Joint transmission across the cluster of radio remote heads (RRHs) by exploiting the centralized processing of the cloud-radio access network (C-RAN) is a promising technique to overcome the severe interference problems in ultra-dense small cell networks. In practical considerations, local clustering of networks is preferred over global clustering as the number of RRHs that can be jointly transmitted on the network is finite. In this study, we attempt to revisit the principles of the well-known affinity propagation (AP) clustering algorithms, especially for the naive method of determining the exemplar with a fixed threshold. To further explain the decision method, we propose a method to easily determine the threshold using the network map of converged value of messages generated by AP algorithm, by combining Otsu's threshold and density peak searching method with the existing AP clustering algorithm. The proposed algorithm provides higher spectral efficiency than the conventional AP algorithms as well as statically coordinated multi-point (CoMP) techniques, although it has similar execution time as the traditional AP algorithms.
|Title of host publication||2020 IEEE 92nd Vehicular Technology Conference, VTC 2020-Fall - Proceedings|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Publication status||Published - 2020 Nov|
|Event||92nd IEEE Vehicular Technology Conference, VTC 2020-Fall - Virtual, Victoria, Canada|
Duration: 2020 Nov 18 → …
|Name||IEEE Vehicular Technology Conference|
|Conference||92nd IEEE Vehicular Technology Conference, VTC 2020-Fall|
|Period||20/11/18 → …|
Bibliographical noteFunding Information:
ACKNOWLEDGMENT This work was supported in part by the Technology Advancement Research Program funded by the Ministry of Land, Infrastructure, and Transport of Korean government under Grant 20CTAP-C151968-02, in part by the National Research Foundation of Korea (NRF) funded by the Korean government(MSIT) under Grant 2019R1A2C4070361, in part by the National Research Foundation of Korea (NRF) funded by the Korean government(MSIT) under Grant 2018R1D1A3B07050327.
© 2020 IEEE.
All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Electrical and Electronic Engineering
- Applied Mathematics