.png){kind=icon}
.png){kind=icon}
Return
A Scalable, Multimode SVD Precoding ASIC Based on the Cyclic Jacobi Method
.png){kind=icon}
PRE
AI
DOI：10.1109/TCSI.2016.2561904.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Modern wireless communication standards define new high-throughput use cases like 8x8 multiple-input, multiple-output (MIMO) antenna setups and a 256-QAM constellation alphabet in the case of IEEE 802.11ac. Baseband precoding at the transmitter is a key technique to achieve the corresponding data rates at a reasonable signal-to-noise ratio (SNR). Multimode capability, (i.e., the ability to support multiple MIMO setups) is crucial for legacy compatibility or for the adaptation to the individual configurations of mobile stations. This paper presents an application-specific integrated circuit (ASIC) template for singular value decomposition (SVD)-based linear precoding supporting multimode MIMO. A two-sided cyclic Jacobi algorithm is applied to decompose the SVD computation exclusively into 2 x 2 vector arithmetic units. A fixed computation pattern is executed iteratively on the input data. Iteration control allows a graceful trading of communication performance for a reduction of computational complexity. As a proof-of-concept, the architecture template is configured to support 2 x 2, 4 x 4, 6 x 6, and 8 x 8 MIMO and is layouted for 90-nm CMOS with a core area of 1.34 mm(2) and a clock frequency of 752 MHz. The achieved throughput is 188, 15.7, 6.27, and 1.68 million SVDs per second, respectively.
Keywords:
Application-specific integrated circuit (ASIC)
IEEE 802.11ac
multiple input
multiple output (MIMO)
multi-mode
precoding
singular value decomposition (SVD)
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
5.2
Papers:
9.7K
Citations:
2.2W