alpha -Fair Dynamic Spectrum Management for QRD-Based Precoding With User Encoding Ordering in Downstream G.Fast Transmission

In next-generation digital subscriber line networks such as G.fast, employing discrete multi-tone transmission in high frequencies up to 212 MHz, the crosstalk among lines reaches very high levels. To precompensate the crosstalk in downstream transmission, QRD-based precoding has been proposed as a...

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Bibliographic Details
Published in:IEEE transactions on communications Vol. 67; no. 4; pp. 2939 - 2950
Main Authors: Lanneer, Wouter, Tsiaflakis, Paschalis, Maes, Jochen, Moonen, Marc
Format: Journal Article
Language:English
Published: IEEE 01.04.2019
Subjects:
Crosstalk
DSL
dynamic spectrum management (DSM)
G.fast
nonlinear precoding (NLP)
Optimization
Precoding
Radio spectrum management
Signal to noise ratio
user encoding ordering
ISSN:0090-6778, 1558-0857
Online Access:Get full text
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Summary:In next-generation digital subscriber line networks such as G.fast, employing discrete multi-tone transmission in high frequencies up to 212 MHz, the crosstalk among lines reaches very high levels. To precompensate the crosstalk in downstream transmission, QRD-based precoding has been proposed as a near-optimal dynamic spectrum management (DSM) technique. However, the performance of QRD-based precoding is greatly affected by the user encoding ordering (UEO). Since current multi-tone UEO methods are rather heuristic in the way they approach fairness, we develop, in this paper, a set of novel DSM algorithms for joint power allocation and UEO that enforce a generalized <inline-formula> <tex-math notation="LaTeX"> \alpha </tex-math></inline-formula>-fairness policy. Since finding the globally optimal UEO entails a combinatorial optimization problem with excessive computational complexity, an iterative algorithm is proposed which uses per-tone exhaustive searches (PTESs) and provides near-optimal approximate solutions. To further reduce the computational complexity, two suboptimal methods are suggested to replace the expensive PTESs, leading to two additional <inline-formula> <tex-math notation="LaTeX"> \alpha </tex-math></inline-formula>-fair DSM algorithms that are tractable for large scenarios against little performance loss. Simulations of a G.fast cable binder show that the <inline-formula> <tex-math notation="LaTeX"> \alpha </tex-math></inline-formula>-fair DSM algorithms achieve an efficient trade-off between fairness and performance in contrast to current UEO methods.
ISSN:0090-6778
1558-0857
DOI:10.1109/TCOMM.2018.2890237