Date of Award
Doctor of Philosophy (PhD)
Electrical Engineering and Computer Science
Information theory, Wireless communication
Interference management is one of the key techniques that drive evolution of wireless networks from one generation to another. Techniques in current cellular networks to deal with interference follow the basic principle of orthogonalizing transmissions in time, frequency, code, and space. My PhD work investigate information theoretic models that represent a new perspective/technique for interference management. The idea is to explore the fact that an interferer knows the interference that it causes to other users noncausally and can/should exploit such information for canceling the interference. In this way, users can transmit simultaneously and the throughput of wireless networks can be substantially improved. We refer to the interference treated in such a way as ``dirty interference'' or "noncausal state".
Towards designing a dirty interference cancelation framework, my PhD thesis investigates two classes of information theoretic models and develops dirty interference cancelation schemes that achieve the fundamental communication limits. One class of models (referred to as state-dependent interference channels) capture the scenarios that users help each other to cancel dirty interference. The other class of models (referred to as state-dependent channels with helper) capture the scenarios that one dominate user interferes a number of other users and assists those users to cancel its dirty interference. For both classes of models, we develop dirty interference cancelation schemes and compared the corresponding achievable rate regions (i.e., inner bounds on the capacity region) with the outer bounds on the capacity region. We characterize the channel parameters under which the developed inner bounds meet the outer bounds either partially of fully, and thus establish the capacity regions or partial boundaries of the capacity regions.
Duan, Ruchen, "CHARACTERIZATION OF FUNDAMENTAL COMMUNICATION LIMITS OF STATE-DEPENDENT INTERFERENCE NETWORKS" (2015). Dissertations - ALL. 339.