mean square error (MMSE)-based channel estimation framework that exploits the spatial correlation between the antennas at the BS to reduce the latter overhead. We investigate how the number of antennas at the BS affects the channel estimation error through analytical and asymptotic analysis. In addition, we derive a lower bound on the spectral efficiency of the communication system. Close form expressions of the asymptotic MSE and the spectral efficiency lower bound are obtained. Furthermore, perfect match between theoretical and simulation results is observed, and results show the feasibility of our proposed scheme.</p>

Name thesis:degree_name

Master of Science in Electrical Engineering (MSEE)

Level thesis:degree_level

Thesis

Year dc:date.available

2016

Author dc:creator

• Mayouche, Abderrahmane

Advisor dc:contributor.advisor

• Yang, Jing

Contributors dc:contributor

• Wu, Jingxian
• McCann, Roy A.

• Applied sciences
• Asymptotic analysis
• Channel estimation overhead
• FDD
• MSE
• Massive MIMO
• Spectral efficiency
• Electrical and Electronics
• Systems and Communications

Repository record dc:identifier

https://scholarworks.uark.edu/etd/1688

OAI identifier oai:identifier

oai:scholarworks.uark.edu:etd-3227