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A Tensor-Based Approach to Joint Channel Estimation/Data Detection in Flexible Multicarrier MIMO Systems

Eleftherios Kofidis

2020IEEE Transactions on Signal Processing19 citationsDOIOpen Access PDF

Abstract

Filter bank-based multicarrier (FBMC) systems have attracted increasing attention recently in view of their many advantages over the classical cyclic prefix (CP)-based orthogonal frequency division multiplexing (CP-OFDM) modulation. However, their more advanced structure (resulting in, for example, self interference) complicates signal processing tasks at the receiver, including synchronization, channel estimation and equalization. In a multiple-input multiple-output (MIMO) configuration, the multi-antenna interference has also to be taken into account. (Semi-) blind receivers, of increasing interest in (massive) MIMO systems, have been little studied so far for FBMC and mainly for the single-antenna case only. The design of such receivers for flexible MIMO FBMC systems, unifying a number of existing FBMC schemes, is considered in this paper through a tensor-based approach, which is shown to encompass existing joint channel estimation and data detection approaches as special cases, adding to their understanding and paving the way to further developments. Simulation-based results are included, for realistic transmission models, demonstrating the estimation and detection performance gains from the adoption of these receivers over their training only-based counterparts.

Topics & Concepts

Cyclic prefixComputer scienceMIMOOrthogonal frequency-division multiplexingElectronic engineeringMIMO-OFDMEqualization (audio)Channel (broadcasting)Synchronization (alternating current)Interference (communication)Filter bankJoint (building)TelecommunicationsEngineeringArchitectural engineeringPAPR reduction in OFDMTensor decomposition and applicationsWireless Communication Networks Research