A modified constant modulus algorithm for adaptive channel equalization for QAM signals

Amin, Moeness G.; He, Liang; Reed, C.; Malkemes, R.C.

doi:10.1109/ssp.2001.955349

Cited by 10 publications

(12 citation statements)

References 9 publications

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“…Adaptive blind equalization based on CMA has been a very active area of research during the past few years. Due to lack of space we shall not summarize all exiting ideas and algorithms; rather we refer the interested reader to [10], [9], [11], [4]. There have been many studies which investigate the convergence-time behavior of the CMA, and an excellent review can be found in [14].…”

Section: Introductionmentioning

confidence: 99%

“…In practice, such a low level of MSE may not always be achievable by the CMA scheme. Recently, a modified CMA (MCMA) for application to wireless networking employing QAM signals has been introduced [4]. In the MCMA, the cost function is weighted sum of two separate well-defined error terms; one is identical to the CMA case, and the other corresponds to a DD mode or any other constellation matched error (CME) term [16], [5].…”

Section: Introductionmentioning

confidence: 99%

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Adaptive blind equalization algorithm for QAM signals in OFDM systems by GI-restoration

Alayyan

Zoubir

Leung

2007

2007 9th International Symposium on Signal Processing and Its Applications

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In this paper, a new blind equalization algorithm is proposed based on guard interval (GI)-restoral property for quadrature amplitude modulation (QAM) signals. The proposed algorithm utilizes existing redundancy in the time domain to completely eliminates inter-symbol-interference. We prove that the usage of GI-restoral property is sufficient to obtain a zeroforcing equalizer of the channel. The main advantage of this approach resides in its simplicity as the equalizer coefficients are estimated using a second-order least square fitting (LSF) scheme. The equalizer uses the LSF in the initial phase and then switches to a proposed constant modulus algorithm (CMA). The proposed CMA is constructed through the exploitation of a fully data information. To achieve a dramatic improvement in equalization performance, a modified CMA (MCMA) is proposed for OFDM systems based on cyclic prefixing approach. The resulting scheme provides a state-of-the-art low complexity with superior performance blind equalization. Extensive simulation shows tat LSF-MCMA has a better steady-state equalization performance than LSF-CMA.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Adaptive blind equalization algorithm for QAM signals in OFDM systems by GI-restoration

Alayyan

Zoubir

Leung

2007

2007 9th International Symposium on Signal Processing and Its Applications

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“…QAM) constellations. The incorporation of partial, or full knowledge, of the signal constellation in the cost function of gradient-based adaptive blind equalization techniques lead to improved receiver performance [4,5,6,7,8,9].…”

Section: Introductionmentioning

confidence: 99%

<title>Performance comparison of dual and combined mode adaptive techniques for dynamic channel equalizations</title>

Amin

2002

SPIE Proceedings

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A cost function, utilizing the signal amplitude as well as the phase information, yields fast convergence and small mean square errors, when used for equalizing dynamic wireless channels. Recently, it has been shown that the minimization of cost functions that include both amplitude-dependent and constellation-dependent terms leads to improved receiver performance for high-order signal constellations, compared to that achieved by only using either term. The amplitudedependent term corresponds to the constant modulus algorithm (CMA), which ensures proper global convergence properties. On the other hand, the constellation-matched error (CME) term provides desirable local convergence properties. Two possible schemes can be used for presenting a combined cost function. One scheme is based on a weighted sum of the CMA and the CME terms, where the weights are fixed, whereas the cost function in the other scheme has time-varying weights that are recursively update using gradient techniques. In this paper, performance comparison is conducted between techniques implementing combined cost functions with fixed and variable weighting parameters. The comparison also includes the CMA and DD techniques as well as adaptive equalizations based on dual modes. In the latter, one term of the cost function is considered at one time. The common dual-mode approach calls for initialization with CMA and thereafter switching to a proper constellation-matched algorithm.

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“…The term E { p ( k ) } is newly introduced to reduce the constellation matched error. Notice that in the selection of the function p(k), the following factors should be considered [5]. Firstly, p ( k ) should provide uniform performance over the information symbols.…”

Section: The Modified Cc-cma Algorithmmentioning

confidence: 99%

“…The minimum values are zeros and only occur at the constellation points. For a PAM-PSK signal constellation, a similar constellation matched error function to that in [5] is employed. That is, p(k) = 1 -sin2" ( ~ ' '~~"~) (13) where 2d is the minimum distance between symbols and n is a positive integer which gives some degree of freedom for the selection ofp(k).…”

Section: The Modified Cc-cma Algorithmmentioning

confidence: 99%

A new cross-correlation and constant modulus type algorithm for PAM-PSK signals

Chambers

Luo

2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03).

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A modified constant modulus algorithm for adaptive channel equalization for QAM signals

Cited by 10 publications

References 9 publications

Adaptive blind equalization algorithm for QAM signals in OFDM systems by GI-restoration

Adaptive blind equalization algorithm for QAM signals in OFDM systems by GI-restoration

<title>Performance comparison of dual and combined mode adaptive techniques for dynamic channel equalizations</title>

A new cross-correlation and constant modulus type algorithm for PAM-PSK signals

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