arXiv:2604.09077v1 [cs.NI] 10 Apr 2026
Scrutinizing Real-life Configurations of Random Access Procedures in Cellular Networks Joris Belder
Anup Bhattacharjee
Fernando Kuipers
D-INFK ETH Zurich, Switzerland [email protected]
Networked Systems Delft University of Technology Delft, the Netherlands [email protected]
Networked Systems Delft University of Technology Delft, the Netherlands [email protected]
Abstract—In cellular networks, base stations broadcast configurations that devices use for the random access procedure, which is a vital part of the connection setup. Ideally, the network should choose configurations based on the deployment scenario to optimize radio resource management. Doing so can, for example, decrease collisions of random access messages. We captured 112,806 data points of cellular broadcast information from nine network operators across three countries and analyzed how the operators configure the random access procedure. We found that configurations often do not fit the deployment scenario, and neighboring cells often use the same configuration, causing an unnecessarily high risk of collisions and, hence, delay in the connection setup. Furthermore, we simulated the random access procedure in NS-3 and found that by varying the configurations in a large area with many cells, the number of collisions can be reduced by 43% on average and up to 61%, and the connection delay can be lowered by 11% on average and up to 42%. Our findings indicate that simple adaptations in the random access configurations can greatly improve the performance of cellular networks. Index Terms—Cellular Networks; 4G; Random Access Procedure; Data Collection; Simulation.
I. I NTRODUCTION In 2024, about 58% of global smartphone subscribers still used 4G [1], excluding those on 5G non-stationalone (NSA) networks that rely on 4G for the control plane. In contrast, adoption of 5G Standalone (SA), where both user and control planes operate on 5G, remains limited in Europe. According to Speedtest, only 2% of samples in Europe were on 5G SA networks, significantly behind China (80%), India (52%), and the United States (24%) [2]. This shows the high relevance of 4G networks and the use of control methods to optimize the configurations of the cellular networks. One vital aspect of cellular networks is connection setup. Devices perform a random access procedure to initialize a connection and receive uplink transmission grants. While researchers have already presented novel random access schemes [3], [4], it remains unclear how actual cellular deployments configure the random access procedure. Such insights into real-life configurations are essential for understanding and improving the performance of cellular networks and, in particular, of the connection setup. This research was supported by the National Growth Fund through the Dutch 6G flagship project “Future Network Services”.
In this paper, we present measurements of random access configurations in 4G networks. Our measurements encompass 112,806 data points and stretch across three countries. In each country, we took measurements for the three largest Mobile Network Operators (MNOs) by subscriber base. Specifically, we collected cell broadcast information that devices use to configure the random access procedure. For instance, cells broadcast information that tells devices which preamble they should use for initializing connections. To the best of our knowledge, we are the first to present such measurements. Our data indicates that random access configurations often do not suit the deployment scenario and are often the same across many cells. For example, neighboring cells commonly use the same preamble configuration for random access, which unnecessarily increases the risk of collisions, prolongs the connection setup, and leads to inefficient network resource usage. To analyze how much of an issue cells using the same configuration is, we simulated the random access procedure in NS-3 and compared the performance when cells use the same configuration with the performance when cells use different configurations. We found that simply deploying different configurations across cells reduces the number of collisions and lowers the connection delay significantly. For example, one can lower the median connection delay by up to 300 ms by deploying simple changes. MNOs can leverage our findings to improve the performance of cellular connection setup and to save network resources. While we measured the configurations in 4G networks, the random access procedure is similar in 5G. When considering Europe, most 5G deployments are currently non-standalone, meaning they have 4G as their control layer [2]. Our insights therefore also hold for more modern networks. As pushed by the Open-Radio Access Network (RAN) initiatives [5], future networks will be more softwarized, with the RAN being controlled by a RAN Interface Controller (RIC) [6]. We envision RICs to adjust the configurations of cells intelligently to improve network performance, and part of these configurations is the random access procedure, which we show can be a crucial factor in the performance of cellular networks. O-RAN provides interfaces to include 4G base stations as part of the O-RAN architecture, which will allow to make adjustments to the configurations for improved performance.
TABLE I M EASUREMENT S TATISTICS
Information Element n
eNodeB
Information Group n
SIB n
SIB2
MIB
SIB1
Downlink Broadcast Channel PRACHPRACHConfigInfo ConfigIndex
MNOs UE
Fig. 1. Transmission of the Master and System Information Blocks. SIB2 contains information on how to perform the random access procedure.
