Dealing With Jamming Attacks in Uplink Pairwise NOMA Using Outage Analysis, Smart Relaying, and Redundant Transmissions
This study focuses on optimizing the performance of an uplink pairwise Non-Orthogonal Multiple Access (NOMA) scenario with and without the support of a relayer, while subject to jamming attacks. We consider two different relaying protocols, one where the sources and the destination are within range...
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description | This study focuses on optimizing the performance of an uplink pairwise Non-Orthogonal Multiple Access (NOMA) scenario with and without the support of a relayer, while subject to jamming attacks. We consider two different relaying protocols, one where the sources and the destination are within range of each other and one where they are not. The relay node can be mobile, e.g., a mobile base station, an unmanned aerial vehicle (UAV) or a stationary node that is chosen as a result of a relay selection procedure. We also benchmark with a NOMA retransmission protocol and an Orthogonal Multiple Access (OMA) scheme without a relayer. We analyze, adjust and compare the four protocols for different settings using outage analysis, which is an efficient tool for establishing communication reliability for both individual nodes and the overall wireless network. Closed-form expressions of outage probabilities can be adopted by deep reinforcement learning (RL) algorithms to optimize wireless networks online. Accordingly, we first derive closed-form expressions for the individual outage probability (IOP) of each source node link and the relayer link using both pairwise NOMA and OMA. Next, we analyze the IOP for one packet (IOPP) for each source node considering all possible links between the source node to the destination, taking both phases into account for the considered protocols when operating in Nakagami- m fading channels. The overall outage probability for all packets (OOPP) is defined as the maximum IOPP obtained among the source nodes. This metric is useful to optimize the whole wireless network, e.g., to ensure fairness among the source nodes. Then, we propose a method using deep RL where the OOPP is used as a reward function in order to adapt to the dynamic environment associated with jamming attacks. Finally, we discuss valuable guidelines for enhancing the communication reliability of the legitimate system. |
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We consider two different relaying protocols, one where the sources and the destination are within range of each other and one where they are not. The relay node can be mobile, e.g., a mobile base station, an unmanned aerial vehicle (UAV) or a stationary node that is chosen as a result of a relay selection procedure. We also benchmark with a NOMA retransmission protocol and an Orthogonal Multiple Access (OMA) scheme without a relayer. We analyze, adjust and compare the four protocols for different settings using outage analysis, which is an efficient tool for establishing communication reliability for both individual nodes and the overall wireless network. Closed-form expressions of outage probabilities can be adopted by deep reinforcement learning (RL) algorithms to optimize wireless networks online. Accordingly, we first derive closed-form expressions for the individual outage probability (IOP) of each source node link and the relayer link using both pairwise NOMA and OMA. Next, we analyze the IOP for one packet (IOPP) for each source node considering all possible links between the source node to the destination, taking both phases into account for the considered protocols when operating in Nakagami-<inline-formula> <tex-math notation="LaTeX">m </tex-math></inline-formula> fading channels. The overall outage probability for all packets (OOPP) is defined as the maximum IOPP obtained among the source nodes. This metric is useful to optimize the whole wireless network, e.g., to ensure fairness among the source nodes. Then, we propose a method using deep RL where the OOPP is used as a reward function in order to adapt to the dynamic environment associated with jamming attacks. Finally, we discuss valuable guidelines for enhancing the communication reliability of the legitimate system.</description><identifier>ISSN: 2644-125X</identifier><identifier>EISSN: 2644-125X</identifier><identifier>DOI: 10.1109/OJCOMS.2023.3339175</identifier><identifier>CODEN: IOJCAZ</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Algorithms ; Closed form solutions ; cooperative NOMA ; deep reinforcement learning ; Dynamic decoding order ; Exact solutions ; imperfect CSI ; Jamming ; Machine learning ; Nodes ; NOMA ; Nonorthogonal multiple access ; Optimization ; outage performance ; Outages ; Power system reliability ; Probability ; Protocols ; Radio equipment ; Relay ; Relaying ; Reliability ; Unmanned aerial vehicles ; Uplink ; Uplinking ; Wireless networks</subject><ispartof>IEEE open journal of the Communications Society, 2024, Vol.5, p.112-126</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2024</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c396t-b4b01899a01758f9d9ed6ac611d6bbcb0fc747fcee05385957f2299f4fad864e3</cites><orcidid>0000-0001-6497-4099 ; 0000-0001-8109-1685 ; 0000-0001-9589-6986</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/10342734$$EHTML$$P50$$Gieee$$Hfree_for_read</linktohtml><link.rule.ids>230,314,552,780,784,864,885,2102,4024,27633,27923,27924,27925,54933</link.rule.ids><backlink>$$Uhttps://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-64352$$DView record from Swedish Publication Index$$Hfree_for_read</backlink></links><search><creatorcontrib>Dao, Van-Lan</creatorcontrib><creatorcontrib>Uhlemann, Elisabeth</creatorcontrib><creatorcontrib>Girs, Svetlana</creatorcontrib><title>Dealing With Jamming Attacks in Uplink Pairwise NOMA Using Outage Analysis, Smart Relaying, and Redundant Transmissions</title><title>IEEE open journal of the Communications Society</title><addtitle>OJCOMS</addtitle><description>This study focuses on optimizing the performance of an uplink pairwise Non-Orthogonal Multiple Access (NOMA) scenario with and without the support of a relayer, while subject to jamming attacks. We consider two different relaying protocols, one where the sources and the destination are within range of each other and one where they are not. The relay node can be mobile, e.g., a mobile base station, an unmanned aerial vehicle (UAV) or a stationary node that is chosen as a result of a relay selection procedure. We also benchmark with a NOMA retransmission protocol and an Orthogonal Multiple Access (OMA) scheme without a relayer. We analyze, adjust and compare the four protocols for different settings using outage analysis, which is an efficient tool for establishing communication reliability for both individual nodes and the overall wireless network. Closed-form expressions of outage probabilities can be adopted by deep reinforcement learning (RL) algorithms to optimize wireless networks online. Accordingly, we first derive closed-form expressions for the individual outage probability (IOP) of each source node link and the relayer link using both pairwise NOMA and OMA. Next, we analyze the IOP for one packet (IOPP) for each source node considering all possible links between the source node to the destination, taking both phases into account for the considered protocols when operating in Nakagami-<inline-formula> <tex-math notation="LaTeX">m </tex-math></inline-formula> fading channels. The overall outage probability for all packets (OOPP) is defined as the maximum IOPP obtained among the source nodes. This metric is useful to optimize the whole wireless network, e.g., to ensure fairness among the source nodes. Then, we propose a method using deep RL where the OOPP is used as a reward function in order to adapt to the dynamic environment associated with jamming attacks. Finally, we discuss valuable guidelines for enhancing the communication reliability of the legitimate system.</description><subject>Algorithms</subject><subject>Closed form solutions</subject><subject>cooperative NOMA</subject><subject>deep reinforcement learning</subject><subject>Dynamic decoding order</subject><subject>Exact solutions</subject><subject>imperfect CSI</subject><subject>Jamming</subject><subject>Machine learning</subject><subject>Nodes</subject><subject>NOMA</subject><subject>Nonorthogonal multiple access</subject><subject>Optimization</subject><subject>outage performance</subject><subject>Outages</subject><subject>Power system reliability</subject><subject>Probability</subject><subject>Protocols</subject><subject>Radio equipment</subject><subject>Relay</subject><subject>Relaying</subject><subject>Reliability</subject><subject>Unmanned aerial vehicles</subject><subject>Uplink</subject><subject>Uplinking</subject><subject>Wireless networks</subject><issn>2644-125X</issn><issn>2644-125X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>ESBDL</sourceid><sourceid>RIE</sourceid><sourceid>D8T</sourceid><sourceid>DOA</sourceid><recordid>eNpVkVtv1DAQhSMEElXbXwAPlnjdXXxP_BhtKbRqCaJd4M2axM7W21wWO9Fq_32dpkLlyZ6Zcz6NfZLkA8ErQrD6XFyvi9u7FcWUrRhjiqTiTXJCJedLQsWft6_u75PzEHYYYyoIIYyfJIcLC43rtui3Gx7QNbTtVOTDANVjQK5Dm30cP6If4PzBBYu-F7c52oRJVYwDbC3KO2iOwYUFumvBD-inbeAY5wsEnYmVGTsD3YDuPXShdSG4vgtnybsammDPX87TZHP55X79bXlTfL1a5zfLiik5LEteYpIpBTi-KquVUdZIqCQhRpZlVeK6SnlaV9ZiwTKhRFpTqlTNazCZ5JadJlcz1_Sw03vv4opH3YPTz43eb3Xc2VWN1RIEAyUgsjKeGquEKjEWNWCmSkNNZC1mVjjY_Vj-R7twv_JnWmsetORM0Cj_NMv3vv872jDoXT_6-FlBU4WlUCRjk4rNqsr3IXhb_8MSrKd89ZyvnvLVL_lG18fZ5ay1rxyM05Rx9gRcrqJK</recordid><startdate>2024</startdate><enddate>2024</enddate><creator>Dao, Van-Lan</creator><creator>Uhlemann, Elisabeth</creator><creator>Girs, Svetlana</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>ESBDL</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>8FD</scope><scope>L7M</scope><scope>ABGEM</scope><scope>ADTPV</scope><scope>AOWAS</scope><scope>D8T</scope><scope>DF7</scope><scope>ZZAVC</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0001-6497-4099</orcidid><orcidid>https://orcid.org/0000-0001-8109-1685</orcidid><orcidid>https://orcid.org/0000-0001-9589-6986</orcidid></search><sort><creationdate>2024</creationdate><title>Dealing With Jamming Attacks in Uplink Pairwise