Semi-Blind Source Separation based on Multi-Modulus Criterion: Application for Pilot Contamination Mitigation in Massive MIMO Communications Systems

Rekik, Ouahbi; Mokraoui, Anissa; Ladaycia, Abdelhamid; Abed-Meraim, Karim

doi:10.1109/iscit.2019.8905167

Cited by 5 publications

(1 citation statement)

References 11 publications

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“…This algorithm has been used in many works in the literature and was also referred to as Multi-Modulus Algorithm [11][12][13]. In [14], a semi-blind receiver using an hybrid cost function based on the Multi-Modulus criterion for the unknown data and the Least Squares criterion for the pilot data has been proposed for pilot contamination mitigation in Massive MIMO systems.…”

Section: Introductionmentioning

confidence: 99%

Semi-blind channel estimation based on Modified CMA and unitary scrambling for massive MIMO systems

Sellami

Siala²

2021

Preprint

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Pilot contamination is one of the main impairments in multi-cell massive Multiple-Input Multiple-Output (MIMO) systems. In order to improve the channel estimation in this context, we propose to use a semi-blind channel estimator based on the constant modulus algorithm (CMA). We consider an enhanced version of the CMA namely the Modified CMA (MCMA) which modifies the cost function of the CMA algorithm to the sum of cost functions for real and imaginary parts. Due to pilot contamination, the channel estimator may estimate the channel of a contaminating user instead of that of the user of interest (the user for which the Base Station wants to estimate the channel and then the data). To avoid this, we propose to scramble the users sequences before transmission. We consider different methods to perform unitary scrambling based on rotating the transmitted symbols (one Dimensional (1-D) scrambling) and using unitary matrices (two-Dimensional (2-D) scrambling). At the base station, the received sequence of the user of interest is descrambled leading to a better convergence of the channel estimator. We also consider the case where the Automatic Repeat reQuest (ARQ) protocol is used. In this case, using scrambling leads to a significant gain in terms of BLock Error Rate (BLER) due to the change of the contaminating users data from one transmission to another induced by scrambling.

show abstract

Section: Introductionmentioning

confidence: 99%

Semi-blind channel estimation based on Modified CMA and unitary scrambling for massive MIMO systems

Sellami

Siala²

2021

Preprint

View full text Add to dashboard Cite

show abstract

Mixing Matrix Estimation Algorithm for Time-Varying Radar Signals in a Dynamic System Under UBSS Model

Bai

Zhou

et al. 2021

Circuits Syst Signal Process

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Semi-blind channel estimation based on modified CMA and unitary scrambling for massive MIMO systems

Sellami

Siala

2021

Telecommun Syst

View full text Add to dashboard Cite

Pilot contamination is one of the main impairments in multi-cell massive Multiple-Input Multiple-Output (MIMO) systems. In order to improve the channel estimation in this context, we propose to use a semiblind channel estimator based on the constant modulus algorithm (CMA). We consider an enhanced version of the CMA namely the Modi ed CMA (MCMA) which modi es the cost function of the CMA algorithm to the sum of cost functions for real and imaginary parts. Due to pilot contamination, the channel estimator may estimate the channel of a contaminating user instead of that of the user of interest (the user for which the Base Station wants to estimate the channel and then the data). To avoid this, we propose to scramble the users sequences before transmission. We consider different methods to perform unitary scrambling based on rotating the transmitted symbols (one Dimensional (1-D) scrambling) and using unitary matrices (two-Dimensional (2-D) scrambling). At the base station, the received sequence of the user of interest is descrambled leading to a better convergence of the channel estimator. We also consider the case where the Automatic Repeat reQuest (ARQ) protocol is used. In this case, using scrambling leads to a signi cant gain in terms of BLock Error Rate (BLER) due to the change of the contaminating users data from one transmission to another induced by scrambling.

show abstract

Semi-Blind Source Separation based on Multi-Modulus Criterion: Application for Pilot Contamination Mitigation in Massive MIMO Communications Systems

Cited by 5 publications

References 11 publications

Semi-blind channel estimation based on Modified CMA and unitary scrambling for massive MIMO systems

Semi-blind channel estimation based on Modified CMA and unitary scrambling for massive MIMO systems

Mixing Matrix Estimation Algorithm for Time-Varying Radar Signals in a Dynamic System Under UBSS Model

Semi-blind channel estimation based on modified CMA and unitary scrambling for massive MIMO systems

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