Contributions. Our contributions are as follows: • We present data on real-life random access configurations and show that configurations often do not suit the deployment scenario and are often the same across cells. • We use NS-3 simulations to show that using different configurations across cells can notably reduce the number of collisions and the connection delay. II. BACKGROUND Basics. In 4G, User Equipments (UEs), e.g., mobile phones, connect to base stations called Evolved NodeBs (eNodeBs), which connect to an Evolved Packet Core (EPC). The EPC is responsible for services such as user authentication, connection setup, and roaming [7]. Each MNO has their own frequency bands [8] to transmit and receive signals. This means that MNOs are not allowed not transmit in each others spectrum. To efficiently utilize these bands, MNOs deploy eNodeBs. Each eNodeB divides the allocated frequency bands into multiple logical cells. These logical cells operate on different frequencies to minimize interference within the same MNO network. A UE connects to one of these logical cells by communicating over a designated frequency band during specific time intervals known as radio frames. From this point onward in the paper, we refer to the “logical cell” as a “cell”. In 4G, the duration of a radio frame is 10 ms. Each radio frame is further divided into ten subframes of equal length. Signals sent on the same frequency and in the same subframe can collide [9]. Therefore, MNOs should optimize their cellular configurations to prevent collisions. Cell Broadcast. Cells broadcast system information using the Radio Resource Control (RRC) protocol [10], which manages network resources pertaining to user connections. With RRC, cells regularly broadcast a Master Information Block (MIB) that contains information that UEs need to synchronize and listen to other broadcast information such as different types of System Information Blocks (SIBs). SIBs provide further information for UEs to access cells. The MIB and the SIBs are divided into multiple Information Groups (IGs) that are further subdivided into Information Elements (IEs). Each IE typically describes some RAN parameter and assists the UEs in choosing configuration settings [11]. SIB1 contains information on the scheduling of other SIBs. SIB2 contains radio resource configuration information that UEs use for several procedures, including random access. Figure 1 illustrates the transmission of the MIB and SIBs and parts of the structure of SIB2.
Frequency bands observed Municipalities measured eNodeBs measured (grouped by MNO ) (Logical) Cells measured (grouped by MNO) Measurement locations Total measurements Measurement period
Country 1 3 1, 3, 7, 8, 20, 28, 38 7
Country 2 3 1, 3, 7, 8, 20, 28, 38 7
Country 3 3 1, 3, 7, 20, 28 10
155
188
43
992
2036
807
29 23,389
62 76,556 August - December 2022
13 12,861
December 2022
December 2022
Random Access Procedure. To connect or reconnect to a cell and receive uplink grants for data transfer, UEs perform a random access procedure. They must send a Physical Random Access Channel (PRACH) preamble to the cell to establish the connection. To decide which preamble to use, UEs listen to the cell broadcast information. SIB2 contains the IG PRACHConfigInfo, and this IG contains IE PRACH-ConfigIndex (as illustrated in Figure 1) that tells UEs which preamble to use and when to send it. There exist four PRACH preamble formats that suit different deployment scenarios. For instance, preamble formats 0 and 2 are suitable for smaller cells (such as those in urban deployments), whereas formats 1 and 3 suit larger cells (such as those in rural deployments), because the latter use longer guard intervals, giving signals more room to travel [9], [12], [13]. For each PRACH preamble format, there are 16 different PRACH preambles. Preambles differ in during which subframe numbers UEs may transmit them and in whether UEs may transmit them during odd, even, or all radio frame numbers. If several UEs attempt to connect at the same time with the same PRACH preamble, the preambles may collide even if they were meant for different cells, causing one or multiple of the connection attempts to fail. When a collision occurs, UEs must retry connecting later. So, collisions prolong the connection setup. Thus, MNOs should configure their cells such that neighboring cells use different preambles to prevent collisions, and they should ensure that they use preamble formats that suit the deployment scenario. III. M EASUREMENTS AND I NSIGHTS We captured SIB messages from cells in three different countries and for three MNOs per country. Section III-A details our setup for the data collection. We analyzed the collected data to see how MNOs configure the random access procedure. We detail our insights in Section III-B. A. Data Collection For our data collection, we used a laptop running Ubuntu 18.04 with Linux kernel 5.4.0-132-lowlatency alongside a Quectel EG25-G USB dongle1 as UE that connects to cells. Using this setup, we captured SIB1 and SIB2 broadcast messages from cells. We developed the code for capturing 1 We used firmware version EG25GGBR07A07M2G.