4,058 research outputs found
Performance analysis and optimal cooperative cluster size for randomly distributed small cells under cloud RAN
One major advantage of cloud/centralized radio access network is the ease of implementation of multi-cell coordination mechanisms to improve the system spectrum efficiency (SE). Theoretically, large number of cooperative cells lead to a higher SE; however, it may also cause significant delay due to extra channel state information feedback and joint processing computational needs at the cloud data center, which is likely to result in performance degradation. In order to investigate the delay impact on the throughput gains, we divide the network into multiple clusters of cooperative small cells and formulate a throughput optimization problem. We model various delay factors and the sum-rate of the network as a function of cluster size, treating it as the main optimization variable. For our analysis, we consider both base stations' as well as users' geometric locations as random variables for both linear and planar network deployments. The output signal-to-interference-plus-noise ratio and ergodic sum-rate are derived based on the homogenous Poisson point processing model. The sum-rate optimization problem in terms of the cluster size is formulated and solved. Simulation results show that the proposed analytical framework can be utilized to accurately evaluate the performance of practical cloud-based small cell networks employing clustered cooperation
Dynamic Radio Cooperation for Downlink Cloud-RANs with Computing Resource Sharing
A novel dynamic radio-cooperation strategy is proposed for Cloud Radio Access
Networks (C-RANs) consisting of multiple Remote Radio Heads (RRHs) connected to
a central Virtual Base Station (VBS) pool. In particular, the key capabilities
of C-RANs in computing-resource sharing and real-time communication among the
VBSs are leveraged to design a joint dynamic radio clustering and cooperative
beamforming scheme that maximizes the downlink weighted sum-rate system utility
(WSRSU). Due to the combinatorial nature of the radio clustering process and
the non-convexity of the cooperative beamforming design, the underlying
optimization problem is NP-hard, and is extremely difficult to solve for a
large network. Our approach aims for a suboptimal solution by transforming the
original problem into a Mixed-Integer Second-Order Cone Program (MI-SOCP),
which can be solved efficiently using a proposed iterative algorithm. Numerical
simulation results show that our low-complexity algorithm provides
close-to-optimal performance in terms of WSRSU while significantly
outperforming conventional radio clustering and beamforming schemes.
Additionally, the results also demonstrate the significant improvement in
computing-resource utilization of C-RANs over traditional RANs with distributed
computing resources.Comment: 9 pages, 6 figures, accepted to IEEE MASS 201
Full-Duplex Cloud Radio Access Network: Stochastic Design and Analysis
Full-duplex (FD) has emerged as a disruptive communications paradigm for
enhancing the achievable spectral efficiency (SE), thanks to the recent major
breakthroughs in self-interference (SI) mitigation. The FD versus half-duplex
(HD) SE gain, in cellular networks, is however largely limited by the
mutual-interference (MI) between the downlink (DL) and the uplink (UL). A
potential remedy for tackling the MI bottleneck is through cooperative
communications. This paper provides a stochastic design and analysis of FD
enabled cloud radio access network (C-RAN) under the Poisson point process
(PPP)-based abstraction model of multi-antenna radio units (RUs) and user
equipments (UEs). We consider different disjoint and user-centric approaches
towards the formation of finite clusters in the C-RAN. Contrary to most
existing studies, we explicitly take into consideration non-isotropic fading
channel conditions and finite-capacity fronthaul links. Accordingly,
upper-bound expressions for the C-RAN DL and UL SEs, involving the statistics
of all intended and interfering signals, are derived. The performance of the FD
C-RAN is investigated through the proposed theoretical framework and
Monte-Carlo (MC) simulations. The results indicate that significant FD versus
HD C-RAN SE gains can be achieved, particularly in the presence of
sufficient-capacity fronthaul links and advanced interference cancellation
capabilities
Millimeter-wave Evolution for 5G Cellular Networks
Triggered by the explosion of mobile traffic, 5G (5th Generation) cellular
network requires evolution to increase the system rate 1000 times higher than
the current systems in 10 years. Motivated by this common problem, there are
several studies to integrate mm-wave access into current cellular networks as
multi-band heterogeneous networks to exploit the ultra-wideband aspect of the
mm-wave band. The authors of this paper have proposed comprehensive
architecture of cellular networks with mm-wave access, where mm-wave small cell
basestations and a conventional macro basestation are connected to
Centralized-RAN (C-RAN) to effectively operate the system by enabling power
efficient seamless handover as well as centralized resource control including
dynamic cell structuring to match the limited coverage of mm-wave access with
high traffic user locations via user-plane/control-plane splitting. In this
paper, to prove the effectiveness of the proposed 5G cellular networks with
mm-wave access, system level simulation is conducted by introducing an expected
future traffic model, a measurement based mm-wave propagation model, and a
centralized cell association algorithm by exploiting the C-RAN architecture.
The numerical results show the effectiveness of the proposed network to realize
1000 times higher system rate than the current network in 10 years which is not
achieved by the small cells using commonly considered 3.5 GHz band.
Furthermore, the paper also gives latest status of mm-wave devices and
regulations to show the feasibility of using mm-wave in the 5G systems.Comment: 17 pages, 12 figures, accepted to be published in IEICE Transactions
on Communications. (Mar. 2015
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