Joint Spectrum Sensing and Resource Allocation Scheme in Cognitive Radio Networks with Spectrum Sensing Data Falsification Attack
Spectrum sensing and spectrum sharing are two fundamental issues in a cognitive radio network (CRN). The spectrum sensing data falsification (SSDF) attack imposes bad effects on both spectrum sensing and spectrum sharing. To deal with SSDF attacks and to incentivize secondary users (SUs) to behave w...
Ausführliche Beschreibung
Autor*in: |
Chen, Huifang [verfasserIn] |
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Format: |
Artikel |
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Sprache: |
Englisch |
Erschienen: |
2016 |
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Schlagwörter: |
cooperative spectrum sensing (CSS) |
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Übergeordnetes Werk: |
Enthalten in: IEEE transactions on vehicular technology - New York, NY : IEEE, 1967, 65(2016), 11, Seite 9181-9191 |
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Übergeordnetes Werk: |
volume:65 ; year:2016 ; number:11 ; pages:9181-9191 |
Links: |
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DOI / URN: |
10.1109/TVT.2016.2520983 |
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Katalog-ID: |
OLC1984345842 |
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245 | 1 | 0 | |a Joint Spectrum Sensing and Resource Allocation Scheme in Cognitive Radio Networks with Spectrum Sensing Data Falsification Attack |
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520 | |a Spectrum sensing and spectrum sharing are two fundamental issues in a cognitive radio network (CRN). The spectrum sensing data falsification (SSDF) attack imposes bad effects on both spectrum sensing and spectrum sharing. To deal with SSDF attacks and to incentivize secondary users (SUs) to behave well, a joint spectrum sensing and resource allocation (JSSRA) scheme in a CRN is proposed in this paper. The JSSRA problem is formulated as a weighted-proportional-fairness-based resource-allocation optimization problem under the constraint that the primary user (PU) network is sufficiently protected. The problem is decomposed into two subproblems, namely, the resource allocation subproblem and cooperative SU number decision subproblem, which are solved by the Lagrangian dual algorithm and the brute-force algorithm, respectively. Moreover, a user-selection method based on reinforcement learning is presented to select reliable SUs for cooperative spectrum sensing (CSS). In addition, the SU's trust degree is updated according to its behavior in CSS and is used in the sensed resource-allocation process. The key point of our proposed scheme is to make SUs improve the sensing reliability and prevent SUs from behaving maliciously by an incentive mechanism. Comprehensive performance evaluation is conducted by computer simulation. It is shown that the proposed JSSRA scheme deals with the SSDF attack well in cooperative sensing process to improve system robustness and achieves a significant system utility gain in resource allocation. | ||
650 | 4 | |a resource allocation | |
650 | 4 | |a incentive mechanism | |
650 | 4 | |a Resource management | |
650 | 4 | |a Sensors | |
650 | 4 | |a cooperative spectrum sensing (CSS) | |
650 | 4 | |a Cognitive radio network (CRN) | |
650 | 4 | |a Data communication | |
650 | 4 | |a Reliability | |
650 | 4 | |a Cascading style sheets | |
650 | 4 | |a spectrum sensing data falsification (SSDF) attack | |
650 | 4 | |a Interference | |
650 | 4 | |a Optimization | |
700 | 1 | |a Zhou, Ming |4 oth | |
700 | 1 | |a Xie, Lei |4 oth | |
700 | 1 | |a Wang, Kuang |4 oth | |
700 | 1 | |a Li, Jie |4 oth | |
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10.1109/TVT.2016.2520983 doi PQ20161201 (DE-627)OLC1984345842 (DE-599)GBVOLC1984345842 (PRQ)c998-a9ea4ac93561392948528ff388ed11d4366d2d87a06688ab251ea1ff71cf45a80 (KEY)0030991520160000065001109181jointspectrumsensingandresourceallocationschemeinc DE-627 ger DE-627 rakwb eng 620 DNB 53.70 bkl 53.74 bkl Chen, Huifang verfasserin aut Joint Spectrum Sensing and Resource Allocation Scheme in Cognitive Radio Networks with Spectrum Sensing Data Falsification Attack 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Spectrum sensing and spectrum sharing are two fundamental issues in a cognitive radio network (CRN). The spectrum sensing data falsification (SSDF) attack imposes bad effects on both spectrum sensing and spectrum sharing. To deal with