# Distributed Cell Clustering Based on Multi-Layer Message Passing for Downlink Joint Processing Coordinated Multipoint Transmission

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## Abstract

**:**

## 1. Introduction

## 2. System Model

#### 2.1. Downlink JP-CoMP

#### 2.2. Channel Model

#### 2.3. JP-CoMP Sum Capacity

## 3. Message Passing for JP-CoMP Clustering

#### 3.1. Main Idea

#### 3.2. Problem Formulation

#### 3.3. Message Passing Derivation

Algorithm 1: Proposed distributed clustering algorithm. |

Set $t\leftarrow 1$ and ${{\phantom{\rule{4pt}{0ex}}\tilde{\lambda}}_{ij}}^{(t)}=0\phantom{\rule{4pt}{0ex}},{\phantom{\rule{4pt}{0ex}}{\tilde{\lambda}}_{i}^{m}}^{(t)}\phantom{\rule{4pt}{0ex}}=0$. Repeat |

Base Stations |

Base Stations |

Update ${{\tilde{\mu}}_{ij}}^{(t)}$ and send to neighboring BSs. |

Update ${{\phantom{\rule{4pt}{0ex}}\tilde{\lambda}}_{ij}}^{(t+1)}$ and send to neighboring BSs. |

Update ${{\tilde{\mu}}_{ii}}^{(t)}$ and send to neighboring BSs. |

Update ${\phantom{\rule{4pt}{0ex}}{\tilde{\lambda}}_{i}^{m}}^{(t+1)}$ and send to neighboring BSs. |

$t=t+1$ |

Until all messages have been converged or max iteration reached. |

Compute ${{C}_{ij}}^{(t)}$ and ${{C}_{ii}}^{(t)}$ to determine the cooperating base station. |

If ${{C}_{ij}}^{(t)}=1$ and ${{C}_{ii}}^{(t)}=k$, |

the ith BS, the jth BS, and the kth BS are cooperating base stations. |

If ${{C}_{ij}}^{(t)}=0$ and ${{C}_{ii}}^{(t)}=k$, |

the ith BS and the kth BS are cooperating base stations. |

If ${{C}_{ij}}^{(t)}=1$ and ${{C}_{ii}}^{(t)}=i$, |

the ith BS and the jth BS are cooperating base stations. |

If ${{C}_{ij}}^{(t)}=0$ and ${{C}_{ii}}^{(t)}=i$, |

the ith BS operates alone. |

## 4. Simulation Results

#### 4.1. Simulation Parameters

^{®}Core™ i7-7700 CPU system operating at 3.60 GHz (8 CPUs). The programming software is MATLAB R2018B. In order to achieve reliable results, the simulation results have been averaged over extensive number of random realizations of wireless channels and user drops during simulations. The simulation parameters are shown in Table 1.

