# Latency-Aware DU/CU Placement in Convergent Packet-Based 5G Fronthaul Transport Networks

## Abstract

**:**

## 1. Introduction

#### 1.1. Related Works

#### 1.2. Contributions

- development of an MILP optimization model for latency-aware DU/CU placement;
- in the MILP model, consideration of three different traffic flows (FH, MH, BH) realized jointly in the NGFI network;
- in the MILP model, consideration of limited PP processing capacities in the NGFI network;
- reporting and discussion of results of numerical experiments assessing performance of the MILP optimization model proposed and evaluating NGFI network performance in different scenarios.

## 2. Network Model

#### 2.1. NGFI Network

#### 2.2. Traffic Flows

#### 2.3. Packet Transport Network

#### 2.4. Traffic Model

#### 2.5. Latencies Modeling

- propagation in links,
- storing and forwarding of frames in switches,
- transmission times of bursts of frames, and
- queuing of frames at output ports of switches.

- delay produced by the flows of either higher or equal priority (${t}^{HEP}$), and
- delay produced by lower priority flows (${t}^{LP}$).

## 3. LDCP Problem

- placement (in selected PP nodes) of DU and CU entities realizing baseband processing functions for a set of RU nodes, assuming given constraints on
- maximum processing capacities of the PP nodes,
- maximum latencies of the fronthaul, midhaul, and backhaul flows realized over the packet transport network between the RUs, the PP nodes selected (for DU and CU processing), and the DC node, and

- allocation of bandwidth in network links so that to transport FH, MH, and BH flows, assuming given constraints on links capacities.

#### 3.1. Notation

- a fronthaul flow—between the RU node and the PP node in which the DU entity is placed;
- a midhaul flow—between the PP node in which the DU entity is located and a different PP node in which the CU entity is placed. Note that if the DU and CU are located in the same PP node for a given demand, then the MH flow is not present in the network for this demand;
- a backhaul flow—between the PP node in which the CU entity is located and a DC node.

- if d is an uplink demand, then: ${\mathcal{V}}^{src}(d,f)=\left\{{v}^{R}\left(d\right)\right\}$ and ${\mathcal{V}}^{dest}(d,f)={\mathcal{V}}^{P}$ if $f=\left\{\mathrm{FH}\right\}$, ${\mathcal{V}}^{src}(d,f)={\mathcal{V}}^{P}$ and ${\mathcal{V}}^{dest}(d,f)={\mathcal{V}}^{P}$ if $f=\left\{\mathrm{MH}\right\}$, and ${\mathcal{V}}^{src}(d,f)={\mathcal{V}}^{P}$ and ${\mathcal{V}}^{dest}(d,f)={\mathcal{V}}^{DC}$ if $f=\left\{\mathrm{BH}\right\}$;
- if d is a downlink demand, then: ${\mathcal{V}}^{src}(d,f)={\mathcal{V}}^{P}$ and ${\mathcal{V}}^{dest}(d,f)=\left\{{v}^{R}\left(d\right)\right\}$ if $f=\left\{\mathrm{FH}\right\}$, ${\mathcal{V}}^{src}(d,f)={\mathcal{V}}^{P}$ and ${\mathcal{V}}^{dest}(d,f)={\mathcal{V}}^{P}$ if $f=\left\{\mathrm{MH}\right\}$, and ${\mathcal{V}}^{src}(d,f)={\mathcal{V}}^{DC}$ and ${\mathcal{V}}^{dest}(d,f)={\mathcal{V}}^{P}$ if $f=\left\{\mathrm{BH}\right\}$.

#### 3.2. Problem Statement

- Clustering of RUs: the DUs associated with the RUs that belong to the same cluster are placed in the same PP node;
- PP node assignment for DU processing: for each demand, locate the DU in the PP node that has been assigned to its cluster (i.e., to which its RU belongs to);
- PP node selection for CU processing: a PP node is selected for the CU processing of the demand;
- PP node capacity: the overall DU and CU processing load of all demands processed in each PP node does not exceed the node processing capacity;
- Traffic flows: the traffic flows (FH, MH, and BH) are terminated in the PP nodes in which DU and CU entities are placed; if DU and CU are located in the same PP node, then flow MH is not realized in the network;
- Capacity of link: the overall bit-rates of all flows going through a link must be lower or equal to the link capacity;
- Latency of flow: the latency of a flow cannot be greater than the maximum latency that is allowable for this flow.

