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User-Centric Cell-Free Massive Multiple-Input-Multiple-Output System with Noisy Channel Gain Estimation and Line of

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This study shows the Beckmann distribution accurately models effective channel gain in user-centric cell-free systems. This enables precise analysis of signal quality and performance metrics like capacity and outage probability.

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Area of Science:

  • Wireless Communications
  • Signal Processing
  • Information Theory

Background:

  • User-centric cell-free (UC CF) systems offer enhanced coverage and capacity.
  • Accurate channel gain characterization is crucial for performance analysis.
  • Noisy channel state information (CSI) and line-of-sight (LoS) impact system performance.

Purpose of the Study:

  • To analyze the Beckmann distribution for characterizing effective channel gain in UC CF systems.
  • To derive the probability density function (PDF) and cumulative density function (CDF) of the signal-to-interference-plus-noise ratio (SINR).
  • To apply these derivations for analyzing ergodic capacity (EC) and outage probability (OP).

Main Methods:

  • Modeling the effective channel gain envelope using the Beckmann distribution.
  • Deriving instantaneous SINR PDF and CDF based on the Beckmann distribution.
  • Utilizing derived SINR functions for EC and OP analysis.

Main Results:

  • The effective channel gain in UC CF systems consistently follows a Beckmann distribution.
  • The Beckmann PDF and CDF were derived for the instantaneous SINR.
  • Expressions for EC and OP were successfully derived using the SINR characteristics.

Conclusions:

  • The Beckmann distribution is a suitable model for effective channel gain in UC CF systems, even with noisy CSI and LoS.
  • The derived SINR, EC, and OP expressions provide valuable tools for system design and optimization.
  • This work offers a novel analytical framework for UC CF systems.