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Simulating 5G HetNets

5G Heterogenous networks (HetNets) typically have a multi-tier structure with two (or more) types of BSs operating in the same or different frequency bands. For example, these could be macro BSs that are sparser but with higher transmit power and small (or micro) BSs that are denser and with lower transmit power

The following steps explain one way to simulate a 5G HetNet in NetSim

  • Drag and drop base stations (gNBs), and UEs per your topology
  • Have N classes of BSs (say 2 namely macro and small) based on frequency, transmit power, and bandwidth
  • Let the properties of the 2 classes be: Frequency F1, F2, Bandwidth: B1, B2, and Transmit Power: P1, P2. The antenna types and counts can also be different between the different classes of BSs
  • NetSim will automatically calculate pathloss based on the frequency and location of the UEs/BSs. Shadowing and fading can also be enabled. The pathloss model can be set differently for each tier
  • UEs will (by default in NetSim) associate with the BS from which it receives the highest power (or the SSB channel SNR to be precise). Other association rules - such as biasing for small cells - can be simulated by modifying the source code
  • UEs will see DL interference from other BSs transmitting in the same frequency.
  • Mobility can be configured for the UEs. Handover can occur within/across the HetNet tiers. A3 event-based handover parameters such as TTT and Offset can be configured
  • Backhaul for all BSs is wired connectivity to the core

An example


In a 5G heterogeneous network, we analyze how the handover margin and time-to-trigger parameters influence two performance metrics: the number of handovers and the sum throughput (aggregate throughput of all UEs)

System Model

The example is based on a 3-tier 5G HetNet simulation. The network comprises three gNB tiers at 1.5 GHz, 2.1 GHz, and 3.5 GHz.

Simulating 5G HetNets: figure one

Each tier has a specific pathloss exponent influencing signal attenuation. The transmit power, antenna types (sector and omni-directional), and antenna heights vary across tiers. The simulation area is 10 km², with 60 UEs distributed randomly along with18 tier-I gNBs, 18 tier-II gNBs, and 12 tier-III gNBs distributed randomly. Simulation parameters include gNB and UE antenna configurations, pathloss models, interference models, and mobility settings. Shadowing effects are modeled using a lognormal distribution with a standard deviation of 5 dB. Note that the gNBs across tiers will not interference since they operate at different frequencies.

Simulating 5G HetNets: figure two

Handover Algorithm: The 5G handover procedure implemented in NetSim is based on the Strongest Adjacent Cell Handover Algorithm (Ref: Handover within 3GPP LTE: Design Principles and Performance. Konstantinos Dimou. Ericcson Research).

The algorithm enables each UE to connect to that gNB which provides the highest Reference Signal Received Power (RSRP). Therefore a handover occurs the moment a better gNB (the adjacent cell has offset stronger RSRP, measured as SNR in NetSim) is detected, and is similar to 38.331, Event A3 wherein Neighbor cell’s RSRP becomes Offset better than serving cell’s RSRP.

Handover parameters: The Time to Trigger (TTT) and Handover Margin (HO Margin) are variables in the study. An A3 event-based handover model is used. An Event A3-based HO is triggered when

  1. The SINR of a user from the target gNB becomes higher than the SINR of the user from the serving gNB by an offset. This offset is termed as handover margin.
  2. This condition (C1) is maintained for a duration known as the time to trigger.

The model focuses on the interaction of these parameters and their effect on network performance, measured in terms of handover count and sum throughput.

The scenario in NetSim looks as shown below.

Simulating 5G HetNets: figure one

Results and discussion

Simulating 5G HetNets: figure one

It is evident from the plot that the handover count tends to decrease as the handover margin increases. This trend is consistent across different TTT values, suggesting that a higher handover margin generally results in fewer handovers. The rationale behind this trend it that an increased handover margin leads to more stringent conditions for handover and thereby reduces the frequency of handover occurrences. Shorter TTT values lead to quicker responses to signal changes, resulting in more frequent handovers, while longer TTT values delay the handover process, thereby reducing the handover count. The plot highlights the effects of both the handover margin and the TTT on handover count.

Simulating 5G HetNets: figure one

In the second chart, we see that sum throughput generally rises and then falls with increasing handover margin. For each handover margin we see the throughput again roughly increases and then drops as TTT increases. Initially, with a higher handover margin and/or higher TTT unnecessary and frequent handovers between cells are avoided. This leads to better throughput, but only to a certain extent. Beyond a point, a high handover margin and/or high TTT causes delayed handovers. Users may stay connected to a weaker cell longer, despite being closer to a stronger cell, leading to poorer signal quality and thus lowering throughput.