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Blind joint maximum likelihood channel estimation and data detection for singleinput multipleoutput systems
 in Proc. 6th IEE Int. Conf. 3G & Beyond
"... Abstract — Blind and semiblind adaptive schemes are proposed for joint maximum likelihood (ML) channel estimation and data detection for multipleinput multipleoutput (MIMO) systems. The joint ML optimisation over channel and data is decomposed into an iterative twolevel optimisation loop. An effi ..."
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Abstract — Blind and semiblind adaptive schemes are proposed for joint maximum likelihood (ML) channel estimation and data detection for multipleinput multipleoutput (MIMO) systems. The joint ML optimisation over channel and data is decomposed into an iterative twolevel optimisation loop. An efficient global optimisation search algorithm called the repeated weighted boosting search is employed at the upper level to identify the unknown MIMO channel model while an enhanced ML sphere detector called the optimised hierarchy reduced search algorithm aided ML detector is used at the lower level to perform the ML detection of the transmitted data. A simulation example is included to demonstrate the effectiveness of these two schemes. I.
CMA and Soft DecisionDirected Scheme for SemiBlind Beamforming of QAM Systems
"... Abstract — We propose a semiblind adaptive beamforming approach for wireless systems that employ highthroughput quadrature amplitude modulation signalling schemes. A minimum number of training symbols, equal to the number of receive antennaarray’s elements, are first utilised to provide a rough i ..."
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Abstract — We propose a semiblind adaptive beamforming approach for wireless systems that employ highthroughput quadrature amplitude modulation signalling schemes. A minimum number of training symbols, equal to the number of receive antennaarray’s elements, are first utilised to provide a rough initial least squares estimate of the beamformer’s weight vector. A concurrent constant modulus algorithm and soft decisiondirected scheme, originally developed for singleuser blind channel equalisation, is then applied to adapt the beamformer. It is demonstrated that this semiblind adaptive beamforming scheme is capable of converging fast to the minimum meansquareerror beamforming solution. I.
Research Article NonCancellation Multistage Kurtosis Maximization with Prewhitening for Blind Source Separation
"... Chi et al. recently proposed two effective noncancellation multistage (NCMS) blind source separation algorithms, one using the turbo source extraction algorithm (TSEA), called the NCMSTSEA, and the other using the fast kurtosis maximization algorithm (FKMA), called the NCMSFKMA. Their computation ..."
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Chi et al. recently proposed two effective noncancellation multistage (NCMS) blind source separation algorithms, one using the turbo source extraction algorithm (TSEA), called the NCMSTSEA, and the other using the fast kurtosis maximization algorithm (FKMA), called the NCMSFKMA. Their computational complexity and performance heavily depend on the dimension of multisensor data, that is, number of sensors. This paper proposes the inclusion of the prewhitening processing in the NCMSTSEA and NCMSFKMA prior to source extraction. We come up with four improved algorithms, referred to as the PNCMSTSEA, the PNCMSFKMA, the PNCMSTSEA(p), and the PNCMSFKMA(p). Compared with the existing NCMSTSEA and NCMSFKMA, the former two algorithms perform with significant computational complexity reduction and some performance improvements. The latter two algorithms are generalized counterparts of the former two algorithms with the single source extraction module replaced by a bank of source extraction modules in parallel at each stage. In spite of the same performance of PNCMSTSEA and PNCMSTSEA(p) (PNCMSFKMA and PNCMSFKMA(p)), the merit of this parallel source extraction structure lies in much shorter processing latency making the PNCMSTSEA(p) and PNCMSFKMA(p) well suitable for software and hardware implementations. Some simulation results are presented to verify the efficacy and computational efficiency of the proposed algorithms. Copyright © 2009 Xiang Chen et al. This is an open access article distributed under the Creative Commons Attribution License,
Fig. 1. ESPAR antennas ELECTRONICALLY STEERABLE PARASITIC ARRAY RADIATOR ANTENNA − PRINCIPLE, CONTROL THEORY AND ITS APPLICATIONS −
"... Principle, control theory, and application of the ESPAR (Electrically Steerable Parasitic Array Radiator) antenna are introduced. A typical ESPAR antenna consists of monopole or dipole elements, one of which is the radiator (fed element) and the others are the parasitic radiators with variable react ..."
