MIMO Wireless Communications under Statistical Queueing Constraints
Mustafa Cenk Gursoy

TL;DR
This paper analyzes the impact of statistical queueing constraints on MIMO wireless system performance across low-power, wideband, and high-SNR regimes, revealing how buffer limitations affect energy efficiency and capacity derivatives.
Contribution
It provides a comprehensive analysis of effective capacity under queueing constraints in various regimes and identifies optimal transmission strategies considering these constraints.
Findings
Second derivative of effective capacity decreases with stricter queueing constraints.
Minimum bit energy remains unchanged, but wideband slope diminishes under constraints.
Sparse multipath fading increases energy requirements with queueing constraints.
Abstract
The performance of multiple-input multiple-output wireless systems is investigated in the presence of statistical queueing constraints. Queuing constraints are imposed as limitations on buffer violation probabilities. The performance under such constraints is captured through the effective capacity formulation. A detailed analysis of the effective capacity is carried out in the low-power, wideband, and high--signal-to-noise ratio (SNR) regimes. In the low-power analysis, expressions for the first and second derivatives of the effective capacity with respect to SNR at SNR= 0 are obtained under various assumptions on the degree of channel state information at the transmitter. Transmission strategies that are optimal in the sense of achieving the first and second derivatives are identified. It is shown that while the first derivative does not get affected by the presence of queueing…
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