By Topic

Resource allocation under uncertainty using the maximum entropy principle

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Johansson, M. ; Signals & Syst. Group, Uppsala Univ., Sweden ; Sternad, M.

In this paper, we formulate and solve a problem of resource allocation over a given time horizon with uncertain demands and uncertain capacities of the available resources. In particular, we consider a number of data sources with uncertain bit rates, sharing a set of parallel channels with time-varying and possibly uncertain transmission capacities. We present a method for allocating the channels so as to maximize the expected system throughput. The framework encompasses quality-of-service (QoS) requirements, e.g., minimum-rate constraints, as well as priorities represented by a user-specific cost per transmitted bit. We assume only limited statistical knowledge of the source rates and channel capacities. Optimal solutions are found by using the maximum entropy principle and elementary probability theory. The suggested framework explains how to make use of multiuser diversity in various settings, a field of recently growing interest in communication theory. It admits scheduling over multiple base stations and includes transmission buffers to obtain a method for optimal resource allocation in rather general multiuser communication systems.

Published in:

Information Theory, IEEE Transactions on  (Volume:51 ,  Issue: 12 )