Multiple-input multiple-output least-squares constant modulus algorithms

Sansrimahachai, P.; Ward, D.B.; Constantinides, A.G.

doi:10.1109/glocom.2003.1258603

Cited by 7 publications

(3 citation statements)

References 10 publications

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“…Scholars have also put forward many proposals [2,3]. However, the separation performance of many algorithms for the coherent sources is poor, a new blind separation algorithm of coherent signals based on Toeplitz matrix reconstruction is proposed in this paper.…”

Section: Introductionmentioning

confidence: 99%

Blind Separation of Coherent Signals Based on Toeplitz Matrix Reconstruction

Tang

Song

2011

AMM

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A new blind beamforming algorithm for separating and estimating coherent signals arriving at an antenna array is proposed in this paper. This algorithm is implemented through arranging the received data’s correlation function of each array element and reference array element (the first array element), to form the Hermitian Toeplitz matrix first. Then through the singular value decomposition of the matrix the signal subspace and noise subspace can be get, in order to achieve the direction vector of coherent sources to beamform, which can separate the independent signals from different directions effectively without knowing the transcendent knowledge of the signals. The new approach can estimate the coherent signals’ direction-of-arrival(DOA) on the basis of separation, and has good performance under the low SNR. The simulation results show that the proposed method is effective．

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Section: Introductionmentioning

confidence: 99%

Blind Separation of Coherent Signals Based on Toeplitz Matrix Reconstruction

Tang

Song

2011

AMM

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“…multi-user systems. Owing to poor bit error rate (BER) performance of such algorithms (as presented in [20], in this paper we present and analyse new blind separation techniques based on the LSCMA and techniques that are used successfully in the multi-user detection. The first two algorithms are formulated from the concept of interference cancellation (successive and parallel), whereas the third algorithm uses an orthogonality constraint (by using the Gram-Schmidt orthogonalisation procedure) to ensure the output signals are recovered from different input streams.…”

Section: Introductionmentioning

confidence: 99%

Blind source separation of instantaneous MIMO systems based on the least-squares Constant Modulus Algorithm

Sansrimahachai

Ward

Constantinides

2005

IEE Proc., Vis. Image Process.

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Blind symbol detection for mobile communications systems has been widely studied and can be implemented by using either adaptive or iterative techniques. However, adaptive blind algorithms require data of sufficient length to converge. Therefore, in a rapidly changing environment, they are likely unable to track the changing channels. In such a situation, one possible solution is to use iterative blind algorithms. Iterative blind source separation algorithms based on the least-squares constant modulus algorithm (LSCMA) for instantaneous multipleinput multiple-output (MIMO) systems are proposed. Since the LSCMA cannot guarantee correct separation and hence cannot be used directly for MIMO channels, two extensions are considered: cancellation techniques (successive and parallel), and using an orthogonality constraint to ensure independence among different outputs. In common with many block iterative algorithms, it is found that for small block sizes there can be a BER flare-up effect at high SNR, although this can be removed for a sufficiently large block size. Of the proposed algorithms, simulation results show that the orthogonality-based algorithm has the best performance, and is comparable to iterative least-squares with projection (ILSP) algorithm, but offers cheaper computational complexity.

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“…In order to improve the performance of CMA for QAM signals a number of modified methods have been introduced such as the algorithm known as MMA 7 and constant norm algorithm (CNA) 8 whose CMA represents a particular case. The CMA can also be used in MIMO systems 9 . However this case is susceptible to the one-to-many problem.…”

mentioning

confidence: 99%

Fast gradient algorithm for complex ICA and its application to the MIMO systems

Mika

2023

Sci Rep

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This paper proposes a new gradient-descent algorithm for complex independent component analysis and presents its application to the Multiple-Input Multiple-Output communication systems. Algorithm uses the Lie structure of optimization landscape and toral decomposition of gradient matrix. The theoretical results are validated by computer simulation and compared to several classes of algorithms, gradient descent, quasi-Newton as well as complex JADE. The simulations performed showed excellent results of the algorithm in terms of speed, stability of operation and the quality of separation. A characteristic feature of gradient methods is their quick response to changes in the input signal. The good results of the proposed algorithm indicate potential use in on-line applications.

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Multiple-input multiple-output least-squares constant modulus algorithms

Cited by 7 publications

References 10 publications

Blind Separation of Coherent Signals Based on Toeplitz Matrix Reconstruction

Blind Separation of Coherent Signals Based on Toeplitz Matrix Reconstruction

Blind source separation of instantaneous MIMO systems based on the least-squares Constant Modulus Algorithm

Fast gradient algorithm for complex ICA and its application to the MIMO systems

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