US 11,968,064 B2
Multiple-input and multiple-output (MIMO) detection in wireless communications
Jian Gu, San Diego, CA (US); Chengzhi Li, San Diego, CA (US); Hang Zhou, San Diego, CA (US); and Bin Liu, San Diego, CA (US)
Assigned to ZEKU TECHNOLOGY (SHANGHAI) CORP., LTD., Shanghai (CN)
Filed by ZEKU TECHNOLOGY (SHANGHAI) CORP., LTD., Shanghai (CN)
Filed on Sep. 26, 2022, as Appl. No. 17/953,088.
Application 17/953,088 is a continuation of application No. PCT/US2021/019081, filed on Feb. 22, 2021.
Claims priority of provisional application 63/031,364, filed on May 28, 2020.
Prior Publication US 2023/0040774 A1, Feb. 9, 2023
Int. Cl. H04L 25/03 (2006.01); H04B 7/022 (2017.01); H04B 7/0417 (2017.01); H04B 7/06 (2006.01); H04L 1/00 (2006.01)
CPC H04L 25/03242 (2013.01) [H04B 7/022 (2013.01); H04B 7/0417 (2013.01); H04B 7/0626 (2013.01); H04L 1/0054 (2013.01); H04L 2025/03426 (2013.01)] 18 Claims
OG exemplary drawing
 
1. A method for improving noise estimation at a receiver, the method comprising:
receiving a plurality of reference signals;
for a given reference signal:
determining a noise estimation; and
determining a distance metric and a log-likelihood ratio (LLR) of the noise estimation; and
determining a final LLR based on the distance metric and the LLR of each noise estimation;
wherein determining the final LLR further comprises:
combining the LLRs of at least two noise estimations; or
selecting the LLR of a particular noise estimation based on the distance metric of the particular noise estimation;
wherein for a first reference signal of the plurality of reference signal, the noise estimation is a first noise estimation, the distance metric is a first distance metric, and the LLR is a first LLR;
for a second reference signal of the plurality of reference signals, the noise estimation is a second noise estimation, the distance metric is a second distance metric, and the LLR is a second LLR;
wherein the method further comprises:
determining a combined noise estimate, wherein determining the combined noise estimate comprises:
combining the first LLR and the second LLR; or
determining that the second distance metric is nearer to a threshold value than the first distance metric; and determining the combined noise estimate according to the second noise estimation.