User-Centric Cell-Free and Co-Located Cellular Large Scale MU-MIMO Systems: A Comparative Performance Study With Spatial Channel Correlation in Dense Urban Scenario

Abstract

Large Scale Multi-user MIMO (LS-MU-MIMO) is a promising technology for the fifthgeneration (5G) and beyond wireless systems. It offers several magnitudes of improvement in data rates and spectral efficiency (SE) due to its ability to suppress the interference and to have the properties of channel hardening and favourable propagation. In its conventional cellular paradigm, a large number of co-located antennas are deployed at the Base Station (BS) to serve a smaller number of user terminals (UTs). In order to deal with the inter-cell interferences more efficiently to achieve higher SE, a Cell-Free paradigm was proposed. Previous studies, which compare the two network deployments, relied on idealized assumptions, such as perfect channel state information, uncorrelated channels, and single-cell processing analysis-based, to name a few. This paper intends to bring further understanding of these two paradigms by examining the potential benefits of each paradigm in more realistic scenarios. Specifically, the influence of channel correlation on the achieved performance and network density in dense urban scenarios is investigated. Here, the performance of a Cell-Free network versus a traditional Co-located Cellular network structure has been compared in a more realistic setting. The comparison is carried out in different settings, taking into consideration the dense urban scenario, which supports low-to-moderate mobility and channel dispersion. First, we study the system performance gain in terms of Per-Terminal SE for different ratios of Antenna-UT and pilot scalers. Next, the Area-SE, defined as the sum SE of all UTs per unit area, is considered for different values of network density. Then, the channel estimation accuracy for both network deployments is compared, and its impact on the system performance as the Antenna-UT ratio increases is presented. Further, the impact of the spatially correlated channels is investigated in both network configurations. Finally, fronthaul requirements and distributed implementation in Cell-Free system deployment are discussed. Numerical simulations have been performed to investigate the performance gap between the two network deployments. Considering a cell-free system with scalable linear detectors and a large number of APs, the results show that the impact of noise and small-scale fading vanishes; moreover, a reduction in the non-coherent interference is observed in the same way as in the Co-Cellular LS-MU-MIMO systems. The findings indicate that employing linear detectors results in non-increasing Per-Terminal SE as the network density increases. It is also found that Area-SE grows exponentially with the network density in both system deployments. Moreover, the increase in the Antenna-UT ratio improves the Per-Terminal SE and channel estimation accuracy. However, increasing the pilot scalers affects the systems' behavior in both deployments differently. Furthermore, local detection schemes are investigated, demonstrating the advantages of distributed implementation in the Cell-Free...

Local-Partial Signal Combining Schemes for Cell-Free Large-Scale MU-MIMO Systems with Limited Fronthaul Capacity and Spatial Correlation Channels

“…The UTs and the APs are distributed uniformly at random in the deployed area. For this simulation setup, the key simulation parameters that have been selected are reported in [25]. The large-scale fading coefficients are given as [17]…”

“…There are typically two implementation approaches for cell-free systems [24][25][26][27]: completely centralized and distributed. In the centralized approach, all signal processing is performed at the CPU.…”

Performance Evaluation of Reconfigurable Intelligent Surface against Distributed Antenna System at the Cell Edge

“…DAS is an architecture wherein many antenna elements are geographically distributed and connect to a central BS in order to shorten the distance to the end users [14]. DAS provide coverage to the nearby users, and they are connected to the central BS via highspeed low-latency links, fiber or microwave [16,17], or connected to the CPU at the central BS through fronthaul links [18]. Intuitively, uniformly distributed antenna clusters in each cell provide a significantly higher chance for a cell-edge user to be close to some BS antenna in the neighboring cell [19].…”