Power allocation for the multi-carrier two-user Gaussian Interference Channel

Pischella, Mylène; Ruyet, Didier Le

doi:10.1109/spawc.2012.6292895

Cited by 2 publications

(2 citation statements)

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“…It is optimal in almost all cases [12,13]. An iterative power allocation and decoding strategy has been proposed for the multi-carrier two-user G-IFC in [14], providing additional insight into the multi-carrier G-IFC with respect to [15]. These results on the two-user G-IFC do not directly extend to the studied cognitive case.…”

Section: Introductionmentioning

confidence: 99%

“…The Han-Kobayashi strategies on the two-user G-IFC achieve the sum-capacity by using private information for s k 2 in the following cases: when interference is very weak (Equation (3)), and with mixed interference; when interference is strong at receiver 2 but weak at receiver 1. These two cases are however rare (around 7% of the cases with Rayleigh fadings for the two-user G-IFC according to [14]) and restricting to them would lead to very low data rates for the secondary system. Consequently, we propose to adapt the decoding strategy in the following way for the two-user cognitive system: When P k 1 D 0, the secondary system uses channel interweave.…”

Section: Introduction Of the Cognitive Constraints In The Two-user Gamentioning

confidence: 99%

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Adaptive resource allocation and decoding strategy for underlay multi‐carrier cooperative cognitive radio systems

Pischella

Ruyet

2013

Trans. Emerging Tel. Tech.

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This paper proposes a resource allocation and decoding strategy at the secondary system for underlay and interweave multi-carrier cooperative cognitive radio. The objective is to maximise the sum rate of both primary and secondary systems, taking into account the interference threshold constraint and the fact that the primary receiver always considers interference as noise. The decoding method at the secondary receivers is either Successive Interference Cancellation or treating interference as noise, depending on their channel gains. The rationale for this strategy is the extension of the Han-Kobayashi capacity-achieving strategy on the Gaussian interference channel to the studied cognitive scenario. The proposed resource allocation algorithm is composed of a subcarrier allocation procedure to avoid intercell interference between secondary cells and of an iterative power allocation algorithm that maximises the sum rate on the primary and secondary cells, respectively. The proposed algorithm achieves high data rate improvements for the secondary systems while maintaining a low degradation on the primary system's rate. It also benefits from multi-user diversity and is robust to the distance variations.

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