Fast Converging Semi-Blind Space-Time Equalisation for Dispersive QAM MIMO Systems
A novel semi-blind space-time equaliser (STE) is proposed for dispersive multiple-input multiple-output systems that employ high-throughput quadrature amplitude modulation signalling. A minimum number of training symbols, approximately equal to the dimension of the STE, are first utilised to provide...
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| Vydáno v: | IEEE transactions on wireless communications Ročník 8; číslo 8; s. 3969 - 3974 |
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| Hlavní autoři: | , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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New York, NY
IEEE
01.08.2009
Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| ISSN: | 1536-1276, 1558-2248 |
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| Abstract | A novel semi-blind space-time equaliser (STE) is proposed for dispersive multiple-input multiple-output systems that employ high-throughput quadrature amplitude modulation signalling. A minimum number of training symbols, approximately equal to the dimension of the STE, are first utilised to provide a rough initial least squares estimate of the STE's weight vector. A concurrent gradient-Newton constant modulus algorithm and soft decision-directed scheme is then applied to adapt the STE. The proposed semi-blind adaptive STE is capable of converging fast to the minimum mean square error STE solution. Simulation results confirms that the convergence speed of this semi-blind adaptive algorithm is very close to that of the training-based recursive least squares algorithm. |
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| AbstractList | A novel semi-blind space-time equaliser (STE) is proposed for dispersive multiple-input multiple-output systems that employ high-throughput quadrature amplitude modulation signalling. A minimum number of training symbols, approximately equal to the dimension of the STE, are first utilised to provide a rough initial least squares estimate of the STE's weight vector. A concurrent gradient-Newton constant modulus algorithm and soft decision-directed scheme is then applied to adapt the STE. The proposed semi-blind adaptive STE is capable of converging fast to the minimum mean square error STE solution. Simulation results confirms that the convergence speed of this semi-blind adaptive algorithm is very close to that of the training-based recursive least squares algorithm. |
| Author | Hanzo, L. Chen, S. |
| Author_xml | – sequence: 1 givenname: S. surname: Chen fullname: Chen, S. organization: Sch. of Electron. & Comput. Sci., Univ. of Southampton, Southampton, UK – sequence: 2 givenname: L. surname: Hanzo fullname: Hanzo, L. organization: Sch. of Electron. & Comput. Sci., Univ. of Southampton, Southampton, UK |
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| Keywords | MIMO system Quadrature amplitude modulation Adaptive algorithm Multiple-input multiple-output Information rate space-time equalisation Space time Stochastic method Signalling Recursive algorithm Blind equalization Information transmission Mean square error Constant modulus algorithm Learning Simulation Least squares method stochastic-gradient adaptive algorithm Convergence rate Soft decision gradient-Newton adaptive algorithm Newton method Gradient method |
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| SubjectTerms | Adaptive algorithm Adaptive algorithms Algorithms Applied sciences Convergence Detection, estimation, filtering, equalization, prediction Dispersion Exact sciences and technology Frequency gradient-Newton adaptive algorithm Information, signal and communications theory Least squares approximation Least squares method Least squares methods Mathematical analysis Mean square error methods MIMO Modulation, demodulation Multiple-input multiple-output Neutron spin echo Quadrature amplitude modulation Signal and communications theory Signal, noise space-time equalisation stochastic-gradient adaptive algorithm Switching and signalling Systems, networks and services of telecommunications Telecommunications Telecommunications and information theory Throughput Transmission and modulation (techniques and equipments) Vectors (mathematics) Wireless communication |
| Title | Fast Converging Semi-Blind Space-Time Equalisation for Dispersive QAM MIMO Systems |
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