The main aspects of this paper are to show the involvement towards coordination strategies amongst multiple RATs and integration of parametric control of higher MAC and upper layer network protocols. Moreover, we also evaluate and examine the possibility to take advantage of the fact of using interworking concepts such as lightweight Internet protocol (LWIP) and LTE-WLAN aggregation (LWA) while making the scheduling decisions. Such a solution would contribute to the software-defined networking (SDN) approach, where multi-RAT aware scheduler adapts to dynamic channel conditions to provide robustness against severe real-time channel conditions. Finally, we provide comparative analysis of multi- RAT scenarios and evaluate the QoE performance of different scheduling algorithms with SINR based information centric LWA switching and QoE-aware LWA switching by using RANC.

This research introduces the importance of the workload prediction for virtualized radio access network (RAN) deployment in the edge micro data center (EMDC). For workload prediction, several machine learning algorithms are evaluated in terms of central processing unit (CPU) usage while deploying the vRAN components.

Communication by jointly precoded transmission from many distributed access points (APs), called cell-free massive multiple-input multiple-output (CF mMIMO), is a promising concept for beyond 5G systems. One of the challenging aspects of CF mMIMO is an efficient management of the radio resources. We propose both reinforcement learning (RL)-based and heuristic precoding aware radio resource scheduling (RRS) algorithms aiming at maximizing sum spectral efficiency (SE). The proposed algorithms allocate resources for Maximum Ratio Transmission (MRT), Zero-Forcing (ZF) and Regularised Zero-Forcing (RZF) precoders. For the resource allocation, both the set of serving APs and the Physical Resource Blocks are considered. In high noise scenarios, the proposed RL-based RRS algorithm combined with the MRT precoder shows 2.4 times higher sum SE than the standard Round Robin scheduler. Moreover, we demonstrate that the proposed heuristic algorithms offer similar sum SE while significantly reducing the complexity compared to the RL-based solution. We also show that the RZF precoding, which is superior to the ZF precoding in noisy environments, results overall in more transmitted power. Therefore, assuming the same radio resource schedule and precoding strategy in the neighbouring cells, it will result in more inter-cell interference and an overall reduced performance.

To keep supporting next-generation requirements, the radio access infrastructure will increasingly densify. Cell-free (CF) network architectures are emerging, combining dense deployments with extreme flexibility in allocating resources to users. In parallel, the Open Radio Access Networks (O-RAN) paradigm is transforming RAN towards an open, intelligent, virtualized, and fully interoperable architecture. This paradigm brings the needed flexibility and intelligent control opportunities for CF networking. In this paper, we document the current O-RAN terminology and contrast it with some common CF processing approaches. We then discuss the main O-RAN innovations and research challenges that remain to be solved.