  This work presents a new resource allocation optimization framework for
cellular networks using neighborhood-based optimization. Under this
optimization framework resources are allocated within virtual cells
encompassing several base-stations and the users within their coverage area.
Incorporating the virtual cell concept enables the utilization of more
sophisticated cooperative communication schemes such as coordinated multi-point
decoding. We form the virtual cells using hierarchical clustering given a
particular number of such cells. Once the virtual cells are formed, we consider
a cooperative decoding scheme in which the base-stations in each virtual cell
jointly decode the signals that they receive. We propose an iterative solution
for the resource allocation problem resulting from the cooperative decoding
within each virtual cell. Numerical results for the average system sum rate of
our network design under hierarchical clustering are presented. These results
indicate that virtual cells with neighborhood-based optimization leads to
significant gains in sum rate over optimization within each cell, yet may also
have a significant sum-rate penalty compared to fully-centralized optimization.