#### 3.3. MILP Formulation

**LDCP-MILP formulation:**

## 4. Numerical Results

#### 4.1. Performance of LDCP-MILP Model

#### 4.2. Analysis of Network Performance

#### 4.3. Evaluation of Larger Network Topologies

## 5. Conclusions

## Funding

## Conflicts of Interest

## References

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**Figure 1.**5G network implementing packet-switched next generation fronthaul interface (NGFI) network architecture.

**Figure 2.**Example of distributed unit (DU) and central unit (CU) placement in processing pool (PP) nodes and resulting traffic flows in the NGFI network.

**Figure 4.**Number of active PPs and average overall RU-DU-CU-DC latency in network RING-10 for scenarios with basic links (

**left**) and longer links (

**right**).

**Figure 5.**Percentage of demands with DU and CU processing performed in the same PP node in network RING-10.

**Figure 6.**Maximum latencies of fronthaul, midhaul, and backhaul flows in network RING-10 for scenarios with basic links (

**left**) and longer links (

**right**).

**Figure 7.**Maximum latencies of fronthaul, midhaul, and backhaul flows, and number of active PPs for different values of PP capacity multiplier (C) in networks DRING-16 (

**left**) and MESH-20 (

**right**).

**Figure 8.**Overall capacity of active PP nodes and number of active PPs for different values of PP capacity multiplier (C) in networks DRING-16 (

**left**) and MESH-20 (

**right**).

**Figure 9.**(

**a**) Percentage of demands with DU and CU processing performed in the same PP node (left) and (

**b**) average usage of PP capacity of active PP nodes (right) in a function of PP capacity multiplier (C) in networks DRING-16 and MESH-20.

**Table 1.**Bit-rate and burst size (number of frames) of traffic flows assuming functional split options 7.2 (in fronthaul) and 2 (in midhaul).

Direction | Type of Flow | Flow Bit-Rate (Gbit/s) | Burst Size |
---|---|---|---|

Uplink | Fronthaul | $9.632$ | 52 |

Midhaul | $1.111$ | 6 | |

Backhaul | $1.111$ | 6 | |

Downlink | Fronthaul | $11.113$ | 60 |

Midhaul | $1.111$ | 6 | |

Backhaul | $1.111$ | 6 |

Sets | |
---|---|

$\mathcal{V}$ | network nodes |

${\mathcal{V}}^{P}$ | PP nodes; where ${\mathcal{V}}^{P}\subset \mathcal{V}$ |

$\mathcal{E}$ | network links |

${\mathcal{E}}^{Sout}$ | switch output links |

$\mathcal{D}$ | demands |

${\mathcal{D}}^{U}$ | uplink demands; ${\mathcal{D}}^{U}\subset \mathcal{D}$ |

${\mathcal{D}}^{D}$ | downlink demands; ${\mathcal{D}}^{D}\subset \mathcal{D}$ |

$\mathcal{F}$ | types of flows; $\mathcal{F}=\{\mathrm{FH},\mathrm{MH},\mathrm{BH}\}$ |

${\mathcal{Q}}^{HEP}(d,f)$ | demand-flow pairs of an equal/higher priority than flow f of demand d |

${\mathcal{Q}}^{LP}(d,f)$ | demand-flow pairs of a lower priority than flow f of demand d |

${\mathcal{V}}^{src}(d,f)$ | allowable source nodes of flow f of demand d; ${\mathcal{V}}^{src}(d,f)\subset \mathcal{V}$ |

${\mathcal{V}}^{dest}(d,f)$ | allowable destination nodes of flow f of demand d; ${\mathcal{V}}^{dest}(d,f)\subset \mathcal{V}$ |

$\mathcal{C}$ | clusters of RUs |

Parameters | |

$\alpha (d,f,i,j,e)$ | $=1$ if flow f of demand d originated in node i and terminated in node j is routed through link e |

$C\left(d\right)$ | cluster to which the RU of demand d belongs |

${\rho}^{D}$ | processing load of a DU |

${\rho}^{C}$ | processing load of a CU |

$\rho \left(v\right)$ | processing capacity of PP node $v\in {\mathcal{V}}^{P}$ |

$H(d,f)$ | bit-rate of flow f of demand d |

$K\left(e\right)$ | capacity (bit-rate) of link e |

${L}^{P}\left(e\right)$ | propagation delay of link e |

${L}^{SF}\left(e\right)$ | store-and-forward delay produced in the origin node (switch) of link e |

$L(d,f,e)$ | delay produced by transmission of the burst of frames of flow f of demand d at link e |

${L}^{max}\left(f\right)$ | maximum one-way latency of flow $f\in \mathcal{F}$ |

Variables | |

${x}_{dfij}$ | binary, ${x}_{dfij}=1$ if flow f of demand d is realized between nodes i and j |

