Real-time dynamic spectrum management for multi-user multi-carrier communication systems

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) under tight real-time constraints. Specifically, a RT-DSM algorithm 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 logarithmicly scaled grid search. The concrete 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.Comment: 14 pages, 9 figures. This work has been submitted to the IEEE for possible publicatio

Spectrum optimization in multi-user multi-carrier systems with iterative convex and nonconvex approximation methods

Several practical multi-user multi-carrier communication systems are characterized by a multi-carrier interference channel system model where the interference is treated as noise. For these systems, spectrum optimization is a promising means to mitigate interference. This however corresponds to a challenging nonconvex optimization problem. Existing iterative convex approximation (ICA) methods consist in solving a series of improving convex approximations and are typically implemented in a per-user iterative approach. However they do not take this typical iterative implementation into account in their design. This paper proposes a novel class of iterative approximation methods that focuses explicitly on the per-user iterative implementation, which allows to relax the problem significantly, dropping joint convexity and even convexity requirements for the approximations. A systematic design framework is proposed to construct instances of this novel class, where several new iterative approximation methods are developed with improved per-user convex and nonconvex approximations that are both tighter and simpler to solve (in closed-form). As a result, these novel methods display a much faster convergence speed and require a significantly lower computational cost. Furthermore, a majority of the proposed methods can tackle the issue of getting stuck in bad locally optimal solutions, and hence improve solution quality compared to existing ICA methods.Comment: 33 pages, 7 figures. This work has been submitted for possible publicatio

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

Swarm-based Intelligent Routing (SIR) - a new approach for efficient routing in content centric delay tolerant networks

This paper introduces Swarm-based Intelligent Routing (SIR), a swarm intelligence based approach used for routing content in content centric Pocket Switched Networks. We first formalize the notion of optimal path in DTN, then introduce a swarm intelligence based routing protocol adapted to content centric DTN that use a publish/subscribe communication paradigm. The protocol works in a fully decentralized way in which nodes do not have any knowledge about the global topology. Nodes, via opportunistic contacts, update utility functions which synthesizes their spatio-temporal proximity from the content subscribers. This individual behavior applied by each node leads to the collective formation of gradient fields between content subscribers and content providers. Therefore, content routing simply sums up to follow the steepest slope along these gradient fields to reach subscribers who are located at the minima of the field. Via real traces analysis and simulation, we demonstrate the existence and relevance of such gradient field and show routing performance improvements when compared to classical routing protocols previously defined for information routing in DTN

Autonomous Spectrum Balancing for Digital Subscriber Lines

The main performance bottleneck of modern Digital Subscriber Line (DSL) networks is the crosstalk among different lines (users). By deploying Dynamic Spectrum Management (DSM) techniques and reducing excess crosstalks 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), for both synchronous and asynchronous transmission cases. In the synchronous case, the transmissions over different tones are orthogonal to each other. In the asynchronous case, the transmissions on different tones are coupled together due to intercarrier- interference. In both cases, ASB utilizes the concept of a 'reference line', which mimics a typical victim line in the interference channel. The basic procedure in ASB algorithms is simple: each user optimizes the weighted sum of the achievable rates on its own line and the reference line while assuming the interferences from other users as noise. Users then iterate until the target rate constraints are met. Good choices of reference line parameters are already available in industry standards, and the ASB algorithm makes the intuitions completely rigorous and theoretically sound. ASB is the first set of algorithms that is fully autonomous, has low complexity, and yet achieves near-optimal performance. It effectively solves the nonconvex and coupled optimization problem of DSL spectrum management, and overcomes the bottleneck of all previous DSM algorithms