Joint User Selection and Energy Minimization for Ultra-Dense Multi-channel C-RAN with Incomplete CSI

TL;DR

This paper introduces a unified framework for optimizing user selection and energy efficiency in dense multi-channel C-RANs with incomplete CSI, using iterative algorithms to minimize power consumption while satisfying network constraints.

Contribution

It proposes a novel joint optimization approach for RRH selection, user association, and beamforming in dense C-RANs with incomplete CSI, employing successive convex approximation and dual decomposition techniques.

Findings

The proposed algorithms effectively reduce network power consumption.

Limited CSI is sufficient to achieve near-optimal performance.

The iterative method guarantees convergence and feasibility.

Abstract

This paper provides a unified framework to deal with the challenges arising in dense cloud radio access networks (C-RAN), which include huge power consumption, limited fronthaul capacity, heavy computational complexity, unavailability of full channel state information (CSI), etc. Specifically, we aim to jointly optimize the remote radio head (RRH) selection, user equipment (UE)-RRH associations and beam-vectors to minimize the total network power consumption (NPC) for dense multi-channel downlink C-RAN with incomplete CSI subject to per-RRH power constraints, each UE's total rate requirement, and fronthaul link capacity constraints. This optimization problem is NP-hard. In addition, due to the incomplete CSI, the exact expression of UEs' rate expression is intractable. We first conservatively replace UEs' rate expression with its lower-bound. Then, based on the successive convex approximation (SCA) technique and the relationship between the data rate and the mean square error (MSE), we propose a single-layer iterative algorithm to solve the NPC minimization problem with convergence guarantee. In each iteration of the algorithm, the Lagrange dual decomposition method is used to derive the structure of the optimal beam-vectors, which facilitates the parallel computations at the Baseband unit (BBU) pool. Furthermore, a bisection UE selection algorithm is proposed to guarantee the feasibility of the problem. Simulation results show the benefits of the proposed algorithms and the fact that a limited amount of CSI is sufficient to achieve performance close to that obtained when perfect CSI is possessed.