Performance Analysis of uRLLC in scalable Cell-free Radio Access Network System

TL;DR

This work analyzes ultra-reliable low-latency communication in a scalable cell-free RAN with multiple edge distributed units under finite block length. It derives upper and lower bounds on the expected spectral efficiency using ZF-like combining, gamma approximations for interference terms, and Jensen-based bounding, then links large-scale fading and EDU placement to a tractable optimization via distance minimization. An improved graph coloring-based interleaving deployment is proposed to maximize spatial DoF and inter-EDU diversity, with tabu-search enhancements to handle scalability. Simulation validates the bounds and shows that interleaved EDU deployment substantially improves SE under finite block length and imperfect CSI, demonstrating a practical reliability-latency trade-off in scalable CF-RAN architectures.

Abstract

As a critical component of beyond fifth-generation (B5G) and sixth-generation (6G) mobile communication systems, ultra-reliable low-latency communication (uRLLC) imposes stringent requirements on latency and reliability. In recent years, with the improvement of mobile communication network, centralized and distributed processing schemes for cellfree massive multiple-input multiple-output (CF-mMIMO) have attracted significant research attention. This paper investigates the performance of a novel scalable cell-free radio access network (CF-RAN) architecture featuring multiple edge distributed units (EDUs) under the finite block length regime. Closed expressions for the upper and lower bounds of its expected spectral efficiency (SE) performance are derived, where centralized and fully distributed deployment can be treated as two special cases, respectively. Furthermore, the spatial distribution of user equipments (UEs) and remote radio units (RRUs) is examined and the analysis reveals that the interleaving RRUs deployment associated with the EDU can enhance SE performance under finite block length constraints with specific transmission error probability. The paper also compares Monte Carlo simulation results with multi-RRU clustering-based collaborative processing, validating the accuracy of the space-time exchange theory in the scalable CF-RAN scenario. By deploying scalable EDUs, a practical trade-off between latency and reliability can be achieved through spatial degree-of-freedom (DoF), offering a distributed and scalable realization of the space-time exchange theory.

Figures (13)

• Figure 1: The system has $M$ EDUs, $L$ RRUs, each RRU equiped with $N$ antennas, and $K$ single-antenna UEs.
• Figure 2: Channel dispersion varies with the number of receiving antennas, $M=2$,$K=10$,$n=50$,$\varepsilon=10^{-6}$.
• Figure 3: The graph coloring algorithm implementation process, $L=32$,$K=10$.
• Figure 4: System uplink SE CDF verification.
• Figure 5: Comparison of uplink SE between clustering and improved graph coloring strategies under different numbers of EDUs with $n=50$, $\varepsilon=10^{-6}$, $L=300$, $N=1$.