Performance Analysis of Scalable User-Centric HC-RAN Over Rician Fading Channels

In this paper, we analyze the uplink performance of a scalable user-centric heterogeneous cloud-radio access network (HC-RAN) implemented by using dynamic cooperative clustering (DCC) framework over a Rician fading channel with phase shifts. This channel describes various practical aspects, such as...

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Bibliographic Details
Main Authors: Hareesh Ayanampudi, Ravindra Dhuli
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/10012389/
Description
Summary:In this paper, we analyze the uplink performance of a scalable user-centric heterogeneous cloud-radio access network (HC-RAN) implemented by using dynamic cooperative clustering (DCC) framework over a Rician fading channel with phase shifts. This channel describes various practical aspects, such as a deterministic line of sight (LoS) component and random non-LoS (N-LoS) components. To account for the phase shifts due to user mobility, the phase of the LoS component is modeled as a uniformly distributed random variable. We assume that phase information is available at each remote radio head (RRH). We derived the phase aware-minimum mean square error (PA-MMSE) and phase unaware Linear-MMSE estimators and obtained the channel state information (CSI). We derived a closed-form expression for the achievable spectral efficiency (SE) to evaluate the system performance with both estimators. To address the effect of coherent interference in the ultra-dense networks, we developed a two-layer decoding scheme in uplink in which maximum ratio (MR) combining is performed at the RRH and large-scale fading decoding is performed at the base-band unit (BBU) pool. Based on the obtained results, the proposed method enhanced the uplink performance in an ultra-dense scenario. It is validated by comparing it with the simulation results. Moreover, the performance loss caused by the lack of phase knowledge will depend on the pilot sequence length.
ISSN:2169-3536