2020422 · The energy efficiency of a network depends on the efficiency of the data transmission when the traffic load is high, and is characterized by the average spectrum
2022825 · System design by standardization is the foundation that enables energy-efficient design of an entire network. But having a good standard is not enough –
202241 · Piovesan et al. highlight two main network energy efficiency techniques (sleep strategies and cell zooming) and two approaches to reducing the energy use of
2022112 · In this survey paper, we thoroughly review the state-of-the-art on current energy efficiency research. We first categorize and carefully analyse the different power
2022624 · This white paper provides the industry''s first definition of a multi-dimensional energy efficiency evaluation system for 5G wireless networks. It helps
2023810 · Our network energy consumption model can predict the energy consumption for both current and future networks, and additionally enhance the current
2022111 · As the UAV has limited on-board energy, we aim to maximize the network energy efficiency (EE) by jointly optimizing the UAV–user association, UAV location, BS resource allocation, and the load allocation between the two systems. The formulated problem is a mixed-integer nonconvex optimization problem, which is intractable. To
L.1331 : Assessment of mobile network energy efficiency. Recommendation L.1331 (01/22) Approved in 2022-01-13. Status : In force (prepublished) Summary.
In this work, we propose an ANN to SNN conversion methodology that uses a time-based neural coding scheme, named Temporal-Switch-Coding (TSC), and a corresponding TSC spiking neural model. The proposed TSC encoding scheme is more energy efficient than the First-spike latency based encoding schemes such as Time-To-First-Spike (TTFS).
2018316 · Network slicing allows 5G network operators to provide service to multiple tenants with diverging service requirements. This paper considers network slicing aware optimal resource allocation in terms of throughput and energy efficiency. We define a heterogeneous Quality of Service (QoS) framework for a sliced radio access network
2021420 · We address the design and analysis of network behaviors for optimizing network energy efficiency, where each small cell is allowed to adjust not only its
Abstract: As a core performance metric for green communications, the conventional energy efficiency (EE) definition has successfully resolved many issues in the energy-efficient
2018316 · Abstract: Network slicing allows 5G network operators to provide service to multiple tenants with diverging service requirements. This paper considers network slicing aware optimal resource allocation in terms of throughput and energy efficiency. We define a heterogeneous Quality of Service (QoS) framework for a sliced radio access network
6 · Nokia AVA Energy Efficiency can reduce energy costs and carbon footprint by up to 30% with no negative impact on performance or end customer experience. This AI-driven solution can be implemented in a matter of weeks, placing CSPs on the fast-track to massive energy savings. Nokia AVA Energy Efficiency is a telco energy management solution that
2021413 · Ensuring energy-efficient networks with artificial intelligence. Available inEnglish . Finding ways to make networks more energy efficient without negatively impacting QoE is critical to network operators for both cost and sustainability reasons. To assist in these efforts, we are exploring the potential of using artificial
Energy consumption in optical network infrastructures is investigated to identify energy-hungry key components and network functionalities. Solutions based on smart coherent pluggables are presented to increase energy efficiency at the edge of the metro segment.
2023413 · Abstract. Spiking Neural Networks are a type of neural networks where neurons communicate using only spikes. They are often presented as a low-power alternative to classical neural networks, but few works have proven these claims to be true. In this work, we present a metric to estimate the energy consumption of SNNs
20211215 · The energy performance of mobile networks has improved over the years due to introduction of new generations of cellular technology, with better spectral efficiency, advanced hardware with lower power consumption and also many energy saving
2023109 · driven framework to optimise energy efficiency in a real network covering a European metropolitan area. First of all, cell-level statistics were collected from 168 BS sites in the area of study, and for each site we compute a QoS-adjusted energy efficiency metric: Energy efficiency = (Data volume / Energy consumption) × Factorrate where
2023727 · When considering only the energy consumed by the cellular network, the base stations energy consumption goes up to 77%. Vodafone has also reported a similar
2023727 · Green Future Networks – Network Energy Efficiency Version 1.1, 07-December-2021 Page 8 (55) 2 INTRODUCTION AND PURPOSE OF DOCUMENT 2.1 Introduction In NGMN 5G White Paper 1 [2], published at the beginning of 2015, we set a goal of an improvement in energy efficiency by a factor of 2000 within 10 years, such that