William Weiliang Li

Learn More
In wireless location-aware networks, mobile nodes (agents) typically obtain their positions using the range measurements to the nodes with known positions. Transmit power allocation not only affects network lifetime and throughput, but also determines localization accuracy. In this paper, we present an optimization framework for robust power allocation in(More)
—Adaptive orthogonal frequency division multiple access (OFDMA) has recently been recognized as a promising technique for providing high spectral efficiency in future broad-band wireless systems. The research over the last decade on adaptive OFDMA systems has focused on adapting the allocation of radio resources, such as subcarriers and power, to the(More)
—Many future wireless applications rely on the availability of position information for mobile wireless nodes (agents). Such information can be obtained through ranging between agents and fixed infrastructure (anchors). Since transmission power efficiency affects network lifetime, throughput, and interference , in this paper we will investigate the power(More)
—Indoor navigation using the existing wireless infrastructure and mobile devices is a very active research area. The major challenge is to leverage the extensive smartphone sensor suite to achieve location tracking with high accuracy. In this paper, we develop a navigation algorithm which fuses the WiFi received signal strength indicator (RSSI) and(More)
—In this paper, we develop a cooperative IMU/radio-location-based navigation system, where each node tracks the location not only based on its own measurements, but also via collaboration with neighbor nodes. The key problem is to design a nonlinear filter to fuse IMU and radiolocation information. We apply the Rao-Blackwellization method by using a(More)
Man y future wireless applications and services will require reliable and accurate positional information of the mobile nodes. Efficient power resource utilization can not onl y increase the network lifetime, but also improve the localization accurac y. The optimal power allocation depends on network parameters, which can onl y be estimated in practice and(More)
  • 1