1,323 research outputs found
Recent advances in radio resource management for heterogeneous LTE/LTE-A networks
As heterogeneous networks (HetNets) emerge as one of the most promising developments toward realizing the target specifications of Long Term Evolution (LTE) and LTE-Advanced (LTE-A) networks, radio resource management (RRM) research for such networks has, in recent times, been intensively pursued. Clearly, recent research mainly concentrates on the aspect of interference mitigation. Other RRM aspects, such as radio resource utilization, fairness, complexity, and QoS, have not been given much attention. In this paper, we aim to provide an overview of the key challenges arising from HetNets and highlight their importance. Subsequently, we present a comprehensive survey of the RRM schemes that have been studied in recent years for LTE/LTE-A HetNets, with a particular focus on those for femtocells and relay nodes. Furthermore, we classify these RRM schemes according to their underlying approaches. In addition, these RRM schemes are qualitatively analyzed and compared to each other. We also identify a number of potential research directions for future RRM development. Finally, we discuss the lack of current RRM research and the importance of multi-objective RRM studies
Leveraging intelligence from network CDR data for interference aware energy consumption minimization
Cell densification is being perceived as the panacea for the imminent capacity crunch. However, high aggregated energy consumption and increased inter-cell interference (ICI) caused by densification, remain the two long-standing problems. We propose a novel network orchestration solution for simultaneously minimizing energy consumption and ICI in ultra-dense 5G networks. The proposed solution builds on a big data analysis of over 10 million CDRs from a real network that shows there exists strong spatio-temporal predictability in real network traffic patterns. Leveraging this we develop a novel scheme to pro-actively schedule radio resources and small cell sleep cycles yielding substantial energy savings and reduced ICI, without compromising the users QoS. This scheme is derived by formulating a joint Energy Consumption and ICI minimization problem and solving it through a combination of linear binary integer programming, and progressive analysis based heuristic algorithm. Evaluations using: 1) a HetNet deployment designed for Milan city where big data analytics are used on real CDRs data from the Telecom Italia network to model traffic patterns, 2) NS-3 based Monte-Carlo simulations with synthetic Poisson traffic show that, compared to full frequency reuse and always on approach, in best case, proposed scheme can reduce energy consumption in HetNets to 1/8th while providing same or better Qo
Interference Management Based on RT/nRT Traffic Classification for FFR-Aided Small Cell/Macrocell Heterogeneous Networks
Cellular networks are constantly lagging in terms of the bandwidth needed to
support the growing high data rate demands. The system needs to efficiently
allocate its frequency spectrum such that the spectrum utilization can be
maximized while ensuring the quality of service (QoS) level. Owing to the
coexistence of different types of traffic (e.g., real-time (RT) and
non-real-time (nRT)) and different types of networks (e.g., small cell and
macrocell), ensuring the QoS level for different types of users becomes a
challenging issue in wireless networks. Fractional frequency reuse (FFR) is an
effective approach for increasing spectrum utilization and reducing
interference effects in orthogonal frequency division multiple access networks.
In this paper, we propose a new FFR scheme in which bandwidth allocation is
based on RT/nRT traffic classification. We consider the coexistence of small
cells and macrocells. After applying FFR technique in macrocells, the remaining
frequency bands are efficiently allocated among the small cells overlaid by a
macrocell. In our proposed scheme, total frequency-band allocations for
different macrocells are decided on the basis of the traffic intensity. The
transmitted power levels for different frequency bands are controlled based on
the level of interference from a nearby frequency band. Frequency bands with a
lower level of interference are assigned to the RT traffic to ensure a higher
QoS level for the RT traffic. RT traffic calls in macrocell networks are also
given a higher priority compared with nRT traffic calls to ensure the low
call-blocking rate. Performance analyses show significant improvement under the
proposed scheme compared with conventional FFR schemes
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