and Nguyen, Huan X. ORCID logoORCID: https://orcid.org/0000-0002-4105-2558 (2022) Digital twins: a survey on enabling technologies, challenges, trends and future prospects. IEEE Communications Surveys and Tutorials .

This paper studies the downlink problem of a cloud-based central station (CCS) to multiple base stations (BSs) in a heterogeneous cellular network sharing the same time and frequency resources. We adopt non-orthogonal multiple access (NOMA) and propose power allocation for the wireless downlink in the heterogeneous cloud radio access network (HCRAN). Taking into account practical channel modelling with power consumptions at BSs of different cell types (e.g. macro-cell, micro-cell, etc.) and backhauling power, we analyse the energy efficiency (EE) of the practical HCRAN utilising NOMA.Simulation results indicate that the proposed NOMA for the HCRAN outperforms the conventional orthogonal frequency division multiple access (OFDMA) scheme in terms of providing higher EE of up to four times. Interestingly, the results reveal a fact that the EE of the NOMA approach is not always an increasing function of the number of BSs but varies as a quasiconcave function. This motivates us to further introduce an optimisation problem to find the optimal number of BSs that maximises the EE of the HCRAN. It is shown that, with a low power supply at the CCS, a double number of micro BSs can be served by HCRAN providing an improved EE of up to 1.6 times compared to the macro BSs and RRHs, while they achieve the same EE performance with high-power CCS. Index TermsHeterogeneous networks; cloud radio access networks; wireless downlink; non-orthogonal multiple access; energy efficiency.

No abstract

Purpose Algorithms are in the mainstream media news on an almost daily basis. Their context is invariably artificial intelligence (AI) and machine learning decision-making. In media articles, algorithms are described as powerful, autonomous actors that have a capability of producing actions that have consequences. Despite a tendency for deification, the prevailing critique of algorithms focuses on ethical concerns raised by decisions resulting from algorithmic processing. However, the purpose of this paper is to propose that the ethical concerns discussed are limited in scope and suggest that it is not clear what concerns dominate the debate. Design/methodology/approach The paper uses a systematic mapping study approach to review articles appearing in leading UK national papers from the perspective of the ethical concerns over a period of one year. The articles are categorised using a widely cited framework detailing a taxonomy of ethical concerns. The UK context is important because of UK public policy initiatives around AI. Findings The research presented in this paper contributes the first systematic mapping study of articles appearing in leading UK national papers from the perspective of widely accepted ethical concerns such as inscrutable evidence, misguided evidence, unfair outcomes and transformative effects. Originality/value The research presented in this paper contributes the first systematic mapping study of articles appearing in leading UK national papers from the perspective of the ethical concerns. The UK context is important because of UK public policy initiatives around AI. To review the media content from the perspective of ethical concerns, this paper uses the synthesised conceptual map of ethical concerns developed by Mittelstad et al. Given the dominance of that framework, this paper’s contribution is also an important instantiation and experimental validation of using that conceptual map.

No abstract