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In this paper, we investigate joint level 2 and 3 dynamic spectrum management (joint DSM 2/3) for downstream (DS) DSL. We consider a DS scenario in which users are divided into a few separate groups, where vector encoding based signal coordination can be applied in each group and spectrum coordination is possible for all users. This can be seen as a mixed interference/broadcast channel (IF/BC) scenario. In order to obtain the optimal transmitter structure, we develop a generalized duality between the vector broadcast and multiple-access channel (MAC) for scenarios in which partial signal coordination is available among users. This theory together with optimal spectrum balancing (OSB) is exploited to calculate the jointly optimal filters and transmit powers for non-linear vector dirty paper coding structures (in the form of Tomlinson-Harashima precoder (THP)) in the groups. The proposed scheme is compared to several other joint DSM 2/3 algorithms for DS DSL. Simulation results show that the proposed scheme (referred to as the IF/BC-OSB algorithm) achieves considerably higher bit rates than the other schemes. IF/BC-OSB encompasses the earlier developed BC-OSB algorithm as a special case. A simplified version of IF/BC-OSB avoiding exhaustive search with near-optimal performance is also proposed. [ABSTRACT FROM PUBLISHER]

Dynamic spectrum management (DSM) has been recognized as a key technology to significantly improve the performance of digital subscriber line (DSL) broadband access networks. The basic concept of DSM is to coordinate transmission over multiple DSL lines so as to mitigate the impact of crosstalk interference amongst them. Many algorithms have been proposed to tackle the nonconvex optimization problems appearing in DSM, many of them relying on a standard subgradient based dual decomposition approach. In practice however, this approach is often found to lead to extremely slowconvergence or even no convergence at all, one of the reasons being the very difficult tuning of the stepsize parameters. In this paper we propose a novel improved dual decomposition approach inspired by recent advances in mathematical programming. It uses a smoothing technique for the Lagrangian combined with an optimal gradient based scheme for updating the Lagrange multipliers. The stepsize parameters are furthermore selected optimally removing the need for a tuning strategy. With this approach we show how the convergence of current state-of-the-art DSM algorithms based on iterative convex approximations (SCALE and CA-DSB)can be improvedby one order of magnitude. Furthermore we apply the improved dual decomposition approach to otherDSM algorithms (OSB, ISB, ASB, (MS)-DSB, and MIW) and propose further improvements to obtain fast and robust DSM algorithms. Finally, we demonstrate the effectiveness of the improved dual decomposition approach for a number of realistic multiuser DSL scenarios. [ABSTRACT FROM AUTHOR]

Modern digital subscriber line (DSL) networks suffer from crosstalk among different lines in the same cable bundle. This crosstalk can lead to a major performance degradation. By balancing the transmit power spectra, the impact of crosstalk can be minimized leading to spectacular performance gains. This is referred to as spectrum management. In this paper, a unifying perspective is presented on distributed spectrum management algorithms based on the Karush-Kuhn-Tucker (KKT) conditions. Furthermore, novel distributed algorithms are presented within the same KKT framework. The proposed distributed algorithms consist of local water-filling-like algorithms running in the individual modems, controlled by the spectrum management center. Extensive simulation results show that the proposed algorithms perform very well for several multi-user ADSL and VDSL scenarios. [ABSTRACT FROM AUTHOR]

The main performance bottleneck of modern digital subscriber line (DSL) networks is the crosstalk among different lines (i.e., users). By deploying dynamic spectrum management (DSM) techniques and reducing excess crosstalk among users, a network operator can dramatically increase the data rates and service reach of broadband access. However, current DSM algorithms suffer from either substantial suboptimality in typical deployment scenarios or prohibitively high complexity due to centralized computation. This paper develops, analyzes, and simulates a new suite of DSM algorithms for DSL interference-channel models called autonomous spectrum balancing (ASB). The ASB algorithms utilize the concept of a ‘reference line,’ which mimics a typical victim line in the interference channel. In ASB, each modem tries to minimize the harm it causes to the reference line under the constraint of achieving its own target data-rate. Since the reference line is based on the statistics of the entire network, rather than any specific knowledge of the binder a modem operates in, ASB can be implemented autonomously without the need for a centralized spectrum management center. ASB has a low complexity and simulations using a realistic simulator show that it achieves large performance gains over existing autonomous algorithms, coming close to the optimal rate region in some typical scenarios. Sufficient conditions for convergence of ASB are also proved. [ABSTRACT FROM AUTHOR]

Crosstalk is a major issue in modern digital subscriber line (DSL) systems such as ADSL and VDSL. Static spectrum management, which is the traditional way of ensuring spectral compatibility, employs spectral masks that can be overly conservative and lead to poor performance. This paper presents a centralized algorithm for optimal spectrum balancing in DSL. The algorithm uses the dual decomposition method to optimize spectra in an efficient and computationally tractable way. The algorithm shows significant performance gains over existing dynamis spectrum management (DSM) techniques, e.g., in one of the cases studied, the proposed centralized algorithm leads to a factor-of-four increase in data rate over the distributed DSM algorithm iterative waterfilling. [ABSTRACT FROM AUTHOR]