The 5th-Generation New Radio (5G-NR) network have been widely deployed around the world in the frequency range 1/range 2 bands. Once specific frequency bands within these ranges can vary across different countries and regions due to regulatory differences, it should be carried out radio network planning to evaluate the 5G coverage considering the particularities of different locations. In this regard, this paper performs a throughly analysis of the following methods for modeling wireless channel propagation in Quito, Ecuador: 3rd Generation Partnership Project, Knife Edge Diffraction (KED), ASTER and Dominant Path model (DPM). Specifically, we focus on KED, ASTER, and DPM for $3.5/28$ -GHz bands to determine the propagation models in three-Dimensional urban macro scenarios. In the radio network planning, the multiple-input multiple-output array antennas, $2\times 2/ 4\times 4$ configuration radiation patterns are deployed using WINPROP tool and $64\times 64$ array configuration with the ATOLL tool. 5G frequency specifications, path-loss, influence of diffraction, reflection, blocking, and fading between transmitter and receiver have been considered for scenarios of interest, such as dense urban and urban in Quito, by using fixed wireless access applications and Vehicular-to-Everything (V2X) communications. In addition, data rates, throughput, and the quality metrics of the received reference signal, i.e., the signal-to-noise plus interference ratio, the reference signal received quality, the reference signal received power, and the received signal strength indicator, are also assessed for each propagation model. Finally, we provide useful insights into propagation models and design usage rules for the bands mentioned in 5G networks for Quito city.

This work presents an overview of fifth-generation (5G) technology, its key functionalities, and its applications. Then, we introduce the topic of 5G radio network planning, making analysis and design methods for coverage and capacity determinations, considering 3GPP standards. With these results, we apply the standards and procedures for a business/dense urban area in Quito city, considering the relevant parameters for calculations and simulations using the Atoll tool. Specifically, we consider the following: the key propagation models Macro/Micro, bandwidths, use cases, data rates, frequency bands (3.5/28 GHz), and modulation orders, etc. Finally, we discuss the proposed network planning and provide some useful insights regarding the 5G mobile network in Quito.

This paper presents an overview of the findings in the handover (HO) process performance within three routes in Quito, Ecuador. We used the Net-Monitor Software to gather information from one of the three national mobile operators. Then, we used the R tool to analyze the HO performance. We analyze several performance metrics, such as HO types, HO conditions, and the ping-pong process. Analysis of the results of the outdoor drive tests demonstrate that the radio frequency (RF) parameters, such as Received Signal Strength Indicator (RSSI), Reference Signal Received Quality (RSRQ), power margin, times radio frequency measurements repeats, and HO percentage to nearest BS, are extremely important during different HO types and ping-pong processes because there are statistical differences in these measured RF parameters. The main measurement results demonstrate that RSSI difference between inter HO and intra HO is 20 dB, whereas HOs are performed when the mobile device (MS) gets farther from the base station (BS), approximately 50% of total HOs. Operator achieves a high ping-pong rate of approximately 10% of total HOs.

This paper proposes a unified Radio Access Network (RAN) planning and dimensioning framework specifically designed for the heterogeneous requirements of sixth-generation (6G) systems. Addressing the limitations of static fifth-generation (5G) planning tools, the proposed methodology mathematically integrates terrestrial, aerial, and non-terrestrial (NTN) domains into a closed-loop optimization engine. The framework couples physically consistent multi-band propagation models (sub-6 GHz to THz) with an Artificial Intelligence (AI)-driven solver that utilizes Pseudo-Spatio-Temporal Residual Networks (PST-ResNet) for traffic prediction and a Self-Coordinated Dynamic Swarm Control System (SC-DSCS) for resource allocation. Unlike generic architectural surveys, this work explicitly formulates the dimensioning problem to jointly optimize site placement, Reconfigurable Intelligent Surface (RIS) phase-shifts, and Fluid Antenna System (FAS) configurations under strict coverage and latency constraints. Validated through extensive system-level simulations across Urban Ultra-Dense, Industrial Internet of Things (IoT), and Smart City scenarios, the results demonstrate that the proposed AI-driven framework achieves a 22% improvement in coverage probability and up to 30% gains in energy efficiency compared to static 5G baselines. The study provides quantitative design guidelines for deploying sustainable, latency-aware 6G infrastructures, bridging the gap between theoretical channel models and practical network dimensioning.

The transition from Fifth Generation (5G) New Radio (NR) systems to Beyond 5G (B5G) and Sixth Generation (6G) networks requires innovative architectures capable of supporting ultra-high data rates, sub-millisecond latency, and massive connection densities in dense urban environments. This paper proposes a comprehensive design methodology for a mini-cluster architecture operating in sub-THz (0.1–0.3 THz) and THz (0.3–3 THz) frequency bands. The proposed framework aims to enhance existing 5G infrastructure while enabling B5G/6G capabilities, with a particular focus on hotspot coverage and mission-critical applications in dense urban environments. The architecture integrates mini Base Stations (mBS), Distributed Edge Computing Units (DECUs), and Intelligent Reflecting Surfaces (IRS) for coverage enhancement and blockage mitigation. Detailed link budget analysis, coverage and capacity planning, and propagation modeling tailored to complex urban morphologies are performed for representative case study cities, Quito and Guayaquil (Ecuador). Simulation results demonstrate up to 100 Gbps peak data rates, sub 100 μs latency, and tenfold energy efficiency gains over conventional 5G deployments. Additionally, the proposed framework highlights the growing importance of THz communications in the 5G evolution towards B5G and 6G systems, where ultra-dense, low-latency, and energy-efficient mini-cluster deployments play a key role in enabling next-generation connectivity for critical and immersive services. Beyond the studied cities, the proposed framework can be generalized to other metropolitan areas facing similar propagation and capacity challenges, providing a scalable pathway for early-stage sub-THz/THz deployments in B5G/6G networks.

The transition to Beyond fifth generation of wireless networks (B5G) and sixth generation of wireless networks (6G) exposes the severe interference and coverage limitations of conventional cell-centric architectures. To overcome these bottlenecks, this paper presents a scalable four-layer radio network planning framework that jointly optimizes the deployment of distributed active antenna arrays and passive reconfigurable intelligent surfaces (RISs). The proposed framework integrates a digital twin (DT) loop within an Open-RAN (O-RAN) architecture, employing multi-agent deep reinforcement learning (MADRL) and fractional programming (FP) for real-time joint active and passive beamforming optimization. Extensive Monte Carlo simulations in a dense urban environment demonstrate a 45% increase in spectral efficiency, a 30% reduction in uplink interference, and an 84% reduction in coverage holes compared to legacy 5G networks. Ultimately, these results provide network operators with a cost-effective, standards-compliant blueprint to extend non-line-of-sight (NLOS) coverage by 40% without incurring the prohibitive capital expenditure (CAPEX) of dense active hardware deployments. Furthermore, the proposed architecture demonstrates a competitive 10–15% margin of improvement in spectral efficiency over recent state-of-the-art DRL-based RIS frameworks.