Performance of adaptive MIMO switching for cognitive MC-CDMA system
The future 5G wireless network will be identified by flexibility design, high combination of services, and higher data rate. In this treatise, we present the performance evaluation physical layer design for multi-carrier code-division-multiple-access (MC-CDMA) system for cognitive radio network (CRN...
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| Vydáno v: | Cluster computing Ročník 22; číslo Suppl 4; s. 7723 - 7731 |
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| Médium: | Journal Article |
| Jazyk: | angličtina |
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01.07.2019
Springer Nature B.V |
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| ISSN: | 1386-7857, 1573-7543 |
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| Abstract | The future 5G wireless network will be identified by flexibility design, high combination of services, and higher data rate. In this treatise, we present the performance evaluation physical layer design for multi-carrier code-division-multiple-access (MC-CDMA) system for cognitive radio network (CRN) employing link adaptive multiple-input multiple- output (MIMO). CRN in conjunction with MIMO promises to achieve massive amelioration in system bandwidth. We consider link adaption scheme (LAS) which will select modulation scheme and MIMO profile based on channel parameters. CRN is a device in wireless communication which can sense the idle unused spectrum and allocate the spectrum dynamically to base station. We utilize sub-band frequency of CRN for multi-carrier communication and to extract for user-specific spreader in CDMA system. Further, we realize iterative decoder at the receiver to achieve better error-rate performance for CRN based MIMO MC-CDMA system with less signal-to-noise ratio (SNR). Furthermore,We study the performance of adaptive MIMO scheme with CRN defined MC-CDMA for Stanford University Interim channel model specifications. We discern through computer simulations that CRN based MC-CDMA system with adaptive MIMO scheme achieves significant performance enhancement both in error-rate and data rate. |
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| AbstractList | The future 5G wireless network will be identified by flexibility design, high combination of services, and higher data rate. In this treatise, we present the performance evaluation physical layer design for multi-carrier code-division-multiple-access (MC-CDMA) system for cognitive radio network (CRN) employing link adaptive multiple-input multiple- output (MIMO). CRN in conjunction with MIMO promises to achieve massive amelioration in system bandwidth. We consider link adaption scheme (LAS) which will select modulation scheme and MIMO profile based on channel parameters. CRN is a device in wireless communication which can sense the idle unused spectrum and allocate the spectrum dynamically to base station. We utilize sub-band frequency of CRN for multi-carrier communication and to extract for user-specific spreader in CDMA system. Further, we realize iterative decoder at the receiver to achieve better error-rate performance for CRN based MIMO MC-CDMA system with less signal-to-noise ratio (SNR). Furthermore,We study the performance of adaptive MIMO scheme with CRN defined MC-CDMA for Stanford University Interim channel model specifications. We discern through computer simulations that CRN based MC-CDMA system with adaptive MIMO scheme achieves significant performance enhancement both in error-rate and data rate. |
| Author | Vishvaksenan, Kuttathati Srinivasan Leela, S. |
| Author_xml | – sequence: 1 givenname: S. surname: Leela fullname: Leela, S. email: ss.leela@yahoo.com organization: Department of Electrical Engineering, Sastra University – sequence: 2 givenname: Kuttathati Srinivasan surname: Vishvaksenan fullname: Vishvaksenan, Kuttathati Srinivasan organization: Department of ECE, SSN College of Engineering |
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| Cites_doi | 10.1109/WCNC.2007.340 10.1109/GLOCOM.2011.6133923 10.1007/s10586-017-0831-6 10.1109/TWC.2007.060907 10.1016/j.compeleceng.2016.01.004 10.1016/j.compeleceng.2015.11.002 10.1109/ACCESS.2016.2596774 10.1109/TVT.2007.907317 10.1109/26.486616 |
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| DOI | 10.1007/s10586-017-1322-5 |
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| Issue | Suppl 4 |
