%0 Journal Article %T Distributed algorithm under cooperative or competitive priority users in cognitive networks %+ Lab-STICC_ENSTAB_CACS_COM %+ Institut d'Électronique et des Technologies du numéRique (IETR) %+ Faculté des Sciences %+ Lab-STICC_ENSTAB_CID_DECIDE %A Almasri, Mahmoud %A Mansour, Ali %A Moy, Christophe %A Assoum, Ammar %A Osswald, Christophe %A Le Jeune, Denis %< avec comité de lecture %@ 1687-1472 %J EURASIP Journal on Wireless Communications and Networking %I SpringerOpen %V 2020 %N 2020:145 %8 2020-12 %D 2020 %R 10.1186/s13638-020-01738-w %K Cooperative or competitive priority access %K Cognitive radio %K Opportunistic spectrum access %K Multi-armed bandit algorithms %K Upper bound of regret %Z Engineering Sciences [physics]/Signal and Image processingJournal articles %X Opportunistic spectrum access (OSA) problem in cognitive radio (CR) networks allows a secondary (unlicensed) user (SU) to access a vacant channel allocated to a primary (licensed) user (PU). By finding the availability of the best channel, i.e., the channel that has the highest availability probability, a SU can increase its transmission time and rate. To maximize the transmission opportunities of a SU, various learning algorithms are suggested: Thompson sampling (TS), upper confidence bound (UCB), ε-greedy, etc. In our study, we propose a modified UCB version called AUCB (Arctan-UCB) that can achieve a logarithmic regret similar to TS or UCB while further reducing the total regret, defined as the reward loss resulting from the selection of non-optimal channels. To evaluate AUCB’s performance for the multi-user case, we propose a novel uncooperative policy for a priority access where the kth user should access the kth best channel. This manuscript theoretically establishes the upper bound on the sum regret of AUCB under the single or multi-user cases. The users thus may, after finite time slots, converge to their dedicated channels. It also focuses on the Quality of Service AUCB (QoS-AUCB) using the proposed policy for the priority access. Our simulations corroborate AUCB’s performance compared to TS or UCB. %G English %2 https://ensta-bretagne.hal.science/hal-02924010/document %2 https://ensta-bretagne.hal.science/hal-02924010/file/s13638-020-01738-w %L hal-02924010 %U https://ensta-bretagne.hal.science/hal-02924010 %~ UNIV-BREST %~ UNIV-NANTES %~ INSTITUT-TELECOM %~ ENSTA-BRETAGNE %~ UNIV-RENNES1 %~ CNRS %~ UNIV-UBS %~ INSA-RENNES %~ IETR %~ SUP_SCEE %~ SUP_IETR %~ ENSTA-BRETAGNE-STIC %~ IETR_SCEE %~ ENIB %~ LAB-STICC_ENIB %~ LAB-STICC %~ STATS-UR1 %~ CENTRALESUPELEC %~ UR1-HAL %~ UR1-MATH-STIC %~ UR1-UFR-ISTIC %~ TEST-UR-CSS %~ CENTRALESUPELEC-SACLAY-VP %~ UNIV-RENNES %~ INSA-GROUPE %~ INSTITUTS-TELECOM %~ TEST-HALCNRS %~ UR1-MATH-NUM %~ HUB-IA %~ IETR-ASIC %~ NANTES-UNIVERSITE %~ UNIV-NANTES-AV2022