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

Dynamic network slicing for multitenant heterogeneous cloud radio access networks

Multitenant cellular network slicing has been gaining huge interest recently. However, it is not well-explored under the heterogeneous cloud radio access network (H-CRAN) architecture. This paper proposes a dynamic network slicing scheme for multitenant H-CRANs, which takes into account tenants' priority, baseband resources, fronthaul and backhaul capacities, quality of service (QoS) and interference. The framework of the network slicing scheme consists of an upper-level, which manages admission control, user association and baseband resource allocation; and a lower-level, which performs radio resource allocation among users. Simulation results show that the proposed scheme can achieve a higher network throughput, fairness and QoS performance compared to several baseline schemes

Fair resource allocation with interference mitigation and resource reuse for LTE/LTE-A femtocell networks

Joint consideration of interference, resource utilization, fairness, and complexity issues is generally lacking in existing resource allocation schemes for Long-Term Evolution (LTE)/LTE-Advanced femtocell networks. To tackle this, we employ a hybrid spectrum allocation approach whereby the spectrum is split between the macrocell and its nearby interfering femtocells based on their resource demands, whereas the distant femtocells share the entire spectrum. A multiobjective problem is formulated for resource allocation between femtocells and is decomposed using a lexicographic optimization approach into two subproblems. A greedy algorithm of reasonably low complexity is proposed to solve these subproblems sequentially. Simulation results show that the proposed scheme achieves substantial throughput and packet loss improvements in low-density femtocell deployment scenarios while performing satisfactorily in high-density femtocell deployment scenarios with substantial complexity and overhead reduction. The proposed scheme also performs nearly as well as the optimal solution obtained by exhaustive search

Multi-objective resource allocation for LTE/LTE-A femtocell/HeNB networks using ant colony optimization

Existing femtocell resource allocation schemes for Long Term Evolution or LTE-Advanced femtocell networks do not jointly achieve efficient resource utilization, fairness guarantee, interference mitigation and reduced complexity in a satisfactory manner. In this paper, a multi-objective resource allocation scheme is proposed to achieve these desired features simultaneously. We first formulate three objective functions to respectively maximize resource utilization efficiency, guarantee a high degree of fairness and minimize interference. A weighted sum approach is then used to combine these objective functions to form a single multi-objective optimization problem. An ant colony optimization algorithm is employed to find the Pareto-optimal solution to this problem. Simulation results demonstrate that the proposed scheme performs jointly well in all aspects, namely resource utilization, fairness and interference mitigation. Additionally, it maintains satisfactory performance in the handover process and has a reasonably low complexity compared to the existing schemes

User association for backhaul load balancing with quality of service provisioning for heterogeneous networks

This letter addresses the user association problem for quality of service (QoS) provisioning and backhaul load balancing (LB) in heterogeneous networks (HetNets). This problem is exacerbated by base stations with different backhaul capacities and users with diverse QoS requirements. A user association scheme is proposed to achieve QoS provisioning and backhaul LB for HetNets. Simulation results show that the proposed scheme outperforms conventional user association schemes in terms of call blocking probability, QoS, and backhaul LB

Adaptive Robust Turbo Equalization for Power-Line Communications

Data communication over power lines requires advanced signal-processing techniques to cope with time-varying intersymbol interference and severe impulsive noise. A further challenge comes from strict regulatory constraints that stipulate low transmission power. In this paper, we propose an adaptive robust turbo equalizer for single-carrier coded systems. The turbo equalizer has a component equalizer to deal with the deep frequency notches present in power-line channels. The component equalizer' exchanges extrinsic information with a component decoder to perform iterative detection. To facilitate adaptive equalization in time-varying power-line channels, a simple system identification-based channel estimator is incorporated. Most important, a nonlinear-matched myriad filter (MMyF) is used for efficient baseband filtering in impulsive channels. The results show that the MMyF is indispensable for the turbo equalizer to achieve reliable channel estimation and data detection in impulsive power lines. Substantial performance improvements over the conventional scheme designed for Gaussian channels are observed

Robust techniques for multiuser CDMA communications in non Gaussian noise environments

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An online learning tool for 5G radio access network dimensioning

The digital-skill gap in the telecommunication industry is widening with the rollout of fifth-generation (5G) cellular networks. The subject of cellular network planning is traditionally taught in advanced university or training courses, mostly in a passive manner because of the lack of suitable hands-on learning tools for effective teacher-learner interactions. Grasping the underlying principles of this subject is often difficult due to the complex interrelationships and high dimensions of the many factors and parameters involved in the network planning process. To fill this gap, this study introduces a standards-compliant 5G radio access network dimensioning (5G-RAND) tool to facilitate active learning of 5G network pre-planning. The 5G-RAND tool has been developed using interactive worksheets with interworking coverage and capacity site count calculators engineered to ensure efficient duplex communications. It allows network planners to track, analyse, and observe the dimensioning outcome by tinkering with network goals, equipment specifications, and channel conditions. Moreover, the tool has been made available online, enabling experiential e-learning of 5G network pre-planning while paving the way for learning more advanced detailed network planning. Classroom observation data collected revealed that learners exposed to the tool demonstrated increased attention and interest in the subject while significantly improving their test scores

Error-resilient transmission of resolution-scalable image and video over wireless channels

A new robust transmission strategy for scalable image and video is proposed. To protect the coded bit-stream according to the channel conditions, the proposed scheme exploits the progressive by resolution' structure of the scalable code-stream and takes into account the unequal importance as well as the effect of channel errors at different resolution levels towards reconstructing the source. A salient feature of the algorithm is its compatibility for multimedia applications requiring multi-resolution transmission to single or multiple clients. Results show that the proposed algorithm enables considerable gains in terms of subjective and objective image qualities over existing approaches.(1