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

Utility greedy discrete bit loading for interference limited multi-cell OFDM system

In this contribution we present the solution of the utility greedy discrete bit loading for interference limited multicell OFDM networks. Setting the utility as the sum of consumed power proportions, the algorithm follows greedy way to achieve the maximum throughput of the system. Simulation has shown that the proposed algorithm has better performance and lower complexity than the traditional optimal algorithm. The discussion of the results is provided

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

On the SCALE Algorithm for Multiuser Multicarrier Power Spectrum Management

This paper studies the successive convex approximation for low complexity (SCALE) algorithm, which was proposed to address the weighted sum rate (WSR) maximized dynamic power spectrum management (DSM) problem for multiuser multicarrier systems. To this end, we first revisit the algorithm, and then present geometric interpretation and properties of the algorithm. A geometric programming (GP) implementation approach is proposed and compared with the low-complexity approach proposed previously. In particular, an analytical method is proposed to set up the default lower-bound constraints added by a GP solver. Finally, numerical experiments are used to illustrate the analysis and compare the two implementation approaches.Comment: 8 pages, 5 figures; IEEE Transactions on Signal Processing, vol. 60, no. 9, Sep. 201

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

Iterative Spectrum Balancing for Digital Subscriber Lines

Dynamic spectrum management (DSM) is an important technique for mitigating crosstalk in DSL. One of the first DSM algorithms proposed, Iterative waterfilling (IW), has a low complexity and demonstrates the spectacular performance gains that are possible. Unfortunately IW tends to be highly suboptimal in mixed CO/RT deployments and upstream VDSL. Another DSM algorithm, Optimal spectrum balancing (OSB), uses a weighted rate-sum to find the theoretically optimal transmit spectra. Unfortunately its complexity scales exponentially with the number of lines in the binder N. Typical binders contain 25-100 lines, for which OSB is intractable. This paper presents a new iterative algorithm for spectrum management in DSL. The algorithm optimizes the weighted rate-sum in an iterative fashion, which leads to a quadratic, rather than exponential, complexity in N. The algorithm is tractable for large N and can be used to optimize entire binders. Simulations show that the algorithm performs very close to the theoretical optimum achieved by OSB