  This paper studies an uplink multicell joint processing model in which the
base-stations are connected to a centralized processing server via rate-limited
digital backhaul links. Unlike previous studies where the centralized processor
jointly decodes all the source messages from all base-stations, this paper
proposes a suboptimal achievability scheme in which the Wyner-Ziv
compress-and-forward relaying technique is employed on a per-base-station
basis, but successive interference cancellation (SIC) is used at the central
processor to mitigate multicell interference. This results in an achievable
rate region that is easily computable, in contrast to the joint processing
schemes in which the rate regions can only be characterized by exponential
number of rate constraints. Under the per-base-station SIC framework, this
paper further studies the impact of the limited-capacity backhaul links on the
achievable rates and establishes that in order to achieve to within constant
number of bits to the maximal SIC rate with infinite-capacity backhaul, the
backhaul capacity must scale logarithmically with the
signal-to-interference-and-noise ratio (SINR) at each base-station. Finally,
this paper studies the optimal backhaul rate allocation problem for an uplink
multicell joint processing model with a total backhaul capacity constraint. The
analysis reveals that the optimal strategy that maximizes the overall sum rate
should also scale with the log of the SINR at each base-station.
