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Improved Likelihood Probability in MIMO Systems Using One-Bit ADCsopen access

Authors
Kim, Tae-Kyoung
Issue Date
Jun-2023
Publisher
MDPI
Keywords
multi-input multi-output systems; one-bit analog-to-digital converters; maximum likelihood probability; weighted combining
Citation
SENSORS, v.23, no.12
Journal Title
SENSORS
Volume
23
Number
12
URI
https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/88591
DOI
10.3390/s23125542
ISSN
1424-8220
Abstract
This study considers an improved likelihood probability in multi-input multi-output (MIMO) systems using one-bit analog-to-digital converters (ADCs). MIMO systems using one-bit ADCs are known to exhibit from performance degradation because of inaccurate likelihood probabilities. To overcome this degradation, the proposed method leverages the detected symbols to estimate the true likelihood probability by combining the initial likelihood probability. An optimization problem is formulated to minimize the mean-squared error between the true and combined likelihood probabilities, and a solution is derived using the least-squares method. Simulation results show that the proposed method obtains a signal-to-noise gain of approximately 0.3 dB to achieve a frame error rate of 10(-1) compared to conventional methods. This improvement in performance is attributed to the enhanced reliability of the likelihood probability.
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반도체대학 (반도체·전자공학부)
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