Optimal multi-user spectrum balancing for digital subscriber lines

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 dynamic 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

Green and fast DSL via joint processing of multiple lines and time–frequency packed modulation

In this paper, strategies to enhance the performance, in terms of available data-rate per user, energy efficiency, and spectral efficiency, of current digital subscriber lines (DSL) are proposed. In particular, a system wherein a group of copper wires is jointly processed at both ends of the communication link is considered. For such a scenario, a resource allocation scheme aimed at energy efficiency maximization is proposed, and, moreover, time–frequency packed modulation schemes are investigated for increased spectral efficiency. Results show that a joint processing of even a limited number of wires at both ends of the communication links brings remarkable performance improvements with respect to the case of individual point-to-point DSL connections; moreover, the considered solution does represent a viable means to increase, in the short term, the data-rate of the wired access network, without an intensive (and expensive) deployment of optical links

Dynamic Resource Allocation in Cognitive Radio Networks: A Convex Optimization Perspective

This article provides an overview of the state-of-art results on communication resource allocation over space, time, and frequency for emerging cognitive radio (CR) wireless networks. Focusing on the interference-power/interference-temperature (IT) constraint approach for CRs to protect primary radio transmissions, many new and challenging problems regarding the design of CR systems are formulated, and some of the corresponding solutions are shown to be obtainable by restructuring some classic results known for traditional (non-CR) wireless networks. It is demonstrated that convex optimization plays an essential role in solving these problems, in a both rigorous and efficient way. Promising research directions on interference management for CR and other related multiuser communication systems are discussed.Comment: to appear in IEEE Signal Processing Magazine, special issue on convex optimization for signal processin

FAST Copper for Broadband Access

FAST Copper is a multi-year, U.S. NSF funded project that started in 2004, and is jointly pursued by the research groups of Mung Chiang at Princeton University, John Cioffi at Stanford University, and Alexander Fraser at Fraser Research Lab, and in collaboration with several industrial partners including AT&T. The goal of the FAST Copper Project is to provide ubiquitous, 100 Mbps, fiber/DSL broadband access to everyone in the US with a phone line. This goal will be achieved through two threads of research: dynamic and joint optimization of resources in Frequency, Amplitude, Space, and Time (thus the name 'FAST') to overcome the attenuation and crosstalk bottlenecks, and the integration of communication, networking, computation, modeling, and distributed information management and control for the multi-user twisted pair network

Joint Spectrum Management and Constrained Partial Crosstalk Cancellation in a Multi-User xDSL Environment

Publication in the conference proceedings of EUSIPCO, Florence, Italy, 200