## 2 System Model  
We consider Figure 1 as the basis of our communication system with RIS. It is assumed that the system uses OFDM to cope with frequency-selective fading. In this study, we consider three different scenarios; two of them are outdoor and indoor, and the last one is indoor only. In every scenario, there are surrounding obstacles that can easily block or obstruct communication links. Such a fact presents itself as critical especially in cases where direct LOS is used, or when the signal suffers attenuation losses. LOS and NLOS cases can be assisted with RIS panels. We consider the downlink and uplink of an OFDM-based mMIMO system, where a BS is equipped with \(N_{tx}/N_{rx}\) antennas that transmit to \(N_{u}\) users. Between each BS and the users, there are plenty of RIS panels with \(N_{RIS}\)-reflecting elements. Each piece of user equipment (UE), which can be an IoT device or a pedestrian, is assumed to have \(N_{rx}/N_{tx}\) antennas, wherein that transmission/reception is composed by grouping the subcarriers into \(N_{prb}\) physical resource blocks (PRBs), with 12 subcarriersin each at any given moment. We denote \(N_{s}\) as the total number of streams assigned to the antennas on each subcarrier with modulated symbols to be transmitted/received by the active antennas. In our scenarios, the communication for different users is based on orthogonal multiple access, and we adopt the optimization method that we proposed in [33], which jointly computes the precoder and the phase-shifts of the RIS panels placed in the vicinity of the receiver and transmitter. Such a strategy aims to maximize the achievable rate in multicarrier point-to-point MIMO communication. The adopted algorithm uses the alternating maximization (AM) method to decouple the optimization variables and split the main problem into two simpler ones. The first subproblem is then solved using the singular value decomposition (SVD) combined with water filling, whereas the second one is addressed with the accelerated proximal gradient (APG) approach. We refer to the resulting algorithm as AM-SVD-APG. Table 1 of [12] summarizes all steps of the proposed joint precoding and RIS optimization algorithm named AM-SVD-APG. This method relies on iteratively applying a gradient-based step followed by proximal mapping.  
Operators of 5G mobile networks (MNOs) are looking to adopt open, virtualized, C-RAN networks for greater network flexibility and cost savings. MNOs have been moving their networks from physical hardware to virtual and cloud-based software deployments since 4G. This step towards virtualization is well underway for the core network. This goal is also valid for the RAN of 5G and B5G. Cell site antennas have remote radio unit (RRUs) connecting to the central office where the baseband unit (BBU) is localized, with the option of intermediate distributed units with intelligence processing, as shown in Figure 2. The processing power distribution between BBU and RRU depends on the specific use case and scenario. As shown in Figure 2, each transmission and reception point (TRP) is equipped with one uniform planar array (UPA) of antennas per sector.  
Figure 1: Illustration of a mMIMO communication system aided by RIS, consisting of BS, UE, and RIS with \(N_{ris}\)-reflecting elements.