Network Capacity when Some Common Information Theoretic Assumptions Break Down

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The proposed research seeks to understand the impact of two common assumptions in multi-user information theory on the capacity region of networks: global codebook knowledge and global synchronism. Under these assumptions, sophisticated coding schemes and coordinated transmission strategies are possible. In distributed networks, as well as networks with a large number of nodes, maintaining synchronicity and keeping track of all users' codebooks may simply not be possible; in today's cellular networks this incurs a severe overhead. The goal of the proposed research is to understand, from an information theoretic perspectiv,e how relaxing these assumptions affects network performance in terms of capacity regions. The core of the proposed new technical approach lies in coding over discrete alphabets rather than by using standard Gaussian-like coding.Understanding from a fundamental perspective the impact of sharing codebooks and guaranteeing synchronism in networks is of direct relevance to improving communications in heterogeneous, distributed, WiFi, cellular, ad hoc military and first responder wireless networks of the present and future. Having accurate network capacity predictions for networks under more realistic assumptions not only acts as a benchmark for engineers building systems, but also provides guidelines on the tradeoffs between acquiring codebooks or synchronism and the corresponding capacity regions. The results may prove that codebook knowledge or synchronism may not be as vital as one might suspect if one tailors transmission schemes properly, which could have dramatic impact on the design of wireless networks. The results of this research are expected to be of immediate as well as far-reaching use to private and public sectors alike.