3,589 research outputs found

    Hierarchical Radio Resource Optimization for Heterogeneous Networks with Enhanced Inter-cell Interference Coordination (eICIC)

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    Interference is a major performance bottleneck in Heterogeneous Network (HetNet) due to its multi-tier topological structure. We propose almost blank resource block (ABRB) for interference control in HetNet. When an ABRB is scheduled in a macro BS, a resource block (RB) with blank payload is transmitted and this eliminates the interference from this macro BS to the pico BSs. We study a two timescale hierarchical radio resource management (RRM) scheme for HetNet with dynamic ABRB control. The long term controls, such as dynamic ABRB, are adaptive to the large scale fading at a RRM server for co-Tier and cross-Tier interference control. The short term control (user scheduling) is adaptive to the local channel state information within each BS to exploit the multi-user diversity. The two timescale optimization problem is challenging due to the exponentially large solution space. We exploit the sparsity in the interference graph of the HetNet topology and derive structural properties for the optimal ABRB control. Based on that, we propose a two timescale alternative optimization solution for the user scheduling and ABRB control. The solution has low complexity and is asymptotically optimal at high SNR. Simulations show that the proposed solution has significant gain over various baselines.Comment: 14 pages, 8 figure

    Throughput and Energy Efficiency for S-FFR in Massive MIMO Enabled Heterogeneous C-RAN

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    This paper considers the massive multiple-input multiple-output (MIMO) enabled heterogeneous cloud radio access network (C-RAN), in which both remote radio heads (RRHs) and massive MIMO macrocell base stations (BS) are deployed to potentially accomplish high throughput and energy efficiency (EE). In this network, the soft fractional frequency reuse (S-FFR) is employed to mitigate the inter-tier interference. We develop a tractable analytical approach to evaluate the throughput and EE of the entire network, which can well predict the impacts of the key system parameters such as number of macrocell BS antennas, RRH density, and S-FFR factor, etc. Our results demonstrate that massive MIMO is still a powerful tool for improving the throughput of the heterogeneous C-RAN while RRHs are capable of achieving higher EE. The impact of S-FFR on the network throughput is dependent on the density of RRHs. Furthermore, more radio resources allocated to the RRHs can greatly improve the EE of the network

    Using agriculture for development: Supply- and demand-side approaches

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    For most poor countries of today, using agriculture for development is widely recognized as a promising strategy. Yet, in these countries, investment in agriculture has mostly been lagging relative to international norms and recommendations. Current wisdom on how to use agriculture for development is that it requires asset building for smallholder farmers, productivity growth in staple foods, an agricultural transformation (diversification of farming systems toward high value crops), and a rural transformation (value addition through rural non-farm activities linked to agriculture). This sequence has too often been hampered by extensive market and government failures. We outline a theory of change where the removal of market and government failures to use this Agriculture for Development strategy can be addressed through two contrasted and complementary approaches. One is from the “supply-side” where public and social agents (governments, international and bilateral development agencies, NGOs, donors) intervene to help farmers overcome the major constraints to adoption: liquidity, risk, information, and access to markets. The other is from the “demand-side” where private agents (entrepreneurs, producer organizations) create incentives for smallholder farmers to modernize through contracting and vertical coordination in value chains. We review the extensive literature that has explored ways of using Agriculture for Development through these two approaches. We conclude by noting that the supply-side approach has benefited from extensive research but met with limited success. The demand-side approach has promise, but received insufficient attention and is in need of additional rigorous research which we outline

    Device-to-Device Communication in 5G Cellular Networks

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    Owing to the unprecedented and continuous growth in the number of connected users and networked devices, the next-generation 5G cellular networks are envisaged to support enormous number of simultaneously connected users and devices with access to numerous services and applications by providing networks with highly improved data rate, higher capacity, lower end-to-end latency, improved spectral efficiency, at lower power consumption. D2D communication underlaying cellular networks has been proposed as one of the key components of the 5G technology as a means of providing efficient spectrum reuse for improved spectral efficiency and take advantage of proximity between devices for reduced latency, improved user throughput, and reduced power consumption. Although D2D communication underlaying cellular networks promises lots of potentials, unlike the conventional cellular network architecture, there are new design issues and technical challenges that must be addressed for proper implementation of the technology. These include new device discovery procedures, physical layer architecture and radio resource management schemes. This thesis explores the potentials of D2D communication as an underlay to 5G cellular networks and focuses on efficient interference management solutions through mode selection, resource allocation and power control schemes. In this work, a joint admission control, resource allocation, and power control scheme was implemented for D2D communication underlaying 5G cellular networks. The performance of the system was evaluated, and comparisons were made with similar schemes.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

    Service Migration from Cloud to Multi-tier Fog Nodes for Multimedia Dissemination with QoE Support.

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    A wide range of multimedia services is expected to be offered for mobile users via various wireless access networks. Even the integration of Cloud Computing in such networks does not support an adequate Quality of Experience (QoE) in areas with high demands for multimedia contents. Fog computing has been conceptualized to facilitate the deployment of new services that cloud computing cannot provide, particularly those demanding QoE guarantees. These services are provided using fog nodes located at the network edge, which is capable of virtualizing their functions/applications. Service migration from the cloud to fog nodes can be actuated by request patterns and the timing issues. To the best of our knowledge, existing works on fog computing focus on architecture and fog node deployment issues. In this article, we describe the operational impacts and benefits associated with service migration from the cloud to multi-tier fog computing for video distribution with QoE support. Besides that, we perform the evaluation of such service migration of video services. Finally, we present potential research challenges and trends

    Energy efficiency using cloud management of LTE networks employing fronthaul and virtualized baseband processing pool

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    The cloud radio access network (C-RAN) emerges as one of the future solutions to handle the ever-growing data traffic, which is beyond the physical resources of current mobile networks. The C-RAN decouples the traffic management operations from the radio access technologies, leading to a new combination of a virtualized network core and a fronthaul architecture. This new resource coordination provides the necessary network control to manage dense Long-Term Evolution (LTE) networks overlaid with femtocells. However, the energy expenditure poses a major challenge for a typical C-RAN that consists of extended virtualized processing units and dense fronthaul data interfaces. In response to the power efficiency requirements and dynamic changes in traffic, this paper proposes C-RAN solutions and algorithms that compute the optimal backup topology and network mapping solution while denying interfacing requests from low-flow or inactive femtocells. A graph-coloring scheme is developed to label new formulated fronthaul clusters of femtocells using power as the performance metric. Additional power savings are obtained through efficient allocations of the virtualized baseband units (BBUs) subject to the arrival rate of active fronthaul interfacing requests. Moreover, the proposed solutions are used to reduce power consumption for virtualized LTE networks operating in the Wi-Fi spectrum band. The virtualized network core use the traffic load variations to determine those femtocells who are unable to transmit to switch them off for additional power savings. The simulation results demonstrate an efficient performance of the given solutions in large-scale network models

    Advances in Teaching & Learning Day Abstracts 2005

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    Proceedings of the Advances in Teaching & Learning Day Regional Conference held at The University of Texas Health Science Center at Houston in 2005
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