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Low-Complexity OFDM Spectral Precoding
KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems Engineering. Ericsson AB.ORCID iD: 0000-0002-5334-4734
KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control. Ericsson AB.ORCID iD: 0000-0002-2289-3159
KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.ORCID iD: 0000-0002-3599-5584
Ericsson AB.
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2019 (English)In: 20th IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC) 2019, 2019Conference paper, Poster (with or without abstract) (Refereed)
Abstract [en]

This paper proposes a new large-scale mask compliant spectral precoder (LS-MSP) for orthogonal frequency division multiplexing systems. In this paper, we first consider a previously proposed mask-compliant spectral precoding scheme that utilizes a generic convex optimization solver which suffers from high computational complexity, notably in large-scale systems. To mitigate the complexity of computing the LS-MSP, we propose a divide-and-conquer approach that breaks the original problem into smaller rank 1 quadratic-constraint problems and each small problem yields closed-form solution. Based on these solutions, we develop three specialized first-order low-complexity algorithms, based on 1) projection on convex sets and 2) the alternating direction method of multipliers. We also develop an algorithm that capitalizes on the closed-form solutions for the rank 1 quadratic constraints, which is referred to as 3) semianalytical spectral precoding. Numerical results show that the proposed LS-MSP techniques outperform previously proposed techniques in terms of the computational burden while complying with the spectrum mask. The results also indicate that 3) typically needs 3 iterations to achieve similar results as 1) and 2) at the expense of a slightly increased computational complexity.

Place, publisher, year, edition, pages
2019.
Keywords [en]
Spectral Precoding, OFDM, 5G, mmWave
National Category
Signal Processing
Research subject
Telecommunication
Identifiers
URN: urn:nbn:se:kth:diva-258067OAI: oai:DiVA.org:kth-258067DiVA, id: diva2:1349745
Conference
SPAWC
Funder
Swedish Foundation for Strategic Research , ID17-0114
Note

QC 20190923

Available from: 2019-09-09 Created: 2019-09-09 Last updated: 2019-09-23Bibliographically approved

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fulltext(1083 kB)9 downloads
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CiteExportLink to record
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Citation style
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