Joint optimization for RIS-assisted multicast D2D communications

Multicast device-to-device (D2D) communication is an important technique to overcome the problem of spectrum shortage. Due to the channel gain difference between users in different locations, receivers in the same multicast D2D group still suffer from the problem of different quality of service (QoS...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Ji, Pengshuo [verfasserIn] Jia, Jie [verfasserIn] Chen, Jian [verfasserIn] Xie, Yunhe [verfasserIn] Wang, Xingwei [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Schlagwörter:	D2D communication Reconfigurable intelligent surface Multicasting Resource allocation Successive convex approximation

Übergeordnetes Werk:	Enthalten in: Computer networks - Amsterdam [u.a.] : Elsevier, 1976, 211
Übergeordnetes Werk:	volume:211

DOI / URN:	10.1016/j.comnet.2022.108977

Katalog-ID:	ELV007913583

Internformat


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520			\|a Multicast device-to-device (D2D) communication is an important technique to overcome the problem of spectrum shortage. Due to the channel gain difference between users in different locations, receivers in the same multicast D2D group still suffer from the problem of different quality of service (QoS) levels. This paper proposes a novel reconfigurable intelligent surface (RIS)-assisted multicast D2D communication system to enhance the QoS of users, in which RIS solves the problem of different QoS between users through intelligent resource optimization. To maximize the achievable sum rate of all multicast D2D users, we formulate a joint optimization problem. This problem combines channel assignment, power allocation, and reflection matrix design by considering the QoS fairness among different D2D users. To solve this problem, we propose a novel joint optimization algorithm, which has three steps. First, we propose a matching algorithm based on swap operations to solve the channel assignment problem. Then, we propose a successive convex approximation (SCA) method to solve the power allocation problem. Finally, we present the optimization of the RIS reflection coefficients with mathematical analysis. The numerical results demonstrate that the proposed algorithm can effectively enhance the QoS of users in the multicast D2D group. With the aid of RIS, the proposed algorithm decreases the service disparities between users in different locations. Furthermore, it reveals that it is helpful to deploy the RIS closer to the receivers or the transmitters.
650		4	\|a D2D communication
650		4	\|a Reconfigurable intelligent surface
650		4	\|a Multicasting
650		4	\|a Resource allocation
650		4	\|a Successive convex approximation
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700	1		\|a Wang, Xingwei \|e verfasserin \|4 aut
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publishDate	2022
allfields	10.1016/j.comnet.2022.108977 doi (DE-627)ELV007913583 (ELSEVIER)S1389-1286(22)00149-9 DE-627 ger DE-627 rda eng 004 620 DE-600 54.32 bkl 53.76 bkl Ji, Pengshuo verfasserin aut Joint optimization for RIS-assisted multicast D2D communications 2022 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Multicast device-to-device (D2D) communication is an important technique to overcome the problem of spectrum shortage. Due to the channel gain difference between users in different locations, receivers in the same multicast D2D group still suffer from the problem of different quality of service (QoS) levels. This paper proposes a novel reconfigurable intelligent surface (RIS)-assisted multicast D2D communication system to enhance the QoS of users, in which RIS solves the problem of different QoS between users through intelligent resource optimization. To maximize the achievable sum rate of all multicast D2D users, we formulate a joint optimization problem. This problem combines channel assignment, power allocation, and reflection matrix design by considering the QoS fairness among different D2D users. To solve this problem, we propose a novel joint optimization algorithm, which has three steps. First, we propose a matching algorithm based on swap operations to solve the channel assignment problem. Then, we propose a successive convex approximation (SCA) method to solve the power allocation problem. Finally, we present the optimization of the RIS reflection coefficients with mathematical analysis. The numerical results demonstrate that the proposed algorithm can effectively enhance the QoS of users in the multicast D2D group. With the