Delay-Aware Uplink Fronthaul Allocation in Cloud Radio Access Networks

TL;DR

This paper proposes a low-complexity, delay-aware fronthaul allocation algorithm for C-RANs, formulated via stochastic optimization, with proven asymptotic optimality and significant performance improvements demonstrated through simulations.

Contribution

It introduces a novel approximate priority function for delay-aware fronthaul allocation in C-RANs, reducing complexity and achieving asymptotic optimality.

Findings

Significant performance gains over baseline methods

Effective delay-aware fronthaul allocation with low complexity

Asymptotic optimality for small cross link gains

Abstract

In cloud radio access networks (C-RANs), the baseband units and radio units of base stations are separated, which requires high-capacity fronthaul links connecting both parts. In this paper, we consider the delay-aware fronthaul allocation problem for C-RANs. The stochastic optimization problem is formulated as an infinite horizon average cost Markov decision process. To deal with the curse of dimensionality, we derive a closed-form approximate priority function and the associated error bound using perturbation analysis. Based on the closed-form approximate priority function, we propose a low-complexity delay-aware fronthaul allocation algorithm solving the per-stage optimization problem. The proposed solution is further shown to be asymptotically optimal for sufficiently small cross link path gains. Finally, the proposed fronthaul allocation algorithm is compared with various baselines through simulations, and it is shown that significant performance gain can be achieved.