SSDF attacks and to incentivize secondary users (SUs) to behave well, a joint spectrum sensing and resource allocation (JSSRA) scheme in a CRN is proposed in this paper. The JSSRA problem is formulated as a weighted-proportional-fairness-based resource-allocation optimization problem under the constraint that the primary user (PU) network is sufficiently protected. The problem is decomposed into two subproblems, namely, the resource allocation subproblem and cooperative SU number decision subproblem, which are solved by the Lagrangian dual algorithm and the brute-force algorithm, respectively. Moreover, a user-selection method based on reinforcement learning is presented to select reliable SUs for cooperative spectrum sensing (CSS). In addition, the SU's trust degree is updated according to its behavior in CSS and is used in the sensed resource-allocation process. The key point of our proposed scheme is to make SUs improve the sensing reliability and prevent SUs from behaving maliciously by an incentive mechanism. Comprehensive performance evaluation is conducted by computer simulation. It is shown that the proposed JSSRA scheme deals with the SSDF attack well in cooperative sensing process to improve system robustness and achieves a significant system utility gain in resource allocation. resource allocation incentive mechanism Resource management Sensors cooperative spectrum sensing (CSS) Cognitive radio network (CRN) Data communication Reliability Cascading style sheets spectrum sensing data falsification (SSDF) attack Interference Optimization Zhou, Ming oth Xie, Lei oth Wang, Kuang oth Li, Jie oth Enthalten in IEEE transactions on vehicular technology New York, NY : IEEE, 1967 65(2016), 11, Seite 9181-9191 (DE-627)129358584 (DE-600)160444-2 (DE-576)014730871 0018-9545 nnns volume:65 year:2016 number:11 pages:9181-9191 http://dx.doi.org/10.1109/TVT.2016.2520983 Volltext http://ieeexplore.ieee.org/document/7390085 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_70 GBV_ILN_2061 53.70 AVZ 53.74 AVZ AR 65 2016 11 9181-9191 |
spelling |
10.1109/TVT.2016.2520983 doi PQ20161201 (DE-627)OLC1984345842 (DE-599)GBVOLC1984345842 (PRQ)c998-a9ea4ac93561392948528ff388ed11d4366d2d87a06688ab251ea1ff71cf45a80 (KEY)0030991520160000065001109181jointspectrumsensingandresourceallocationschemeinc DE-627 ger DE-627 rakwb eng 620 DNB 53.70 bkl 53.74 bkl Chen, Huifang verfasserin aut Joint Spectrum Sensing and Resource Allocation Scheme in Cognitive Radio Networks with Spectrum Sensing Data Falsification Attack 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Spectrum sensing and spectrum sharing are two fundamental issues in a cognitive radio network (CRN). The spectrum sensing data falsification (SSDF) attack imposes bad effects on both spectrum sensing and spectrum sharing. To deal with SSDF attacks and to incentivize secondary users (SUs) to behave well, a joint spectrum sensing and resource allocation (JSSRA) scheme in a CRN is proposed in this paper. The JSSRA problem is formulated as a weighted-proportional-fairness-based resource-allocation optimization problem under the constraint that the primary user (PU) network is sufficiently protected. The problem is decomposed into two subproblems, namely, the resource allocation subproblem and cooperative SU number decision subproblem, which are solved by the Lagrangian dual algorithm and the brute-force algorithm, respectively. Moreover, a user-selection method based on reinforcement learning is presented to select reliable SUs for cooperative spectrum sensing (CSS). In addition, the SU's trust degree is updated according to its behavior in CSS and is used in the sensed resource-allocation process. The key point of our proposed scheme is to make SUs improve the sensing reliability and prevent SUs from behaving maliciously by an incentive mechanism. Comprehensive performance evaluation is conducted by computer simulation. It is shown that the proposed JSSRA scheme deals with the SSDF attack well in cooperative sensing process to improve system robustness and achieves a significant system utility gain in resource allocation. resource allocation incentive mechanism Resource management Sensors cooperative spectrum sensing (CSS) Cognitive radio network (CRN) Data communication Reliability Cascading style sheets spectrum sensing data falsification (SSDF) attack Interference Optimization Zhou, Ming oth Xie, Lei oth Wang, Kuang oth Li, Jie oth Enthalten in IEEE transactions on vehicular technology New York, NY : IEEE, 1967 65(2016), 11, Seite 9181-9191 (DE-627)129358584 (DE-600)160444-2 (DE-576)014730871 0018-9545 nnns volume:65 year:2016 number:11 pages:9181-9191 http://dx.doi.org/10.1109/TVT.2016.2520983 Volltext http://ieeexplore.ieee.org/document/7390085 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_70 GBV_ILN_2061 53.70 AVZ 53.74 AVZ AR 65 2016 11 9181-9191 |
