Martin Wolkerstorfer

Dynamic spectrum management for energy-efficient transmission in DSL

Dynamic spectrum management (DSM) is an important technique for mitigating crosstalk noise in multi-user digital subscriber line (DSL) environments. Until now, most of the proposed algorithms for DSM have been designed solely for the purpose of bitrate maximization. These algorithms assume a fixed maximum total power and neglect the energy consumption in DSL modems. However, since recently there is a strong interest in the DSL field to reduce energy consumption as shown, e.g., by the European Commissions¿ code of conduct on energy consumption of broadband equipment. In contrast to traditional DSM, this paper will show how DSM can be used for minimizing the energy consumption. We will formulate a global optimization problem for energy minimization and discuss several of its peculiarities compared to the current DSM problems. Furthermore, we derive an iterative, dual-based and semi-distributed algorithm for its local solution, which we call energy-efficient spectrum balancing (EESB). The performance of the algorithm is evaluated through simulations, which show similar results to optimal schemes. In addition, EESB achieves substantial energy savings that can be exploited by adapting the transmit powers to users¿ bitrate demand.

Measurement and simulation framework for throughput evaluation of narrowband power line communication links in low-voltage grids

High-data-rate narrowband Power Line Communication (PLC) is a prominent candidate for smart grid communications in the low-voltage grid at low operational costs. However, the power-line channel is fairly harsh in terms of time-variance, frequency selectivity, and observable impulsive and narrowband noise sources. These unpredictable phenomena motivate selective measurement campaigns in addition to common channel modeling. While previously published measurement studies were fairly limited in duration, we report on a measurement setup for capturing power-line channels over weeks and show measurement results highlighting day-dependent channel effects on selected communication links. Furthermore, previous performance simulations are typically based on simplified channel models and limited in terms of the detail level at the physical layer or lack a consideration of higher-layer protocol overhead. We present a novel simulation methodology which is based on detailed physical-layer simulations exploiting measured, time-varying channel data, and incorporates protocol overhead models for transport-layer throughput estimation. Exemplary simulation results include the newest, commercially available narrowband PLC standards in their latest version, that is ITU-T G.9903 (G3) and G.9904 (PRIME), as well as IEEE 1901.2.

Column Generation for Discrete-Rate Multi-User and Multi-Carrier Power Control

We consider a constrained multi-carrier power allocation problem in interference-limited multi-user systems with a finite set of transmission rates. The Lagrange relaxation is a common technique for decomposing such problems into independently solvable per-subcarrier problems. Deviating from this approach our main contribution is the proposal of a novel spectrum management framework based on a Nonlinear Dantzig-Wolfe problem decomposition. It allows for suboptimal initialization and suboptimal power allocation methods with low complexity. While we show that the combinatorial per-subcarrier problems have polynomial complexity in the number of users, we find that such suboptimal methods are indispensable in large systems. Thus we give an overview of various basic dual heuristics and provide simulation results on a set of thousand digital subscriber line (DSL) networks which show the superior performance of our framework compared to previous power control algorithms.

Low-complexity optimal discrete-rate spectrum balancing in digital subscriber lines

Discrete-rate spectrum balancing in interference-limited multi-user and multi-carrier digital subscriber lines (DSL) is a large-scale, non-convex and combinatorial problem. Previously proposed algorithms for its (dual) optimal solution are only applicable for networks with few users, while the suboptimality of less complex bit-loading algorithms has not been adequately studied so far. We deploy constrained optimization techniques as well as problem-specific branch-and-bound and search-space reduction methods, which for the first time give a low-complexity guarantee of optimality in certain multi-user DSL networks of practical size. Simulation results precisely quantify the suboptimality of multi-user bit-loading schemes in a thousand ADSL2 scenarios under measured channel data.

Robust Spectrum Management for DMT-Based Systems

In recent years an increasing effort was made to reduce the energy consumption in digital subscriber line equipment. Dynamic spectrum management (DSM) has been identified as one promising method to achieve energy-efficiency in discrete multitone based systems. An open research question is how to ensure system robustness when applying highly optimized energy-efficient spectrum management. In this paper, we study the problem of uncertainty in crosstalk noise and parameters, the knowledge of which is indispensable for many DSM algorithms. We introduce robust optimization for spectrum balancing as a technique to achieve feasibility of the optimal power-allocation under a deterministic parameter uncertainty model. This can be seen as an extension of current schemes for spectrum balancing. As a special case we consider the simple strategy of scaling the crosstalk parameters to their worst-case values, which corresponds to a specific uncertainty model and entails no changes to current DSM algorithms. Finally, we quantify the benefit in worst-case performance and the price in terms of energy by simulations.

