Paschalis Tsiaflakis

Distributed Spectrum Management Algorithms for Multiuser DSL Networks

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.

Spectrum- and Energy-Efficient OFDM Based on Simultaneous Multi-Channel Reconstruction

Time domain synchronous OFDM (TDS-OFDM) has a higher spectrum and energy efficiency than standard cyclic prefix OFDM (CP-OFDM) by replacing the unknown CP with a known pseudorandom noise (PN) sequence. However, due to mutual interference between the PN sequence and the OFDM data block, TDS-OFDM cannot support high-order modulation schemes such as 256QAM in realistic static channels with large delay spread or high-definition television (HDTV) delivery in fast fading channels. To solve these problems, we propose the idea of using multiple inter-block-interference (IBI)-free regions of small size to realize simultaneous multi-channel reconstruction under the framework of structured compressive sensing (SCS). This is enabled by jointly exploiting the sparsity of wireless channels as well as the characteristic that path delays vary much slower than path gains. In this way, the mutually conditional time-domain channel estimation and frequency-domain data demodulation in TDS-OFDM can be decoupled without the use of iterative interference removal. The Cramér-Rao lower bound (CRLB) of the proposed estimation scheme is also derived. Moreover, the guard interval amplitude in TDS-OFDM can be reduced to improve the energy efficiency, which is infeasible for CP-OFDM. Simulation results demonstrate that the proposed SCS-aided TDS-OFDM scheme has a higher spectrum and energy efficiency than CP-OFDM by more than 10% and 20% respectively in typical applications.

A low complexity optimal spectrum balancing algorithm for digital subscriber lines

In modern DSL systems, multi-user crosstalk is a major source of performance degradation. Optimal spectrum balancing (OSB) is a centralized algorithm that mitigates the effect of crosstalk by allocating optimal transmit spectra to all interfering DSL modems. By the use of Lagrange multipliers the algorithm decouples the spectrum management problem into per-tone optimization problems. The remaining issues are then finding the Lagrange multipliers that enforce the constraints and solving the per-tone optimization problems. Finding the optimal Lagrange multipliers can become complex when more than two users are considered. Starting from the single-user case, this paper presents a number of properties, which are then extended to the multi-user case and lead to an efficient search algorithm for the Lagrange multipliers. Simulations show that the number of Lagrange multiplier evaluations is as small as 20-50, independent of the number of users. Secondly, the complexity of the per-tone optimization problems grows exponentially with the number of lines in the binder. For multiple-user scenarios this becomes computationally intractable. This paper presents an efficient branch-and-bound approach for the per-tone optimization problem. Simulations show enormous complexity reductions, especially for a large number of users.

Improved Dual Decomposition Based Optimization for DSL Dynamic Spectrum Management

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 slow convergence 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 improved by one order of magnitude. Furthermore we apply the improved dual decomposition approach to other DSM 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.

An Efficient Search Algorithm for the Lagrange Multipliers of Optimal Spectrum Balancing in Multi-User XDSL Systems

In modern DSL systems, multi-user crosstalk is a major source of performance degradation. Optimal spectrum balancing (OSB) is a centralized algorithm that optimally allocates the available transmit power over frequencies, thereby mitigating the effect of crosstalk. OSB uses Lagrange multipliers to enforce constraints that are coupled over frequencies. However, finding the optimal Lagrange multipliers can become complex when more than two users are considered. This paper presents a number of properties of the Lagrange multipliers which lead to an efficient search algorithm. Simulations show that the required number of Lagrange multiplier evaluations is independent of the number of users and much smaller compared to the number of evaluations of currently known search algorithms

Multiple Access Channel Optimal Spectrum Balancing for Upstream DSL Transmission

Upstream DSL transmission suffers from in-domain crosstalk as well as out-of-domain or alien crosstalk. Here, the use of multi-user receiver signal coordination e.g. generalized decision feedback equalization, can lead to spectacular performance gains. This paper presents a transmission scheme, referred to as MAC-OSB, which focuses on the weighted rate sum capacity by joint receiver signal coordination and transmit spectrum coordination. The proposed scheme incorporates per-user total power constraints, spectral mask constraints and discrete bit or power loading constraints. Furthermore a low-complexity scheme, referred to as MAC-ISB, is presented which performs similar to MAC-OSB. Simulations show large performance gains over existing methods especially for scenarios with significant alien crosstalk

Partial crosstalk cancellation in a multi-user xDSL environment

In modern DSL systems, crosstalk is a major source of performance degradation. Crosstalk cancellation schemes have been proposed to mitigate the effect of crosstalk. However, the complexity of crosstalk cancellation grows with the square of the number of lines in the binder. Fortunately, most of the crosstalk originates from a limited number of lines on a limited number of tones. As a result, a fraction of the complexity of full crosstalk cancellation suffices to cancel most of the crosstalk. The challenge is then to determine which crosstalk to cancel on which tones, given a certain complexity constraint. This paper presents an algorithm based on a dual decomposition to optimally solve this problem. The proposed algorithm naturally incorporates rate constraints and the complexity of the algorithm compares favourably to a known resource allocation algorithm, where a multi-user extension is made to incorporate the rate constraints.

Novel bitloading algorithms for coded G.fast DSL transmission with linear and nonlinear precoding

Precoding is a technique that counteracts the crosstalk in downlink digital subscriber line (DSL) transmission. While linear precoding is adequate in the VDSL2 technology because of the moderate crosstalk environment, this might no longer be the case in the G.fast technology, which uses higher frequencies and therefore is affected by higher crosstalk levels. In this contribution we compare linear and nonlinear precoding for G.fast transmission protected by trellis-coded modulation, and present two bitloading algorithms that are suited for both precoding schemes. We show that for a set of measured broad-band channels, each representing a binder of eight twisted-pair cables, these bitloading algorithms have substantially different complexities but yield a similar information bitrate, which is about 10% higher for nonlinear precoding as compared to linear precoding.

Power optimization in vectored and non-vectored G.fast transmission

We extend studies on power optimization in VDSL2 to G.fast, the technology under definition. In vectored G.fast the power of the signals before precoding needs to be optimized to meet power spectral density and maximum aggregate transmit power constraints per line. We formulate this interplay between vectoring and power optimization, with non-vectored transmission as a particular case. Three power allocation algorithms are devised that allow a tradeoff between optimality and computational complexity. Measured channel data from a European operator up to 106 MHz is considered. Numerical evaluation reveals that low complex heuristics for power optimization yield near optimal solutions both with perfect and imperfect channel state information. Similar conclusions hold for the 212 MHz profile.

DMT MIMO IC Rate Maximization in DSL With Combined Signal and Spectrum Coordination

Theoretical research has demonstrated that the achievable gains in data rate with dynamic spectrum management, i.e., signal coordination or spectrum coordination, are substantial for digital subscriber line (DSL) networks. Work on these two fronts has progressed steadily and, more often than not, independently. In this paper, we combine the two types of coordination for a mixed DSL scenario, in which some of the infrastructure required for full two-sided signal coordination is available, but not all. This scenario, which is referred to as the discrete multitone multiple-input, multiple-output interference channel (DMT MIMO IC), consists of multiple interfering users, each operating a distinct subset of DSL lines as a MIMO system. Coordination is done both on the signal level (with per user MIMO techniques) and on the spectrum level (with multi-user power allocation). We propose two algorithms for the DMT MIMO IC weighted rate maximization problem. In the first algorithm, we profit from recent work showing the close relation between the weighted rate sum maximization problem and the weighted MMSE minimization problem. We show that with a simple extension, we can adapt the previous work to the scenario of interest. In the second algorithm, the signal and spectrum coordination parts are solved separately. For the signal coordination part, we obtain multiple independent single tone MIMO ICs, which allows us to leverage on the previous work on the topic. For the spectrum coordination part, one of the interesting results of our analysis is a generalization of the distributed spectrum balancing (DSB) power allocation formula for the DMT MIMO IC scenario. Simulation results demonstrate that both algorithms obtain significant gains when compared to pure spectrum coordination algorithms.