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Improved Likelihood Probability in MIMO Systems Using One-Bit ADCs.

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Summary
This summary is machine-generated.

This study improves likelihood probability in multi-input multi-output (MIMO) systems with one-bit analog-to-digital converters (ADCs). The new method enhances signal-to-noise ratio by refining likelihood probability estimation, boosting system performance.

Keywords:
maximum likelihood probabilitymulti-input multi-output systemsone-bit analog-to-digital convertersweighted combining

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Area of Science:

  • Electrical Engineering
  • Signal Processing
  • Wireless Communications

Background:

  • Multi-input multi-output (MIMO) systems with one-bit analog-to-digital converters (ADCs) suffer performance degradation due to inaccurate likelihood probabilities.
  • Accurate likelihood probability estimation is crucial for reliable signal detection in MIMO systems.

Purpose of the Study:

  • To develop an improved method for estimating likelihood probability in one-bit ADC MIMO systems.
  • To mitigate performance degradation caused by inaccurate likelihood estimations.

Main Methods:

  • Leveraging detected symbols to estimate the true likelihood probability by combining it with the initial likelihood probability.
  • Formulating an optimization problem to minimize the mean-squared error between true and combined likelihood probabilities.
  • Deriving a solution using the least-squares method.

Main Results:

  • The proposed method achieves a signal-to-noise gain of approximately 0.3 dB for a frame error rate of 10-1.
  • Demonstrates improved performance compared to conventional methods in one-bit ADC MIMO systems.

Conclusions:

  • The enhanced reliability of the likelihood probability is key to the observed performance improvement.
  • The proposed method offers a viable solution for enhancing MIMO system performance with one-bit ADCs.