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For a couple of decades, optimal use of the restricted amount of accessible spectrum to consider the exponentially increasing interest in throughput has been the focal point of communication systems and signal processing. The sporadic rise in technology has, through the use of sensors, galvanized the once predominantly offline appliances and devices into data generation points and thus pushed the demand for higher throughput (Achlioptas, Karnin, & Liberty, 2013; Balandin, Korzun, Kashevnik, Smirnov, & Gurtov, 2017; Mukubwa & Sokoya, 2020a). The existing fifth generation (5G) and future communication systems are being upgraded to account for this as well as traditional mobile devices.
The primary enabling technologies for 5G networks have been described as the Cloud-Radio Access Network (C-RAN) and the massive Multiple-Input Multiple-Output (MIMO), as they promise to minimize operational costs and boost performance. When using massive MIMO in remote radio heads (RRH), front-haul becomes the limiting factor due to its inherent finite capacity (Francis & Fettweis, 2018). One of the anticipated fronthaul finite capacity solutions is to break functions such that some are performed at the RRH and others at the baseband unit (BBU). Taking this suggested architecture into account, the RRH is tasked with performing basic functions such as beamforming and the BBU is left to perform digital functions like channel estimation. This then makes fronthaul traffic largely dependent on user terminals (UT) data rates and not on antenna numbers (Francis & Fettweis, 2019; J. Park, Kim, Carvalho, & Manch, 2017). This results in massive MIMO partially centralized cloud-radio access (MPC-RAN) network (S. Park, Lee, Chae, & Bahk, 2017).
When paired with distributed cooperation for the case where RRHs are interconnected, partial centralization significantly mitigates capacity constraint and time latency on the fronthaul of MPC-RANs. The common notion is therefore to configure the topology to be adaptive in such a way as to strike a common balance between the constraints of the fronthaul and the complexity of distributed cooperative processing (Peng, Wang, Lau, & Poor, 2015). The BBU 's cooperative processing is intended to suppress inter-RRH interference through the use of the channel state information (CSI) from both the RRHs and the wireless fronthaul (S. H. Park, Simeone, Sahin, & Shamai, 2014).