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Communication dans un congrès

Opportunistic Spectrum Access in Cognitive Radio for Tactical Network

Mahmoud Almasri Ali Mansour 1 Christophe Moy 2, 3, 4 Ammar Assoum Christophe Osswald 5 Denis Le Jeune 1
1 Lab-STICC_ENSTAB_CACS_COM
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance
5 Lab-STICC_ENSTAB_CID_DECIDE
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (UMR 3192), STIC - Pôle STIC [Brest], Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance
Abstract : This manuscript addresses the problem of Opportunistic Spectrum Access (OSA) in Cognitive Radio Networks (CRNs). In the context of CRN, two types of users may coexist: primary users (PU) , i.e. licensed user and the secondary user (SU), i.e. opportunistic user who is willing to transmit over the licensed bandwidth of PU. The main aim of a SU is to maximize his transmission rate. Hence, he must target the best channels, i.e. the must available one with the best performance. To estimate the availability of channels, one can use the Multi-Armed Bandit (MAB) learning algorithms such as (Thompson Sampling, Upper Confidence Bound, and e-greedy, etc.). Generally, these algorithms are proposed to handle the simple case of a single SU. MAB algorithms are composed of two stages: exploration and exploitation. In this study, we consider the multi-user case where a novel policy is proposed to manage the CRN network. In our study, we consider the case where the SUs have different ranks and transmission priorities. To evaluate our policy, we use the parameter regret which is the reward loss between the maximum reward getting from the best channel and the actual reward got from selecting sub-optimal channels (i.e. less vacant ones). Our simulations show that the proposed policy achieves better results than some known policies such as Random Rank or SL(K) (Selective learning of the k-th largest expected rewards) policies.
Type de document :
Communication dans un congrès
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https://hal.archives-ouvertes.fr/hal-01899591
Contributeur : Christophe Moy <>
Soumis le : vendredi 19 octobre 2018 - 16:17:22
Dernière modification le : mercredi 14 octobre 2020 - 03:41:19

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Mahmoud Almasri, Ali Mansour, Christophe Moy, Ammar Assoum, Christophe Osswald, et al.. Opportunistic Spectrum Access in Cognitive Radio for Tactical Network. 2nd European Conference on Electrical Engineering & Computer Scienc (EECS 2018), Dec 2018, Bern, Switzerland. ⟨10.1109/eecs.2018.00116⟩. ⟨hal-01899591⟩

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