Wireless Communications

In cellular wireless communication systems, transmitted power is regulated to provide each user an acceptable connection by limiting the interference caused by other users. Several models have been considered including: (1) fixed base station assignment where the assignment of users to base stations is fixed, (2) minimum power assignment where a user is iteratively assigned to the base station at which its signal to interference ratio is highest, and (3) diversity reception where a user's signal is combined from several or perhaps all base stations. For the above models, the uplink power control problem can be reduced to finding a vector p of users' transmitter powers satisfying p/spl ges/I(p) where the jth constraint p/sub j//spl ges/I/sub j/(p) describes the interference that user j must overcome to achieve an acceptable connection. This work unifies results found for these systems by identifying common properties of the interference constraints. It is also shown that systems in which transmitter powers are subject to maximum power limitations share these common properties. These properties permit a general proof of the synchronous and totally asynchronous convergence of the iteration p(t+1)=I(p(t)) to a unique fixed point at which total transmitted power is minimized. >

A framework for uplink power control in cellular radio systems

A systematic understanding of the decomposability structures in network utility maximization is key to both resource allocation and functionality allocation. It helps us obtain the most appropriate distributed algorithm for a given network resource allocation problem, and quantifies the comparison across architectural alternatives of modularized network design. Decomposition theory naturally provides the mathematical language to build an analytic foundation for the design of modularized and distributed control of networks. In this tutorial paper, we first review the basics of convexity, Lagrange duality, distributed subgradient method, Jacobi and Gauss-Seidel iterations, and implication of different time scales of variable updates. Then, we introduce primal, dual, indirect, partial, and hierarchical decompositions, focusing on network utility maximization problem formulations and the meanings of primal and dual decompositions in terms of network architectures. Finally, we present recent examples on: systematic search for alternative decompositions; decoupling techniques for coupled objective functions; and decoupling techniques for coupled constraint sets that are not readily decomposable

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A tutorial on decomposition methods for network utility maximization

A geometric program (GP) is a type of mathematical optimization problem characterized by objective and constraint functions that have a special form. Recently developed solution methods can solve even large-scale GPs extremely efficiently and reliably; at the same time a number of practical problems, particularly in circuit design, have been found to be equivalent to (or well approximated by) GPs. Putting these two together, we get effective solutions for the practical problems. The basic approach in GP modeling is to attempt to express a practical problem, such as an engineering analysis or design problem, in GP format. In the best case, this formulation is exact; when this is not possible, we settle for an approximate formulation. This tutorial paper collects together in one place the basic background material needed to do GP modeling. We start with the basic definitions and facts, and some methods used to transform problems into GP format. We show how to recognize functions and problems compatible with GP, and how to approximate functions or data in a form compatible with GP (when this is possible). We give some simple and representative examples, and also describe some common extensions of GP, along with methods for solving (or approximately solving) them.

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A tutorial on geometric programming

This paper considers the multiuser power control problem in a frequency-selective interference channel. The interference channel is modeled as a noncooperative game, and the existence and uniqueness of a Nash equilibrium are established for a two-player version of the game. An iterative water-filling algorithm is proposed to efficiently reach the Nash equilibrium. The iterative water-filling algorithm can be implemented distributively without the need for centralized control. It implicitly takes into account the loop transfer functions and cross couplings, and it reaches a competitively optimal power allocation by offering an opportunity for loops to negotiate the best use of power and frequency with each other. When applied to the upstream power backoff problem in very-high bit-rate digital subscriber lines and the downstream spectral compatibility problem in asymmetric digital subscriber lines, the new power control algorithm is found to give a significant performance improvement when compared with existing methods.

Distributed multiuser power control for digital subscriber lines

For wireless cellular communication systems, one seeks a simple effective means of power control of signals associated with randomly dispersed users that are reusing a single channel in different cells. By effecting the lowest interference environment, in meeting a required minimum signal-to-interference ratio of rho per user, channel reuse is maximized. Distributed procedures for doing this are of special interest, since the centrally administered alternative requires added infrastructure, latency, and network vulnerability. Successful distributed powering entails guiding the evolution of the transmitted power level of each of the signals, using only focal measurements, so that eventually all users meet the rho requirement. The local per channel power measurements include that of the intended signal as well as the undesired interference from other users (plus receiver noise). For a certain simple distributed type of algorithm, whenever power settings exist for which all users meet the rho requirement, the authors demonstrate exponentially fast convergence to these settings. >

A simple distributed autonomous power control algorithm and its convergence

The excitation system of the hydro unit is a static self-excitation system that uses thyristor rectifiers in a three-phase fully controllable bridge connection with a digital two-channel regulation system characterized by a very fast response (eng. high initial response ratio). The excitation system is powered by an excitation transformer connected to the busbars of the aggregate with a transmission ratio of 14.4/0.42 kV. The aim of this project is to show the characteristics of the old ABB UNITROL 5000 excitation system as well as the improvements obtained by installing the new ABB UNITROL 6000 excitation system of unit 1 at the Trebinje Hydroelectric Power Plant 1. The reconstruction of the excitation system was carried out as part of the regular annual overhaul of the hydroelectric power plant by representatives of the company "Advensys engineering" d.o.o. - Zagreb, through cooperation with the staff of the power plant. The basic scope of the system reconstruction consists of three units and includes the replacement of the control part of the excitation, the replacement of the excitation switch and the replacement of the excitation control panel.

Z. Miljanic

Papers

A simple distributed autonomous power control algorithm and its convergence

Reconstruction of the hydro generator excitation system on hydro power plant Trebinje 1