In this paper we consider cell-free (CF) massive MIMO (MaMIMO) systems, which comprise a very large number of geographically distributed access points (APs) serving a much smaller number of users. We exploit channel sparsity to tackle pilot contamination, which originates from the reuse of pilot sequences. Specifically, we consider semi-blind methods for joint channel estimation and data detection. Under the challenging assumption of deterministic parameters, we determine sufficient conditions and necessary conditions for semi-blind identifiability, which guarantee the non-singularity of the Fisher Information Matrix (FIM) and the existence of the Cramer-Rao bound (CRB). We propose a message passing (MP) algorithm which determines the exact channel coefficients in the case of semiblind identifiability. We show that the system is identifiable if the Karp-Sipser algorithm yields an empty core. Additionally, we propose a Bayesian semi-blind approach which results in an effective algorithm for joint channel estimation and multi-user detection. This algorithm alternates between channel estimation and linear multi-user detection. Numerical simulations verify the analytical derivations.

Smart meters that allow information to flow between users and utility service providers are expected to foster intelligent energy consumption. Previous studies focusing on demand-side management have been predominantly restricted to factors that utilities can manage and manipulate, but have ignored factors specific to residential characteristics. They also often presume that households consume similar amounts of energy and electricity. To fill these gaps in literature, the authors investigate two research questions: (RQ1) Does a data mining approach outperform traditional statistical approaches for modelling residential energy consumption? (RQ2) What factors influence household energy consumption? They identify household clusters to explore the underlying factors central to understanding electricity consumption behavior. Different clusters carry specific contextual nuances needed for fully understanding consumption behavior. The findings indicate electricity can be distributed according to the needs of six distinct clusters and that utilities can use analytics to identify load profiles for greater energy efficiency.

State government has been moving from manual and paper-based processes to digital services. However, digital divide, declining trust in technology, and low IT/IS adoption rates by public sector employees are important challenges for successful delivery of e-government services to citizens. Previous studies in the area of IT/IS adoption and e-government have mainly focused on citizens. This paper examines IT/IS adoption by employees rather than citizens and the focus is on non-market environment and state government agencies. A research model has been proposed based on the theory of planned behavior (TPB) and technology acceptance model (TAM) which has been extended to include digital divide related constructs and trust in technology. To test the proposed model, a survey was conducted among early adopters of Office 365 at Illinois Department of Transportation (IDOT) in Springfield and Chicago. The paper contributes to research on IT/IS adoption in public sector. The findings also provide insightful design and practical implications for successful IT/IS deployment in public sector.

This paper investigates the relationship between the use of digital and non-digital sources of information on sustainable farming practices, institutional pressure and adoption of such practices by farmers in Brazilian semi-arid lands. The research uses a model based on the theory of reasoned action (TRA) and the institutional theory. Our results for a sample of 100 Brazilian farmers show that non-digital sources of information and ‘Coercive’ and ‘Normative’ pressures have a positive impact on farmers’ attitude towards and actual adoption of sustainable farming practices. However, digital sources of information such as TV and Radio do not play a significant role. In addition, pro-environmental attitude drives sustainable behaviour through the adoption of three out of the five sustainable farming practices investigated. Research and policy implications are also discussed.

Cell-free MIMO, employing distributed antenna systems (DAS), is a promising approach to deal with the capacity crunch of next generation wireless communications. In this paper, we consider a wireless network with transmit and receive antennas distributed according to homogeneous point processes. The received signals are jointly processed at a central processing unit. We study if the favorable propagation properties, which enable almost optimal low complexity detection via matched filtering in massive MIMO systems, hold for DAS with line of sight (LoS) channels and general attenuation exponent. Making use of Euclidean random matrices (ERM) and their moments, we show that the analytical conditions for favorable propagation are not satisfied. Hence, we propose multistage detectors, of which the matched filter represents the initial stage. We show that polynomial expansion detectors and multistage Wiener filters coincide in DAS and substantially outperform matched filtering. Simulation results are presented which validate the analytical results.

We consider a cell-free MIMO system in uplink, comprising a massive number of distributed transmit and receive antennas. In our distributed antenna system (DAS), transmit and receive antennas are distributed according to homogeneous point processes (PP) and the received signals are processed jointly at a central processing unit (CPU). In centralized massive MIMO systems, the phenomenon of favorable propagation has been observed: when the number of receive antennas tends to infinity while the number of transmit antennas remains finite, the users' channels become almost orthogonal and low complexity detection via matched filtering is almost optimal. We analyze the properties of DASs in asymptotic conditions when the network dimensions go to infinity with given intensities of the transmit and receive antenna PPs. We study the analytical conditions of favorable propagation in DASs with two kinds of channels, namely, channels with path loss and transmit and receive antennas in line of sight (LoS) or in multipath Rayleigh fading. We show that the analytical conditions of favorable propagation are satisfied for channels impaired by path loss and Rayleigh fading while they do not hold in the case of LoS channels, motivating the use and analysis of multi-stage receivers. Simulation results of the favorable propagation conditions and the performance of multi-stage detectors for finite systems validate the asymptotic analytical results.

The continuous development of energy management systems, coupled with a growing population, and increasing energy consumption, highlights the necessity to develop a deep understanding of household energy consumption behavior and interventions that facilitate behavioral change. Using a data mining segmentation technique, 2,505 Northern Ireland households were segmented into four distinctive profiles, based on their energy consumption patterns, socio-demographic, and dwelling characteristics. The change in attitude towards energy consumption behavior was analyzed to evaluate the impact of smart meter feedback as well. The key finding was 81% of trial participants perceived smart meters to be helpful in reducing their energy consumption. In addition, we found that the potential to reduce energy bills and environmental concerns were the strongest motivations for behavior change.

Using panel data for 52 developed and developing countries over the period 1998-2006, this article examines the links between information and communication technology diffusion and human development. We conducted a panel regression analysis of the investments per capita in healthcare, education and information and communication technology against human development index scores. Using a quantile regression approach, our findings suggest that changes in healthcare, education and information and communication technology provision have a stronger impact on human development index scores for less developed than for highly developed countries. Furthermore, at lower levels of development education fosters development directly and also indirectly through their enhanced effects on ICT. At higher levels of development education has only an indirect effect on development through the return to ICT.

This study investigates the impact of FDI and trade openness on ICT diffusion in the Asia-Pacific and Middle East regions from 1996-2005. The results indicate that while dissimilarities exist between the economies included in this study in terms of their level of socio-economic and political development, education and the growth of GDP have had a positive impact on ICT diffusion in both regions. However, while FDI has generally had a positive and significant impact on ICT diffusion in Asia-Pacific economies, its impact on Middle Eastern economies has been detrimental. The results of this study also show that trade-openness has had, in general, a positive and significant impact on ICT diffusion.