The Community for Technology Leaders
RSS Icon
Issue No.07 - July (2011 vol.10)
pp: 954-967
Yi Shi , Virginia Polytechnic Institute and State University, Blacksburg
Y. Thomas Hou , Virginia Polytechnic Institute and State University, Blacksburg
Sastry Kompella , U.S. Naval Research Laboratory, Washington DC
Hanif D. Sherali , Virginia Polytechnic Institute and State University, Blacksburg
Cognitive radio networks (CRNs) have the potential to utilize spectrum efficiently and are positioned to be the core technology for the next-generation multihop wireless networks. An important problem for such networks is its capacity. We study this problem for CRNs in the SINR (signal-to-interference-and-noise-ratio) model, which is considered to be a better characterization of interference (but also more difficult to analyze) than disk graph model. The main difficulties of this problem are two-fold. First, SINR is a nonconvex function of transmission powers; an optimization problem in the SINR model is usually a nonconvex program and NP-hard in general. Second, in the SINR model, scheduling feasibility and the maximum allowed flow rate on each link are determined by SINR at the physical layer. To maximize capacity, it is essential to follow a cross-layer approach, but joint optimization at physical (power control), link (scheduling), and network (flow routing) layers with the SINR function is inherently difficult. In this paper, we give a mathematical characterization of the joint relationship among these layers. We devise a solution procedure that provides a (1- \varepsilon ) optimal solution to this complex problem, where \varepsilon is the required accuracy. Our theoretical result offers a performance benchmark for any other algorithms developed for practical implementation. Using numerical results, we demonstrate the efficacy of the solution procedure and offer quantitative understanding on the interaction of power control, scheduling, and flow routing in a CRN.
Theory, multihop cognitive radio network, nonlinear optimization, SINR model, cross-layer, capacity.
Yi Shi, Y. Thomas Hou, Sastry Kompella, Hanif D. Sherali, "Maximizing Capacity in Multihop Cognitive Radio Networks under the SINR Model", IEEE Transactions on Mobile Computing, vol.10, no. 7, pp. 954-967, July 2011, doi:10.1109/TMC.2010.204
[1] A. Agarwal and P.R. Kumar, "Capacity Bounds for Ad Hoc and Hybrid Wireless Networks," ACM SIGCOMM Computer Communications Rev., vol. 34, no. 3, pp. 71-81, July 2004.
[2] M. Alicherry, R. Bhatia, and L. Li, "Joint Channel Assignment and Routing for Throughput Optimization in Multiradio Wireless Mesh Networks," Proc. ACM MobiCom, pp. 58-72, Aug.-Sept. 2005.
[3] M. Andrews and M. Dinitz, "Maximizing Capacity in Arbitrary Wireless Networks in the SINR Model: Complexity and Game Theory," Proc. IEEE INFOCOM, pp. 1332-1340, Apr. 2009.
[4] A. Behzad and I. Rubin, "Impact of Power Control on the Performance of Ad Hoc Wireless Networks," Proc. IEEE INFOCOM, pp. 102-113, Mar. 2005.
[5] V. Bhandari and N.H. Vaidya, "Capacity of Multichannel Wireless Networks with Random (c, f) Assignment," Proc. ACM MobiHoc, pp. 229-238, Sept. 2007.
[6] R. Bhatia and M. Kodialam, "On Power Efficient Communication over Multihop Wireless Networks: Joint Routing, Scheduling and Power Control," Proc. IEEE INFOCOM, pp. 1457-1466, Mar. 2004.
[7] C.C. Chen and D.S. Lee, "A Joint Design of Distributed QoS Scheduling and Power Control for Wireless Networks," Proc. IEEE INFOCOM, Apr. 2006.
[8] R.L. Cruz and A.V. Santhanam, "Optimal Routing, Link Scheduling and Power Control in Multihop Wireless Networks," Proc. IEEE INFOCOM, pp. 702-711, Mar.-Apr. 2003.
[9] T. Elbatt and A. Ephremides, "Joint Scheduling and Power Control for Wireless Ad-Hoc Networks," Proc. IEEE INFOCOM, pp. 976-984, June 2002.
[10] A. Fanghanel, T. Kesselheim, H. Racke, and B. Vocking, "Oblivious Interference Scheduling," Proc. ACM SIGACT-SIGOPS Symp. Principles of Distributed Computing, pp. 220-229, Aug. 2009.
[11] M.R. Garey and D.S. Johnson, Computers and Intractability: A Guide to the Theory of NP-Completeness, pp. 245-248. W.H. Freeman and Company, 1979.
[12] A.J. Goldsmith and S.-G. Chua, "Adaptive Coded Modulation for Fading Channels," IEEE Trans. Communications, vol. 46, no. 5, pp. 595-602, May 1998.
