Improving Capacity and Energy Efficiency of Femtocell Based Cellular Network Through Cell Biasing

Abstract-Future of cellular networks lies in heterogeneity. Heterogeneous cellular networks are characterized by overlay of low power nodes such as microcells, picocells, and femtocells along with traditional macrocell base stations. These nodes help operators to improve system capacity in cost effective manner while making the environment greener by reducing the carbon footprint. Research has shown that femtocells can be an effective solution to handle the increasing demands for indoor mobile traffic. However, low utilization of femtocell resources limits the gain obtained from their large scale deployment. Also, random placement of femtocells accumulate additional interference to macrocell users. In this paper, we introduce the concept of cell biasing for femtocells to improve user association and resource utilization. Our work analyses the effects of cell biasing on femtocell based cellular network and provides improvement in capacity and energy efficiency of the network through frequency reuse and subchannel power control. The obtained analytical results are verified through simulation

Effect of Change in Meaningful Use Intensity of EHR System on Cost of Care

While Health IT has become ubiquitous in US hospitals, the impact of change of its Meaningful Use (MU) certification status on hospitals\u27 cost of care remains underexplored. In this paper, we verify the effect of the change of MU certification status from Stage 1 to Stage 2 on cost of care. We created a panel dataset using two publicly available datasets related to hospitals Meaningful Use attestation status and Medicare payment to hospitals. We use the Difference-in-Differences method and find significant negative impact of change in the MU Stage from 1 to 2 on the average cost of clinical procedure, in short and long term. Therefore, we find empirical evidence that suggests an increase in intensity of Meaningful Use of electronic health record results in lowering of average cost of procedures from the payer’s (Medicare) point of view. Our study has significant implications for Health IT policy makers