Performance and ASIC designs of the K-best LSD and LMMSE detectors for LTE downlink
|Author:||Suikkanen, Essi1; Juntti, Markku2|
1Keysight Technologies Finland Oy, Elektroniikkatie 10, FIN-90590 Oulu, Finland
2Centre for Wireless Communications, University of Oulu, P.O. Box 4500, FIN-90014 Oulu, Finland
|Online Access:||PDF Full Text (PDF, 0.6 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2019072323170
|Publish Date:|| 2020-02-04
We consider performance comparison and application specific integrated circuit (ASIC) designs of linear minimum mean-square error (LMMSE) and K-best list sphere detector (LSD) algorithms for 4 × 4 and 8 × 8 multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems. Requirements for higher data rate and lower power consumption set new challenges for implementation. In order to minimize the power consumption, an optimal detector would be able to switch the detection algorithm to suit the channel conditions. The detectors are designed for three different modulation schemes using 28 nm complementary metal oxide semiconductor (CMOS) technology. The communications performance is evaluated in the Third Generation Partnership Project (3GPP) Long-Term Evolution (LTE) system. The impact of transmit precoding is considered. The ASIC designs aim at providing the hardware design aspects to the comparison of detectors. The designs are synthesized and complexity and power consumption results are found. Based on the ASIC synthesis and communications performance results, we show the performance–energy efficiency and performance–complexity comparison. We also present the most suitable scenarios for a low-power detector and show how the transmit precoding impacts the detector selection.
Journal of signal processing systems for signal image and video technology
|Pages:||1291 - 1304|
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
213 Electronic, automation and communications engineering, electronics
This research was financially supported in part by Tekes, the Finnish Funding Agency for Innovation, Academy of Finland, Nokia Solutions and Networks, Broadcom Communications Finland and Xilinx.
© Springer Science+Business Media, LLC, part of Springer Nature 2019. This is a post-peer-review, pre-copyedit version of an article published in Journal of Signal Processing Systems. The final authenticated version is available online at: https://doi.org/10.1007/s11265-019-1441-8.