allfields_unstemmed |
10.1109/TVT.2016.2520983 doi PQ20161201 (DE-627)OLC1984345842 (DE-599)GBVOLC1984345842 (PRQ)c998-a9ea4ac93561392948528ff388ed11d4366d2d87a06688ab251ea1ff71cf45a80 (KEY)0030991520160000065001109181jointspectrumsensingandresourceallocationschemeinc DE-627 ger DE-627 rakwb eng 620 DNB 53.70 bkl 53.74 bkl Chen, Huifang verfasserin aut Joint Spectrum Sensing and Resource Allocation Scheme in Cognitive Radio Networks with Spectrum Sensing Data Falsification Attack 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Spectrum sensing and spectrum sharing are two fundamental issues in a cognitive radio network (CRN). The spectrum sensing data falsification (SSDF) attack imposes bad effects on both spectrum sensing and spectrum sharing. To deal with SSDF attacks and to incentivize secondary users (SUs) to behave well, a joint spectrum sensing and resource allocation (JSSRA) scheme in a CRN is proposed in this paper. The JSSRA problem is formulated as a weighted-proportional-fairness-based resource-allocation optimization problem under the constraint that the primary user (PU) network is sufficiently protected. The problem is decomposed into two subproblems, namely, the resource allocation subproblem and cooperative SU number decision subproblem, which are solved by the Lagrangian dual algorithm and the brute-force algorithm, respectively. Moreover, a user-selection method based on reinforcement learning is presented to select reliable SUs for cooperative spectrum sensing (CSS). In addition, the SU's trust degree is updated according to its behavior in CSS and is used in the sensed resource-allocation process. The key point of our proposed scheme is to make SUs improve the sensing reliability and prevent SUs from behaving maliciously by an incentive mechanism. Comprehensive performance evaluation is conducted by computer simulation. It is shown that the proposed JSSRA scheme deals with the SSDF attack well in cooperative sensing process to improve system robustness and achieves a significant system utility gain in resource allocation. resource allocation incentive mechanism Resource management Sensors cooperative spectrum sensing (CSS) Cognitive radio network (CRN) Data communication Reliability Cascading style sheets spectrum sensing data falsification (SSDF) attack Interference Optimization Zhou, Ming oth Xie, Lei oth Wang, Kuang oth Li, Jie oth Enthalten in IEEE transactions on vehicular technology New York, NY : IEEE, 1967 65(2016), 11, Seite 9181-9191 (DE-627)129358584 (DE-600)160444-2 (DE-576)014730871 0018-9545 nnns volume:65 year:2016 number:11 pages:9181-9191 http://dx.doi.org/10.1109/TVT.2016.2520983 Volltext http://ieeexplore.ieee.org/document/7390085 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_70 GBV_ILN_2061 53.70 AVZ 53.74 AVZ AR 65 2016 11 9181-9191 |
allfieldsGer |
10.1109/TVT.2016.2520983 doi PQ20161201 (DE-627)OLC1984345842 (DE-599)GBVOLC1984345842 (PRQ)c998-a9ea4ac93561392948528ff388ed11d4366d2d87a06688ab251ea1ff71cf45a80 (KEY)0030991520160000065001109181jointspectrumsensingandresourceallocationschemeinc DE-627 ger DE-627 rakwb eng 620 DNB 53.70 bkl 53.74 bkl Chen, Huifang verfasserin aut Joint Spectrum Sensing and Resource Allocation Scheme in Cognitive Radio Networks with Spectrum Sensing Data Falsification Attack 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Spectrum sensing and spectrum sharing are two fundamental issues in a cognitive radio network (CRN). The spectrum sensing data falsification (SSDF) attack imposes bad effects on both spectrum sensing and spectrum sharing. To deal with SSDF attacks and to incentivize secondary users (SUs) to behave well, a joint spectrum sensing and resource allocation (JSSRA) scheme in a CRN is proposed in this paper. The JSSRA problem is formulated as a weighted-proportional-fairness-based resource-allocation optimization problem under the constraint that the primary user (PU) network is sufficiently protected. The problem is decomposed into two subproblems, namely, the resource allocation subproblem and cooperative SU number decision subproblem, which are