A 1.8Gb/s 70.6pJ/b 128×16 link-adaptive near-optimal massive MIMO detector in 28nm UTBB-FDSOI
(2018) 65th IEEE International Solid-State Circuits Conference, ISSCC 2018 61. p.224-226- Abstract
This work presents a 2.0mm2 128×16 massive MIMO detector IC that provides 21dB array gain and 16x multiplexing gain at the system level. The detector implements iterative expectation-propagation detection (EPD) for up to 256-QAM modulation. Tested with measured channel data [1], the detector achieves 4.3dB processing gain over state-of-the-art massive MlMo detectors [2, 3], enabling 2.7x reduction in transmit power for battery-powered mobile terminals. The iC uses link-adaptive processing to meet a variety of practical channel conditions with scalable energy consumption. The design is realized in a condensed systolic array architecture and an approximate moment-matching circuitry to reach 1.8Gb/s at 70.6pJ/b. The performance... (More)
This work presents a 2.0mm2 128×16 massive MIMO detector IC that provides 21dB array gain and 16x multiplexing gain at the system level. The detector implements iterative expectation-propagation detection (EPD) for up to 256-QAM modulation. Tested with measured channel data [1], the detector achieves 4.3dB processing gain over state-of-the-art massive MlMo detectors [2, 3], enabling 2.7x reduction in transmit power for battery-powered mobile terminals. The iC uses link-adaptive processing to meet a variety of practical channel conditions with scalable energy consumption. The design is realized in a condensed systolic array architecture and an approximate moment-matching circuitry to reach 1.8Gb/s at 70.6pJ/b. The performance and energy efficiency can be tuned over a wide range by UTBB-FDSOI body bias.
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- author
- Tang, Wei LU ; Prabhu, Hemanth LU ; Liu, Liang LU ; Öwall, Viktor LU and Zhang, Zhengya
- organization
- publishing date
- 2018-03-08
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- 2018 IEEE International Solid-State Circuits Conference, ISSCC 2018
- volume
- 61
- pages
- 3 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 65th IEEE International Solid-State Circuits Conference, ISSCC 2018
- conference location
- San Francisco, United States
- conference dates
- 2018-02-11 - 2018-02-15
- external identifiers
-
- scopus:85046434545
- ISBN
- 978-1-5090-4940-0
- 978-1-5386-2227-8
- DOI
- 10.1109/ISSCC.2018.8310265
- language
- English
- LU publication?
- yes
- id
- 66b887c3-6cac-4935-a246-6d3b86b93d19
- date added to LUP
- 2018-05-17 15:45:43
- date last changed
- 2024-09-16 21:47:03
@inproceedings{66b887c3-6cac-4935-a246-6d3b86b93d19, abstract = {{<p>This work presents a 2.0mm<sup>2</sup> 128×16 massive MIMO detector IC that provides 21dB array gain and 16x multiplexing gain at the system level. The detector implements iterative expectation-propagation detection (EPD) for up to 256-QAM modulation. Tested with measured channel data [1], the detector achieves 4.3dB processing gain over state-of-the-art massive MlMo detectors [2, 3], enabling 2.7x reduction in transmit power for battery-powered mobile terminals. The iC uses link-adaptive processing to meet a variety of practical channel conditions with scalable energy consumption. The design is realized in a condensed systolic array architecture and an approximate moment-matching circuitry to reach 1.8Gb/s at 70.6pJ/b. The performance and energy efficiency can be tuned over a wide range by UTBB-FDSOI body bias.</p>}}, author = {{Tang, Wei and Prabhu, Hemanth and Liu, Liang and Öwall, Viktor and Zhang, Zhengya}}, booktitle = {{2018 IEEE International Solid-State Circuits Conference, ISSCC 2018}}, isbn = {{978-1-5090-4940-0}}, language = {{eng}}, month = {{03}}, pages = {{224--226}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, title = {{A 1.8Gb/s 70.6pJ/b 128×16 link-adaptive near-optimal massive MIMO detector in 28nm UTBB-FDSOI}}, url = {{http://dx.doi.org/10.1109/ISSCC.2018.8310265}}, doi = {{10.1109/ISSCC.2018.8310265}}, volume = {{61}}, year = {{2018}}, }