Joint Optimization of Wireless Fronthaul and Access Links in CRAN with a Massive MIMO Central Unit

Huang, Y.; Ikhlef, A.

Abstract

We propose a new downlink cloud radio access network (CRAN) architecture with wireless fronthaul and access links and a central unit (CU) that is equipped with a very large antenna array to serve multiple multi-antenna remote radio heads (RRHs) that in turn serve a number of user equipments (UEs). The use of a very large antenna array at the CU allows to improve the fronthaul capacity leading to improved capacity of the whole network. We propose to minimize the total transmit power at the CU and RRHs subject to maximum powers allowed at the CU and RRHs and rate constraints of UEs via jointly optimizing the power allocation at the CU, the precoders at the RRHs, and the quantization noise covariance matrices. Both independent and joint compression schemes are considered. An iterative algorithm is proposed via reformulating the non-convex optimization problem as a semidefinite relaxation (SDR) problem of which the solution is proved to be also optimal for the original problem. Simulation results show that the performance of the proposed system can significantly decrease the total transmit power compared to two benchmark schemes.

• Presentation Conference Type: Conference Paper (Published)
• Conference Name: 2022 IEEE International Conference on Communications
• Start Date: May 16, 2022
• End Date: May 20, 2022
• Online Publication Date: Aug 11, 2022
• Publication Date: 2022
• Deposit Date: Mar 24, 2022
• Publisher: Institute of Electrical and Electronics Engineers
• Pages: 1906-1911
• Series Title: IEEE International Conference on Communications
• Series ISSN: 1938-1883
• DOI: https://doi.org/10.1109/ICC45855.2022.9839160
• Keywords: Wireless communication , Power demand , Quantization (signal) , Simulation , Massive MIMO , Benchmark testing , Iterative methods
• Public URL: https://durham-repository.worktribe.com/output/1138407