solved by the Lagrangian dual algorithm and the brute-force algorithm, respectively. Moreover, a user-selection method based on reinforcement learning is presented to select reliable SUs for cooperative spectrum sensing (CSS). In addition, the SU's trust degree is updated according to its behavior in CSS and is used in the sensed resource-allocation process. The key point of our proposed scheme is to make SUs improve the sensing reliability and prevent SUs from behaving maliciously by an incentive mechanism. Comprehensive performance evaluation is conducted by computer simulation. It is shown that the proposed JSSRA scheme deals with the SSDF attack well in cooperative sensing process to improve system robustness and achieves a significant system utility gain in resource allocation. resource allocation incentive mechanism Resource management Sensors cooperative spectrum sensing (CSS) Cognitive radio network (CRN) Data communication Reliability Cascading style sheets spectrum sensing data falsification (SSDF) attack Interference Optimization Zhou, Ming oth Xie, Lei oth Wang, Kuang oth Li, Jie oth Enthalten in IEEE transactions on vehicular technology New York, NY : IEEE, 1967 65(2016), 11, Seite 9181-9191 (DE-627)129358584 (DE-600)160444-2 (DE-576)014730871 0018-9545 nnns volume:65 year:2016 number:11 pages:9181-9191 http://dx.doi.org/10.1109/TVT.2016.2520983 Volltext http://ieeexplore.ieee.org/document/7390085 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_70 GBV_ILN_2061 53.70 AVZ 53.74 AVZ AR 65 2016 11 9181-9191 |
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10.1109/TVT.2016.2520983 doi PQ20161201 (DE-627)OLC1984345842 (DE-599)GBVOLC1984345842 (PRQ)c998-a9ea4ac93561392948528ff388ed11d4366d2d87a06688ab251ea1ff71cf45a80 (KEY)0030991520160000065001109181jointspectrumsensingandresourceallocationschemeinc DE-627 ger DE-627 rakwb eng 620 DNB 53.70 bkl 53.74 bkl Chen, Huifang verfasserin aut Joint Spectrum Sensing and Resource Allocation Scheme in Cognitive Radio Networks with Spectrum Sensing Data Falsification Attack 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Spectrum sensing and spectrum sharing are two fundamental issues in a cognitive radio network (CRN). The spectrum sensing data falsification (SSDF) attack imposes bad effects on both spectrum sensing and spectrum sharing. To deal with SSDF attacks and to incentivize secondary users (SUs) to behave well, a joint spectrum sensing and resource allocation (JSSRA) scheme in a CRN is proposed in this paper. The JSSRA problem is formulated as a weighted-proportional-fairness-based resource-allocation optimization problem under the constraint that the primary user (PU) network is sufficiently protected. The problem is decomposed into two subproblems, namely, the resource allocation subproblem and cooperative SU number decision subproblem, which are solved by the Lagrangian dual algorithm and the brute-force algorithm, respectively. Moreover, a user-selection method based on reinforcement learning is presented to select reliable SUs for cooperative spectrum sensing (CSS). In addition, the SU's trust degree is updated according to its behavior in CSS and is used in the sensed resource-allocation process. The key point of our proposed scheme is to make SUs improve the sensing reliability and prevent SUs from behaving maliciously by an incentive mechanism. Comprehensive performance evaluation is conducted by computer simulation. It is shown that the proposed JSSRA scheme deals with the SSDF attack well in cooperative sensing process to improve system robustness and achieves a significant system utility gain in resource allocation. resource allocation incentive mechanism Resource management Sensors cooperative spectrum sensing (CSS) Cognitive radio network (CRN) Data communication Reliability Cascading style sheets spectrum sensing data falsification (SSDF) attack Interference Optimization Zhou, Ming oth Xie, Lei oth Wang, Kuang oth Li, Jie oth Enthalten in IEEE transactions on vehicular technology New York, NY : IEEE, 1967 65(2016), 11, Seite 9181-9191 (DE-627)129358584 (DE-600)160444-2 (DE-576)014730871 0018-9545 nnns volume:65 year:2016 number:11 pages:9181-9191 http://dx.doi.org/10.1109/TVT.2016.2520983 Volltext http://ieeexplore.ieee.org/document/7390085 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_70 GBV_ILN_2061 53.70 AVZ 53.74 AVZ AR 65 2016 11 9181-9191 |
