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

Self-Sustaining Caching Stations: Towards Cost-Effective 5G-Enabled Vehicular Networks

In this article, we investigate the cost-effective 5G-enabled vehicular networks to support emerging vehicular applications, such as autonomous driving, in-car infotainment and location-based road services. To this end, self-sustaining caching stations (SCSs) are introduced to liberate on-road base stations from the constraints of power lines and wired backhauls. Specifically, the cache-enabled SCSs are powered by renewable energy and connected to core networks through wireless backhauls, which can realize "drop-and-play" deployment, green operation, and low-latency services. With SCSs integrated, a 5G-enabled heterogeneous vehicular networking architecture is further proposed, where SCSs are deployed along roadside for traffic offloading while conventional macro base stations (MBSs) provide ubiquitous coverage to vehicles. In addition, a hierarchical network management framework is designed to deal with high dynamics in vehicular traffic and renewable energy, where content caching, energy management and traffic steering are jointly investigated to optimize the service capability of SCSs with balanced power demand and supply in different time scales. Case studies are provided to illustrate SCS deployment and operation designs, and some open research issues are also discussed.Comment: IEEE Communications Magazine, to appea

Labour Administration Reforms in China

[Excerpt] This publication provides an explanation of the comprehensive labour administration system in China, including its recent advances, with emphasis on its public services functions, such as public employment, labour inspection and social insurance services. With the recent improvements to both the legal framework and the institutions of labour administration, it is believed that these public services will play bigger and more active roles in ensuring compliance with legislation and protecting the legitimate rights and interests of employers and workers alike

Approaches to capitation and risk adjustment in health care: an international survey

This report is a survey of current capitation methods in health care finance in developed countries. It was commissioned as part of the fundamental review by UK Ministers of the formula used to allocate health care finance to local areas in England, being carried out under the auspices of the Advisory Committee on Resource Allocation (ACRA). The study was commissioned in February 1999 and completed in May 1999. It was informed by a review of published literature and an extensive network of contacts in government departments and academic institutions. A capitation can be defined as the amount of health service funds to be assigned to a person for the service in question, for the time period in question, subject to any national budget constraints. In effect, a capitation system puts a “price” on the head of every citizen. Capitations are usually varied according to an individual’s personal and social characteristics, using a process known as risk adjustment. In most nations, the intention is that the risk-adjusted capitation should represent an unbiased estimate of the expected costs of the citizen to the health care plan over the chosen time period (typically one year). There is an element of capitation funding in the health care systems of almost all developed countries. Capitation is seen as an important mechanism for securing both equity and efficiency objectives. The review examined capitation schemes in 19 countries and concentrated on major strategic risk adjustment schemes implemented at the national or regional level. It identified two broad approaches to setting capitations, which we term matrix methods and index methods. The fundamental difficulties affecting both approaches are a lack of suitable data and the problem of disentangling needs effects from supply effects on health care utilization. Almost all schemes rely on analysis of empirical data, and various analytic methods have been used for setting capitations. Numerous need and cost factors have been used in setting capitations. However, the choice has usually been determined more by data availability than a compelling link to health care expenditure needs. The review concluded that there were elements of many schemes that may be of relevance to the review of methods currently used in England, and which deserve further investigation. However, until improvements in data availability are in place, it is difficult to envisage major enhancements to methods currently in use.capitation