#### 4.2. Throughput Evaluation

#### 4.3. Network Scalability

#### 4.4. Complexity Evaluation

## 5. Conclusions

## Author Contributions

## Funding

## Conflicts of Interest

## Abbreviations

JP-CoMP | Joint Processing Coordinated Multipoint |

BS | Base Station |

AP | Affinity Propagation |

## References

- Wong, V.W.S. (Ed.) Key Technologies for 5G Wireless Systems; Cambridge University Press: Cambridge, UK; New York, NY, USA, 2017. [Google Scholar]
- Cisco Systems, Inc. Cisco Visual Networking Index: Global Media Data Traffic Forecast Update, 2016–2021; Cisco White Paper C11-738419-00; Cisco Systems, Inc.: San Jose, CA, USA, February 2017. [Google Scholar]
- Irmer, R.; Droste, H.; Fettweis, G.; Brueck, S.; Mayer, H.-P.; Thiele, L.; Jungnickel, V.; Marsch, P.; Grieger, M. Coordinated Multipoint: Concepts, Performance, and Field Trial Results. IEEE Commun. Mag.
**2011**, 49, 102–111. [Google Scholar] [CrossRef] [Green Version] - Karakayali, M.; Foschini, G.; Valenzuela, R. Advances in Smart Antennas—Network Coordination for Spectrally Efficient Communications in Cellular Systems. IEEE Wirel. Commun.
**2006**, 13, 56–61. [Google Scholar] [CrossRef] - 3GPP. Coordinated Multi-Point Operation for LTE Physical Layer Aspects. 3rd Gener. Partnership Project (3GPP), TR 36.819 R11 v11.2.0. September 2013. Available online: https://portal.3gpp.org/desktopmodules/Specifications/SpecificationDetails.aspx?specificationId=2498 (accessed on 24 July 2020).
- Elfadil, H.E.; Ali, M.A.I.; Abas, M. Performance Evaluation of Joint Processing Coordinated Multipoint Transmission in LTE Networks. In Proceedings of the 2015 International Conference on Computing, Control, Networking, Electronics and Embedded Systems Engineering (ICCNEEE), Khartoum, Sudan, 7–9 September 2015; pp. 287–292. [Google Scholar] [CrossRef]
- Muqaibel, A.H.; Jadallah, A.N. Practical Performance Evaluation of Coordinated Multi-Point (CoMP) Networks. In Proceedings of the 2015 IEEE 8th GCC Conference & Exhibition, Muscat, Oman, 1–4 February 2015; pp. 1–6. [Google Scholar] [CrossRef]
- Bassoy, S.; Farooq, H.; Imran, M.A.; Imran, A. Coordinated Multi-Point Clustering Schemes: A Survey. IEEE Commun. Surv. Tutor.
**2017**, 19, 743–764. [Google Scholar] [CrossRef] - Meurer, M.; Baier, P.; Weber, T.; Lu, Y.; Papathanassiou, A. Joint Transmission: Advantageous Downlink Concept for CDMA Mobile Radio Systems Using Time Division Duplexing. Electron. Lett.
**2000**, 36, 900. [Google Scholar] [CrossRef] - Qiang, L.; Yang, Y.; Shu, F.; Wu, G. Coordinated Beamforming in Downlink CoMP Transmission System. In Proceedings of the 5th International ICST Conference on Communications and Networking in China, Beijing, China, 25–27 August 2010. [Google Scholar] [CrossRef]
- Qiang, L.; Yang, Y.; Shu, F.; Wu, G. Static Clustering for Cooperative Multi-Point (CoMP) in Mobile Communications. In Proceedings of the 2011 IEEE International Conference on Communications (ICC), Kyoto, Japan, 5–9 June 2011; pp. 1–6. [Google Scholar] [CrossRef]
- Moon, J.-M.; Cho, D.-H. Formation of Cooperative Cluster for Coordinated Transmission in Multi-Cell Wireless Networks. In Proceedings of the 2013 IEEE 10th Consumer Communications and Networking Conference (CCNC), Las Vegas, NV, USA, 11–14 January 2013; pp. 528–533. [Google Scholar] [CrossRef]
- Ali, S.S.; Saxena, N. A Novel Static Clustering Approach for CoMP. In Proceedings of the 2012 7th Int. Conf. on Computing and Convergence Technology (ICCCT), Seoul, Korea, 3–5 December 2012; pp. 757–762. [Google Scholar]
- Li, H.; Tian, H.; Qin, C.; Pei, Y. A Novel Distributed Cluster Combination Method for Comp In LTE-A System. In Proceedings of the IEEE 15th International Symposium on Wireless Personal Multimedia Communications (WPMC), Taipei, Taiwan, 24–27 September 2012; pp. 614–618. [Google Scholar]
- Ye, N.; Dong, L.; Tao, X.-M.; Ge, N. Efficient Multi-Cell Clustering for Coordinated Multi-Point Transmission with Blossom Tree Algorithm. In Proceedings of the 2015 IEEE 82nd Vehicular Technology Conference (VTC2015-Fall), Boston, MA, USA, 6–9 September 2015; pp. 1–4. [Google Scholar] [CrossRef]
- Liu, J.; Sun, S. Clustering-Based Interference Management for QoS Guarantees in Dense Small Cell Networks. In Proceedings of the 2016 2nd IEEE International Conference on Computer and Communications (ICCC), Chengdu, China, 14–17 October 2016; pp. 2985–2989. [Google Scholar] [CrossRef]
- Sun, H.; Zhang, X.; Fang, W. Dynamic Cell Clustering Design for Realistic Coordinated Multipoint Downlink Transmission. In Proceedings of the 2011 IEEE 22nd International Symposium on Personal, Indoor and Mobile Radio Communications, Toronto, ON, Canada, 11–14 September 2011; pp. 1331–1335. [Google Scholar] [CrossRef]
- Bassoy, S.; Jaber, M.J.; Imran, M.A.; Xiao, P. Load Aware Self-Organising User-Centric Dynamic CoMP Clustering for 5G Networks. IEEE Access
**2016**, 4, 2895–2906. [Google Scholar] [CrossRef] [Green Version] - Bassoy, S.; Abbasi, Q.H.; Yang, S.; Tafazolli, R. A Load-Aware Clustering Model for Coordinated Transmission in Future Wireless Networks. IEEE Access
**2019**, 7, 92693–92708. [Google Scholar] [CrossRef] - Ren, Y.; Xu, R. An Adaptive Clustering Scheme Based on Modified Density-Based Spatial Clustering of Applications with Noise Algorithm in Ultra-Dense Networks. In Proceedings of the 2019 IEEE 90th Vehicular Technology Conference (VTC2019-Fall), Honolulu, HI, USA, 22–25 September 2019; pp. 1–5. [Google Scholar] [CrossRef]
- Khan, J.; Jacob, L. Learning Based CoMP Clustering for URLLC in Millimeter Wave 5G Networks with Blockages. In Proceedings of the 2019 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS), GOA, India, 16–19 December 2019; pp. 1–6. [Google Scholar] [CrossRef]
- Daher, A.; Coupechoux, M.; Godlewski, P.; Ngouat, P.; Minot, P. A Dynamic Clustering Algorithm for Multi-Point Transmissions in Mission-Critical Communications. IEEE Trans. Wireless Commun.
**2020**, 19, 4934–4946. [Google Scholar] [CrossRef] - Dai, Y.; Lyu, L. NOMA-Enabled CoMP Clustering and Power Control for Green Internet of Things Networks. IEEE Access
**2020**, 8, 90109–90117. [Google Scholar] [CrossRef] - Ma, W.; Zhang, L.; Jiang, Y. Optimized Joint LiFi Coordinated Multipoint Joint Transmission Clustering and Load Balancing For Hybrid LiFi and WiFi Networks. J. Opt. Commun. Netw.
**2020**, 12, 227. [Google Scholar] [CrossRef] - Servetnyk, M.; Fung, C.C. Precoding and Selection for Coordinated Multipoint Transmission in Fronthaul-Constrained Cloud-RAN. IEEE Wireless Commun. Lett.
**2020**, 9, 51–55. [Google Scholar] [CrossRef] - Zhang, H.; Liu, H.; Jiang, C.; Chu, X.; Nallanathan, A.; Wen, X. A Practical Semidynamic Clustering Scheme Using Affinity Propagation in Cooperative Picocells. IEEE Trans. Veh. Technol.
**2015**, 64, 4372–4377. [Google Scholar] [CrossRef] - Wesemann, S.; Fettweis, G. Decentralized Formation of Uplink CoMP Clusters Based on Affinity Propagation. In Proceedings of the 2012 International Symposium on Wireless Communication Systems (ISWCS), Paris, France, 28–31 August 2012; pp. 850–854. [Google Scholar]
- Kschischang, F.R.; Frey, B.; Loeliger, H.-A. Factor Graphs and The Sum-Product Algorithm. IEEE Trans. Inf. Theory
**2001**, 47, 498–519. [Google Scholar] [CrossRef] [Green Version] - Frey, B.J.; Dueck, D. Clustering by Passing Messages Between Data Points. Science
**2007**, 315, 972–976. [Google Scholar] [CrossRef] [PubMed] [Green Version] - Givoni, I.E.; Frey, B.J. A Binary Variable Model for Affinity Propagation. Neural Comput.
**2009**, 21, 1589–1600. [Google Scholar] [CrossRef] [PubMed] - Wang, C.-D.; Lai, J.-H.; Suen, C.Y.; Zhu, J.-Y. Multi-Exemplar Affinity Propagation. IEEE Trans. Pattern Anal. Mach. Intell.
**2013**, 35, 2223–2237. [Google Scholar] [CrossRef] [PubMed]

