## 1 Introduction
Since RISs have low power consumption and the possibility to be embedded in surrounding objects, these surfaces can be seen as a cost-effective solution for future wireless networks [11]. We extend our previous work in [12], where we presented an iterative algorithm for RIS-empowered systems to accomplish the joint design of the access point precoder and phase-shifts of the RIS elements, considering a multi-stream MIMO-OFDM link. The strategy aimed to maximize the achievable rate in multicarrier point-to-point MIMO communication. The proposed algorithm used the alternating maximization (AM) method to decouple the optimization variables and split the main problem into two simpler ones. The first subproblem was solved using singular value decomposition (SVD) combined with water filling, whereas the second one was addressed with the accelerated proximal gradient (APG) approach. The resulting algorithm was designated an AM-SVD-APG iterative algorithm. The emphasis of this article is joint precoding and RIS optimization and finding the best places to position the RIS for downlink communications. B5G networks using radio access virtualization strategies, and advanced computational platforms will exploit network densification. The virtual cell concept removes the traditional cell boundary for the end IoT device and provides a consequent reduction in the detrimental \"cell-edge experience\" for the end IoT device. Traditionally, IoT devices are associated with a cell and, as a consequence, the link performance may degrade as a terminal is located far away from the cell center. In a C-RAN, the network determines which BSs are to be associated with each IoT device. It seems that the cell is moving with the IoT device in order to provide a cell-center experience throughout the entire network. Each IoT device is served by its preferred set of BSs. The actual serving set for a IoT device may contain one or multiple BSs and the IoT device's data are partially or fully available at some or a small set of potential serving BSs. The BS controller (central processor) will accommodate each IoT device with its preferred set and transmission mode at every communication instance while considering load and channel state information (CSI) knowledge associated with the BS [13]. We will consider a 5G NR system [14; 15; 16; 17; 18] using scalable OFDM numerology introducing specific subcarrier spacing (SCS), a transmission time interval (TTI), a cyclic prefix (CP), and the number of slots. Higher numerology indices correspond to larger SCS. The numerology index \(n\) depends on various factors (i.e., service requirements, deployment type, carrier frequency, etc.). The introduction of wider SCS is essential for mitigating inter-carrier interference (ICI) and phase noise at millimeter-wave (mmWave) and Terahertz (THz) frequencies. The TTI assumes smaller values ranging from 1 ms to 31.25 \(\upmu\)s for numerology 0 and 5, respectively. Moreover, 5G NR was designed to lower interference and increase EE by reducing always-on transmissions, which is a crucial aspect of extending the lifetime of IoT devices; 5G NR ensures forward compatibility, as it is prepared for future 6G evolution in use cases and technologies. At mmWave and THz frequencies, high capacity and extreme data rates are possible, even though higher frequencies introduce limitations in coverage due to increased signal attenuation [19]. The specifications of 5G NR are projected to accommodate dense urban and micro or indoor scenarios, but with the introduction of mmWave and THz, it may be more likely that some part of the signal is blocked by obstacles or severely affected by distance, which causes a substantial decrease in the signal strength, making it hard to compensate for without the use of RIS elements and advanced signal processing [20; 21]. The large distance attenuation that takes place in the mmWave and THz bands makes it difficult to achieve large coverage under the limitation of the maximum available terminal or BS transmit power.