Joint power minimization in wireless relay channels

ABSTRACT

We consider energy-constrained multihop wireless links where the power consumption must be minimized under given requirements on the end-to-end bit error probability. As multihop is known to be able to save transmission energy in a wireless environment, we study the power scheduling schemes over intermediate hops where each source-relay-destination link is modeled as a cascaded binary symmetric channel. The optimal power scheduling problem is formulated with the end-to-end bit error probability constraints. Results show that with the proposed joint power scheduling strategy, a maximum power reduction factor of M is possible in a M-hop route compared with the individual link requirement strategy where each hop assigns power individually to meet certain bit error probability at each intermediate link.

REFERENCES

• 1: S. Cui, A. J. Goldsmith and A. Bahai, "Energy-constrainted modulation optimization", IEEE Trans. on Wireless Communications, Vol. 4, No. 5, pp. 2349--2360, September, 2005.
• 2: M. Gastpar, B. Rimoldi and M. Vetterli, "To code, or not to code: Lossy source-channel communication revisited," IEEE Transactions on Information Theory, 49(5):1147--1158, May 2003.
• 3: S. Cui, R. Madan, A. J. Goldsmith, and S. Lall, "Joint Routing, MAC, and Link Layer Optimization in Sensor Networks with Energy Constraints", Proceedings of ICC'05, Korean, May, 2005.
• 4: J-H. Chang and L. Tassiulas, "Energy Conserving Routing in Wireless Ad-Hoc Networks," proceedings of INFOCOM 2000, March 2000.
• 5: M. Johansson, L. Xiao, and S. Boyd, "Simultaneous Routing and Power Allocation in CDMA Wireless Data Networks," at proceedings of ICC, Alaska, U.S.A, May, 2003.
• 6: J. Laneman and G. Wornell, "Energy-efficient antenna sharing and relaying for wireless networks," in Proc. IEEE Wireless Communications, Networking Conf. 2000, pp. 7--12.
• 7: T. Holliday and A. J. Goldsmith, "Optimal power control and source-channel coding for delay constrained traffic over wireless channels," at proceedings of ICC' 02, New York, NY, U.S.A., April 2002.
• 8: V. Rodoplu and T. H. Meng, "Minimum Energy Mobile Wireless Networks", IEEE Journal on Sel. Areas in Comm., vol. 17, no. 8, Aug 1999, pg. 1333--1344.
• 9: L. Li and J. Y. Halpern, "Minimum-energy mobile wireless networks revisited," in proc. IEEE International Conference on Communications, vol. 1, 11-14 June 2001 pg. 278--283.
• 10: K. Scott and N. Bambos, "Routing and channel assignment for low power transmission in PCS," in Proc. ICUPC, Fifth Int. Conf. Universal Personal Communications, Oct. 1996, vol. 2, pp. 498--502.
• 11: J. Boyer, D. D. Falconer, and H. Yanikomeroglu, "Multihop Diversity in Wireless Relaying Channels", IEEE Trans. on Communications, vol. 52, no. 10, Oct. 2004, pg. 1820--1830.
• 12: H. A. David, Order Statistics (2nd ed.) Wiley, New York, 1981.
• 13: R. Fletcher and M. J. D. Powell, "A Rapidly Convergent Descent Method for Minimization," Computer Journal, Vol. 6, pp. 163--168, 1963.
• 14: D. Goldfarb, "A Family of Variable Metric Updates Derived by Variational Means," Mathematics of Computing, Vol. 24, pp. 23--26, 1970.
• 15: Andrea Goldsmith , Andrew Goldsmith, Wireless Communications, Cambridge University Press, New York, NY, 2005
• 16: Stephen Boyd , Lieven Vandenberghe, Convex Optimization, Cambridge University Press, New York, NY, 2004

INDEX TERMS

Primary Classification:
  E. Data
  E.4 CODING AND INFORMATION THEORY
      Subjects: Formal models of communication

General Terms:
Theory

Keywords:
energy constrained communications, sensor networks, wireless communications