Energy-saving by low-power modes in ADSL2

The large number of broadband users and its forecast growth has recently triggered research on energy-efficiency in digital subscriber lines (DSLs). A promising technique are low-power modes (LPMs) as standardized in asymmetric DSL 2 (ADSL2) which let the DSL connection operate in downstream direction with reduced transmit rate and power. We study the problem of optimizing the LPM rate-level for energy-efficiency. A traffic-independent rate setting is proposed based on an analytical competitive framework. Also, a Markov chain based LPM model is derived which facilitates the fast numerical optimization of the LPM rate-level under realistic traffic models and system constraints. Simulation results under various traffic settings and DSL scenarios demonstrate energy savings by LPMs of around 30-40% of the ADSL2 transceivers power consumption. Furthermore, they provide insights on how to set the LPM rate-levels in practice for energy-efficient DSL operation.

Energy-Efficient DSL Using Vectoring

A multi-user signal coordination scheme known as Vectoring will play a crucial role in next generation digital subscriber lines (DSL). Previous studies have demonstrated that vectoring increases the bitrate of DSL systems due to its ability to mitigate the interference. In this work we show how Vectoring improves the energy-efficiency of DSL over state-of-the-art spectrum balancing methods. In addition we investigate the impact of channel-state information errors and low-complexity implementations on the performance of Vectoring. We find that Vectoring yields large energy savings in terms of line-driver power consumption even under high channel estimation errors.

Sum-rate maximization for multiple users in partial frequency reuse cellular networks

We apply constrained optimization techniques to optimally allocate the bandwidth and power to the users in a cellular network. We investigate partial frequency reuse with multiple users in the full and partial frequency regions for inter-cell interference mitigation. We show that the non-convex sum-rate maximization problem becomes convex under certain simplifying assumptions. Moreover, an efficient algorithm is developed to solve the problem for a fixed bandwidth allocation. The optimal solution assigns all available power to the users. Finally, we prove that even without simplifications the non-convex problems of maximizing the minimum rate among users and minimizing the sum-power are transformable into convex forms.

Sum-rate maximization by bandwidth re-allocation for two users in partial frequency reuse cellular networks

In this paper we apply constrained optimization techniques to optimally allocate bandwidth and transmit power to the users in a cellular network. We utilize partial frequency reuse with one user in the full and one user in the partial frequency reuse regions as inter-cell interference mitigation technique. We show that the non-convex sum-rate maximization problem becomes convex under some simplifying assumptions. Moreover, an efficient algorithm is used to solve the problem for a fixed bandwidth allocation. Our results show that in the optimum, the full amount of power is assigned to the users. We further demonstrate by simulations that re-allocating the outer cell bandwidth to the inner user when no outer user is present, results in a significantly increased sum-rate.

Enabling greener DSL access networks by their stabilization with artificial noise and SNR margin

Low-power modes (LPM) are a standardized means in asymmetric digital subscriber lines (ADSL) 2 for reducing the power consumption at the central office. However, the activation of LPMs is hampered by the operators’ concern for instability introduced by frequent transmit power changes. The injection of artificial noise (AN) has been proposed as a standard-compliant stabilization technique. We develop an analytical solution for setting the AN power spectrum. Based on this solution we jointly optimize the AN power spectrum and the signal-to-noise ratio (SNR) margin. Simulation results show the performance gain in terms of rate and energy compared to heuristic rules for setting the AN power spectrum. We propose and demonstrate three approaches for evaluating the performance of AN-enabled DSL systems, including (a) joint spectrum balancing, AN, and margin optimization, (b) single-user worst-case-stable optimization, and (c) worst-case-stable optimization based on sequential initialization. Simulation results confirm a strong dependency of the performance under AN on the selected SNR margins, and highlight the total AN power consumption as well as the residual energy savings under low-power modes stabilized by AN.