[13] O. Goussevskaia, Y.A. Oswald, and R. Wattenhofer, "Complexity in Geometric SINR," Proc. ACM MobiHoc, pp. 100-109, Sept. 2007.
[14] O. Goussevskaia and R. Wattenhofer, "Capacity of Arbitrary Wireless Networks," Proc. IEEE INFOCOM, pp. 1872-1880, Apr. 2009.
[15] P. Gupta and P.R. Kumar, "The Capacity of Wireless Networks," IEEE Trans. Information Theory, vol. 46, no. 2, pp. 388-404, Mar. 2000.
[16] A.-K. Haddad and R. Riedi, "Bounds for the Capacity of Wireless Multihop Networks Imposed by Topology and Demand," Proc. ACM MobiHoc, pp. 256-265, Sept. 2007.
[17] M.M. Halldorsson and R. Wattenhofer, "Wireless Communication is in APX," Proc. Int'l Colloquium on Automata, Languages and Programming, pp. 525-536, July 2009.
[18] K. Jain, J. Padhye, V. Padmanabhan, and L. Qiu, "Impact of Interference on Multihop Wireless Network Performance," Proc. ACM MobiCom, pp. 66-80, Sept. 2003.
[19] S.-W. Jeon, N. Devroye, M. Vu, S.-Y. Chung, and V. Tarokh, "Cognitive Networks Achieve Throughput Scaling of a Homogeneous Network," Proc. ICST Int'l. Symp. Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt), June 2009.
[20] M. Kodialam and T. Nandagopal, "Characterizing the Capacity Region in Multiradio Multichannel Wireless Mesh Networks," Proc. ACM MobiCom, pp. 73-87, Aug.-Sept. 2005.
[21] P. Kyasanur and N.H. Vaidya, "Capacity of Multichannel Wireless Networks: Impact of Number of Channels and Interfaces," Proc. ACM MobiCom, pp. 43-57, Aug.-Sept. 2005.
[22] S. Li, Y. Liu, and X.-Y. Li, "Capacity of Large Scale Wireless Networks under Gaussian Channel Model," Proc. ACM MobiCom, pp. 140-151, Sept. 2008.
[23] B. Radunovic and J.-Y. Le Boudec, "Rate Performance Objectives of Multihop Wireless Networks," Proc. IEEE INFOCOM, pp. 1916-1927, Mar. 2004.
[24] K. Ramachandran, E. Belding-Royer, K. Almeroth, and M. Buddhikot, "Interference-Aware Channel Assignment in Multiradio Wireless Mesh Networks," Proc. IEEE INFOCOM, Apr. 2006.
[25] H.D. Sherali and W.P. Adams, A Reformulation-Linearization Technique for Solving Discrete and Continuous Nonconvex Problems, Kluwer Academic, 1999.
[26] Y. Shi and Y.T. Hou, "Optimal Power Control for Multihop Software Defined Radio Networks," Proc. IEEE INFOCOM, pp. 1694-1702, May 2007.
[27] T. Shu and M. Krunz, "Coordinated Channel Access in Cognitive Radio Networks: A Multilevel Spectrum Opportunity Perspective," Proc. IEEE INFOCOM, pp. 2976-2980, Apr. 2009.
[28] D. Ugarte and A.B. McDonald, "On the Capacity of Dynamic Spectrum Access Enabled Networks," Proc. IEEE DySPAN, pp. 630-633, Nov. 2005.
[29] M. Vu, N. Devroye, M. Sharif, and V. Tarokh, "Scaling Laws of Cognitive Networks," Proc. ICST Int'l Conf. Cognitive Radio Oriented Wireless Networks and Communications (CrownCom), pp. 2-8, July-Aug. 2007.
[30] Z. Wang, P. Giaccone, and E. Leonardi, "A Unifying Perspective on the Capacity of Wireless Ad Hoc Networks," Proc. IEEE INFOCOM, pp. 211-215, Apr. 2008.
[31] Y. Xu and W. Wang, "Scheduling Partition for Order Optimal Capacity in Large-Scale Wireless Networks," Proc. ACM MobiCom, pp. 109-120, Sept. 2009.
[32] C. Yin, L. Gao, and S. Cui, "Scaling Laws of Overlaid Wireless Networks: A Cognitive Radio Network vs. a Primary Network," Proc. IEEE GLOBECOM, pp. 1235-1239, Nov.-Dec. 2008.
[33] Y. Yuan, P. Bahl, R. Chandra, T. Moscibroda, and Y. Wu, "Allocating Dynamic Time-Spectrum Blocks in Cognitive Radio Networks," Proc. ACM MobiHoc, pp. 130-139, Sept. 2007.
[34] J. Zhao, H. Zheng, and G. Yang, "Distributed Coordination in Dynamic Spectrum Allocation Networks," Proc. IEEE DySPAN, pp. 259-268, Nov. 2005.
15 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool