Robotic systems are increasingly being used in healthcare. These systems improve patient care both by freeing healthcare professionals from repetitive tasks and by assisting them with complex procedures. This analysis examines the development and implementation of the use of robotic systems in healthcare. It also examines the application of artificial intelligence (AI), which focuses on the autonomy of robotic systems, enabling them to perform tasks autonomously. It describes the main areas of use of robots in hospitals, gives examples of the main commercial or research robots, and analyzes the main practical and safety issues associated with the use of these systems. Using the main databases, including PubMed, IEEE Xplore, MDPI, ScienceDirect, ACM Digital Library, BioMed Central, Springer, and others, an extensive search for papers related to the topic was conducted. This resulted in 59 papers being identified as eligible for this review. The article concludes with a discussion of future research areas that will ensure the effective integration of autonomous robotic systems in healthcare.

Reconfigurable Intelligent Surfaces (RISs) are considered to be a key enabling technology for 6G as they can potentially provide a boost in performance with a high energy efficiency. RISs rely on the use of arrays with a large number of low-cost quasi-passive reflecting elements which can be individually tuned in order to shape the radio wave propagation. This can effectively enable the implementation of smart radio environments, increasing the capacity and improving the coverage of the system. Since most RISs related studies focus on evaluating the gains of RIS based solutions in simplified communication scenarios, in this paper we investigate the potential benefits of RISs when integrated into future wireless networks within the context of post-5G/ 6G systems. With this aim, we present an iterative algorithm for accomplishing the joint design of the access point precoder and phase-shifts of the RIS elements considering a multi-stream multiple-input multiple output (MIMO) orthogonal frequency division multiplexing (OFDM) link. Based on this approach, we then present the system-level evaluation of a RIS-aided post-5G/6G network deployment operating in two different bands, mmWave and sub-THz, and which considers both near-field and far-field propagation models. The results obtained in two different environments namely, Indoor Open Office (IOO) and Urban Micro Truncated (UMT), show that the adoption of the proposed RIS-based approach can effectively improve the throughput and coverage area.

Fifth generation (5G) and Beyond-5G (B5G) will be characterized by highly dense deployments, both on network plane and user plane. Internet of Things, massive sensor deployments and base stations will drive even more energy consumption. User behavior towards mobile service usage is witnessing a paradigm shift with heavy capacity, demanding services resulting in an increase of both screen time and data transfers, which leads to additional power consumption. Mobile network operators will face additional energetic challenges, mainly related to power consumption and network sustainability, starting right in the planning phase with concepts like energy efficiency and greenness by design coming into play. The main contribution of this work is a two-tier method to address such challenges leading to positively-offset carbon dioxide emissions related to mobile networks using a novel approach. The first tier contributes to overall power reduction and optimization based on energy efficient methods applied to 5G and B5G networks. The second tier aims to offset the remaining operational power usage by completely offsetting its carbon footprint through geosequestration. This way, we show that the objective of minimizing overall networks’ carbon footprint is achievable. Conclusions are drawn and it is shown that carbon sequestration initiatives or program adherence represent a negligible cost impact on overall network cost, with the added value of greener and more environmentally friendly network operation. This can also relieve the pressure on mobile network operators in order to maximize compliance with environmentally neutral activity.

In this article, we investigate in different scenarios the feasibility of using massive multiple-input–multiple-output (mMIMO) with reconfigurable intelligent surfaces (RISs) to increase the throughput and coverage with high energy efficiency, considering sub-6 GHz, mmWave, and THz bands. With that objective, a centralized radio access network (C-RAN) suitable for beyond fifth-generation (B5G) systems is considered, where we integrate the base stations (BSs) with multiple RISs and IoT devices or user equipment. RISs with a large number of quasi-passive reflecting elements constitute a low-cost approach capable of shaping radio wave propagation and improving wireless connectivity. We consider a scenario where multiple RISs are combined with mMIMO in the uplink in order to provide connectivity to a smart city (with thousands of active low-power IoT devices), wirelessly, in the 3.6 GHz and 28 GHz bands. We also address a scenario where RISs are adopted with mMIMO in the downlink so as to offer connectivity to a stadium with a pitch, (and thousands of active users’ equipment) in the 28 GHz band. Finally, we also studied the connectivity at 100 GHz of a factory in which several RIS panels, replacing most of the BSs equipped with mMIMO, assure improved throughput and coverage. We concluded that RISs are capable of improving the performance in any of these analyzed scenarios at the different frequency bands, justifying that they are a key enabling technology for 6G.

Fourth Generation (4G) wireless communication systems support current and emergent multimedia services such as mobile TV, social networks and gaming, high-definition TV, video teleconferencing, and messaging services. These systems feature the All-over-IP concept and boast improved quality of service. Several important R&D activities are curren