Dynamic spectrum management of digital subscriber lines (DSLs) has the potential to dramatically increase the capacity of the aging last-mile copper access network. This paper takes an important step toward fulfilling this potential through power spectrum balancing. We derive a novel algorithm called SCALE, that provides a significant performance improvement over the existing iterative water-filling (IWF) algorithm in multiuser DSL networks, doing so with comparable low complexity. The algorithm is easily distributed through measurement and limited message passing with the use of a spectrum management center. We outline how overhead can be managed, and show that in the limit of zero message-passing, performance reduces to IWF.

Band preference (BP) attempts to improve the performance of iterative water-filling (IWF) when applied to the multiuser interference channel. With important applications relating to digital subscriber line (DSL) access networks such as those based on current-day ADSL2 and VDSL standards, we develop novel techniques for determining suitable band levels that lead to significant performance gains in those circumstances where IWF would otherwise perform far from the optimum. Our techniques are based on a novel optimization framework that avoids inherent difficulties in analysis that have, until now, obscured an elegant design path. Our developments are easily customized to any clustering band-pattern, particularizing to the spectrum balancing result in the special-case of unit band-sizes. A practically palatable implementation is induced by a two-level primal decomposition whereby a master problem is responsible for band management, based on the result from independent slaves each undertaking a relaxed water-filling (WF) operation. Numerical results show that 2-3 bands are sufficient for a downstream near-far scenario comprising two user-groups.

Cross-layer design can significantly improve the performance of mobile ad-hoc networks (MANETs), as indicated by the flurry of recent results in the literature. Much of this work stems from the Kelly network utility maximization (NUM) framework, where convexity is crucial for developing algorithms that reach the global optimum. Unfortunately many problems are nonconvex in nature, so convex approximations are abundant. In this paper, we consider the joint optimization of source data-rates and link transmitter powers in a MANET, specifically dealing with the statistical variations of the wireless channel. In this paradigm we show that the commonly applied high-SIR convex approximation is unrealistic, so we seek to find solutions of the unmodified NUM problem. Our first result shows that the canonical formulation (previously thought to be nonconvex) is indeed a convex problem for logarithmic TCP-Vegas utilities; we then derive an algorithm reaching the global optimum. Our main result caters for the general case of strictly concave utilities, where we derive an algorithm that provably converges to the global solution of the underlying nonconvex NUM problem.

Dynamic Spectrum Management of Digital Subscriber Lines (DSL) has the potential to dramatically increase the capacity of the aging last-mile copper access network. This paper takes an important step toward fulfilling this potential through power spectrum balancing. We derive a novel algorithm called SCALE, that provides a significant performance improvement over the existing iterative water-filling (IWF) algorithm in multi-user DSL networks, doing so with comparable low complexity. The algorithm is easily distributed through measurement and limited message-passing with the use of a Spectrum Management Center. We outline how overhead can be managed, and show that in the limit of zero message-passing, performance reduces to IWF. Numerical convergence of SCALE was found to be extremely fast when applied to VDSL, with performance exceeding that of iterative water-filling in just a few iterations, and to over 90% of the final rate in under 5 iterations. Lastly, we return to the problem of iterative water-filling and derive a new algorithm named SCAWF that is shown to be a very simple way to waterfill, particularly suited to the multi-user context.

In the present paper, we consider the problem of joint bandwidth (subcarriers) and power allocation for the downlink of a multi-user multi-cell OFDM cellular network. This resource allocation problem is formulated as a power minimization problem, subject to meeting the target rates of all users in the network. We develop a distributed solution to find the globally optimal allocation which determines the subcarrier and power allocation dynamically. In addition, we investigate the impact of reducing the complexity by reducing the number of degrees of freedom available in the optimization. In particular, we consider a static bandwidth allocation scheme, and a static power allocation scheme. The numerical results show that the penalty on network performance due to the reduction in the available degrees of freedom is not significant.

We address the problem of achieving outage probability constraints on the uplink of a code-division multiple-access (CDMA) system employing power control and linear multiuser detection, where we aim to minimize the total expended power. We propose a generalized framework for solving such problems under modest assumptions on the underlying channel fading distribution. Unlike previous work, which dealt with a Rayleigh fast-fading model, we allow each user to have a different fading distribution. We show how this problem can be formed as an optimization over user transmit powers and linear receivers, and, where the problem is feasible, we provide conceptually simple iterative algorithms that find the minimum power solution while achieving outage specifications with equality. We further generalize a mapping from outage probability specifications to average signal-to-interference-ratio constraints that was previously applicable only to Rayleigh-faded channels. This mapping allows us to develop suboptimal, computationally efficient algorithms to solve the original problem. Numerical results are provided that validate the iterative schemes, showing the closeness of the optimal and mapped solutions, even under circumstances where the map does not guarantee that constraints will be achieved.

How can we achieve the conflicting goals of reduced transmission power and increased capacity in a wireless network, without attempting to follow the instantaneous state of a fading channel? In this paper, we address this problem by jointly considering power control and multiuser detection (MUD) with outage-probability constraints in a Rayleigh fast-fading environment. The resulting power-control algorithms (PCAs) utilize the statistics of the channel and operate on a much slower timescale than traditional schemes. We propose an optimal iterative solution that is conceptually simple and finds the minimum sum power of all users while meeting their outage targets. Using a derived bound on outage probability, we introduce a mapping from outage to average signal-to-interference ratio (SIR) constraints. This allows us to propose a suboptimal iterative scheme that is a variation of an existing solution to a joint power control and MUD problem involving SIR constraints. We further use a recent result that transforms complex SIR expressions into a compact and decoupled form, to develop a noniterative and computationally inexpensive PCA for large systems of users. Simulation results are presented showing the closeness of the optimal and mapped schemes, speed of convergence, and performance comparisons.

We consider an uplink power control problem with constraints on outage probability, for cellular CDMA systems where allocation decisions are made on a slow time-scale. A generalized framework to solve such problems for a wide range of fading distributions is proposed, including an extension that couples power control with a minimum outage probability multiuser receiver. The resulting algorithms are simple and iterative in nature that yield the optimal minimum sum-power solution. Deriving a general upper bound on outage probability, we map these problems to equivalent, sub-optimal and computationally efficient iterative algorithms. We give numerical results to validate the methods developed for a variety of Nakagami-m fading figures.

This paper proposes a new scheme coupling power control with a minimum outage probability multiuser detector. The resultant iterative algorithm is conceptually simple and finds the minimum sum transmission power of all users with a set of outage probability constraints. Bound on the outage probability expression are found that extend a previous result that did not include receiver noise. These bounds are used to create a suboptimal scheme coupling power control and a MMSE multiuser detector. This new problem becomes a variant of an existing problem where outage probability constraints are first mapped to average SIR threshold constraints. Simulation results are presented showing the closeness of the two schemes and speed of convergence.