Final report on the evaluation of RRM/CRRM algorithms

Deliverable public del projecte EVERESTThis deliverable provides a definition and a complete evaluation of the RRM/CRRM algorithms selected in D11 and D15, and evolved and refined on an iterative process. The evaluation will be carried out by means of simulations using the simulators provided at D07, and D14.Preprin

Towards More Efficient 5G Networks via Dynamic Traffic Scheduling

Department of Electrical EngineeringThe 5G communications adopt various advanced technologies such as mobile edge computing and unlicensed band operations, to meet the goal of 5G services such as enhanced Mobile Broadband (eMBB) and Ultra Reliable Low Latency Communications (URLLC). Specifically, by placing the cloud resources at the edge of the radio access network, so-called mobile edge cloud, mobile devices can be served with lower latency compared to traditional remote-cloud based services. In addition, by utilizing unlicensed spectrum, 5G can mitigate the scarce spectrum resources problem thus leading to realize higher throughput services. To enhance user-experienced service quality, however, aforementioned approaches should be more fine-tuned by considering various network performance metrics altogether. For instance, the mechanisms for mobile edge computing, e.g., computation offloading to the edge cloud, should not be optimized in a specific metric's perspective like latency, since actual user satisfaction comes from multi-domain factors including latency, throughput, monetary cost, etc. Moreover, blindly combining unlicensed spectrum resources with licensed ones does not always guarantee the performance enhancement, since it is crucial for unlicensed band operations to achieve peaceful but efficient coexistence with other competing technologies (e.g., Wi-Fi). This dissertation proposes a focused resource management framework for more efficient 5G network operations as follows. First, Quality-of-Experience is adopted to quantify user satisfaction in mobile edge computing, and the optimal transmission scheduling algorithm is derived to maximize user QoE in computation offloading scenarios. Next, regarding unlicensed band operations, two efficient mechanisms are introduced to improve the coexistence performance between LTE-LAA and Wi-Fi networks. In particular, we develop a dynamic energy-detection thresholding algorithm for LTE-LAA so that LTE-LAA devices can detect Wi-Fi frames in a lightweight way. In addition, we propose AI-based network configuration for an LTE-LAA network with which an LTE-LAA operator can fine-tune its coexistence parameters (e.g., CAA threshold) to better protect coexisting Wi-Fi while achieving enhanced performance than the legacy LTE-LAA in the standards. Via extensive evaluations using computer simulations and a USRP-based testbed, we have verified that the proposed framework can enhance the efficiency of 5G.clos

Industrial Wireless Sensor Networks

Wireless sensor networks are penetrating our daily lives, and they are starting to be deployed even in an industrial environment. The research on such industrial wireless sensor networks (IWSNs) considers more stringent requirements of robustness, reliability, and timeliness in each network layer. This Special Issue presents the recent research result on industrial wireless sensor networks. Each paper in this Special Issue has unique contributions in the advancements of industrial wireless sensor network research and we expect each paper to promote the relevant research and the deployment of IWSNs

Balancing Interactive Performance and Budgeted Resources in Mobile Computing.

In this dissertation, we explore the various limited resources involved in mobile applications --- battery energy, cellular data usage, and, critically, user attention --- and we devise principled methods for managing the tradeoffs involved in creating a good user experience. Building quality mobile applications requires developers to understand complex interactions between network usage, performance, and resource consumption. Because of this difficulty, developers commonly choose simple but suboptimal approaches that strictly prioritize performance or resource conservation. These extremes are symptoms of a lack of system-provided abstractions for managing the complexity inherent in managing performance/resource tradeoffs. By providing abstractions that help applications manage these tradeoffs, mobile systems can significantly improve user-visible performance without exhausting resource budgets. This dissertation explores three such abstractions in detail. We first present Intentional Networking, a system that provides synchronization primitives and intelligent scheduling for multi-network traffic. Next, we present Informed Mobile Prefetching, a system that helps applications decide when to prefetch data and how aggressively to spend limited battery energy and cellular data resources toward that end. Finally, we present Meatballs, a library that helps applications consider the cloudy nature of predictions when making decisions, selectively employing redundancy to mitigate uncertainty and provide more reliable performance. Overall, experiments show that these abstractions can significantly reduce interactive delay without overspending the available energy and data resources.PHDComputer Science and EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/108956/1/brettdh_1.pd

Journal of Telecommunications and Information Technology, 2018, nr 1

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Smart Planning and Operation in Cellular Networks

Cellular networks are less and less regular as operators add base stations (BSs) to increase coverage and performance. Given these facts, we explore the network planning and operation stages of the downlink of a multi-cell Orthogonal Frequency Division Multiple Access (OFDMA)-based network. In the planning stage, which is an offline process, we look at improving expected performance while maintaining good coverage. To do so, we parameterize offline a simple power map assignment to be used by all BSs. In the operation stage, which is an online process, we look at improving performance by handling load imbalance and hotspots in the network. To do so, we propose a heuristic that modifies the power map (from the planning stage) by allocating subchannels to BSs, and specifying for each BS the transmit power to use on the subchannels. The research questions are as follows: i) Is conventional planning good enough in view of the fact that networks are less and less regular? ii) BS subchannel allocation is typically done only in the planning stage, can we (re)do it more often (i.e., during the operation stage) to improve performance? iii) How can we take load imbalance and hotspots into account when operating a network? To answer these questions, we propose and investigate one planning scheme and one simple and practical operation scheme in the downlink. We evaluate these schemes on three different network topologies (i.e., 19-cell regular, highly irregular, and lightly irregular). For each we consider both uniform and non-uniform distributions of users (i.e., hotspots). The simulations take place in a dynamic setting with arriving and departing users. The contributions are as follows: i) We propose a simple power map assignment that we parameterize to offer good performance and good coverage even in highly irregular networks, ii) We propose a heuristic based on BS coordination that allocates subchannels to BSs and specifies for each BS the transmit power to use on the subchannels to handle load imbalance and hotspots, and iii) A practical heuristic implementation that reduces BS coordination