A cellular environment is more complicated than its wireline counterpart since it seeks to provide services in the context of variable available bandwidth, location dependencies, and user mobilities at different speeds. In a cellular network, the user may reach the cell edge, which may lead to a significant number of retransmissions to deliver the data from the base station to the destination and vice versa. These radio links will often act as a bottleneck for the rest of the network and will eventually lead to excessive delays or packet drops. An efficient retransmission or link adaptation mechanism can reduce the packet loss probability, but some packet losses and delay variations will remain. Moreover, with increased cell load or handover to a congested cell, congestion in the transport network will become even worse. Besides, there exist certain characteristics that distinguish the cellular network from other wireless access networks such as Wi-Fi. In a cellular network:
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The bottleneck is often a shared link with relatively few users.
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The cost per bit over the shared link varies over time and is different for different users.
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Leftover/unused resources can be consumed by other greedy users.
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Queues are always per radio bearer, hence each user can have many such queues.
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Users can experience both inter- and intra-Radio Access Technology (RAT) handovers (see [HO-def-3GPP] for the definition of "handover").
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Handover between cells or change of serving cells (as described in [HO-LTE-3GPP] and [HO-UMTS-3GPP]) might cause user plane interruptions, which can lead to bursts of packet losses, delay, and/or jitter. The exact behavior depends on the type of radio bearer. Typically, the default best-effort bearers do not generate packet loss, instead, packets are queued up and transmitted once the handover is completed.
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The network part decides how much the user can transmit.
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The cellular network has variable link capacity per user.
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It can vary as fast as a period of milliseconds.
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It depends on many factors (such as distance, speed, interference, different flows).
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It uses complex and smart link adaptation, which makes the link behavior ever more dynamic.
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The scheduling priority depends on the estimated throughput.
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Both Quality of Service (QoS) and non-QoS radio bearers can be used.
Hence, a real-time communication application operating over a cellular network needs to cope with a shared bottleneck link and variable link capacity, events like handover, non-congestion-related loss, and abrupt changes in bandwidth (both short term and long term) due to handover, network load, and bad radio coverage. Even though 3GPP has defined QoS bearers [
QoS-3GPP] to ensure high-quality user experience, it is still preferable for real-time applications to behave in an adaptive manner.
Different mobile operators deploy their own cellular networks with their own set of network functionalities and policies. Usually, a mobile operator network includes a range of radio access technologies such as 3G and 4G/LTE. Looking at the specifications of such radio technologies, it is evident that only the more recent radio technologies can support the high bandwidth requirements from real-time interactive video applications. Future real-time interactive applications will impose even greater demand on cellular network performance, which makes 4G (and beyond) radio technologies more suitable for such genre of application.
The key factors in defining test cases for cellular networks are:
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Shared and varying link capacity
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Mobility
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Handover
However, these factors are typically highly correlated in a cellular network. Therefore, instead of devising separate test cases for individual important events, we have divided the test cases into two categories. It should be noted that the goal of the following test cases is to evaluate the performance of candidate algorithms over the radio interface of the cellular network. Hence, it is assumed that the radio interface is the bottleneck link between the communicating peers and that the core network does not introduce any extra congestion along the path. Consequently, this document has left out of scope the combination of multiple access technologies involving both cellular and Wi-Fi users. In this latter case, the shared bottleneck is likely at the wired backhaul link. These test cases further assume a typical real-time telephony scenario where one real-time session consists of one voice stream and one video stream.
Even though it is possible to carry out tests over operational cellular networks (e.g., LTE/5G), and actually such tests are already available today, these tests cannot in general be carried out in a deterministic fashion to ensure repeatability. The main reason is that these networks are controlled by cellular operators, and there exists various amounts of competing traffic in the same cell(s). In practice, it is only in underground mines that one can carry out near deterministic testing. Even there, it is not guaranteed either as workers in the mines may carry with them their personal mobile phones. Furthermore, the underground mining setting may not reflect typical usage patterns in an urban setting. We, therefore, recommend that a cellular network simulator be used for the test cases defined in this document, for example -- the LTE simulator in [
NS-3].
The goal of this test is to evaluate the performance of the candidate congestion control algorithm under varying network load. The network load variation is created by adding and removing network users, a.k.a. User Equipment (UE), during the simulation. In this test case, each user/UE in the media session is an endpoint following RTP-based congestion control. User arrivals follow a Poisson distribution proportional to the length of the call, to keep the number of users per cell fairly constant during the evaluation period. At the beginning of the simulation, there should be enough time to warm up the network. This is to avoid running the evaluation in an empty network where network nodes have empty buffers and low interference at the beginning of the simulation. This network initialization period should be excluded from the evaluation period. Typically, the evaluation period starts 30 seconds after test initialization.
This test case also includes user mobility and some competing traffic. The latter includes both the same types of flows (with same adaptation algorithms) and different types of flows (with different services and congestion control schemes).
Each mobile user is connected to a fixed user. The connection between the mobile user and fixed user consists of a cellular radio access, an Evolved Packet Core (EPC), and an Internet connection. The mobile user is connected to the EPC using cellular radio access technology, which is further connected to the Internet. At the other end, the fixed user is connected to the Internet via a wired connection with sufficiently high bandwidth, for instance, 10 Gbps, so that the system bottleneck is on the cellular radio access interface. The wired connection in this setup does not introduce any network impairments to the test; it only adds 10 ms of one-way propagation delay.
