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MS Final Examination – Yichuan Tian


Friday, September 16, 2016 3:00 PM - 5:00 PM

Channel Estimation in TDD Massive MIMO Systems with Subsampled Data at BS
Massive MIMO is a promising technique for future 5G communications due to its high spectrum and energy efficiency. To realize its potential performance gain, accurate channel state information at transmitter side (CSIT) is essential. Frequency division duplex (FDD) is widely employed by the most cellular systems today. However, it will introduce unaffordable pilot overhead as well as computational complexity. On the other hand, by exploiting the channel reciprocity using uplink pilots, the time division duplex (TDD) can overcome the overwhelming pilot training as well as the pilot feedback overhead. Considering these advantages, we propose a subsampling algorithm that based on time division duplex (TDD). Particularly, we first exploit the intrinsic sparsity of CSIT, and then employing the Walsh-Hadamard Transform (WHT), which will subsample the received signal at BS, into channel estimation. Additionally, we discuss the proposed channel estimation scheme in multicell scenario. Simulation results demonstrate that the proposed algorithm can accurately estimate channels with reduced computational complexity.

Major Advisor: Mario Magaña
Committee: Jinsub Kim
Committee: Huaping Liu
Committee: William Warnes


Kelley Engineering Center (campus map)
3114
Nicole Thompson
1 541 737 3617
Nicole.Thompson at oregonstate.edu
Sch Elect Engr/Comp Sci
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