Dung Phuong Trinh

Location-aware visual radios

Location awareness creates a new paradigm for distributing scalable multimedia data over wireless networks, enabling a variety of context-aware applications that require precise location information of network nodes. An emerging concept for robust and accurate network localization is to exploit cooperation and heterogeneous design for harnessing multimodal fusion of sensing measurements to extract location information. This article gives a brief introduction to vision- and radio-based positioning technologies, and then presents illustrative machine-learning methodology to successfully integrate vision information and radio time-of-arrival measurements for cooperative localization of ultra-wideband visual radios in harsh indoor environments.

Anomalous Diffusion in Molecular Communication

We consider anomalous diffusion to model a molecular communication channel. To account for general and practical molecular propagation, we use the fractional diffusion equation and derive the distribution of first passage time in terms of Foxs H-function. We then analyze the bit error rate for timing and amplitude binary modulation schemes in anomalous diffusion.

V2V communication in a Cox field of vehicles

We study the effect of vehicles random locations in vehicle-to-vehicle (V2V) communication. To account for a doubly stochastic property of a vehicular ad-hoc network (VANET), we model vehicles random locations as a stationary Cox process. The key wireless propagations - path loss, shadowing, and multipath fading - are also considered. The modeling and analysis resort to the H-transform theory to develop a unifying framework for characterizing V2V communication. We also analyze the maximal number of hops in a doubly stochastic VANET.

Markov-population vehicular networks

In this paper, we investigate the statistical properties of a network size in vehicular ad-hoc networks. The vehicles arrive or depart at the highway through one of the traffic entry points according to a Markov population process. Using the general immigration-death process - coined as general arrival rate and general departure rate, we derive the probability distribution of the network size, i.e., the number of vehicles in a segment.