95,951 research outputs found
A cell outage management framework for dense heterogeneous networks
In this paper, we present a novel cell outage management (COM) framework for heterogeneous networks with split control and data planes-a candidate architecture for meeting future capacity, quality-of-service, and energy efficiency demands. In such an architecture, the control and data functionalities are not necessarily handled by the same node. The control base stations (BSs) manage the transmission of control information and user equipment (UE) mobility, whereas the data BSs handle UE data. An implication of this split architecture is that an outage to a BS in one plane has to be compensated by other BSs in the same plane. Our COM framework addresses this challenge by incorporating two distinct cell outage detection (COD) algorithms to cope with the idiosyncrasies of both data and control planes. The COD algorithm for control cells leverages the relatively larger number of UEs in the control cell to gather large-scale minimization-of-drive-test report data and detects an outage by applying machine learning and anomaly detection techniques. To improve outage detection accuracy, we also investigate and compare the performance of two anomaly-detecting algorithms, i.e., k-nearest-neighbor- and local-outlier-factor-based anomaly detectors, within the control COD. On the other hand, for data cell COD, we propose a heuristic Grey-prediction-based approach, which can work with the small number of UE in the data cell, by exploiting the fact that the control BS manages UE-data BS connectivity and by receiving a periodic update of the received signal reference power statistic between the UEs and data BSs in its coverage. The detection accuracy of the heuristic data COD algorithm is further improved by exploiting the Fourier series of the residual error that is inherent to a Grey prediction model. Our COM framework integrates these two COD algorithms with a cell outage compensation (COC) algorithm that can be applied to both planes. Our COC solution utilizes an actor-critic-based reinforcement learning algorithm, which optimizes the capacity and coverage of the identified outage zone in a plane, by adjusting the antenna gain and transmission power of the surrounding BSs in that plane. The simulation results show that the proposed framework can detect both data and control cell outage and compensate for the detected outage in a reliable manner
Integrating Symbolic and Neural Processing in a Self-Organizing Architechture for Pattern Recognition and Prediction
British Petroleum (89A-1204); Defense Advanced Research Projects Agency (N00014-92-J-4015); National Science Foundation (IRI-90-00530); Office of Naval Research (N00014-91-J-4100); Air Force Office of Scientific Research (F49620-92-J-0225
Will 5G See its Blind Side? Evolving 5G for Universal Internet Access
Internet has shown itself to be a catalyst for economic growth and social
equity but its potency is thwarted by the fact that the Internet is off limits
for the vast majority of human beings. Mobile phones---the fastest growing
technology in the world that now reaches around 80\% of humanity---can enable
universal Internet access if it can resolve coverage problems that have
historically plagued previous cellular architectures (2G, 3G, and 4G). These
conventional architectures have not been able to sustain universal service
provisioning since these architectures depend on having enough users per cell
for their economic viability and thus are not well suited to rural areas (which
are by definition sparsely populated). The new generation of mobile cellular
technology (5G), currently in a formative phase and expected to be finalized
around 2020, is aimed at orders of magnitude performance enhancement. 5G offers
a clean slate to network designers and can be molded into an architecture also
amenable to universal Internet provisioning. Keeping in mind the great social
benefits of democratizing Internet and connectivity, we believe that the time
is ripe for emphasizing universal Internet provisioning as an important goal on
the 5G research agenda. In this paper, we investigate the opportunities and
challenges in utilizing 5G for global access to the Internet for all (GAIA). We
have also identified the major technical issues involved in a 5G-based GAIA
solution and have set up a future research agenda by defining open research
problems
A new QoS routing algorithm based on self-organizing maps for wireless sensor networks
For the past ten years, many authors have focused
their investigations in wireless sensor networks. Different
researching issues have been extensively developed: power
consumption, MAC protocols, self-organizing network algorithms,
data-aggregation schemes, routing protocols, QoS
management, etc. Due to the constraints on data processing
and power consumption, the use of artificial intelligence
has been historically discarded. However, in some special
scenarios the features of neural networks are appropriate to
develop complex tasks such as path discovery. In this paper,
we explore and compare the performance of two very well
known routing paradigms, directed diffusion and Energy-
Aware Routing, with our routing algorithm, named SIR,
which has the novelty of being based on the introduction of
neural networks in every sensor node. Extensive simulations
over our wireless sensor network simulator, OLIMPO, have
been carried out to study the efficiency of the introduction
of neural networks. A comparison of the results obtained
with every routing protocol is analyzed. This paper attempts
to encourage the use of artificial intelligence techniques in
wireless sensor nodes
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