${x}_{dfe}$ | binary, ${x}_{dfe}=1$ if flow f of demand d is routed over link e |

${x}_{d\overline{d}f\overline{f}e}$ | binary, ${x}_{d\overline{d}f\overline{f}e}=1$ if flow f of demand d and flow $\overline{f}$ of demand $\overline{d}$ are routed over link e |

${u}_{dv}^{D}$ | binary, ${u}_{dv}^{D}=1$ if DU processing of demand d is performed in PP node v |

${u}_{dv}^{C}$ | binary, ${u}_{dv}^{C}=1$ if CU processing of demand d is performed in PP node v |

${u}_{dv}^{CD}$ | binary, ${u}_{dv}^{CD}=1$ if both CU and DU processing of demand d is performed in PP node v |

${y}_{cv}$ | binary, ${y}_{cv}=1$ if cluster c has assigned PP node v for DU processing |

${y}_{v}$ | binary, ${y}_{v}=1$ if PP node v is active |

${w}_{df}$ | continuous, latency of flow f belonging to demand d |

${w}_{dfe}^{stat}$ | continuous, static latency in link e for flow f belonging to demand d |

${w}_{dfe}^{dyn}$ | continuous, dynamic latency in link e for flow f belonging to demand d |

${w}_{dfe}^{HEP}$ | continuous, latency in link e for flow f of demand d caused by higher/equal priority flows |

${w}_{dfe}^{LP}$ | continuous, latency in link e for flow f of demand d caused by lower priority flows |

Network Link | Link Length (km) | Link Capacity (Gbit/s) |
---|---|---|

Switch–RU | $[0.2\dots 0.5]$ | 25 |

Switch–PP | $[0.2\dots 0.5]$ | 400 |

Switch–DC | $[10\dots 15]$ | 400 |

Switch–switch | $[1\dots 3]$ | 100 |

Scenario | Optimization Results | |||||||
---|---|---|---|---|---|---|---|---|

Network | $\left|\mathcal{D}\right|$ | $\mathbf{C}$ | ${\mathbf{z}}^{\mathbf{LB}}$ | ${\mathbf{z}}^{\mathbf{MILP}}$ | ${\Delta}^{\mathbf{MILP}}$ | ${\mathbf{T}}^{\mathbf{MILP}}$(s) | Active PPs | Latency [$\mathsf{\mu}$s] |

RING-10 | 80 | 1 | 715,485 | 715,668 | 0.03% | 10,800 | 7 | 15,668 |

2 | 418,224 | 418,224 | 0.00% | 935 | 4 | 18,224 | ||

3 | 418,224 | 418,224 | 0.00% | 446 | 4 | 18,224 | ||

DRING-16 | 64 | 1 | 973,213 | 1,013,174 | 3.94% | 10,800 | 10 | 13,174 |

2 | 513,737 | 514,023 | 0.06% | 10,800 | 5 | 14,023 | ||

3 | 513,514 | 513,514 | 0.00% | 961 | 5 | 13,514 | ||

80 | 1 | 1,016,681 | 1,017,050 | 0.04% | 10,800 | 10 | 17,050 | |

2 | 521,205 | 521,443 | 0.05% | 10,800 | 5 | 21,443 | ||

3 | out-of-memory | |||||||

MESH-20 | 40 | 1 | 805,959 | 805,959 | 0.00% | 696 | 8 | 5959 |

2 | 406,450 | 406,450 | 0.00% | 295 | 4 | 6450 | ||

3 | 405,822 | 405,822 | 0.00% | 91 | 4 | 5822 | ||

60 | 1 | 809,233 | 910,424 | 11.12% | 10,800 | 9 | 10,424 | |

2 | 463,297 | 510,047 | 9.17% | 10,800 | 5 | 10,047 | ||

3 | 412,050 | 412,050 | 0.00% | 348 | 4 | 12,050 |

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**MDPI and ACS Style**

Klinkowski, M.
Latency-Aware DU/CU Placement in Convergent Packet-Based 5G Fronthaul Transport Networks. *Appl. Sci.* **2020**, *10*, 7429.
https://doi.org/10.3390/app10217429

**AMA Style**

Klinkowski M.
Latency-Aware DU/CU Placement in Convergent Packet-Based 5G Fronthaul Transport Networks. *Applied Sciences*. 2020; 10(21):7429.
https://doi.org/10.3390/app10217429

**Chicago/Turabian Style**

Klinkowski, Mirosław.
2020. "Latency-Aware DU/CU Placement in Convergent Packet-Based 5G Fronthaul Transport Networks" *Applied Sciences* 10, no. 21: 7429.
https://doi.org/10.3390/app10217429