Reference : Closed-Form Solution for Computationally Efficient Symbol-Level Precoding
Scientific congresses, symposiums and conference proceedings : Unpublished conference
Engineering, computing & technology : Computer science
Computational Sciences
http://hdl.handle.net/10993/37619
Closed-Form Solution for Computationally Efficient Symbol-Level Precoding
English
Krivochiza, Jevgenij mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Merlano Duncan, Juan Carlos mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Andrenacci, Stefano mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Chatzinotas, Symeon mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Ottersten, Björn mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Dec-2018
Yes
No
IEEE Global Communications Conference 2018
from 9-12-2018 to 14-12-2018
Abu Dhabi
UAE
[en] MIMO ; Precoding ; Interference Mitigation
[en] We present a convex optimization based Symbol-Level Precoding (SLP) for sum power minimization and propose the low-latency closed-form algorithm to find a heuristic solution to the optimization problem. The technique exploits constructive interference at the multi-user MIMO systems and minimizes the sum power of the transmitted precoded signal per each symbol slot. As a result, the received signals gain extra Signal-to-Noise Ratio (SNR), which leads to the improved data rate and energy efficiency. We benchmark the low-complexity algorithm for solving the optimization technique against the conventional Fast Non-Negative Least Squares algorithm (NNLS). The demonstrated design of the SLP technique combined with the proposed closed-form algorithm has low computational complexity and fast processing time, which is applicable in low-latency high-throughput satellite communication systems.
Researchers ; Professionals ; Students ; General public
http://hdl.handle.net/10993/37619
FnR ; FNR11481283 > Jevgenij Krivochiza > SigProSat > End-to-end Signal Processing Algorithms for Precoded Satellite Communications > 01/03/2017 > 28/02/2021 > 2016

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