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Resource allocation strategies for multicarrier radio systems

Ing. Marco Moretti
Dipartimento di Ingegneria dell'Informazione: Elettronica, Informatica, Telecomunicazioni, Università di Pisa

16 hours, 4 credits

June 21 - 22, June 28 - 29, 2010

Dipartimento di Ingegneria dell'Informazione: Elettronica, Informatica, Telecomunicazioni, via Caruso, meeting room, ground floor

Abstract

Orthogonal frequency-division multiple access (OFDMA) is the preferred air interface of many current standards (e.g., the IEEE 802.16 WiMAX) and is also a strong candidate for next-generation cellular systems. One of the key issues determining the adoption of OFDMA for future wireless systems is the capacity to dynamically allocate channels and power to reduce power consumption and increase the spectral efficiency.

In particular, co-channel interference (CCI) caused by transmission in neighboring cells represents a major impairment that limits cell throughput. Current wireless networks mitigate CCI by locating co-channel base stations as far apart as possible via frequency reuse planning at the cost of low spectral efficiency. One of the proposals for future systems is to let all cells reuse the same frequency band and manage the interference employing resource allocation strategies specially tailored to combat co-channel interference.

The aim of this series of lessons is to give the basics of resource allocation schemes for multi-carrier radio systems. The lessons will cover most of the existing approaches ranging from standard single-cell allocation strategies to advanced power and subcarrier allocation algorithm for multi-cellular systems. Resource allocation will be presented as a constrained optimization problem and the tools used to solve it will be linear programming, convex optimization and message passing.

Syllabus

Brief introduction to multi-carrier systems.
Introduction to resource allocation as a constrained optimization problem.
Single-cell algorithms: state of the art. Review of the most important allocation strategies.
Multi-cellular algorithms: coordinated approach. Performance bounds and practical schemes.
Multi-cellular algorithms: distributed approach. Practical schemes.