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Principle, control theory, and application of the ESPAR (Electrically Steerable Parasitic Array Radiator) antenna are introduced. A typical ESPAR antenna consists of monopole or dipole elements, one of which is the radiator (fed element) and the others are the parasitic radiators with variable reactance devices loaded on them. It can provide a lowercost solution as an adaptive array antenna or angle diversity antenna, since it needs only a single receiver circuit. ESPAR antennas can be applied to adaptive beam formers, diversity receivers, and DoA (Direction of Arrival) finders. This paper shows the principle of ESPAR antenna from the view point of radio system design and applications.
Adaptive Antenna Array Beamforming Using A Concatenation of Recursive Least Square and Least Mean
, 2011
"... Srar, Jalal Abdulsayed. 2011. Adaptive antenna array beamforming using a concatenation of recursive least ..."
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Srar, Jalal Abdulsayed. 2011. Adaptive antenna array beamforming using a concatenation of recursive least
Research Article NonCancellation Multistage Kurtosis Maximization with Prewhitening for Blind Source Separation
"... Chi et al. recently proposed two effective noncancellation multistage (NCMS) blind source separation algorithms, one using the turbo source extraction algorithm (TSEA), called the NCMSTSEA, and the other using the fast kurtosis maximization algorithm (FKMA), called the NCMSFKMA. Their computation ..."
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Chi et al. recently proposed two effective noncancellation multistage (NCMS) blind source separation algorithms, one using the turbo source extraction algorithm (TSEA), called the NCMSTSEA, and the other using the fast kurtosis maximization algorithm (FKMA), called the NCMSFKMA. Their computational complexity and performance heavily depend on the dimension of multisensor data, that is, number of sensors. This paper proposes the inclusion of the prewhitening processing in the NCMSTSEA and NCMSFKMA prior to source extraction. We come up with four improved algorithms, referred to as the PNCMSTSEA, the PNCMSFKMA, the PNCMSTSEA(p), and the PNCMSFKMA(p). Compared with the existing NCMSTSEA and NCMSFKMA, the former two algorithms perform with significant computational complexity reduction and some performance improvements. The latter two algorithms are generalized counterparts of the former two algorithms with the single source extraction module replaced by a bank of source extraction modules in parallel at each stage. In spite of the same performance of PNCMSTSEA and PNCMSTSEA(p) (PNCMSFKMA and PNCMSFKMA(p)), the merit of this parallel source extraction structure lies in much shorter processing latency making the PNCMSTSEA(p) and PNCMSFKMA(p) well suitable for software and hardware implementations. Some simulation results are presented to verify the efficacy and computational efficiency of the proposed algorithms. Copyright © 2009 Xiang Chen et al. This is an open access article distributed under the Creative Commons Attribution License,
Semiblind Adaptive Beamforming for Highthroughput Quadrature Amplitude Modulation Systems
"... A semiblind adaptive beamforming scheme is proposed for wireless systems that employ highthroughput quadrature amplitude modulation signalling. A minimum number of training symbols, equal to the number of receiver antenna array ′ s elements, are first utilised to provide a rough initial least squa ..."
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A semiblind adaptive beamforming scheme is proposed for wireless systems that employ highthroughput quadrature amplitude modulation signalling. A minimum number of training symbols, equal to the number of receiver antenna array ′ s elements, are first utilised to provide a rough initial least squares estimate of the beamformer ′ s weight vector. A concurrent constant modulus algorithm and soft decisiondirected scheme is then applied to adapt the beamformer. This semiblind adaptive beamforming scheme is capable of converging fast to the minimum meansquareerror beamforming solution, as demonstrated in our simulation study.