A Parameterized Base Station Power Model

Power models are needed to assess the power consumption of cellular Base Station (BS) on an abstract level. Currently available models are either too simplified to cover necessary aspects or overly complex. We provide a parameterized linear power model which covers the individual aspects of a BS which are relevant for a power consumption analysis, especially the transmission bandwidth and the number of radio chains. Details reflecting the underlying architecture are abstracted in favor of simplicity and applicability. We identify current power-saving techniques of cellular networks for which this model can be used. Furthermore, the parameter set of typical commercial BS is provided and compared to the underlying complex model. The complex model is well approximated while only using a fraction of the input parameters.Comment: 9 page

A Novel Multiobjective Cell Switch-Off Framework for Cellular Networks

Cell Switch-Off (CSO) is recognized as a promising approach to reduce the energy consumption in next-generation cellular networks. However, CSO poses serious challenges not only from the resource allocation perspective but also from the implementation point of view. Indeed, CSO represents a difficult optimization problem due to its NP-complete nature. Moreover, there are a number of important practical limitations in the implementation of CSO schemes, such as the need for minimizing the real-time complexity and the number of on-off/off-on transitions and CSO-induced handovers. This article introduces a novel approach to CSO based on multiobjective optimization that makes use of the statistical description of the service demand (known by operators). In addition, downlink and uplink coverage criteria are included and a comparative analysis between different models to characterize intercell interference is also presented to shed light on their impact on CSO. The framework distinguishes itself from other proposals in two ways: 1) The number of on-off/off-on transitions as well as handovers are minimized, and 2) the computationally-heavy part of the algorithm is executed offline, which makes its implementation feasible. The results show that the proposed scheme achieves substantial energy savings in small cell deployments where service demand is not uniformly distributed, without compromising the Quality-of-Service (QoS) or requiring heavy real-time processing

Energy efficiency benefits of RAN-as-a-service concept for a cloud-based 5G mobile network infrastructure

This paper focuses on energy efficiency aspects and related benefits of radio-access-network-as-a-service (RANaaS) implementation (using commodity hardware) as architectural evolution of LTE-advanced networks toward 5G infrastructure. RANaaS is a novel concept introduced recently, which enables the partial centralization of RAN functionalities depending on the actual needs as well as on network characteristics. In the view of future definition of 5G systems, this cloud-based design is an important solution in terms of efficient usage of network resources. The aim of this paper is to give a vision of the advantages of the RANaaS, to present its benefits in terms of energy efficiency and to propose a consistent system-level power model as a reference for assessing innovative functionalities toward 5G systems. The incremental benefits through the years are also discussed in perspective, by considering technological evolution of IT platforms and the increasing matching between their capabilities and the need for progressive virtualization of RAN functionalities. The description is complemented by an exemplary evaluation in terms of energy efficiency, analyzing the achievable gains associated with the RANaaS paradigm

Bayesian online learning for energy-aware resource orchestration in virtualized RANs

Proceedings of: IEEE International Conference on Computer Communications, 10-13 May 2021, Vancouver, BC, Canada.Radio Access Network Virtualization (vRAN) will spearhead the quest towards supple radio stacks that adapt to heterogeneous infrastructure: from energy-constrained platforms deploying cells-on-wheels (e.g., drones) or battery-powered cells to green edge clouds. We perform an in-depth experimental analysis of the energy consumption of virtualized Base Stations (vBSs) and render two conclusions: (i) characterizing performance and power consumption is intricate as it depends on human behavior such as network load or user mobility; and (ii) there are many control policies and some of them have non-linear and monotonic relations with power and throughput. Driven by our experimental insights, we argue that machine learning holds the key for vBS control. We formulate two problems and two algorithms: (i) BP-vRAN, which uses Bayesian online learning to balance performance and energy consumption, and (ii) SBP-vRAN, which augments our Bayesian optimization approach with safe controls that maximize performance while respecting hard power constraints. We show that our approaches are data-efficient and have provably performance, which is paramount for carrier-grade vRANs. We demonstrate the convergence and flexibility of our approach and assess its performance using an experimental prototype.This work was supported by the European Commission through Grant No. 856709 (5Growth) and Grant No. 101017109 (DAEMON); and by SFI through Grant No. SFI 17/CDA/4760

Separation Framework: An Enabler for Cooperative and D2D Communication for Future 5G Networks

Soaring capacity and coverage demands dictate that future cellular networks need to soon migrate towards ultra-dense networks. However, network densification comes with a host of challenges that include compromised energy efficiency, complex interference management, cumbersome mobility management, burdensome signaling overheads and higher backhaul costs. Interestingly, most of the problems, that beleaguer network densification, stem from legacy networks' one common feature i.e., tight coupling between the control and data planes regardless of their degree of heterogeneity and cell density. Consequently, in wake of 5G, control and data planes separation architecture (SARC) has recently been conceived as a promising paradigm that has potential to address most of aforementioned challenges. In this article, we review various proposals that have been presented in literature so far to enable SARC. More specifically, we analyze how and to what degree various SARC proposals address the four main challenges in network densification namely: energy efficiency, system level capacity maximization, interference management and mobility management. We then focus on two salient features of future cellular networks that have not yet been adapted in legacy networks at wide scale and thus remain a hallmark of 5G, i.e., coordinated multipoint (CoMP), and device-to-device (D2D) communications. After providing necessary background on CoMP and D2D, we analyze how SARC can particularly act as a major enabler for CoMP and D2D in context of 5G. This article thus serves as both a tutorial as well as an up to date survey on SARC, CoMP and D2D. Most importantly, the article provides an extensive outlook of challenges and opportunities that lie at the crossroads of these three mutually entangled emerging technologies.Comment: 28 pages, 11 figures, IEEE Communications Surveys & Tutorials 201

