Diversity-Multiplexing Tradeoff via Asymptotic Analysis of Large MIMO Systems
Sergey Loyka, George Levin

TL;DR
This paper analyzes the finite-SNR diversity-multiplexing tradeoff in large MIMO systems, showing how different definitions of multiplexing gain affect convergence to the asymptotic DMT and highlighting the impact of channel correlation.
Contribution
It derives finite-SNR DMT for various channels using recent outage capacity results and clarifies how multiplexing gain definitions influence convergence and accuracy.
Findings
Finite-SNR DMT converges at realistic SNR when using ergodic capacity-based multiplexing gain.
Slow convergence occurs with high-SNR asymptote-based multiplexing gain, especially for large systems.
Correlation and power imbalance reduce diversity gain, which is captured by size-asymptotic DMT but not by SNR-asymptotic DMT.
Abstract
Diversity-multiplexing tradeoff (DMT) presents a compact framework to compare various MIMO systems and channels in terms of the two main advantages they provide (i.e. high data rate and/or low error rate). This tradeoff was characterized asymptotically (SNR-> infinity) for i.i.d. Rayleigh fading channel by Zheng and Tse [1]. The asymptotic DMT overestimates the finite-SNR one [2]. In this paper, using the recent results on the asymptotic (in the number of antennas) outage capacity distribution, we derive and analyze the finite-SNR DMT for a broad class of channels (not necessarily Rayleigh fading). Based on this, we give the convergence conditions for the asymptotic DMT to be approached by the finite-SNR one. The multiplexing gain definition is shown to affect critically the convergence point: when the multiplexing gain is defined via the mean (ergodic) capacity, the convergence takes…
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