A Low Complexity Massive MIMO Detection Scheme Using Angular-Domain Processing

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title = "A Low Complexity Massive MIMO Detection Scheme Using Angular-Domain Processing",
abstract = "Signal processing complexity and required memory become problematic in massive MIMO systems as the dimension of channel state information (CSI) matrix grows significantly with the large number of antennas and users. To address these challenges, we propose the first angular-domain massive MIMO detection scheme, which is based on three concepts: transferring the baseband processing from the spatial domain to the angular domain; exploiting the sparsity of received beams to reduce the dimension of CSI matrix; and performing the whole detection and precoding in the angular domain using the reduced CSI matrix. We have measured the massive MIMO channel at 2.6 GHz with a 128-antenna linear array communicating with 16 users to evaluate our scheme. Complexity analysis and simulations show that proposed idea leads to 40{\%} – 70{\%} reduction in the processing complexity and memory without significant performance loss, which significantly outperforms the antenna-domain schemes.",
keywords = "massive MIMO, angular domain, channel compression, CSI matrix, MIMO detection, low complexity, channel sparsity",
author = "Mojtaba Mahdavi and Ove Edfors and Viktor {\"O}wall and Liang Liu",
year = "2018",
doi = "10.1109/GlobalSIP.2018.8646483",
language = "English",
isbn = "978-1-7281-1296-1",
pages = "181--185",
booktitle = "IEEE Global Conference on Signal and Information Processing (GlobalSIP)",
publisher = "IEEE - Institute of Electrical and Electronics Engineers Inc.",