Date of Graduation
Master of Science in Electrical Engineering (MSEE)
Second Committee Member
Applied sciences, Asymptotic analysis, Channel estimation overhead, FDD, MSE, Massive MIMO, Spectral efficiency
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.
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