Date of Award
Doctor of Philosophy (PhD)
Electrical Engineering and Computer Science
Interference is an important issue for wireless communication systems where multiple
uncoordinated users try to access to a common medium. The problem is even more
crucial for next-generation cellular networks where frequency reuse becomes ever more
intense, leading to more closely placed co-channel cells. This thesis describes our attempt to understand the impact of interference on communication performance as well as optimal ways to handle interference. From the theoretical point of view, we examine how interference affects the fundamental performance limits, and provide insights on how interference should be treated for various channel models under different operating
conditions. From the practical design point of view, we provide solutions to improve the
system performance under unknown interference using multiple independent receptions
of the same information.
For the simple two-user Gaussian interference channel, we establish that the simple
Frequency Division Multiplexing (FDM) technique suffices to provide the optimal sum-
rate within the largest computable subregion of the general achievable rate region for a
certain interference range.
For the two-user discrete memoryless interference channels, we characterize different
interference regimes as well as the corresponding capacity results. They include one-
sided weak interference and mixed interference conditions. The sum-rate capacities are
derived in both cases. The conditions, capacity expressions, as well as the capacity achieving schemes are analogous to those of the Gaussian channel model. The study
also leads to new outer bounds that can be used to resolve the capacities of several new
discrete memoryless interference channels.
A three-user interference up-link transmission model is introduced. By examining how
interference affects the behavior of the performance limits, we capture the differences
and similarities between the traditional two-user channel model and the channel model
with more than two users. If the interference is very strong, the capacity region is just
a simple extension of the two-user case. For the strong interference case, a line segment
on the boundary of the capacity region is attained. When there are links with weak
interference, the performance limits behave very differently from that of the two-user
case: there is no single case that is found of which treating interference as noise is
optimal. In particular, for a subclass of Gaussian channels with mixed interference, a
boundary point of the capacity region is determined. For the Gaussian channel with
weak interference, sum capacities are obtained under various channel coefficients and
power constraint conditions. The optimalities in all the cases are obtained by decoding
part of the interference.
Finally, we investigate a topic that has practical ramifications in real communication
systems. We consider in particular a diversity reception system where independently
copies of low density parity check (LDPC) coded signals are received. Relying only on
non-coherent reception in a highly dynamic environment with unknown interference, soft-decision combining is achieved whose performance is shown to improve significantly over existing approaches that rely on hard decision combining.
Zhu, Fangfang, "Capacity Analysis for Gaussian and Discrete Memoryless Interference Networks" (2015). Dissertations - ALL. 252.