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

TL;DR

This paper analyzes the spectral efficiency of a scalable cell-free radio access network architecture with multiple edge units, deriving bounds and examining deployment strategies to optimize latency and reliability for 6G mobile systems.

Contribution

It introduces a novel scalable CF-RAN architecture with closed-form bounds on spectral efficiency, considering finite block length and spatial deployment strategies.

Findings

Interleaving RRUs with EDUs enhances spectral efficiency under finite block length.

Closed-form bounds for spectral efficiency are derived for centralized and distributed deployments.

Monte Carlo simulations validate the space-time exchange theory in the proposed architecture.

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.