Dynamic Spectrum Management Algorithm Research Articles

Dynamic Spectrum Management in DSL With Asynchronous Crosstalk

In this paper we focus on discrete multitone (DMT) dynamic spectrum management (DSM) in digital subscriber lines (DSL) networks with asynchronous crosstalk. DSM aims to optimally allocate per-user transmit spectra so that the effect of multi-user crosstalk is minimized and the capabilities of the network maximized. Most DSM solutions so far address an idealized situation, one in which all users DMT blocks in the network are perfectly synchronized and crosstalk is dealt with on a per-tone basis. We focus on the case in which the DMT blocks of the various users are offset amongst each other, which leads to inter-carrier interference (ICI). ICI significantly impacts the performance of the system and complicates the DSM optimization problem considerably, as the per-tone decoupling used for the synchronous case is no longer directly applicable. Our contribution is twofold: First, we derive a new and accurate model for the effect of the ICI; Second, we provide a novel DMT DSM algorithm that outperforms the existing state-of-the-art.

$\alpha$ -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 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 $ \alpha $ -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 $ \alpha $ -fair DSM algorithms that are tractable for large scenarios against little performance loss. Simulations of a G.fast cable binder show that the $ \alpha $ -fair DSM algorithms achieve an efficient trade-off between fairness and performance in contrast to current UEO methods.

Crosstalk-aware dynamic spectrum management algorithm for green DSL systems

Dynamic spectrum management (DSM) techniques mitigate crosstalk in digital subscriber line (DSL) networks by adapting the transmit spectra to the actual noise and channel conditions. Conventional DSM schemes are designed based on single-objective optimization, either belonging to the rate-adaptive or margin-adaptive category. In this paper, an efficient crosstalk-aware DSM (CA-DSM) algorithm which jointly considers both the data rate and power is proposed to search for the best rate-power tradeoff solution based on the network conditions. The crosstalk-aware power strategy prevents transmitters which contribute excessive crosstalk from being allocated high power, thereby reducing the aggregate crosstalk noise in the system. A convex cost function is used to formulate the DSM optimization problem wherein two coefficients are introduced to make the CA-DSM algorithm adaptive to different network conditions. An iterative power update strategy is proposed for the CA-DSM algorithm to minimize the cost function. Convergence properties of the CA-DSM algorithm along with existence and uniqueness of optimal power solutions are examined analytically and illustrated graphically. Simulation results show that the proposed CA-DSM algorithm can provide a significantly better rate-power tradeoff performance compared to existing spectrum management schemes.

Dynamic Spectrum Management in Digital Subscriber Line Networks With Unequal Error Protection Requirements

Digital subscriber line (DSL) technology remains the most popular broadband access technology. A variety of algorithms has been developed to improve performance in DSL networks, which are commonly referred to as dynamic spectrum management (DSM) algorithms. The main goal of these algorithms is to fight crosstalk between different lines in a cable bundle. Current DSM algorithms provide an equal level of error protection for each serviced application and each user. However, different applications may have unequal error protection (UEP) requirements. The equal level of error protection usually provided by DSM algorithms may then be excessive for some applications, which leads to a waste of valuable resources. This paper, therefore, considers DSM for DSL networks providing UEP. Four joint signal and spectrum coordination algorithms are presented, enabling a different level of error protection for different applications. These algorithms are modified versions of existing optimal spectrum balancing and distributed spectrum balancing algorithms for joint signal and spectrum coordination in upstream as well as downstream DSL. In addition, an algorithm is presented which, for each application, selects a suitable modulation and coding (MC) scheme from a set of admissible MC schemes. Through simulations, it is shown that DSM with UEP can indeed lead to moderate performance gains.

A dynamic spectrum management algorithm in VDSL systems

A modified iterative water-filling algorithm is proposed in which power from only those subcarriers of the near end user are reduced, which has the worst effect on bit rates of far end users. The power back off from these subcarriers is done by reducing power spectral masks at respective subcarriers. The results after simulating the proposed algorithm give significant performance advantages in terms of data rate over the traditional iterative water-filling algorithm. These results approach the performance of highly complex optimal spectrum management algorithms while maintaining the complexity of the traditional iterative water-filling algorithm.

