Real-time Coordinated Scheduling for Cloud Radio Access Networks in a Software-only Environment using the OpenAirInterface Platform

The objective of this paper is to extend into the OpenAirInterface platform the Coordinated Scheduling (CS) technique to allocate resource blocks among User Equipment (UE) in a wisely way and to control the energy efficiency, the throughput, and the inter-cell interference for Cloud Radio Access Networks (C-RANs). It is achieved by modifying the OpenAirInterface scheduler code, increasing the Remote Radio Unit (RRU) scalability, and employing some component carriers of the Radio Cloud Center (RCC), each one them with one or more UEs. The hardware utilized is composed of general-purpose processors and fast Ethernet transport ports, and the software is recent frequency-domain methodologies in a software-only environment where the use of radio units are not required. However, the USRP B200 mini-i radio unit and the UE (Samsung Galaxy S8) were considered only for validation purposes. The emulations using frequency-domain methodologies, compatible with fourth and fifth-generation cellular systems, allowed real-time emulations and reduced 10-fold the multipath channel’s signal processing complexity compared to time-domain methodologies. The results show we can emulate a real-time static coordinated scheduling proof-of-concept for one C-RAN composed of one RCC, three RRUs, and three UEs. In the end, it is evaluated the reproducibility and the scalability of synthetic networks composed of one RRU and at least one UE, without using software-defined radio units, reducing prototyping uncertainties of the physical hardware and the total price of the experiment.

Rate-Splitting Multiple Access in Cache-Aided Cloud-Radio Access Networks

Rate-splitting multiple access (RSMA) has been recognized as a promising physical layer strategy for 6G. Motivated by the ever-increasing popularity of cache-enabled content delivery in wireless communications, this paper proposes an innovative multigroup multicast transmission scheme based on RSMA for cache-aided cloud-radio access networks (C-RAN). Our proposed scheme not only exploits the properties of content-centric communications and local caching at the base stations (BSs) but also incorporates RSMA to better manage interference in multigroup multicast transmission with statistical channel state information (CSI) known at the central processor (CP) and the BSs. At the RSMA-enabled cloud CP, the message of each multicast group is split into a private and a common part with the former private part being decoded by all users in the respective group and the latter common part being decoded by multiple users from other multicast groups. Common message decoding is done for the purpose of mitigating the interference. In this work, we jointly optimize the clustering of BSs and the precoding with the aim of maximizing the minimum rate among all multicast groups to guarantee fairness serving all groups. The problem is a mixed-integer nonlinear stochastic program (MINLSP), which is solved by a practical algorithm we propose including a heuristic clustering algorithm for assigning a set of BSs to serve each user followed by an efficient iterative algorithm that combines the sample average approximation (SAA) and weighted minimum mean square error (WMMSE) to solve the stochastic non-convex subproblem of precoder design. Numerical results show the explicit max-min rate gain of our proposed transmission scheme compared to the state-of-the-art trivial interference processing methods. Therefore, we conclude that RSMA is a promising technique for cache-aided C-RAN.