Green Power Control in Cognitive Wireless Networks
Mael Le Treust, Samson Lasaulce, Yezekael Hayel, Gaoning He

TL;DR
This paper analyzes how cognitive and non-cognitive transmitters interact in a decentralized wireless network to optimize energy efficiency, revealing that partial cognition maximizes network performance and that sequential sensing and power control strategies outperform joint optimization.
Contribution
It introduces a hierarchical game model for cognitive radio power control, analyzes the equilibrium conditions, and demonstrates the benefits of sequential decision-making over joint optimization.
Findings
Network energy-efficiency is maximized with a fraction of cognitive transmitters.
The sensing decision game is a weighted potential game with multiple equilibria.
Sequential sensing and power control improve individual and network performance.
Abstract
A decentralized network of cognitive and non-cognitive transmitters where each transmitter aims at maximizing his energy-efficiency is considered. The cognitive transmitters are assumed to be able to sense the transmit power of their non-cognitive counterparts and the former have a cost for sensing. The Stackelberg equilibrium analysis of this level hierarchical game is conducted, which allows us to better understand the effects of cognition on energy-efficiency. In particular, it is proven that the network energy-efficiency is maximized when only a given fraction of terminals are cognitive. Then, we study a sensing game where all the transmitters are assumed to take the decision whether to sense (namely to be cognitive) or not. This game is shown to be a weighted potential game and its set of equilibria is studied. Playing the sensing game in a first phase (e.g., of a time-slot)…
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