A low complexity based spectrum management algorithm for ‘Near–Far’ problem in VDSL environment

In digital subscriber line (DSL) system, crosstalk created by electromagnetic interference among twisted pairs degrades the system performance. Very high bit rate DSL (VDSL), utilizes higher bandwidth of copper cable for data transmission. During upstream transmission, a ‘Near–Far’ problem occurs in VDSL system. In this problem the far end crosstalk (FEXT) is produced from near end user degrades the data rate achieved at the far end user. The effect of FEXT can be reduced by properly managing power spectral densities (PSD) of transmitters of near and far users. This kind of power allocation is called dynamic spectrum management (DSM). In this paper, a new distributed DSM algorithm is proposed in which power from only those sub channels of near end user are reduced which create interference to far end user. This power back off strategy takes place with the help of power spectral density (PSD) masks at interference creating sub channels of near end user. The simulation results of the proposed algorithm show an improvement in terms of data rate and approaches near to that of optimal spectrum balancing (OSB) algorithm.

A Modified Low Complexity Based Distributed Iterative Water-Filling (IWF) Spectrum Management Algorithm

In digital subscriber line (DSL) system, crosstalk created by electromagnetic interference among twisted pairs degrades the system performance. Very high bit rate DSL (VDSL), utilizes higher bandwidth of copper cable for data transmission. In upstream data transmission, a `Near---Far' problem occurs in VDSL system. In this problem the far end crosstalk is produced from near end user degrades the data rate achieved at the far end user. Several dynamic spectrum management (DSM) algorithms were proposed in literature to remove this problem. In this paper, a new distributed DSM algorithm is proposed in which power from only those subcarriers of near end user are reduced which create interference to far end user. This power back off strategy takes place with the help of power spectral density masks at those interference creating subcarriers of near end user. The results after simulating the low complex proposed algorithm show an improvement in terms of data rate and approaches near the rate of highly complex optimal spectrum balancing algorithm.

Real-Time Dynamic Spectrum Management for Multi-User Multi-Carrier Communication Systems} \newcommandargmaxoperatornamewithlimits{argmax

Dynamic spectrum management is recognized as a key technique to tackle interference in multi-user multi-carrier communication systems and networks. However existing dynamic spectrum management algorithms may not be suitable when the available computation time and compute power are limited, i.e., when a very fast responsiveness is required. In this paper, we present a new paradigm, theory and algorithm for real-time dynamic spectrum management (RT-DSM). Specifically, a RT-DSM algorithm is real-time in the sense that it can be stopped at any point in time while guaranteeing a feasible and improved solution. This is enabled by the introduction of a novel difference-of-variables (DoV) transformation and problem reformulation, for which a primal coordinate ascent approach is proposed with exact line search via a logarithmically-scaled grid search. The proposed algorithm is referred to as iterative power difference balancing (IPDB). Simulations for different realistic wireline and wireless interference-limited systems demonstrate its good performance, low complexity and wide applicability under different configurations.

Dynamic Spectrum Management (DSM) Algorithms for Multi-User xDSL

Dynamic Spectrum Management (DSM) is an effective method for reducing the effect of crosstalk in Digital Subscriber Line (DSL) systems. This paper discusses various DSM algorithms, including Optimal Spectrum Balancing (OSB), Iterative Spectrum Balancing (ISB), Autonomous Spectrum Balancing (ASB), Iterative Water-Filling (IWF), Selective Iterative Water-filling (SIW), Successive Convex Approximation for Low complExity (SCALE), the Difference of Convex functions Algorithm (DCA), and Distributed Spectrum Balancing (DSB). They are compared in terms of performance (achievable data rate) and computational complexity.

Rate-Pricing Spectrum Management Algorithm for Green VDSL

Dynamic Spectrum Management (DSM) in terms of reducing the power consumption has been utilized to lower the system energy consumption. A largely distributed energy-efficient DSM algorithm based on rate-pricing is proposed in this paper. In this approach, each user adds the predetermined rate-pricing factors to its target data rate constraints, and then, with the rate-pricing factors given, autonomously determines its PSD using modified EE-LC (Energy Efficient Levin-Campello) bit-loading algorithm to minimize its total power under the fixed priced-rate and total power constraints. With the updating of each user's PSD, users successively apply the bit-loading process until the set of the target rates is achieved. Simulation results in a practical VDSL environment show that the proposed algorithm achieves nearly the same level of energy efficiency as that of the near-optimal method.

