1,434 research outputs found
Energy-Efficient Resource Allocation Optimization for Multimedia Heterogeneous Cloud Radio Access Networks
The heterogeneous cloud radio access network (H-CRAN) is a promising paradigm
which incorporates the cloud computing into heterogeneous networks (HetNets),
thereby taking full advantage of cloud radio access networks (C-RANs) and
HetNets. Characterizing the cooperative beamforming with fronthaul capacity and
queue stability constraints is critical for multimedia applications to
improving energy efficiency (EE) in H-CRANs. An energy-efficient optimization
objective function with individual fronthaul capacity and inter-tier
interference constraints is presented in this paper for queue-aware multimedia
H-CRANs. To solve this non-convex objective function, a stochastic optimization
problem is reformulated by introducing the general Lyapunov optimization
framework. Under the Lyapunov framework, this optimization problem is
equivalent to an optimal network-wide cooperative beamformer design algorithm
with instantaneous power, average power and inter-tier interference
constraints, which can be regarded as the weighted sum EE maximization problem
and solved by a generalized weighted minimum mean square error approach. The
mathematical analysis and simulation results demonstrate that a tradeoff
between EE and queuing delay can be achieved, and this tradeoff strictly
depends on the fronthaul constraint
Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey
Wireless sensor networks (WSNs) consist of autonomous and resource-limited
devices. The devices cooperate to monitor one or more physical phenomena within
an area of interest. WSNs operate as stochastic systems because of randomness
in the monitored environments. For long service time and low maintenance cost,
WSNs require adaptive and robust methods to address data exchange, topology
formulation, resource and power optimization, sensing coverage and object
detection, and security challenges. In these problems, sensor nodes are to make
optimized decisions from a set of accessible strategies to achieve design
goals. This survey reviews numerous applications of the Markov decision process
(MDP) framework, a powerful decision-making tool to develop adaptive algorithms
and protocols for WSNs. Furthermore, various solution methods are discussed and
compared to serve as a guide for using MDPs in WSNs
Multiband Spectrum Access: Great Promises for Future Cognitive Radio Networks
Cognitive radio has been widely considered as one of the prominent solutions
to tackle the spectrum scarcity. While the majority of existing research has
focused on single-band cognitive radio, multiband cognitive radio represents
great promises towards implementing efficient cognitive networks compared to
single-based networks. Multiband cognitive radio networks (MB-CRNs) are
expected to significantly enhance the network's throughput and provide better
channel maintenance by reducing handoff frequency. Nevertheless, the wideband
front-end and the multiband spectrum access impose a number of challenges yet
to overcome. This paper provides an in-depth analysis on the recent
advancements in multiband spectrum sensing techniques, their limitations, and
possible future directions to improve them. We study cooperative communications
for MB-CRNs to tackle a fundamental limit on diversity and sampling. We also
investigate several limits and tradeoffs of various design parameters for
MB-CRNs. In addition, we explore the key MB-CRNs performance metrics that
differ from the conventional metrics used for single-band based networks.Comment: 22 pages, 13 figures; published in the Proceedings of the IEEE
Journal, Special Issue on Future Radio Spectrum Access, March 201
Energy-Efficient NOMA Enabled Heterogeneous Cloud Radio Access Networks
Heterogeneous cloud radio access networks (H-CRANs) are envisioned to be
promising in the fifth generation (5G) wireless networks. H-CRANs enable users
to enjoy diverse services with high energy efficiency, high spectral
efficiency, and low-cost operation, which are achieved by using cloud computing
and virtualization techniques. However, H-CRANs face many technical challenges
due to massive user connectivity, increasingly severe spectrum scarcity and
energy-constrained devices. These challenges may significantly decrease the
quality of service of users if not properly tackled. Non-orthogonal multiple
access (NOMA) schemes exploit non-orthogonal resources to provide services for
multiple users and are receiving increasing attention for their potential of
improving spectral and energy efficiency in 5G networks. In this article a
framework for energy-efficient NOMA H-CRANs is presented. The enabling
technologies for NOMA H-CRANs are surveyed. Challenges to implement these
technologies and open issues are discussed. This article also presents the
performance evaluation on energy efficiency of H-CRANs with NOMA.Comment: This work has been accepted by IEEE Network. Pages 18, Figure
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