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Enthalten in IEEE transactions on vehicular technology 65(2016), 11, Seite 9181-9191 volume:65 year:2016 number:11 pages:9181-9191 |
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Chen, Huifang @@aut@@ Zhou, Ming @@oth@@ Xie, Lei @@oth@@ Wang, Kuang @@oth@@ Li, Jie @@oth@@ |
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The spectrum sensing data falsification (SSDF) attack imposes bad effects on both spectrum sensing and spectrum sharing. To deal with SSDF attacks and to incentivize secondary users (SUs) to behave well, a joint spectrum sensing and resource allocation (JSSRA) scheme in a CRN is proposed in this paper. The JSSRA problem is formulated as a weighted-proportional-fairness-based resource-allocation optimization problem under the constraint that the primary user (PU) network is sufficiently protected. The problem is decomposed into two subproblems, namely, the resource allocation subproblem and cooperative SU number decision subproblem, which are solved by the Lagrangian dual algorithm and the brute-force algorithm, respectively. Moreover, a user-selection method based on reinforcement learning is presented to select reliable SUs for cooperative spectrum sensing (CSS). In addition, the SU's trust degree is updated according to its behavior in CSS and is used in the sensed resource-allocation process. The key point of our proposed scheme is to make SUs improve the sensing reliability and prevent SUs from behaving maliciously by an incentive mechanism. Comprehensive performance evaluation is conducted by computer simulation. 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Chen, Huifang |
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Chen, Huifang ddc 620 bkl 53.70 bkl 53.74 misc resource allocation misc incentive mechanism misc Resource management misc Sensors misc cooperative spectrum sensing (CSS) misc Cognitive radio network (CRN) misc Data communication misc Reliability misc Cascading style sheets misc spectrum sensing data falsification (SSDF) attack misc Interference misc Optimization Joint Spectrum Sensing and Resource Allocation Scheme in Cognitive Radio Networks with Spectrum Sensing Data Falsification Attack |
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620 DNB 53.70 bkl 53.74 bkl Joint Spectrum Sensing and Resource Allocation Scheme in Cognitive Radio Networks with Spectrum Sensing Data Falsification Attack resource allocation incentive mechanism Resource management Sensors cooperative spectrum sensing (CSS) Cognitive radio network (CRN) Data communication Reliability Cascading style sheets spectrum sensing data falsification (SSDF) attack Interference Optimization |
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ddc 620 bkl 53.70 bkl 53.74 misc resource allocation misc incentive mechanism misc Resource management misc Sensors misc cooperative spectrum sensing (CSS) misc Cognitive radio network (CRN) misc Data communication misc Reliability misc Cascading style sheets misc spectrum sensing data falsification (SSDF) attack misc Interference misc Optimization |
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ddc 620 bkl 53.70 bkl 53.74 misc resource allocation misc incentive mechanism misc Resource management misc Sensors misc cooperative spectrum sensing (CSS) misc Cognitive radio network (CRN) misc Data communication misc Reliability misc Cascading style sheets misc spectrum sensing data falsification (SSDF) attack misc Interference misc Optimization |
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Joint Spectrum Sensing and Resource Allocation Scheme in Cognitive Radio Networks with Spectrum Sensing Data Falsification Attack |
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joint spectrum sensing and resource allocation scheme in cognitive radio networks with spectrum sensing data falsification attack |
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Joint Spectrum Sensing and Resource Allocation Scheme in Cognitive Radio Networks with Spectrum Sensing Data Falsification Attack |
abstract |
