Tensor Decompositions for MIMO Relaying Systems

Tensor modeling in MIMO relaying systemsFigure 9: Tensor modeling in MIMO relaying systems uses tensor coding matrices at the source and the relay nodes.

In cooperative MIMO relaying systems, channel estimation involves estimating channel matrices at the receiver and/or relay. Starting from this setup and its generalizations (multiple relays, three-hop, and multi-hop cases), tensor decompositions have been largely applied to solve the channel estimation and the joint channel-symbol estimation problems for tensor-coded MIMO relaying systems.

These tensor-based approaches leverage the multilinear nature of MIMO relaying channels, providing structured methods for channel estimation that reduce the need for pilot signals while enabling semi-blind decoding techniques.

References

[1] L. R. Ximenes, G. Favier, A. L. F. de Almeida, “Semi-blind receivers for non-regenerative cooperative MIMO communications based on nested PARAFAC modeling,” IEEE Transactions on Signal Processing, vol. 63, pp. 4985-4998, 2015.

[2] L. R. Ximenes, G. Favier, A. L. F. de Almeida, Y. C. B. Silva, “PARAFAC-PARATUCK semi-blind receivers for two-hop cooperative MIMO relay systems,” IEEE Transactions on Signal Processing, vol. 62, no. 14, pp. 3604-3615, 2014.

[3] B. Sokal, A. L. F. de Almeida, M. Haardt, “Semi-blind receivers for MIMO multi-relaying systems via rank-one tensor approximations,” Signal Processing, vol. 166, 107254, 2019.

[4] W. C. Freitas Jr., G. Favier, A. L. F. de Almeida, “Sequential closed-form semi-blind receiver for space-time coded multi-hop relaying systems,” IEEE Signal Processing Letters, vol. 24, no. 12, p. 1773-1777, 2017.