As a platform for synergistic theory-experiment exploration in the field of wireless networking, wireless testbeds have been used to facilitate a broad range of research. From the perspective of system-level wireless emulation, average link SNR is the dominant factor in the performance of a wireless link. Thus, this work seeks to develop a systematic link SNR mapping method that replicates real-world link SNRs on an indoor testbed. The challenge is to optimize the nodes' spatial configuration and transmission powers to overcome the inherent propagation differences, as expressed in terms of pathloss exponents and environmental shadowing, between the real world and a given testbed. To avoid the technical difficulty of "forward mapping" from the real world to the testbed, we have developed a reverse mapping method to turn a testbed configuration with given link SNRs into a corresponding real-world configuration. By inducing the dB link gain differences between the testbed and the real world distance-dependent path loss to have a Gaussian distribution, a close approximation to real-world log-normal shadow fading is achieved. We present results for a variety of indoor and outdoor real-world scenarios.
['Jing Lei', 'Roy D. Yates', 'Larry J. Greenstein', 'Hang Liu']
Mapping link SNRs of wireless mesh networks onto an indoor testbed