Linear and nonlinear precoding based dynamic spectrum management for downstream vectored G.fast transmission

© 1972-2012 IEEE. In the G.fast digital subscriber line frequency range (up to 106 or 212 MHz), where crosstalk channels may even become larger than direct channels, linear zero-forcing (ZF) precoding is no longer near-optimal for downstream (DS) vectored transmission. To improve performance, we develop a novel low-complexity algorithm for both linear and nonlinear precoding-based dynamic spectrum management that maximizes the weighted sum-rate under realistic per-line total power and per-tone spectral mask constraints. It applies to DS scenarios with a single copper line at each customer site [i.e., broadcast channel (BC) scenarios], as well as to DS scenarios with multiple copper lines at some or all customer sites (i.e., the so-called multiple-input-multiple-output-BC scenarios). The algorithm alternates between precoder and equalizer optimization, where the former relies on a Lagrange multiplier based transformation of the DS dual decomposition approach formulation into its dual upstream (US) formulation, together with a low-complexity iterative fixed-point formula to solve the resulting US problem. Simulations with measured G.fast channel data of a very high crosstalk cable binder are provided revealing a significantly improved performance of this algorithm over ZF techniques for various scenarios, and in addition, a faster convergence rate compared with the state-of-the-art WMMSE algorithm.status: publishe

Joint alpha-fairness based DSM and user encoding ordering for zero-forcing nonlinear precoding in G.Fast downstream transmission (poster)

© 2017 IEEE. In the G.fast frequency range with strong levels of crosstalk, nonlinear precoding (NLP) is proposed as a near-optimal technique for crosstalk precompensation in downstream transmission. While existing methods for multi-tone NLP user encoding ordering (UEO) are rather heuristic in how they approach fairness and suffer from substantial suboptimality, we develop a novel algorithm for joint dynamic spectrum management (DSM) and UEO that enforces a generalized alpha-fairness policy. Since finding the optimal UEO is a combinatorial optimization problem with excessive computational complexity, the proposed algorithm uses a low-complexity iterative method which provides near-optimal approximate solutions. Simulations demonstrate that the novel algorithm achieves a trade-off between fairness and performance that outperforms current UEO methods.status: publishe

Linear and nonlinear precoding based dynamic spectrum management for downstream vectored G.fast transmission

© 2015 IEEE. In the G.fast frequency range (up to 212 MHz), the diagonal dominance structure of the channel matrix is no longer valid at the higher frequencies. As a result, the linear Zero Forcing (ZF) precoder in combination with dynamic spectrum management (DSM) is no longer near-optimal for downstream vectored G.fast transmission. To boost performance, we develop a novel low-complexity algorithm for both linear and non-linear precoding based DSM that maximizes the weighted line sum-rate under realistic per-line total power and per-tone spectral mask constraints. The algorithm relies on a Lagrange multiplier based transformation of the downstream dual decomposition approach formulation into its dual upstream formulation, together with a low-complexity iterative fixed-point formula to solve the resulting upstream problems. Simulations with measured G.fast channel data up to both 106 and 212 MHz are provided revealing a significantly increased performance of this algorithm over linear ZF precoding.status: publishe

Physical-Layer Multicasting Design for Downstream G.fast DSL Transmission

status: publishe

Low-Complexity Nonlinear Zero-Forcing Precoding Under Per-Line Power Constraints for Improved Downstream G.fast Active-User Peak-Rates

© 1972-2012 IEEE. We consider nonlinear zero-forcing (ZF) precoding design to improve the downstream G.fast peak-rates when only a few users in the cable binder are active. In order to compute the optimal nonlinear ZF precoder under per-line power constraints (PLPCs), we present a novel low-complexity dual decomposition algorithm, in which the key is the use of Lagrange multiplier based virtual precoders to transform the PLPCs into an easier virtual sum-power constraint (SPC), such that the SPC-optimality of the QR decomposition-based precoder may be exploited. We show a reduced computational complexity of this algorithm over the state-of-the-art SVD-block-diagonalization-based dual decomposition algorithm. We present simulations of a 10-line cable binder that demonstrate substantial peak-rate gains over standard QR decomposition-based ZF precoding in DSL, due to the increasingly stronger crosstalk channels in the G.fast frequency range (up to 212 MHz). Furthermore, we show that the proposed algorithm naturally extends to the scenario with multiple lines terminating at the customer premise equipments.status: publishe

Vectoring-Based Dynamic Spectrum Management for G.fast Multi-User Full-Duplex Transmission

© 2017 IEEE. Full-duplex (FDX) transmission is a promising technique emerging in DSL networks that theoretically may double the spectral efficiency by simultaneously transmitting in the downstream (DS) and upstream (US) on the same frequency band. Unfortunately, this may lead to severe near-end crosstalk (NEXT) interference in addition to the usual far-end crosstalk (FEXT) among the lines within a cable binder. To limit the NEXT impact by balancing the user transmit powers, tailored vectoring-based dynamic spectrum management (DSM) techniques are vital. In this paper, we develop a DSM algorithm for the specific case of perfect NEXT cancellation at the access node. This assumption in combination with US-DS duality theory allows to reformulate the DS-US structure of the non-convex weighted sum-rate maximization problem into an easier US-US structure, which can be solved with low-complexity iterative fixed-point power updates. Simulations of G.fast multi-user FDX transmission demonstrate significant improvements over time division duplex transmission.status: publishe

Optimal Dynamic Spectrum Management Algorithms for Multi-User Full-Duplex DSL Networks

status: publishe