Impact Of Rate Control On The Capacity Of An IUB Link: Multiple Service Case

Universal Mobile Telecommunications System (UMTS) networks are capable of serving packet-switched data applications at bit rates as high as 384 Kbps. Multiplexing multiple data sessions in the Radio Access Network (RAN) of a UMTS network brings a tremendous capacity gain with respect to the circuit-switched networks, however the utilization of resources are very low due to the bursty nature of data traffic. This memo studies the capacity and utilization of the downlink of the Iub interface, which lies between the Radio Network Controller (RNC) and the base station (NodeB) in a UMTS network. In our earlier memo, we presented simulation results that indicate that the Iub link utilization is very low with bursty web browsing data especially if each data user is allowed to peak at 384 Kbps. Thus, we introduced a rate control algorithm by which the MAC layer constrains the peak rate of a user based on current load conditions. We provided performance results for various test scenarios: 64Kbps users only, 128 Kbps users only, and 384 Kbps users only; each for the web-browsing service. We show that for that single service case, the rate control algorithm that we have designed can improve the Iub link capacity by 50-60%. In this memo, we extend that study to the case where multiple service classes (64, 128 and 384 Kbps) are multiplexed on the same Iub link. There are some fundamental differences between the way rate control is implemented in the single-service case and the way it is implemented in the multi-service case. The multi-service rate control algorithm is implemented as a table search. In this algorithm, a lookup table contains various rate combinations for the 3 bearer types, beginning with highest rates at the top row of the table. The search is terminated when the rate combination that gets closest to the Iub link capacity is achieved. We tested the algorithm with some mixed service scenarios where we noted significant increase in capacity. In addition to web-browsing traffic, we also evaluate capacity where the input traffic consists of traffic generated by 5 different applications: E-mail, calendaring, data synchronization, web-browsing and FTP. We demonstrate that with the proposed rate control algorithm, capacity can be improved similar to the case with web-browsing traffic only.