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Proportional fair scheduling (PFS) has been adopted as a standard solutionfor fair resource allocation in modern wireless cellular networks. With theemergence of heterogeneous networks with widely varying user loads, it is ofgreat importance to characterize the performance of PFS under bursty traffic,which is the case in most wireless streaming and data transfer services. Inthis letter, we provide the first analytical solution to the performance of PFSunder bursty on-off traffic load. We use the Gaussian approximation model toderive a closed-form expression of the achievable user data rates. In order tofurther improve the accuracy of our baseline analytical solution for multi-cellnetworks, we design a hybrid approximation by employing multi-interferenceanalysis. The simulation results verify that our model guarantees extremely lowdata rate estimation error, which is further insensitive to changes in sessionduration, traffic load and user density.

Analysis of Proportional Fair Scheduling Under Bursty On-Off Traffic