You are here

A Novel Heavy Traffic Approach to Stochastic Optimal Control of Mobile Communications

Award Information
Agency: Department of Defense
Branch: Army
Contract: W911NF-04-C-0138
Agency Tracking Number: A032-2145
Amount: $730,000.00
Phase: Phase II
Program: SBIR
Solicitation Topic Code: A03-050
Solicitation Number: 2003.2
Timeline
Solicitation Year: 2003
Award Year: 2004
Award Start Date (Proposal Award Date): 2004-09-27
Award End Date (Contract End Date): 2005-09-26
Small Business Information
15400 Calhoun Place
Rockville, MD 20855
United States
DUNS: 161911532
HUBZone Owned: No
Woman Owned: Yes
Socially and Economically Disadvantaged: No
Principal Investigator
 Chiman Kwan
 Vice President, R & D
 (301) 294-5238
 ckwan@i-a-i.com
Business Contact
 Mark James
Title: Contracts Administrator
Phone: (301) 294-5238
Email: mjames@i-a-i.com
Research Institution
N/A
Abstract

Balancing high throughput with short wait times for queued data requires explicit stochastic process modeling of the channel and queuing behaviors. Such control problems are too complicated for a direct solution. In this proposal, Intelligent Automation, Inc. (IAI) and its subcontractor, Prof. Robert Buche of the North Carolina State University, propose a novel heavy traffic approach to optimal stochastic control of mobile networks. From the heavy traffic analysis, one can arrive at a limit system which can be used to obtain the optimal control policy. Additional advantages of the proposed approach include: First, the controls obtained from the heavy traffic analysis are effective in the practical system. Second, the heavy traffic modeling is general enough to handle a variety of configurations including TDMA, channel estimation, etc. Third, the proposed admission control design is independent of power control. Fourth, the proposed numerical methods are sound and have been theoretically justified by the convergence proofs. Phase I results have shown the feasibility and optimality of the proposed control policies for systems of reduced dimensions. Our Primary Phase II objective is to extend the proposed optimal control policy to system of practical dimensions and to carry out practical demonstrations and hardware prototype development.

* Information listed above is at the time of submission. *

US Flag An Official Website of the United States Government