INFORMATION-THEORETIC CAPACITY BOUNDS FOR DYNAMIC WIRELESS NETWORKS VIA IA (INTERFERENCE ALIGNMENT)

Abstract

In this thesis, we try to obtain efficient IA-based transmission schemes. Multiple source-destination pairs utilize the same communication channel in wireless interference networks. The interference from unintended sources affects the signal receipt at each destination. It could lead to a strategic scenario in which every source attempts to recompense for the nonpositive impact from interfering at their wanted destination while expanding interference in the other destinations by raising its driving force. Failure to do so will follow in a substantial waste of the radio resource available. That can also decode signals of interest as well as remove interfering signals of unwanted transmitters. The transmissions of the channels appear to be orthogonal with common IA strategies. However, users can then send by using a system for alignment of interference to address inter-user interference. Preferably, the IA principle regulates its transmitting purposes, including its transmitter, in a rather manner whereby interference signals from multiple unwanted transmitters are mitigated at each receiver within the same subspace, that differs compared to the signals of interest from the subspace.