Date of Graduation
8-2016
Document Type
Thesis
Degree Name
Master of Science in Electrical Engineering (MSEE)
Degree Level
Graduate
Department
Electrical Engineering
Advisor/Mentor
Jing Yang
Committee Member
Jingxian Wu
Second Committee Member
Roy Mccann
Keywords
Applied sciences, Asymptotic analysis, Channel estimation overhead, FDD, MSE, Massive MIMO, Spectral efficiency
Abstract
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.
Citation
Mayouche, A. (2016). Channel Estimation Overhead Reduction for Downlink FDD Massive MIMO Systems. Graduate Theses and Dissertations Retrieved from https://scholarworks.uark.edu/etd/1688