aid of RIS, the proposed algorithm decreases the service disparities between users in different locations. Furthermore, it reveals that it is helpful to deploy the RIS closer to the receivers or the transmitters. D2D communication Reconfigurable intelligent surface Multicasting Resource allocation Successive convex approximation Jia, Jie verfasserin aut Chen, Jian verfasserin aut Xie, Yunhe verfasserin (orcid)0000-0002-2685-857X aut Wang, Xingwei verfasserin aut Enthalten in Computer networks Amsterdam [u.a.] : Elsevier, 1976 211 Online-Ressource (DE-627)306652749 (DE-600)1499744-7 (DE-576)081954360 nnns volume:211 GBV_USEFLAG_U SYSFLAG_U GBV_ELV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 54.32 Rechnerkommunikation 53.76 Kommunikationsdienste Fernmeldetechnik AR 211
spelling	10.1016/j.comnet.2022.108977 doi (DE-627)ELV007913583 (ELSEVIER)S1389-1286(22)00149-9 DE-627 ger DE-627 rda eng 004 620 DE-600 54.32 bkl 53.76 bkl Ji, Pengshuo verfasserin aut Joint optimization for RIS-assisted multicast D2D communications 2022 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Multicast device-to-device (D2D) communication is an important technique to overcome the problem of spectrum shortage. Due to the channel gain difference between users in different locations, receivers in the same multicast D2D group still suffer from the problem of different quality of service (QoS) levels. This paper proposes a novel reconfigurable intelligent surface (RIS)-assisted multicast D2D communication system to enhance the QoS of users, in which RIS solves the problem of different QoS between users through intelligent resource optimization. To maximize the achievable sum rate of all multicast D2D users, we formulate a joint optimization problem. This problem combines channel assignment, power allocation, and reflection matrix design by considering the QoS fairness among different D2D users. To solve this problem, we propose a novel joint optimization algorithm, which has three steps. First, we propose a matching algorithm based on swap operations to solve the channel assignment problem. Then, we propose a successive convex approximation (SCA) method to solve the power allocation problem. Finally, we present the optimization of the RIS reflection coefficients with mathematical analysis. The numerical results demonstrate that the proposed algorithm can effectively enhance the QoS of users in the multicast D2D group. With the aid of RIS, the proposed algorithm decreases the service disparities between users in different locations. Furthermore, it reveals that it is helpful to deploy the RIS closer to the receivers or the transmitters. D2D communication Reconfigurable intelligent surface Multicasting Resource allocation Successive convex approximation Jia, Jie verfasserin aut Chen, Jian verfasserin aut Xie, Yunhe verfasserin (orcid)0000-0002-2685-857X aut Wang, Xingwei verfasserin aut Enthalten in Computer networks Amsterdam [u.a.] : Elsevier, 1976 211 Online-Ressource (DE-627)306652749 (DE-600)1499744-7 (DE-576)081954360 nnns volume:211 GBV_USEFLAG_U SYSFLAG_U GBV_ELV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 54.32 Rechnerkommunikation 53.76 Kommunikationsdienste Fernmeldetechnik AR 211
allfields_unstemmed	10.1016/j.comnet.2022.108977 doi (DE-627)ELV007913583 (ELSEVIER)S1389-1286(22)00149-9 DE-627 ger DE-627 rda eng 004 620 DE-600 54.32 bkl 53.76 bkl Ji, Pengshuo verfasserin aut Joint optimization for RIS-assisted multicast D2D communications 2022 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Multicast device-to-device (D2D) communication is an important technique to overcome the problem of spectrum shortage. Due to the channel gain difference between users in different locations, receivers in the same multicast D2D group still suffer from the problem of different quality of service (QoS) levels. This paper proposes a novel reconfigurable intelligent surface (RIS)-assisted multicast D2D communication system to enhance the QoS of users, in which RIS solves the problem of different QoS between users through intelligent resource optimization. To maximize the achievable sum rate of all multicast D2D users, we formulate a joint optimization problem. This problem combines channel assignment, power allocation, and reflection matrix design by considering the QoS fairness among different D2D users. To solve this problem, we propose a novel joint optimization algorithm, which has three steps. First, we propose a matching algorithm based on swap operations to solve the channel assignment problem. Then, we