The mean received power in ad hoc networks and its dependence on geometrical quantities

System-level simulations for ad hoc networks require the mean power that is received by an arbitrary unit of the piconet as an input parameter. Since the radio channel in piconets depends strongly on the environment in which two communicating units are located, easily applicable models for the mean received power must be determined by a few relevant, explicitly geometrical quantities. Starting from a very general description of the stochastic radio channel by an integral equation, it is shown that these quantities are the surface area and the volume of the domain in which the transmitter and the receiver can move. On the basis of an exponential path loss model with path loss exponent q, a lower and an upper bound for the mean received power are derived. The resulting analytical expressions are highly flexible and allow a quick calculation of bounds for the mean received power in many practically relevant cases.

[1]  Werner Wiesbeck,et al.  Planungsmethoden für die Mobilkommunikation , 1998 .

[2]  John G. Proakis,et al.  Probability, random variables and stochastic processes , 1985, IEEE Trans. Acoust. Speech Signal Process..

[3]  Aaas News,et al.  Book Reviews , 1893, Buffalo Medical and Surgical Journal.

[4]  E. N. da C. A.,et al.  Lehrbuch der theoretischen Physik , 1933, Nature.

[5]  Joong Soo Ma,et al.  Mobile Communications , 2003, Lecture Notes in Computer Science.

[6]  William C. Y. Lee,et al.  Mobile Communications Design Fundamentals: Lee/Mobile , 1993 .

[7]  L. Santaló Integral geometry and geometric probability , 1976 .

[8]  Jochen Schiller,et al.  Mobile Communications , 1996, IFIP — The International Federation for Information Processing.

[9]  Thomas Zwick,et al.  A stochastic spatial channel model based on wave-propagation modeling , 2000, IEEE Journal on Selected Areas in Communications.

[10]  Jan Hansen A novel stochastic millimeter-wave indoor radio channel model , 2002, IEEE J. Sel. Areas Commun..

[11]  Bruno O. Shubert,et al.  Random variables and stochastic processes , 1979 .

[12]  A. Stephens,et al.  Wi-Fi (802.11b) and Bluetooth: enabling coexistence , 2001, IEEE Netw..

[13]  T. Carleman,et al.  Über eine isoperimetrische Aufgabe und ihre physikalischen Anwendungen , 1919 .

[14]  Von Hippel,et al.  Dielectric materials and applications : papers by twenty-two contributors , 1954 .

[15]  Bernard Henri Fleury,et al.  Stochastic radio channel model for advanced indoor mobile communication systems , 1997, Proceedings of 8th International Symposium on Personal, Indoor and Mobile Radio Communications - PIMRC '97.

[16]  H. Hashemi,et al.  The indoor radio propagation channel , 1993, Proc. IEEE.

[17]  Kaveh Pahlavan,et al.  A new statistical model for site-specific indoor radio propagation prediction based on geometric optics and geometric probability , 2002, IEEE Trans. Wirel. Commun..

[18]  J. Schneider Calculation of eddy currents in linear motor geometries--A two-dimensional integral equation approach , 1974 .

[19]  Theodore S. Rappaport,et al.  Site-specific propagation prediction for wireless in-building personal communication system design , 1994 .

[20]  Abbas Jamalipour,et al.  Wireless communications , 2005, GLOBECOM '05. IEEE Global Telecommunications Conference, 2005..

[21]  Ernst Zollinger,et al.  Eigenschaften von Funkübertragungsstrecken in Gebäuden , 1993 .

[22]  Theodore S. Rappaport,et al.  Statistical channel impulse response models for factory and open plan building radio communicate system design , 1991, IEEE Trans. Commun..

[23]  G. V. Chester,et al.  Solid State Physics , 2000 .