Investigation of Upstream Near-Far Problem in VDSL Systems via Complete Adaptive Iterative Water Filling Algorithm

Crosstalk is the main degrading factor in Digital Subscriber Line (DSL) systems which are the result of electromagnetic coupling between two adjacent twisted pairs in a cable. Very-high bit-rate Digital Subscriber Line (VDSL) systems which use higher frequencies for data transmission than the other DSL systems, this effect is more considerable in Bit Error Rate (BER) degradation. This paper considers a complete adaptive iterative water-filling (IWF) algorithm for Resolving Upstream Near-Far Problem in VDSL Systems. The new distributed dynamic spectrum management algorithm is proposed, which improve achievable bit rate of iterative water-filling algorithm. The paper proffers a new power back-off strategy of the spectral mask at the near-end users, in order to protect the far-end users. Simulation of the proposed algorithm indicates that the bit rate is increased considerably rather the IWF and adaptive water-filling (AIWF) algorithms by keeping their low complexity. Furthermore, by adding the number of users in network, the new algorithm achieves performance gains over the AIWF, completely adaptive.

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.

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, almost all 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, 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, 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 multi-user DSL scenarios.

An optimal spectrum‐balancing algorithm for digital subscriber lines based on particle swarm optimization

AbstractThis paper presents a new algorithm for optimal spectrum balancing in modern digital subscriber line (DSL) systems using particle swarm optimization (PSO). In DSL, crosstalk is one of the major performance bottlenecks, therefore various dynamic spectrum management algorithms have been proposed to reduce excess crosstalks among users by dynamically optimizing transmission power spectra. In fact, the objective function in the spectrum optimization problem is always nonconcave. PSO is a new evolution algorithm based on the movement and intelligence of swarms looking for the most fertile feeding location, which can solve discontinuous, nonconvex and nonlinear problems efficiently. The proposed algorithm optimizes the weighted rate sum. These weights allow the system operator to place differing qualities of service or importance levels on each user, which makes it possible for the system to avoid the selfish‐optimum. We can show that the proposed algorithm converges to the global optimal solutions. Simulation results demonstrate that our algorithm can guarantee fast convergence within a few iterations and solve the nonconvex optimization problems efficiently. Copyright © 2008 John Wiley & Sons, Ltd.

Distributed Dynamic Spectrum Management for Digital Subscriber Lines

This paper investigates the dynamic spectrum management problem for digital subscriber lines. Two new distributed dynamic spectrum management algorithms, which improve upon the existing iterative water-filling algorithm, are proposed. Unlike the iterative water-filling algorithm, in which crosstalk interference is reduced by using adaptive power backoff, the new algorithms employ full power and mitigate crosstalk interference by shifting one user's spectrum away from the other's. Simulation results show that the new algorithms achieve significant performance gains over the iterative water-filling algorithm in mixed central office/remote terminal (CO/RT) deployment asymmetric digital subscriber line (ADSL) and upstream very-high bit-rate digital subscriber line (VDSL).

The Normalized-Rate Iterative Algorithm: A Practical Dynamic Spectrum Management Method for DSL

We present a practical solution for dynamic spectrum management (DSM) in digital subscriber line systems: the normalized-rate iterative algorithm (NRIA). Supported by a novel optimization problem formulation, the NRIA is the only DSM algorithm that jointly addresses spectrum balancing for frequency division duplexing systems and power allocation for the users sharing a common cable bundle. With a focus on being implementable rather than obtaining the highest possible theoretical performance, the NRIA is designed to efficiently solve the DSM optimization problem with the operators' business models in mind. This is achieved with the help of two types of parameters: the desired network asymmetry and the desired user priorities. The NRIA is a centralized DSM algorithm based on the iterative water-filling algorithm (IWFA) for finding efficient power allocations, but extends the IWFA by finding the achievable bitrates and by optimizing the bandplan. It is compared with three other DSM proposals: the IWFA, the optimal spectrum balancing algorithm (OSBA), and the bidirectional IWFA (bi-IWFA). We show that the NRIA achieves better bitrate performance than the IWFA and the bi-IWFA. It can even achieve performance almost as good as the OSBA, but with dramatically lower requirements on complexity. Additionally, the NRIA can achieve bitrate combinations that cannot be supported by any other DSM algorithm.

ADSL Transceivers Applying DSM and Their Nonstationary Noise Robustness

Dynamic spectrum management (DSM) comprises a new set of techniques for multiuser power allocation and/or detection in digital subscriber line (DSL) networks. At the Alcatel Research and Innovation Labs, we have recently developed a DSM test bed, which allows the performance of DSM algorithms to be evaluated in practice. With this test bed, we have evaluated the performance of a DSM level-1 algorithm known as iterative water-filling in an ADSL scenario. This paper describes the results of, on the one hand, the performance gains achieved with iterative water-filling, and, on the other hand, the nonstationary noise robustness of DSM-enabled ADSL modems. It will be shown that DSM trades off nonstationary noise robustness for performance improvements. A new bit swap procedure is then introduced to increase the noise robustness when applying DSM.