Saturday, 20 October 2018

RACH Optimization

The configuration of the random access procedure has a critical impact on end-user experience and overall network performance. A poorly configured Random Access CHannel (RACH) may increase access setup time and accesses failures, impacting both call setup and handover performance. With optimal random access parameter setting, maximum end-user experience can be obtained. This is achieved by reaching the desired balance in the radio resource allocation between random accesses and services while at the same time avoiding creating excessive interference. To keep the RACH optimized for all cells during varying conditions, the optimization can be repeated periodically or run continuously.

In LTE, RACH (Random Access Channel) is an uplink unsynchronized channel, used for initial access or uplink synchronization. The triggers for Random Access procedure include:

• Connection setup
• Radio Link Failure
• Downlink data transmission in uplink unsynchronized state
• Uplink data transmission in uplink unsynchronized state
• Handover

So the Random Access procedure performance influences the call setup delay, handover delay, data resuming delay, call setup success rate and handover success rate. Besides, physical resources for RACH are reserved for its special use. So the configuration for RACH influences the capacity of the whole network.

An optimized RACH configuration enables end-user benefits and network performance gains through:

• Reduced connection time
• Higher throughput
• Better cell coverage.

By automating the optimization of RACH, maximum performance is achieved with no operator intervention or effort. The network will dynamically adapt to network changes and end-user behavior to always deliver best possible performance and resource utilization.

Necessity for RACH optimization
The performance of Random Access performance is evaluated by its delay and success rate. The performance depends on following factors:

• Population under the cell coverage;
• Call arrival rate;
• Incoming handover rate;
• Whether the cell is at the edge of a tracking area;
• Traffic pattern, as it affects the DRX (Discontinuous Reception) and uplink synchronization states, and hence the need to use RACH.

These factors are affected by network configurations, such as antenna tilt, transmission power and handover threshold, and also by the load of network. If network configurations or load is changed, the performance of Random Access procedure may change greatly, which influences the performance of other procedures, such as call setup, data resuming and handover. Therefore the automatic optimization of RACH would be beneficial.

Possible RACH optimization algorithm The configurations of RACH include:

• RACH physical resources
• RACH preamble allocation for different sets (dedicated, random-low and randomhigh)
• RACH persistence level and backoff control
• RACH transmission power control

Measurements are done in eNB, recording random access delay, random access success rate and random access load. The random access load can be indicated by the number of received preambles in a cell in a time interval. It is measured per preamble range (dedicated, random-low and random-high), and averaged over the PRACHs configured in a cell.

Thresholds are set separately for random access delay and success rate. If either of the thresholds is reached, RACH optimization is triggered. First, Random access load is analyzed to check if the random access is overload in any of the three preamble ranges. If one of them is overload, RACH preambles are reallocated among these three preamble ranges. If all of them are overload, more physical resources need to be reserved for RACH. If none of them is overload, other parameters need to be adjusted, such as increasing the transmission power step and distributing the backoff time in a wider range.


A User Equipment (UE) in idle state is unknown to an LTE network. In order to start establishing a relation to the LTE network, the UE searches for the most suitable cell and reads its broadcast system information. The broadcast system information (SIB2) from the cell provides the UE with cell-specific random access format and procedure details. These details determine essential parameters, such as preamble format and initial power setting. The UE randomly selects one of the preambles in an attempt to establish a relation to the cell. As long as no other UE is using the selected preamble at the same time instant, the access attempt can succeed. The success also relies on that the preamble can be heard and identified by the eNB. If there is no response or rejection from the eNB, the UE needs to retry until it succeed. The impact on user experience during the random access procedure is mainly delayed access and interrupted transmission during a handover. The automatic RACH optimization function will balance between optimal access performance and least resource utilization needed to meet set quality target such as, an acceptable level of access success rate. By selecting the most suitable preamble format, based on say traffic type, and dynamically adjusting the broadcast power control parameter (P0), the access success rate can be optimized while still maintaining a low interference level. This results in best user experience with fast access and best possible throughput.

The automatic RACH optimization function can be executed continuously resulting in RACH related parameters being modified automatically. The changes could be based on inputs from both the connected UEs and each cell’s neighboring cells. By collecting the recently introduced RACH report from the UE, the actual access delay can be determined. The RACH report is included in the message UEInformationResponse (3GPP Rel-9 spec TS 36.331). It contains two new parameters: numberOfPreamblesSent and contentionDetected. Based on this new information, the automatic RACH optimization function can adjust the power control parameter (P0) or change the preamble format to reach the set target access delay. By optimizing P0, the probability for an eNB to read the preamble increases. However, as a result, the interference on neighboring cells may also increase. The second option adjusts the preamble format to use, under the premise that a correct preamble format assures successful preamble detection for the traffic type in a cell.

The automatic RACH optimization function automates the required continuous adaptation of the RACH. The automatic RACH optimization function can automatically react when receiving notification over X2 of a RACH parameter change in a neighboring cell. The information is transmitted via the eNB configuration update X2 message. For instance, allocation of same root sequence index in neighboring cells should be avoided to reduce interference. Automatic RACH optimization, based on the optimization on real traffic data and neighbor cell information, makes it well suitable for eNB function localization. The automatic RACH optimization function can execute autonomously with no operator intervention or effort. The operator controls the function with a few policies that set the outer limits for the function. These limits assure that the function will not move to an extreme setting when finding the best tradeoff between access delay and resource utilization.

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