The path from the fixed user to the mobile users is defined as "downlink", and the path from the mobile users to the fixed user is defined as "uplink". We assume that only uplink or downlink is congested for mobile users. Hence, we recommend that the uplink and downlink simulations are run separately.
uplink
++))) +-------------------------->
++-+ ((o))
| | / \ +-------+ +------+ +---+
+--+ / \----+ +-----+ +----+ |
/ \ +-------+ +------+ +---+
UE BS EPC Internet fixed
<--------------------------+
downlink
The values enclosed within "[ ]" for the following simulation attributes follow the same notion as in [
RFC 8867]. The desired simulation setup is as follows:
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Radio environment:
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Deployment and propagation model:
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3GPP case 1 (see [HO-deploy-3GPP])
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Antenna:
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Multiple-Input and Multiple-Output (MIMO), 2D or 3D antenna pattern
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Mobility:
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[3 km/h, 30 km/h]
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Transmission bandwidth:
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10 MHz
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Number of cells:
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multi-cell deployment (3 cells per Base Station (BS) * 7 BS) = 21 cells
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Cell radius:
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166.666 meters
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Scheduler:
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Proportional fair with no priority
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Bearer:
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Default bearer for all traffic
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Active Queue Management (AQM) settings:
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AQM [on, off]
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End-to-end Round Trip Time (RTT):
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[40 ms, 150 ms]
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User arrival model:
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Poisson arrival model
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User intensity:
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Downlink user intensity:
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{0.7, 1.4, 2.1, 2.8, 3.5, 4.2, 4.9, 5.6, 6.3, 7.0, 7.7, 8.4, 9,1, 9.8, 10.5}
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Uplink user intensity:
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{0.7, 1.4, 2.1, 2.8, 3.5, 4.2, 4.9, 5.6, 6.3, 7.0}
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Simulation duration:
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91 s
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Evaluation period:
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30 s - 60 s
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Media traffic:
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Media type:
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Video
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Media direction:
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[uplink, downlink]
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Number of media sources per user:
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One (1)
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Media duration per user:
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30 s
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Media source:
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same as defined in Section 4.3 of RFC 8867
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Media type:
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Audio
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Media direction:
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[uplink, downlink]
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Number of media sources per user:
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One (1)
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Media duration per user:
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30 s
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Media codec:
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Constant Bit Rate (CBR)
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Media bitrate:
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20 Kbps
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Adaptation:
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off
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Other traffic models:
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Downlink simulation:
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Maximum of 4 Mbps/cell (web browsing or FTP traffic following default TCP congestion control [RFC 5681])
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Uplink simulation:
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Maximum of 2 Mbps/cell (web browsing or FTP traffic following default TCP congestion control [RFC 5681])
The investigated congestion control algorithms should result in maximum possible network utilization and stability in terms of rate variations, lowest possible end-to-end frame latency, network latency, and Packet Loss Rate (PLR) at different cell load levels.
The goal of this test is to evaluate the performance of the candidate congestion control algorithm when users visit part of the network with bad radio coverage. The scenario is created by using a larger cell radius than that in the previous test case. In this test case, each user/UE in the media session is an endpoint following RTP-based congestion control. User arrivals follow a Poisson distribution proportional to the length of the call, to keep the number of users per cell fairly constant during the evaluation period. At the beginning of the simulation, there should be enough time to warm up the network. This is to avoid running the evaluation in an empty network where network nodes have empty buffers and low interference at the beginning of the simulation. This network initialization period should be excluded from the evaluation period. Typically, the evaluation period starts 30 seconds after test initialization.
This test case also includes user mobility and some competing traffic. The latter includes the same kind of flows (with same adaptation algorithms).
The desired simulation setup is the same as the Varying Network Load test case defined in
Section 2.1 except for the following changes:
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Radio environment:
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Same as defined in Section 2.1.2 except for the following:
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Deployment and propagation model:
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3GPP case 3 (see [HO-deploy-3GPP])
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Cell radius:
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577.3333 meters
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Mobility:
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3 km/h
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User intensity:
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{0.7, 1.4, 2.1, 2.8, 3.5, 4.2, 4.9, 5.6, 6.3, 7.0}
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Media traffic model:
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Same as defined in Section 2.1.2
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Other traffic models:
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Downlink simulation:
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Maximum of 2 Mbps/cell (web browsing or FTP traffic following default TCP congestion control [RFC 5681])
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Uplink simulation:
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Maximum of 1 Mbps/cell (web browsing or FTP traffic following default TCP congestion control [RFC 5681])
The investigated congestion control algorithms should result in maximum possible network utilization and stability in terms of rate variations, lowest possible end-to-end frame latency, network latency, and Packet Loss Rate (PLR) at different cell load levels.
The evaluation criteria document [
RFC 8868] defines the metrics to be used to evaluate candidate algorithms. Considering the nature and distinction of cellular networks, we recommend that at least the following metrics be used to evaluate the performance of the candidate algorithms:
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Average cell throughput (for all cells), shows cell utilization.
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Application sending and receiving bitrate, goodput.
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Packet Loss Rate (PLR).
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End-to-end media frame delay. For video, this means the delay from capture to display.
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Transport delay.
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Algorithm stability in terms of rate variation.