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This paper studies an uplink multicell joint processing model in which thebase-stations are connected to a centralized processing server via rate-limiteddigital backhaul links. Unlike previous studies where the centralized processorjointly decodes all the source messages from all base-stations, this paperproposes a suboptimal achievability scheme in which the Wyner-Zivcompress-and-forward relaying technique is employed on a per-base-stationbasis, but successive interference cancellation (SIC) is used at the centralprocessor to mitigate multicell interference. This results in an achievablerate region that is easily computable, in contrast to the joint processingschemes in which the rate regions can only be characterized by exponentialnumber of rate constraints. Under the per-base-station SIC framework, thispaper further studies the impact of the limited-capacity backhaul links on theachievable rates and establishes that in order to achieve to within constantnumber of bits to the maximal SIC rate with infinite-capacity backhaul, thebackhaul capacity must scale logarithmically with thesignal-to-interference-and-noise ratio (SINR) at each base-station. Finally,this paper studies the optimal backhaul rate allocation problem for an uplinkmulticell joint processing model with a total backhaul capacity constraint. Theanalysis reveals that the optimal strategy that maximizes the overall sum rateshould also scale with the log of the SINR at each base-station.

Uplink Multicell Processing with Limited Backhaul via Per-Base-Station Successive Interference Cancellation