|Thesis abstract: |
Collaborative communication is a major tenet of multi-agent
networking and it has received much attention from the signal
processing communities, because it increases reliability, coverage and
spectral efficiency inside the network. This thesis considers networks of nodes,
which cooperatively monitor, compute and exchange information
from the surrounding environment with their neighbors. The research
project is focused on the estimation of parameters that characterize the network
state, such as channel state information, nodes' locations or timing.
For distributed estimation consensus approach is employed, based on
successive refinements of local estimate mainteined at individual
nodes with information
exchange between neighbors. Performance analyses are carried out
in terms of accuracy and convergence speed, also analytically,
using fundamental performance bounds as benchmarks.
Efficient and optimized different algorithms will be designed,
also to understand the impact of computational cost.