204 research outputs found
Joint Design of Fronthauling and Hybrid Beamforming for Downlink C-RAN Systems
Hybrid beamforming is known to be a cost-effective and wide-spread solution
for a system with large-scale antenna arrays. This work studies the
optimization of the analog and digital components of the hybrid beamforming
solution for remote radio heads (RRHs) in a downlink cloud radio access network
(C-RAN) architecture. Digital processing is carried out at a baseband
processing unit (BBU) in the "cloud" and the precoded baseband signals are
quantized prior to transmission to the RRHs via finite-capacity fronthaul
links. In this system, we consider two different channel state information
(CSI) scenarios: 1) ideal CSI at the BBU 2) imperfect effective CSI.
Optimization of digital beamforming and fronthaul quantization strategies at
the BBU as well as analog radio frequency (RF) beamforming at the RRHs is a
coupled problem, since the effect of the quantization noise at the receiver
depends on the precoding matrices. The resulting joint optimization problem is
examined with the goal of maximizing the weighted downlink sum-rate and the
network energy efficiency. Fronthaul capacity and per-RRH power constraints are
enforced along with constant modulus constraint on the RF beamforming matrices.
For the case of perfect CSI, a block coordinate descent scheme is proposed
based on the weighted minimum-mean-square-error approach by relaxing the
constant modulus constraint of the analog beamformer. Also, we present the
impact of imperfect CSI on the weighted sum-rate and network energy efficiency
performance, and the algorithm is extended by applying the sample average
approximation. Numerical results confirm the effectiveness of the proposed
scheme and show that the proposed algorithm is robust to estimation errors
Fronthaul-Constrained Cloud Radio Access Networks: Insights and Challenges
As a promising paradigm for fifth generation (5G) wireless communication
systems, cloud radio access networks (C-RANs) have been shown to reduce both
capital and operating expenditures, as well as to provide high spectral
efficiency (SE) and energy efficiency (EE). The fronthaul in such networks,
defined as the transmission link between a baseband unit (BBU) and a remote
radio head (RRH), requires high capacity, but is often constrained. This
article comprehensively surveys recent advances in fronthaul-constrained
C-RANs, including system architectures and key techniques. In particular, key
techniques for alleviating the impact of constrained fronthaul on SE/EE and
quality of service for users, including compression and quantization,
large-scale coordinated processing and clustering, and resource allocation
optimization, are discussed. Open issues in terms of software-defined
networking, network function virtualization, and partial centralization are
also identified.Comment: 5 Figures, accepted by IEEE Wireless Communications. arXiv admin
note: text overlap with arXiv:1407.3855 by other author
Cross-Layer Optimization for Industrial Internet of Things in NOMA-based C-RANs
This paper investigates non-orthogonal multiple access (NOMA)-based cloud radio access networks (C-RANs), where edge caching is adopted to cut down the crowdedness of the fronthaul links. We aim to maximize the energy efficency (EE) by jointly optimizing the power allocation, analog and digital precoding, which turns out to be an intractable non-convex optimization problem. To tackle this problem, we first select cluster heads using the selecting cluster-head (SCH) algorithm, where the analog precoding matrix can be resolved by means of maximizing the array gains. Then, the device grouping algorithm is proposed to group devices according to the equivalent channel correlations, and thus the NOMA devices in the same beam are capable of sharing the same digital precoding vector. Finally, joint digital precoding design and power allocation algorithm is proposed to decompose the resultant optimization problem into two subproblems and solve them iteratively by applying Taylor expansion operation and the minimum mean square error (MMSE) detection. Simulation results validate that the proposed NOMA-based C-RANs with hybrid precoding (HP) scheme can achieve higher SE and EE than traditional orthogonal multiple access (OMA)-based approach and two-stage HP scheme
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