Joint scheduling and power allocation in Cognitive Radio systems

Masmoudi, R.; Belmega, Elena Veronica; Fijalkow, Inbar; Sellami, Noura

doi:10.1109/iccw.2015.7247212

Cited by 4 publications

(3 citation statements)

References 13 publications

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“…Specifically, we study the problem of SUs throughput maximization while keeping the interference caused to the network's PUs under a fixed tolerance set by the PUs. This problem has attracted considerable interest in the literature [5][6][7][8], but the vast majority of works on this topic have focused on the case where the users' channels remain static -or, at least, stationary -throughout the transmission horizon.…”

Section: Introductionmentioning

confidence: 99%

“…In more realistic network scenarios however, the users' mobility, their unpredictable behavior (going online and offline in an ad hoc manner), and the complex multi-path fading attributes of the wireless network cause this stringent stationarity assumption to fail. As a result, static solution concepts (such as social optima or Nash equilibria) [5][6][7] are no longer relevant when the users' wireless environment changes arbitrarily over time. Instead, a suitable solution framework is provided by online optimization and regret minimization methods [9,10] which allow users to adapt to changes in the wireless environment, quickly and efficiently.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Online Power Allocation for Opportunistic Radio Access in Dynamic OFDM Networks

Marcastel

Belmega

Mertikopoulos

et al. 2016

2016 IEEE 84th Vehicular Technology Conference (VTC-Fall)

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User mobility has become a key attribute in the design of optimal resource allocation policies for future wireless networks. This has become increasingly apparent in cognitive radio (CR) systems where the licensed, primary users (PUs) of the network must be protected from harmful interference by the network's opportunistic, secondary users (SUs): here, unpredictability due to mobility requires the implementation of safety net mechanisms that are provably capable of adapting to changes in the users' wireless environment. In this context, we propose a distributed learning algorithm that allows SUs to adjust their power allocation profile (over the available frequency carriers) "on the fly", relying only on strictly causal channel state information. To account for the interference caused to the network's PUs, we incorporate a penalty function in the rate-driven objectives of the SUs, and we show that the proposed scheme matches asymptotically the performance of the best fixed power allocation policy in hindsight. Specifically, in a system with S orthogonal subcarriers and transmission horizon T , this performance gap (known as the algorithm's average regret) is bounded from above as O(T −1 log S). We also validate our theoretical analysis with numerical simulations which confirm that the network's SUs rapidly achieve a "noregret" state under realistic wireless cellular conditions. Moreover, by finetuning the choice of penalty function, the interference induced by the SUs can be kept at a sufficiently low level, thus guaranteeing the PUs' requirements.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Online Power Allocation for Opportunistic Radio Access in Dynamic OFDM Networks

Marcastel

Belmega

Mertikopoulos

et al. 2016

2016 IEEE 84th Vehicular Technology Conference (VTC-Fall)

Self Cite

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“…Future works can include the analyzis of others access strategies for spectrum sharing systems (such as the overlay access strategy). Analyzing underlay access strategy with multiple primary and secondary users can be considered in the future as well [16].…”

Section: Discussionmentioning

confidence: 99%

Spectrum Sharing in Cognitive Radio Systems

Masmoudi

2018

2018 9th IFIP International Conference on New Technologies, Mobility and Security (NTMS)

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Abstract-In this paper, we focus on a wireless flat fading channel in a Cognitive radio network composed of licensed users (primary) and unlicensed users (secondary). We propose a framework for analyzing the access strategy based on the received interference at the secondary receiver and analyzing the achievable capacity of the secondary under the average power and average interference constraints. The proposed approach to the spectrum sharing, based on the received interference at the secondary receiver, significantly reduces the system complexity. We categorize the spectrum sharing into two cases based on the maximum interference threshold. We obtain a critical system parameter to eliminate the interference threshold constraint.Index Terms-Cognitive radio systems, access strategy, achievable capacity, interference threshold, spectrum sharing.

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Green Energy-Powered Allocations for OFDM-based Cognitive Radio Networks

Ghodhbane

2019

2019 16th International Multi-Conference on Systems, Signals &Amp; Devices (SSD)

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Joint scheduling and power allocation in Cognitive Radio systems

Cited by 4 publications

References 13 publications

Online Power Allocation for Opportunistic Radio Access in Dynamic OFDM Networks

Online Power Allocation for Opportunistic Radio Access in Dynamic OFDM Networks

Spectrum Sharing in Cognitive Radio Systems

Green Energy-Powered Allocations for OFDM-based Cognitive Radio Networks

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