propose a successive convex approximation (SCA) method to solve the power allocation problem. Finally, we present the optimization of the RIS reflection coefficients with mathematical analysis. The numerical results demonstrate that the proposed algorithm can effectively enhance the QoS of users in the multicast D2D group. With the aid of RIS, the proposed algorithm decreases the service disparities between users in different locations. Furthermore, it reveals that it is helpful to deploy the RIS closer to the receivers or the transmitters. D2D communication Reconfigurable intelligent surface Multicasting Resource allocation Successive convex approximation Jia, Jie verfasserin aut Chen, Jian verfasserin aut Xie, Yunhe verfasserin (orcid)0000-0002-2685-857X aut Wang, Xingwei verfasserin aut Enthalten in Computer networks Amsterdam [u.a.] : Elsevier, 1976 211 Online-Ressource (DE-627)306652749 (DE-600)1499744-7 (DE-576)081954360 nnns volume:211 GBV_USEFLAG_U SYSFLAG_U GBV_ELV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 54.32 Rechnerkommunikation 53.76 Kommunikationsdienste Fernmeldetechnik AR 211
allfieldsGer	10.1016/j.comnet.2022.108977 doi (DE-627)ELV007913583 (ELSEVIER)S1389-1286(22)00149-9 DE-627 ger DE-627 rda eng 004 620 DE-600 54.32 bkl 53.76 bkl Ji, Pengshuo verfasserin aut Joint optimization for RIS-assisted multicast D2D communications 2022 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Multicast device-to-device (D2D) communication is an important technique to overcome the problem of spectrum shortage. Due to the channel gain difference between users in different locations, receivers in the same multicast D2D group still suffer from the problem of different quality of service (QoS) levels. This paper proposes a novel reconfigurable intelligent surface (RIS)-assisted multicast D2D communication system to enhance the QoS of users, in which RIS solves the problem of different QoS between users through intelligent resource optimization. To maximize the achievable sum rate of all multicast D2D users, we formulate a joint optimization problem. This problem combines channel assignment, power allocation, and reflection matrix design by considering the QoS fairness among different D2D users. To solve this problem, we propose a novel joint optimization algorithm, which has three steps. First, we propose a matching algorithm based on swap operations to solve the channel assignment problem. Then, we propose a successive convex approximation (SCA) method to solve the power allocation problem. Finally, we present the optimization of the RIS reflection coefficients with mathematical analysis. The numerical results demonstrate that the proposed algorithm can effectively enhance the QoS of users in the multicast D2D group. With the aid of RIS, the proposed algorithm decreases the service disparities between users in different locations. Furthermore, it reveals that it is helpful to deploy the RIS closer to the receivers or the transmitters. D2D communication Reconfigurable intelligent surface Multicasting Resource allocation Successive convex approximation Jia, Jie verfasserin aut Chen, Jian verfasserin aut Xie, Yunhe verfasserin (orcid)0000-0002-2685-857X aut Wang, Xingwei verfasserin aut Enthalten in Computer networks Amsterdam [u.a.] : Elsevier, 1976 211 Online-Ressource (DE-627)306652749 (DE-600)1499744-7 (DE-576)081954360 nnns volume:211 GBV_USEFLAG_U SYSFLAG_U GBV_ELV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 54.32 Rechnerkommunikation 53.76 Kommunikationsdienste Fernmeldetechnik AR 211
allfieldsSound	10.1016/j.comnet.2022.108977 doi (DE-627)ELV007913583 (ELSEVIER)S1389-1286(22)00149-9 DE-627 ger DE-627 rda eng 004 620 DE-600 54.32 bkl 53.76 bkl Ji, Pengshuo verfasserin aut Joint optimization for RIS-assisted multicast D2D communications 2022 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Multicast device-to-device (D2D) communication is an important technique to overcome the problem of spectrum shortage. Due to the channel gain difference between users in different locations, receivers in the same multicast D2D group still suffer from the problem of different quality of service (QoS) levels. This paper proposes a novel reconfigurable intelligent surface (RIS)-assisted multicast D2D communication system to enhance the QoS of users, in which RIS solves the problem of different QoS between users through intelligent resource optimization. To maximize the achievable sum rate of all multicast D2D users, we formulate a joint optimization problem. This problem