TY - GEN
T1 - Cross-layer Optimization for Wireless Networks with Deterministic Channel Models
AU - Shao, Ziyu
AU - Chen, Minghua
AU - Avestimehr, Salman
AU - Li, Shuo-Yen Robert
PY - 2010/3
Y1 - 2010/3
N2 - Existing work on cross-layer optimization for wireless networks adopts simple physical-layer models, i.e., treating interference as noise. In this paper, we adopt a deterministic channel model proposed in [11, 12], a simple abstraction of the physical layer that effectively captures the effect of channel strength, broadcast and superposition in wireless channels. Within the Network Utility Maximization (NUM) framework, we study the cross-layer optimization for wireless networks based on this deterministic channel model. First, we extend the well-applied conflict graph model to capture the flow interactions over the deterministic channels and characterize the feasible rate region. Then we study distributed algorithms for general wireless multi-hop networks. The convergence of algorithms is proved by Lyapunov stability theorem and stochastic approximation method. Further, we show the convergence to the bounded neighborhood of optimal solutions with probability one under constant steps and constant update intervals. Our numerical evaluation validates the analytical results. ©2010 IEEE.
AB - Existing work on cross-layer optimization for wireless networks adopts simple physical-layer models, i.e., treating interference as noise. In this paper, we adopt a deterministic channel model proposed in [11, 12], a simple abstraction of the physical layer that effectively captures the effect of channel strength, broadcast and superposition in wireless channels. Within the Network Utility Maximization (NUM) framework, we study the cross-layer optimization for wireless networks based on this deterministic channel model. First, we extend the well-applied conflict graph model to capture the flow interactions over the deterministic channels and characterize the feasible rate region. Then we study distributed algorithms for general wireless multi-hop networks. The convergence of algorithms is proved by Lyapunov stability theorem and stochastic approximation method. Further, we show the convergence to the bounded neighborhood of optimal solutions with probability one under constant steps and constant update intervals. Our numerical evaluation validates the analytical results. ©2010 IEEE.
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UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-77953294706&origin=recordpage
U2 - 10.1109/INFCOM.2010.5462247
DO - 10.1109/INFCOM.2010.5462247
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 978-1-4244-5836-3
T3 - Proceedings - IEEE INFOCOM
BT - 2010 Proceedings IEEE INFOCOM
PB - IEEE
T2 - IEEE Conference on Computer Communications (INFOCOM 2010)
Y2 - 15 March 2010 through 19 March 2010
ER -