1,287 research outputs found
Cell-centric and user-centric multi-user scheduling in visible light communication aided networks
Visible Light Communication (VLC) combined withadvanced illumination has been expected to become an integralpart of next generation heterogeneous networks at the time ofwriting, by inspiring further research interests. From both theCell-Centric (CC) and the User-Centric (UC) perspectives, variousVLC cell formations, ranging from fixed-shape regular cellswith different Frequency Reuse (FR) patterns and merged cellsemploying advanced transmission scheme to amorphous userspecificcells are investigated. Furthermore, different Multi-UserScheduling (MUS) algorithms achieving Proportional Fairness(PF) are implemented according to different cell formations.By analysing some critical and unique characteristics of VLC,our simulation results demonstrate that, the proposed MUSalgorithms are capable of providing a high aggregate throughputand achieving modest fairness with low complexity in most of thescenarios considered.<br/
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
User association in cloud RANs with massive MIMO
This paper studies a resource allocation problem where a set of users within a specific region is served by cloud radio access network (C-RAN) structure consisting of a set of base-band units (BBUs) connected to a set of radio remote heads (RRHs) equipped with a large number of antennas via limited capacity front-haul links. User association to each RRH, BBU and front-haul link is essential to achieve high rates for cell-edge users under network limitations. We introduce two types of optimization variables to formulate this resource allocation problem: (i) C-RAN user association factor (UAF) including RRH, BBU and front-haul allocation for each user and (ii) power allocation vector. The formulated optimization problem is non-convex with high computational complexity. An efficient two-level iterative approach is proposed. The higher level consists of two steps where, in each step, one of these two optimization variables is fixed to derive the other. At the lower level, by applying different transformations and convexification techniques, the optimization problem in each step is broken down into a sequence of geometric programming (GP) problems to be solved by the successive convex approximation (SCA). Simulation results reveal the effectiveness of the proposed approach to increase the total throughput of network, specifically for cell-edge users. It outperforms the traditional user association approach, in which, each user is first assigned to the RRH with the largest average value of signal strength, and then, based on this fixed user association, front-haul link association and power allocation are optimized
Reliable Prediction of Channel Assignment Performance in Wireless Mesh Networks
The advancements in wireless mesh networks (WMN), and the surge in
multi-radio multi-channel (MRMC) WMN deployments have spawned a multitude of
network performance issues. These issues are intricately linked to the adverse
impact of endemic interference. Thus, interference mitigation is a primary
design objective in WMNs. Interference alleviation is often effected through
efficient channel allocation (CA) schemes which fully utilize the potential of
MRMC environment and also restrain the detrimental impact of interference.
However, numerous CA schemes have been proposed in research literature and
there is a lack of CA performance prediction techniques which could assist in
choosing a suitable CA for a given WMN. In this work, we propose a reliable
interference estimation and CA performance prediction approach. We demonstrate
its efficacy by substantiating the CA performance predictions for a given WMN
with experimental data obtained through rigorous simulations on an ns-3 802.11g
environment.Comment: Accepted in ICACCI-201
Leveraging synergy of SDWN and multi-layer resource management for 5G networks
Fifth-generation (5G) networks are envisioned to predispose service-oriented and flexible edge-to-core infrastructure to offer diverse applications. Convergence of software-defined networking (SDN), software-defined radio (SDR), and virtualization on the concept of software-defined wireless networking (SDWN) is a promising approach to support such dynamic networks. The principal technique behind the 5G-SDWN framework is the separation of control and data planes, from deep core entities to
edge wireless access points. This separation allows the abstraction of resources as transmission parameters of users. In such
user-centric and service-oriented environment, resource management plays a critical role to achieve efficiency and reliability. In this paper, we introduce a converged multi-layer resource management (CML-RM) framework for SDWN-enabled 5G networks, that involves a functional model and an optimization framework. In such framework, the key questions are if 5G-SDWN can be leveraged to enable CML-RM over the portfolio of resources, and reciprocally, if CML-RM can effectively provide performance
enhancement and reliability for 5G-SDWN. In this paper, we tackle these questions by proposing a flexible protocol structure for 5G-SDWN, which can handle all the required functionalities in a more cross-layer manner. Based on this, we demonstrate how the proposed general framework of CML-RM can control the end-user quality of experience. Moreover, for two scenarios of 5G-SDWN, we investigate the effects of joint user-association and resource allocation via CML-RM to improve performance in
virtualized networks
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