combines channel assignment, power allocation, and reflection matrix design by considering the QoS fairness among different D2D users. To solve this problem, we propose a novel joint optimization algorithm, which has three steps. First, we propose a matching algorithm based on swap operations to solve the channel assignment problem. Then, we propose a successive convex approximation (SCA) method to solve the power allocation problem. Finally, we present the optimization of the RIS reflection coefficients with mathematical analysis. The numerical results demonstrate that the proposed algorithm can effectively enhance the QoS of users in the multicast D2D group. With the aid of RIS, the proposed algorithm decreases the service disparities between users in different locations. Furthermore, it reveals that it is helpful to deploy the RIS closer to the receivers or the transmitters. D2D communication Reconfigurable intelligent surface Multicasting Resource allocation Successive convex approximation Jia, Jie verfasserin aut Chen, Jian verfasserin aut Xie, Yunhe verfasserin (orcid)0000-0002-2685-857X aut Wang, Xingwei verfasserin aut Enthalten in Computer networks Amsterdam [u.a.] : Elsevier, 1976 211 Online-Ressource (DE-627)306652749 (DE-600)1499744-7 (DE-576)081954360 nnns volume:211 GBV_USEFLAG_U SYSFLAG_U GBV_ELV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 54.32 Rechnerkommunikation 53.76 Kommunikationsdienste Fernmeldetechnik AR 211
language	English
source	Enthalten in Computer networks 211 volume:211
sourceStr	Enthalten in Computer networks 211 volume:211
format_phy_str_mv	Article
bklname	Rechnerkommunikation Kommunikationsdienste Fernmeldetechnik
institution	findex.gbv.de
topic_facet	D2D communication Reconfigurable intelligent surface Multicasting Resource allocation Successive convex approximation
dewey-raw	004
isfreeaccess_bool	false
container_title	Computer networks
authorswithroles_txt_mv	Ji, Pengshuo @@aut@@ Jia, Jie @@aut@@ Chen, Jian @@aut@@ Xie, Yunhe @@aut@@ Wang, Xingwei @@aut@@
publishDateDaySort_date	2022-01-01T00:00:00Z
hierarchy_top_id	306652749
dewey-sort	14
id	ELV007913583
language_de	englisch
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author	Ji, Pengshuo
spellingShingle	Ji, Pengshuo ddc 004 bkl 54.32 bkl 53.76 misc D2D communication misc Reconfigurable intelligent surface misc Multicasting misc Resource allocation misc Successive convex approximation Joint optimization for RIS-assisted multicast D2D communications
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topic_title	004 620 DE-600 54.32 bkl 53.76 bkl Joint optimization for RIS-assisted multicast D2D communications D2D communication Reconfigurable intelligent surface Multicasting Resource allocation Successive convex approximation
topic	ddc 004 bkl 54.32 bkl 53.76 misc D2D communication misc Reconfigurable intelligent surface misc Multicasting misc Resource allocation misc Successive convex approximation
topic_unstemmed	ddc 004 bkl 54.32 bkl 53.76 misc D2D communication misc Reconfigurable intelligent surface misc Multicasting misc Resource allocation misc Successive convex approximation
topic_browse	ddc 004 bkl 54.32 bkl 53.76 misc D2D communication misc Reconfigurable intelligent surface misc Multicasting misc Resource allocation misc Successive convex approximation
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title	Joint optimization for RIS-assisted multicast D2D communications
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title_full	Joint optimization for RIS-assisted multicast D2D communications
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author_browse	Ji, Pengshuo Jia, Jie Chen, Jian Xie, Yunhe Wang, Xingwei
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title_sort	joint optimization for ris-assisted multicast d2d communications
title_auth	Joint optimization for RIS-assisted multicast D2D communications
