Abstract This paper investigates the energy-efficient resource allocation algorithm for a massive multiple input multiple output (MIMO) system, in which each base station adapts the number of antennas to the daily load profile. Our paper examines the effect of two user location distribution (ULD) models, on the energy-efficiency (EE) of load adaptive masive MIMO system. We propose a resource allocation strategy to adapt the number of antennas based on tracking variations of ULD and cell loading maximizing the EE. We also evaluate impact of cell size, available bandwidth and output power level of the BS on EE at different cell loading.

This paper investigates the allocation model, the flexibility, and the scalability of fully distributed communication architectures for metering systems in smart grids. Smart metering infrastructure aggregates data from Smart Meters (SMs) and sends the collected data to the fog or the cloud data centres to be stored and analysed. The system needs to be scalable and reliable and to respond to increased demand with minimal cost. The problem is to find the optimal distribution of application data among devices, data centres or clouds. The need for support computing at marginal resources, which can be hosted within the building itself or shared within the construction of the complex, has become important over recent years. The resource allocation model is presented to optimize the cost of the resources in the communications and relevance parts of computing (the data processing cost). The fog helps cloud computing connectivity on the edge network. This paper explains how calculation/analysis can be performed closer to the data collection site to complement the analysis that would be undertaken at the data centre. Results for a range of typical scenarios are presented to show the effectiveness of the proposed method.

Introduction of LTE-Advanced network brings a series of new techniques as well as an improvement of the existing ones, which contributes to better performance in relation to LTE network. Enhanced MIMO represents one of LTE-Advanced network’s most significant techniques which enable considerably better performance. Spectral efficiency and throughput are important system performance indicators. The paper aims to estimate LTE-Advanced network performance by applying an enhanced MIMO. The results verify consistency with given the analytical values, as well as which system parameter has the greatest influence on the achieved results. When enhanced MIMO is applied, several performance testing scenarios have been created depending on the parameter which was analysed for the given scenario, namely: LTE-Advanced channel scenario, antenna configuration, number of HARQ retransmissions and the type of subframe mode. DOI: http://dx.doi.org/10.5755/j01.eee.22.1.7698