Channel Estimation in TDD Massive MIMO Systems with Subsampled Data at BS Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/kh04ds905

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  • 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 requires unaffordable pilot overhead and has high 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 can be implemented in a TDD mode. Particularly, we first exploit the intrinsic sparsity of CSIT, and then employ the Walsh-Hadamard Transform (WHT), which will subsample the received signal at BS, to perform channel estimation. Additionally, we discuss the proposed channel estimation scheme in a multicell scenario. Simulation results demonstrate that the proposed algorithm can accurately estimate channels with reduced computational complexity.
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  • description.provenance : Submitted by Yichuan Tian (tianyi@oregonstate.edu) on 2016-09-18T06:56:00Z No. of bitstreams: 1 YichuanTian2016.pdf: 49912689 bytes, checksum: 3a77b4c34761e20717f6fa404a6049a2 (MD5)
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  • description.provenance : Approved for entry into archive by Julie Kurtz(julie.kurtz@oregonstate.edu) on 2016-09-26T16:28:55Z (GMT) No. of bitstreams: 1 YichuanTian2016.pdf: 49912689 bytes, checksum: 3a77b4c34761e20717f6fa404a6049a2 (MD5)
  • description.provenance : Approved for entry into archive by Laura Wilson(laura.wilson@oregonstate.edu) on 2016-09-28T16:27:10Z (GMT) No. of bitstreams: 1 YichuanTian2016.pdf: 49912689 bytes, checksum: 3a77b4c34761e20717f6fa404a6049a2 (MD5)

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