NOMA Using Outage Analysis, Smart Relaying, and Redundant Transmissions</title><author>Dao, Van-Lan ; Uhlemann, Elisabeth ; Girs, Svetlana</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c396t-b4b01899a01758f9d9ed6ac611d6bbcb0fc747fcee05385957f2299f4fad864e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Algorithms</topic><topic>Closed form solutions</topic><topic>cooperative NOMA</topic><topic>deep reinforcement learning</topic><topic>Dynamic decoding order</topic><topic>Exact solutions</topic><topic>imperfect CSI</topic><topic>Jamming</topic><topic>Machine learning</topic><topic>Nodes</topic><topic>NOMA</topic><topic>Nonorthogonal multiple access</topic><topic>Optimization</topic><topic>outage performance</topic><topic>Outages</topic><topic>Power system reliability</topic><topic>Probability</topic><topic>Protocols</topic><topic>Radio equipment</topic><topic>Relay</topic><topic>Relaying</topic><topic>Reliability</topic><topic>Unmanned aerial vehicles</topic><topic>Uplink</topic><topic>Uplinking</topic><topic>Wireless networks</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Dao, Van-Lan</creatorcontrib><creatorcontrib>Uhlemann, Elisabeth</creatorcontrib><creatorcontrib>Girs, Svetlana</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE Open Access Journals</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>SWEPUB Mälardalens högskola full text</collection><collection>SwePub</collection><collection>SwePub Articles</collection><collection>SWEPUB Freely available online</collection><collection>SWEPUB Mälardalens högskola</collection><collection>SwePub Articles full text</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>IEEE open journal of the Communications Society</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Dao, Van-Lan</au><au>Uhlemann, Elisabeth</au><au>Girs, Svetlana</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Dealing With Jamming Attacks in Uplink Pairwise NOMA Using Outage Analysis, Smart Relaying, and Redundant Transmissions</atitle><jtitle>IEEE open journal of the Communications Society</jtitle><stitle>OJCOMS</stitle><date>2024</date><risdate>2024</risdate><volume>5</volume><spage>112</spage><epage>126</epage><pages>112-126</pages><issn>2644-125X</issn><eissn>2644-125X</eissn><coden>IOJCAZ</coden><abstract>This study focuses on optimizing the performance of an uplink pairwise Non-Orthogonal Multiple Access (NOMA) scenario with and without the support of a relayer, while subject to jamming attacks. We consider two different relaying protocols, one where the sources and the destination are within range of each other and one where they are not. The relay node can be mobile, e.g., a mobile base station, an unmanned aerial vehicle (UAV) or a stationary node that is chosen as a result of a relay selection procedure. We also benchmark with a NOMA retransmission protocol and an Orthogonal Multiple Access (OMA) scheme without a relayer. We analyze, adjust and compare the four protocols for different settings using outage analysis, which is an efficient tool for establishing communication reliability for both individual nodes and the overall wireless network. Closed-form expressions of outage probabilities can be adopted by deep reinforcement learning (RL) algorithms to optimize wireless networks online. Accordingly, we first derive closed-form expressions for the individual outage probability (IOP) of each source node link and the relayer link using both pairwise NOMA and OMA. Next, we analyze the IOP for one packet (IOPP) for each source node considering all possible links between the source node to the destination, taking both phases into account for the considered protocols when operating in Nakagami-<inline-formula> <tex-math notation="LaTeX">m </tex-math></inline-formula> fading channels. The overall outage probability for all packets (OOPP) is defined as the maximum IOPP obtained among the source nodes. This metric is useful to optimize the whole wireless network, e.g., to ensure fairness among the source nodes. Then, we propose a method using deep RL where the OOPP is used as a reward function in order to adapt to the dynamic environment associated with jamming attacks. Finally, we discuss valuable guidelines for enhancing the communication reliability of the legitimate system.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/OJCOMS.2023.3339175</doi><tpages>15</tpages><orcidid>https://orcid.org/0000-0001-6497-4099</orcidid><orcidid>https://orcid.org/0000-0001-8109-1685</orcidid><orcidid>https://orcid.org/0000-0001-9589-6986</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Closed form solutions cooperative NOMA deep reinforcement learning Dynamic decoding order Exact solutions imperfect CSI Jamming Machine learning Nodes NOMA Nonorthogonal multiple access Optimization outage performance Outages Power system reliability Probability Protocols Radio equipment Relay Relaying Reliability Unmanned aerial vehicles Uplink Uplinking Wireless networks |
title | Dealing With Jamming Attacks in Uplink Pairwise NOMA Using Outage Analysis, Smart Relaying, and Redundant Transmissions |
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