Accurate Performance Analysis of Coded Large-Scale Multiuser MIMO Systems with MMSE Receivers.

Area of Science:

• Wireless communication networks
• Signal processing
• Information theory

Background:

• Large-scale multi-user MIMO systems are crucial for future wireless networks.
• Accurate performance estimation is essential for system design and optimization.
• Existing models may not fully capture the complexities of uplink performance under various channel conditions.

Purpose of the Study:

• To estimate the uplink performance of large-scale multi-user MIMO networks.
• To derive a novel statistical distribution for the signal-to-interference-plus-noise ratio (SINR).
• To obtain analytical expressions for pairwise error probability (PEP) and the upper bound of bit error rate (BER).

Main Methods:

• Application of minimum-mean-square-error (MMSE) detection.
• Derivation of SINR distribution considering path loss, shadowing, and Rayleigh fading.
• Analytical derivation of PEP and BER upper bounds assuming perfect channel state information.

Main Results:

• A novel statistical distribution for SINR in multi-user MIMO systems was derived.
• Analytical expressions for PEP and an upper bound for BER were obtained.
• Simulations validated the derived analytical results across various scenarios.

Conclusions:

• The study provides accurate analytical tools for evaluating uplink performance in massive multi-user MMSE-MIMO systems.
• The derived SINR distribution and BER upper bound are valuable for system designers.
• The findings contribute to the understanding and optimization of future wireless communication networks.