abstract	Multicast device-to-device (D2D) communication is an important technique to overcome the problem of spectrum shortage. Due to the channel gain difference between users in different locations, receivers in the same multicast D2D group still suffer from the problem of different quality of service (QoS) levels. This paper proposes a novel reconfigurable intelligent surface (RIS)-assisted multicast D2D communication system to enhance the QoS of users, in which RIS solves the problem of different QoS between users through intelligent resource optimization. To maximize the achievable sum rate of all multicast D2D users, we formulate a joint optimization problem. This problem combines channel assignment, power allocation, and reflection matrix design by considering the QoS fairness among different D2D users. To solve this problem, we propose a novel joint optimization algorithm, which has three steps. First, we propose a matching algorithm based on swap operations to solve the channel assignment problem. Then, we propose a successive convex approximation (SCA) method to solve the power allocation problem. Finally, we present the optimization of the RIS reflection coefficients with mathematical analysis. The numerical results demonstrate that the proposed algorithm can effectively enhance the QoS of users in the multicast D2D group. With the aid of RIS, the proposed algorithm decreases the service disparities between users in different locations. Furthermore, it reveals that it is helpful to deploy the RIS closer to the receivers or the transmitters.
abstractGer	Multicast device-to-device (D2D) communication is an important technique to overcome the problem of spectrum shortage. Due to the channel gain difference between users in different locations, receivers in the same multicast D2D group still suffer from the problem of different quality of service (QoS) levels. This paper proposes a novel reconfigurable intelligent surface (RIS)-assisted multicast D2D communication system to enhance the QoS of users, in which RIS solves the problem of different QoS between users through intelligent resource optimization. To maximize the achievable sum rate of all multicast D2D users, we formulate a joint optimization problem. This problem combines channel assignment, power allocation, and reflection matrix design by considering the QoS fairness among different D2D users. To solve this problem, we propose a novel joint optimization algorithm, which has three steps. First, we propose a matching algorithm based on swap operations to solve the channel assignment problem. Then, we propose a successive convex approximation (SCA) method to solve the power allocation problem. Finally, we present the optimization of the RIS reflection coefficients with mathematical analysis. The numerical results demonstrate that the proposed algorithm can effectively enhance the QoS of users in the multicast D2D group. With the aid of RIS, the proposed algorithm decreases the service disparities between users in different locations. Furthermore, it reveals that it is helpful to deploy the RIS closer to the receivers or the transmitters.
abstract_unstemmed	Multicast device-to-device (D2D) communication is an important technique to overcome the problem of spectrum shortage. Due to the channel gain difference between users in different locations, receivers in the same multicast D2D group still suffer from the problem of different quality of service (QoS) levels. This paper proposes a novel reconfigurable intelligent surface (RIS)-assisted multicast D2D communication system to enhance the QoS of users, in which RIS solves the problem of different QoS between users through intelligent resource optimization. To maximize the achievable sum rate of all multicast D2D users, we formulate a joint optimization problem. This problem combines channel assignment, power allocation, and reflection matrix design by considering the QoS fairness among different D2D users. To solve this problem, we propose a novel joint optimization algorithm, which has three steps. First, we propose a matching algorithm based on swap operations to solve the channel assignment problem. Then, we propose a successive convex approximation (SCA) method to solve the power allocation problem. Finally, we present the optimization of the RIS reflection coefficients with mathematical analysis. The numerical results demonstrate that the proposed algorithm can effectively enhance the QoS of users in the multicast D2D group. With the aid of RIS, the proposed algorithm decreases the service disparities between users in different locations. Furthermore, it reveals that it is helpful to deploy the RIS closer to the receivers or the transmitters.
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title_short	Joint optimization for RIS-assisted multicast D2D communications
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author2	Jia, Jie Chen, Jian Xie, Yunhe Wang, Xingwei
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up_date	2024-07-06T17:54:04.694Z
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Joint optimization for RIS-assisted multicast D2D communications

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