Orchestrating energy-efficient vRANs: Bayesian learning and experimental results

Virtualized base stations (vBS) can be implemented in diverse commodity platforms and are expected to bring unprecedented operational flexibility and cost efficiency to the next generation of cellular networks. However, their widespread adoption is hampered by their complex configuration options that affect in a non-traditional fashion both their performance and their power consumption requirements. Following an in-depth experimental analysis in a bespoke testbed, we characterize the vBS power cost profile and reveal previously unknown couplings between their various control knobs. Motivated by these findings, we develop a Bayesian learning framework for the orchestration of vBSs and design two novel algorithms: (i) BP-vRAN, which employs online learning to balance the vBS performance and energy consumption, and (ii) SBP-vRAN, which augments our optimization approach with safe controls that maximize performance while respecting hard power constraints. We show that our approaches are data-efficient, i.e., converge an order of magnitude faster than state-of-the-art Deep Reinforcement Learning methods, and achieve optimal performance. We demonstrate the efficacy of these solutions in an experimental prototype using real traffic traces.This work has been supported by the European Commission through Grant No. 101017109 (DAEMON project), and the CERCA Programme/Generalitat de Catalunya

Modelling the power consumption and trade-offs of virtualised cloud radio access networks

In large-scale computing centres, the advancement of knowledge in regards to the predicted power consumption (PC) and concerns of host servers that run virtual machines (VMs) could improve the capacity planning and networks’ Energy Efficiency (EE). In this paper, a parameterised power model is proposed to explore the individual components within the virtualisation based cloud-radio access network (vC-RAN). The model evaluates the PC and trade-offs of a server undergoing virtualisation. After, cooling and total PC for C-RAN architecture with and without virtualisation have been compared using differentiated parameters, such as varying number of bare-metal base band units (BBUs), VMs and system’s resource blocks (RBs) share/bandwidth. The results show dramatic decrease in the total PC via virtualising the core network (CN). In addition, the degraded performance of each virtualised server is demonstrated via modelling the execution time and overhead costs. These costs have been resulted from increasing the number of hosted VMs and utilised RBs by each VM

Análise da Interoperabilidade de Sistemas de Comunicações Móveis na Operação e Controle Resiliente de Microrredes.

O grau de inteligência atribuído a um sistema elétrico é diretamente proporcional à quantidade de informações coletadas através de seus sensores em tempo real, atuando através de uma integração da rede elétrica com as redes de comunicações de forma robusta, confiável e flexível. A modernização do sistema passa por várias etapas, desde a integração de sistemas de energia distribuídos, sistemas de armazenamento, à operação desconectada. Neste contexto, as microrredes, com as suas próprias unidades de geração de energia e cargas controladas, podendo trabalhar ilhadas ou conectadas à rede de energia principal, são consideradas essenciais para o desenvolvimento da próxima geração do sistema elétrico. A operação em modo ilhado, durante algum evento de falha ou desastre natural, permite que o sistema opere em cenários adversos, tais como falta de energia na rede principal, fornecimento de energia independente do sistema principal nos horários de pico devido a preços elevados de energia e, principalmente, para o fornecimento de energia em áreas remotas. No entanto, a operação de microrredes em modo ilhado requer uma maior atenção devido ao risco de interrupção, pois a capacidade de geração de energia é limitada. Consequentemente, as microrredes devem ser dotadas de sistemas capazes de gerir e controlar todas as fontes de recursos energéticos, a fim de manter o fornecimento de energia o maior tempo possível para os usuários conectados a microrredes. Essa gestão de energia é uma tarefa complicada e ambiciosa e exige a integração com um sistema de comunicação altamente robusto e confiável. Comunicações sem fio são flexíveis, escalonáveis e cobrem todos os requisitos necessários para suprir as necessidades das futuras aplicações inteligentes. A rede elétrica inteligente pode ser considerada como uma grande rede de sensores conectados, gerando um elevado número de informações, com várias máquinas trocando informações, com uma grande variedade de dispositivos conectados para controle e monitoramento do sistema. Todavia, a investigação e análise desta grande rede de sensores na operação resiliente do sistema de energia se faz necessária. Novas metodologias de controle e gestão de energia devem ser investigadas, bem como a influência e restrição de tecnologias de comunicação para prover conectividade ao sistema. Tendo em vista esta complexa integração, faz-se necessária uma análise precisa dos requisitos e parâmetros essenciais para o funcionamento de redes de comunicações aplicadas a sistemas operando em modo ilhado. Neste trabalho, são propostas metodologias para a gestão e controle de energia da microrrede com uma infraestrutura de comunicação robusta para maximizar e otimizar a operação em modo ilhado. Para amenizar a influência do consumo de cargas de comunicação durante o ilhamento, regras de controle são criadas para otimizar a resiliência, bem como fornecer energia pelo maior tempo possível. A análise do impacto do grande número de dispositivos conectados e as restrições impostas pelas diferentes tecnologias são analisadas, assim como regras de gestão de troca de mensagens entre dispositivos com o objetivo de prover a maior robustez ao sistema. O intuito deste trabalho é contribuir com o estudo da operação otimizada de microrredes