 effectively transferred at a higher MCS, leading to a shorter 'net' TBF time and therefore less TBF blocking and congestion. Depending on the network's mix of applications and services, a healthy balance of both functions may be employed to optimise EGPRS throughput and latency. In practice, the last factor of user versus signalling payload heavily influences MCS distribution. This is because a significant proportion of the payload is driven by routing area updates (RAU) and GMM/SM signalling (attach and PDP context). It is therefore important to distinguish the user payload from the signalling payload SO the performance engineer can tune the optimum EGPRS throughput and Radio Network Optimisation latency for the data subscribers. RAUs can be reduced and the attach success rate (ASR) increased by modifying the periodic routing area update (PRAU) timer and by careful RAC boundary planning using similar techniques to those applied in traditional GSM LAC planning (e.g. clearly defined boundaries using well-isolated geographical or highway transitions rather than ill-defined or ambiguous boundaries parallel to density populated/high mobility regions). GMM/SM (session management) signalling can also be optimised by modifying the SGSN and GGSN settings for releasing and retaining attached and PDP activated subscribers. Figure 2.89 illustrates typical downlink and uplink MCS distributions on two representative BSCs respectively. Note that the BSC on the left contains more MCS-9 in both directions. Also, the distribution (on both the uplink and downlink) shows the first BSC having more MCS-3 and the second BSC having more MCS-5. The difference in distribution in this example is due to certain link adaptation parameters that bias the coding scheme on the first BSC to MCS-3 and the second BSC to MCS-5. The larger proportion of higher MCSs indicates a combination of more favourable channel conditions, less signalling and more opportunity of link adaptation to higher MCSs (due to a longer TBF transmission time). TBF Perform