| Keywords | Minimum-mean-square-error(MMSE) estimation Multi-user detection(MUD) Code-division multiple-access(CDMA) Zero-forcing algorithm(ZF) BCJR decoder Maximum likely-hood detection(ML) |
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| References_xml | – reference: NelsonIVishvaksenanKSRajendranVPalanimuruganRMitigating ambient noise and multi-path propagation in under water communication using the DSTTD-OFDM systemJ. Comput. Electr. Eng.201653409417 – reference: KondoSMilsteinLBPerformance of multicarrier DS CDMA systemsIEEE Trans. Commun.1996442238246 – reference: AttarAReza NakhaiMHamid AghvamiACognitive radio transmission based on direct sequence MC-CDMAIEEE Trans. Wirel. Commun.2008711571162 – reference: AlJerjawiMSHamoudaWPerformance analysis of multiuser DS-CDMA in MIMO systems over rayleigh fading channelsIEEE Trans. Veh. Technol.200857314801493 – reference: MithraKVishvaksenanKSPerformance of coded STBC-IDMA system using polarization diversity for downlink transmissionCluster Comput.201720216151624 – reference: Zhang, R., Hanzo, L.: Iteratively detected multi-carrier interleave division multiple access. In: International conference MICROC0LL’07, BUDAPEST, Hungary, May 2007 – reference: Vishvaksenan, K.S., Vasanth raj, P.T.: Coded downlink multi-user MC-CDMA system using transmitter pre-processing: performance results. IEEE Access, 4:4534-4542 (2016). https://doi.org/10.1109/ACCESS.2016.2596774 – reference: KarthipanRVishvaksenanKSKalidossRKrishanAPerformance of turbo coded triply-polarized MIMO-CDMA system for downlink communicationJ. Comput. Electr. Eng.201656182192 – reference: Han, C., Doufexi, A., Armour, S., Ng, K.H., McGeehan, J.: Adaptive MIMO OFDMA for future generation cellular systems in a realistic outdoor environment. In: 63rd IEEE Vehicular Technology Conference (VTC 2006-Spring) Australia, pp. 142–146, 7-10 May 2006 – reference: Xiao, J., Ye, F., Tian, T., Hu, R.Q.: CR enabled TD-LTE within TV white space: system level performance analysis. In: IEEE Global Telecommunications Conference, pp. 1–6, December 2011 – reference: YangLLWangLCZero-forcing and minimum mean square error multiuser detection in generalized multicarrier DSCDMA systems for cognitive radioEURASIP J. Wirel. Commun. Netw.2008142541410 – reference: Muquet, B., Biglieri, E., Sari, H.: MIMO link adaptation in mobile WiMAX systems. In: IEEE Wireless Communications and Networking Conference (WCNC 2007) China, pp. 1812–1815, 11-15 March 2007 – reference: Maucher, J., Furrer, J., Heise: IEEE Std. 2007, IEEE Standard for WIMAX 802.16, Hannover (2007) – reference: LiWGulliverTASuccessive interference cancellation for DSCDMA systems with transmit diversityEURASIP J. Wirel. Commu. Netw.200414654 – ident: 1322_CR1 doi: 10.1109/WCNC.2007.340 – ident: 1322_CR5 doi: 10.1109/GLOCOM.2011.6133923 – volume: 14 start-page: 541410 issue: 2 year: 2008 ident: 1322_CR8 publication-title: EURASIP J. Wirel. Commun. Netw. – volume: 20 start-page: 1615 issue: 2 year: 2017 ident: 1322_CR4 publication-title: Cluster Comput. doi: 10.1007/s10586-017-0831-6 – volume: 7 start-page: 1157 year: 2008 ident: 1322_CR11 publication-title: IEEE Trans. Wirel. Commun. doi: 10.1109/TWC.2007.060907 – ident: 1322_CR2 – ident: 1322_CR9 – volume: 56 start-page: 182 year: 2016 ident: 1322_CR3 publication-title: J. Comput. Electr. Eng. doi: 10.1016/j.compeleceng.2016.01.004 – volume: 53 start-page: 409 year: 2016 ident: 1322_CR13 publication-title: J. Comput. Electr. Eng. doi: 10.1016/j.compeleceng.2015.11.002 – volume: 1 start-page: 46 year: 2004 ident: 1322_CR10 publication-title: EURASIP J. Wirel. Commu. Netw. – ident: 1322_CR14 – ident: 1322_CR12 doi: 10.1109/ACCESS.2016.2596774 – volume: 57 start-page: 1480 issue: 3 year: 2008 ident: 1322_CR7 publication-title: IEEE Trans. Veh. Technol. doi: 10.1109/TVT.2007.907317 – volume: 44 start-page: 238 issue: 2 year: 1996 ident: 1322_CR6 publication-title: IEEE Trans. Commun. doi: 10.1109/26.486616 |
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| SubjectTerms | Adaptive systems Antennas Bandwidths Code Division Multiple Access Cognitive radio Communication Computer Communication Networks Computer Science Iterative methods MIMO communication Operating Systems Performance enhancement Performance evaluation Processor Architectures Receivers & amplifiers Sensors Signal to noise ratio Spacetime Spectrum allocation Transmitters Wireless communications Wireless networks |
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