An adaptive blind equalizer with signal separation for a MIMO system transmitting QAM signals

Moazzami, Farzad; Cole-Rhodes, Arlene

doi:10.1109/milcom.2008.4753271

Cited by 14 publications

(10 citation statements)

References 8 publications

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“…This allows the algorithm to minimize the distance between the equalized symbols and the original symbols in the constellation, hence improving the likelihood of correct detection. Likewise, in [21], the authors consider a CMA+AMA equalizer which minimizes a linear combination of the CMA and the AMA cost function. In our implementation of these two algorithms, we found both provide similar performance.…”

Section: Constant Modulus-based Algorithmsmentioning

confidence: 99%

Precoder Detection for Cooperative Decode-and-Forward Relaying in OFDMA Systems

Valluri

Shayman

2014

2014 IEEE Military Communications Conference

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We consider an LTE network where a secondary user acts as a relay, transmitting data to the primary user using a decode-and-forward mechanism, transparent to the base-station (eNodeB). Clearly, the relay can decode symbols more reliably if the employed precoder matrix indicators (PMIs) are known. However, for closed loop spatial multiplexing (CLSM) transmit mode, this information is not always embedded in the downlink signal, leading to a need for effective methods to determine the PMI. In this thesis, we consider 2x2 MIMO and 4x4 MIMO downlink channels corresponding to CLSM and formulate two techniques to estimate the PMI at the relay using a hypothesis testing framework. We evaluate their performance via simulations for various ITU channel models over a range of SNR and for different channel quality indicators (CQIs). We compare them to the case when the true PMI is known at the relay and show that the performance of the proposed schemes are within 2 dB at 10% block error rate (BLER) in almost all scenarios. Furthermore, the techniques add minimal computational overhead over existent receiver structure.Finally, we also identify scenarios when using the proposed precoder detection algorithms in conjunction with the cooperative decode-and-forward relaying mechanism benefits the PUE and improves the BLER performance for the PUE. Therefore, we conclude from this that the proposed algorithms as well as the cooperative relaying mechanism at the CMR can be gainfully employed in a variety of real-life scenarios in LTE networks.

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Section: Constant Modulus-based Algorithmsmentioning

confidence: 99%

Precoder Detection for Cooperative Decode-and-Forward Relaying in OFDMA Systems

Valluri

Shayman

2014

2014 IEEE Military Communications Conference

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“…It has been shown in [1] that by using the (K_1/ h lag of the autocorrelation of the received signal, and the equalizer weight vector, an accurate estimate of the effective channel vector acting on the recovered source can be determined by…”

Section: Channel Estimation and Signal Cancellationmentioning

confidence: 99%

“…In an earlier work a multistage equalization and blind source separation method for time invariant MIMO systems was developed and evaluated [1]. By nature CMA equalizer converges to the most powerful signal in the received signal mixture.…”

Section: Introductionmentioning

confidence: 99%

“…The channel estimate was derived by using the fact that the equalizer error is orthogonal to the received signal, and it is an extension of the work of Shynk [2] to wideband systems. The blind MIMO equalization and source separation method described here has been successfully tested with time invariant channels [1]. In this work a time-varying Rayleigh fading channel model is used to evaluate the robustness of the multistage blind equalization and channel estimation scheme over the channel paths with time variation.…”

Section: Introductionmentioning

confidence: 99%

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Multistage blind equalization in time-varying MIMO systems

Moazzami

Cole-Rhodes

2011

2011 45th Annual Conference on Information Sciences and Systems

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In this work we evaluate the performance of multistage blind equalization scheme for time-varying MIMO systems. Equalization of the signals is achieved by minimizing a cost function, which is of a linear combination of the constant modulus algorithm (CMA) and the alphabet-matched algorithm (AMA). This has been previously shown to outperform the conventional CMA equalizer in recovery of non-constant modulus signals, such as I6-QAM The transmitted sources in a MIMO system can be recovered in a multistage fashion using a cascade of CMA-based MISO equalizers. After equalization each captured source is cancelled by estimating its corresponding channel vector and subtracting the contribution of that captured source from the received signal. The modified received signal vector is then used as input to the equalizer at the next stage. A time-varying Gaussian channel model is used to evaluate the effect of time variation on multistage equalization and cancellation.

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“…The general equalization scheme is not optimal for accuracy and computational complexity. The Constant Modulus Algorithm (CMA) is well-established and frequently used blind equalization technique in many practical applications, since it does not require carrier synchronization [11][12][13][14][15][16][17][18][19][20]. The widely used CMA algorithms are Least Square CMA (LS-CMA) and Recursive Least Square CMA (RLS-CMA) for MIMO system.…”

Section: Introductionmentioning

confidence: 99%