Spectrum sensing and spectrum sharing are two fundamental issues in a cognitive radio network (CRN). The spectrum sensing data falsification (SSDF) attack imposes bad effects on both spectrum sensing and spectrum sharing. To deal with SSDF attacks and to incentivize secondary users (SUs) to behave well, a joint spectrum sensing and resource allocation (JSSRA) scheme in a CRN is proposed in this paper. The JSSRA problem is formulated as a weighted-proportional-fairness-based resource-allocation optimization problem under the constraint that the primary user (PU) network is sufficiently protected. The problem is decomposed into two subproblems, namely, the resource allocation subproblem and cooperative SU number decision subproblem, which are solved by the Lagrangian dual algorithm and the brute-force algorithm, respectively. Moreover, a user-selection method based on reinforcement learning is presented to select reliable SUs for cooperative spectrum sensing (CSS). In addition, the SU's trust degree is updated according to its behavior in CSS and is used in the sensed resource-allocation process. The key point of our proposed scheme is to make SUs improve the sensing reliability and prevent SUs from behaving maliciously by an incentive mechanism. Comprehensive performance evaluation is conducted by computer simulation. It is shown that the proposed JSSRA scheme deals with the SSDF attack well in cooperative sensing process to improve system robustness and achieves a significant system utility gain in resource allocation. |
abstractGer |
Spectrum sensing and spectrum sharing are two fundamental issues in a cognitive radio network (CRN). The spectrum sensing data falsification (SSDF) attack imposes bad effects on both spectrum sensing and spectrum sharing. To deal with SSDF attacks and to incentivize secondary users (SUs) to behave well, a joint spectrum sensing and resource allocation (JSSRA) scheme in a CRN is proposed in this paper. The JSSRA problem is formulated as a weighted-proportional-fairness-based resource-allocation optimization problem under the constraint that the primary user (PU) network is sufficiently protected. The problem is decomposed into two subproblems, namely, the resource allocation subproblem and cooperative SU number decision subproblem, which are solved by the Lagrangian dual algorithm and the brute-force algorithm, respectively. Moreover, a user-selection method based on reinforcement learning is presented to select reliable SUs for cooperative spectrum sensing (CSS). In addition, the SU's trust degree is updated according to its behavior in CSS and is used in the sensed resource-allocation process. The key point of our proposed scheme is to make SUs improve the sensing reliability and prevent SUs from behaving maliciously by an incentive mechanism. Comprehensive performance evaluation is conducted by computer simulation. It is shown that the proposed JSSRA scheme deals with the SSDF attack well in cooperative sensing process to improve system robustness and achieves a significant system utility gain in resource allocation. |
abstract_unstemmed |
Spectrum sensing and spectrum sharing are two fundamental issues in a cognitive radio network (CRN). The spectrum sensing data falsification (SSDF) attack imposes bad effects on both spectrum sensing and spectrum sharing. To deal with SSDF attacks and to incentivize secondary users (SUs) to behave well, a joint spectrum sensing and resource allocation (JSSRA) scheme in a CRN is proposed in this paper. The JSSRA problem is formulated as a weighted-proportional-fairness-based resource-allocation optimization problem under the constraint that the primary user (PU) network is sufficiently protected. The problem is decomposed into two subproblems, namely, the resource allocation subproblem and cooperative SU number decision subproblem, which are solved by the Lagrangian dual algorithm and the brute-force algorithm, respectively. Moreover, a user-selection method based on reinforcement learning is presented to select reliable SUs for cooperative spectrum sensing (CSS). In addition, the SU's trust degree is updated according to its behavior in CSS and is used in the sensed resource-allocation process. The key point of our proposed scheme is to make SUs improve the sensing reliability and prevent SUs from behaving maliciously by an incentive mechanism. Comprehensive performance evaluation is conducted by computer simulation. It is shown that the proposed JSSRA scheme deals with the SSDF attack well in cooperative sensing process to improve system robustness and achieves a significant system utility gain in resource allocation. |
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Joint Spectrum Sensing and Resource Allocation Scheme in Cognitive Radio Networks with Spectrum Sensing Data Falsification Attack |
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Zhou, Ming Xie, Lei Wang, Kuang Li, Jie |
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