**Figure 3.**Message passing of each variable. The figure on the left shows the non-diagonal variable and that on the right shows the diagonal variable.

Parameter | Value |
---|---|

Number of cells | 7 cells |

Number of transmitter antennas at each cell | 2 antennas |

Number of receiver antennas at each user mobile | 1 antenna |

Type of CoMP | Joint Processing |

Number of users at each cell * | 100 users |

Cell radius * | 500 m |

BS Transmit Power | 40 dBm |

Subcarrier spacing | 15 kHz |

Number of subcarriers | 1200 |

System bandwidth | 18 MHz |

Noise | −174 dBm/Hz |

Wireless channel modeling | Short-scale fading (Rayleigh) |

Pathloss exponent | 3.7 |

Tranmission time interval | 1 ms |

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**MDPI and ACS Style**

Dewa, G.R.R.; Park, C.; Sohn, I.
Distributed Cell Clustering Based on Multi-Layer Message Passing for Downlink Joint Processing Coordinated Multipoint Transmission. *Appl. Sci.* **2020**, *10*, 5154.
https://doi.org/10.3390/app10155154

**AMA Style**

Dewa GRR, Park C, Sohn I.
Distributed Cell Clustering Based on Multi-Layer Message Passing for Downlink Joint Processing Coordinated Multipoint Transmission. *Applied Sciences*. 2020; 10(15):5154.
https://doi.org/10.3390/app10155154

**Chicago/Turabian Style**

Dewa, Gilang Raka Rayuda, Cheolsoo Park, and Illsoo Sohn.
2020. "Distributed Cell Clustering Based on Multi-Layer Message Passing for Downlink Joint Processing Coordinated Multipoint Transmission" *Applied Sciences* 10, no. 15: 5154.
https://doi.org/10.3390/app10155154