Abstract
This paper presents a unified tensor model for space–frequency spreading-multiplexing (SFSM) multiple-input multiple-output (MIMO) wireless communication systems that combine space- and frequency-domain spreadings, followed by a space–frequency multiplexing. Spreading across space (transmit antennas) and frequency (subcarriers) adds resilience against deep channel fades and provides space and frequency diversities, while orthogonal space–frequency multiplexing enables multi-stream transmission. We adopt a tensor-based formulation for the proposed SFSM MIMO system that incorporates space, frequency, time, and code dimensions by means of the parallel factor model. The developed SFSM tensor model unifies the tensorial formulation of some existing multiple-access/multicarrier MIMO signaling schemes as special cases, while revealing interesting tradeoffs due to combined space, frequency, and time diversities which are of practical relevance for joint symbol-channel-code estimation. The performance of the proposed SFSM MIMO system using either a zero forcing receiver or a semi-blind tensor-based receiver is illustrated by means of computer simulation results under realistic channel and system parameters.
Highlights
Wireless communication systems employing multiple antennas at both ends of the link, commonly known as multiple-input multiple-output (MIMO) systems, are being considered as one of the key technologies to be deployed in current and upcoming wireless communication standards [1]
4 zero forcing (ZF) receiver Assuming that the channel (H), code (C), and spreading (, ) matrices are known at the receiver, we propose a ZF receiver that simultaneously estimates all the R transmitted data streams by means of a joint blockdecoding and an equalization without de-spreading
We have shown that the received signal can be formulated as a trilinear parallel factor (PARAFAC) model, and capitalizing on its uniqueness property we have put in evidence lower bounds on the design parameters for a joint symbolcode-channel recovery
Summary
Wireless communication systems employing multiple antennas at both ends of the link, commonly known as multiple-input multiple-output (MIMO) systems, are being considered as one of the key technologies to be deployed in current and upcoming wireless communication standards [1]. An orthogonal space–frequency multiplexing enables interference-free multistream transmission For this system, we adopt a tensorial formulation of the transmitted and received signals that jointly incorporates space, frequency, time, and code dimensions by means of a PARAFAC tensor model. Time, frequency, and code diversities inherent to the unified SFSM tensor model, we obtain new results providing useful bounds on the required number of transmit and receive antennas, subcarriers, and spreading length for ensuring a unique recovery of users’ symbols, channels, and codes.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
