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Mohammad Javad Azizipour

Mohammad Javad Azizipour

Academic rank: Assistant Professor
ORCID:
Education: PhD.
ScopusId:
Faculty: Faculty of Technology and Engineering
Address: University of Mazandaran
Phone: 01135305111

Research

Title
A burst-form CSI estimation approach for FDD massive MIMO systems
Type
JournalPaper
Keywords
Massive MIMO, Compressed sensing, Channel estimation, Pilot overhead, Burst-form least square
Year
2022
Journal SIGNAL PROCESSING
DOI
Researchers Mohammad Javad Azizipour ، Kamal Mohamed-pour ، A. Lee Swindlehurst

Abstract

Pilot and channel state information (CSI) feedback overhead in the downlink and uplink paths are two major implementation challenges in frequency-division duplex (FDD) based massive MIMO systems. When the massive MIMO channel satisfies the burst-sparsity property, we can acquire the channel with compressed pilots and CSI feedback in a more efficient approach. This paper proposes a burst-form estimation approach, referred to as the burst-form least squares (BFLS) algorithm, to fully utilize the burstsparsity property of massive MIMO channels. The proposed algorithm is based on knowledge of the starting location of each burst at the user side. For situations where the starting locations change quickly or are otherwise initially unknown at the user, a starting point estimation (SPE) algorithm is proposed to provide the position of each burst in the channel vector. Numerical results demonstrate that the BFLS algorithm acquires the channel better than competing approaches and reaches the performance upper bound. It is shown that the SPE algorithm can find the location of bursts with high accuracy and using the estimated values do not significantly degrade the estimation quality.