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This article is part of the series Fairness in Radio Resource Management for Wireless Networks.

Open Access Research Article

Cross-Layer Optimal Rate Allocation for Heterogeneous Wireless Multicast

Amr Mohamed1* and Hussein Alnuweiri2

Author Affiliations

1 Department of Computer Engineering, Qatar University, P.O. Box 2317, Doha, Qatar

2 Department of Electrical Engineering, Texas A&M University at Qatar, P.O. Box 23874, Doha, Qatar

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EURASIP Journal on Wireless Communications and Networking 2009, 2009:467182  doi:10.1155/2009/467182

The electronic version of this article is the complete one and can be found online at: http://jwcn.eurasipjournals.com/content/2009/1/467182

Received:30 March 2008
Revisions received:5 December 2008
Accepted:12 January 2009
Published:11 February 2009

© 2009 The Author(s).

This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Heterogeneous multicast is an efficient communication scheme especially for multimedia applications running over multihop networks. The term heterogeneous refers to the phenomenon when multicast receivers in the same session require service at different rates commensurate with their capabilities. In this paper, we address the problem of resource allocation for a set of heterogeneous multicast sessions over multihop wireless networks. We propose an iterative algorithm that achieves the optimal rates for a set of heterogeneous multicast sessions such that the aggregate utility for all sessions is maximized. We present the formulation of the multicast resource allocation problem as a nonlinear optimization model and highlight the cross-layer framework that can solve this problem in a distributed ad hoc network environment with asynchronous computations. Our simulations show that the algorithm achieves optimal resource utilization, guarantees fairness among multicast sessions, provides flexibility in allocating rates over different parts of the multicast sessions, and adapts to changing conditions such as dynamic channel capacity and node mobility. Our results show that the proposed algorithm not only provides flexibility in allocating resources across multicast sessions, but also increases the aggregate system utility and improves the overall system throughput by almost 30% compared to homogeneous multicast.

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