Energy Consumption Comparison Between Macro-Micro and Public Femto Deployment in a Plausible LTE Network

We study the energy consumptions of two strategies that increase the capacity of an LTE network: (1) the deployment of redundant macro and micro base stations by the operator at locations where the traffic is high, and (2) the deployment of publicly accessible femto base stations by home users. Previous studies show the deployment of publicly accessible residential femto base stations is considerably more energy efficient; however, the results are proposed using an abstracted model of LTE networks, where the coverage constraint was neglected in the study, as well as some other important physical and traffic layer specifications of LTE networks. We study a realistic scenario where coverage is provided by a set of non-redundant macro-micro base stations and additional capacity is provided by redundant macro-micro base stations or by femto base stations. We quantify the energy consumption of macro-micro and femto deployment strategies by using a simulation of a plausible LTE deployment in a mid-size metropolitan area, based on data obtained from an operator and using detailed models of heterogeneous devices, traffic, and physical layers. The metrics of interest are operator-energy-consumption/total-energy-consumption per unit of network capacity. For the scenarios we studied, we observe the following: (1) There is no significant difference between operator energy consumption of femto and macro-micro deployment strategies. From the point of view of society, i.e. total energy consumption, macro-micro deployment is even more energy efficient in some cases. This differs from the previous findings, which compared the energy consumption of femto and macro-micro deployment strategies, and found that femto deployment is considerably more energy efficient. (2) The deployment of femto base stations has a positive effect on mobile-terminal energy consumption; however, it is not significant compared to the macro-micro deployment strategy. (3) The energy saving that could be obtained by making macro and micro base stations more energy proportional is much higher than that of femto deployment

Technical, financial and environmental evaluation of 4G long term evolution: advanced with femtocell base stations

Recent advances in mobile communication technology have allowed for considerable growth both in traffic and user numbers. However, in order to maintain acceptable quality of experience and service levels with increasing network capacity requirements, a mobile communications operator is challenged with high investment costs and high operating costs. Cost effectiveness and environmental sustainability are two major factors a mobile telecommunications operator must take into account in order to maintain its network planning techniques ready for the accelerated growth of traffic in future mobile networks. With the incoming LTE-Advanced system and with the increasing popularity of femtocells, it becomes necessary to evaluate and quantify the economic viability and sustainability of this new type of base station when used as a standalone deployment option, as well as when used in a two-tier network. Therefore, different cases were used with a deployment method based on capacity used with a varying non-uniform traffic distribution in order to assess the future resistance and flexibility of this proposed solution. A comparison was made between macro cell coverage only, full femtocell coverage and a two-tier joint solution. Our study has concluded that for low capacity demands, the best approach is a two-tier network with femtocells used for indoor backhaul. A joint solution also allows for the cost-effective resolution of indoor coverage issues. According to our future capacity requirements projected, it has been concluded that a full femtocell deployment, by far, the most economically viable option. A method for the quantification and suppression of carbon emissions due to energy consumption is also proposed, through which we studied and estimated the price for the achievement of a zero carbon emissions network.Os recentes avanços na tecnologia de comunicações móveis têm permitido um crescimento considerável da indústria, tanto em termos de tráfego como em número de clientes. No entanto, para conseguir manter uma qualidade de experiência aceitável e com elevada qualidade de serviço, um operador de comunicações móveis depara-se com elevados custos de investimento e operação. A eficácia em termos de custos e a pegada ambiental são dois factores que, entre outros, um operador de telecomunicações móveis deve ter em conta de modo a manter as suas técnicas de planeamento de rede preparadas para o acelerado crescimento do tráfego nas redes móveis do futuro. Com a chegada próxima do LTE-Advanced e com a crescente popularidade de femtocells, torna-se necessário avaliar e quantificar a viabilidade económica e o potencial de poupança de energia deste novo tipo de estação de base quando utilizado como uma opção de implantação autónoma, ou quando utilizado para suporte de uma rede de macro células. Dessa forma, foram dimensionados diferentes casos de implementação baseados nos requisitos de capacidade. Foi também aplicada uma distribuição de tráfego não-uniforme, a fim de avaliar a resistência ao futuro e a flexibilidade de aplicação desta solução proposta. Fez-se uma comparação entre uma implementação apenas com recurso a macro células, uma implementação feita completamente com recurso a femtocells e uma solução conjunta destes dois tipos de estação-base. O estudo concluiu que, para requisitos de baixa capacidade, a melhor implementação é uma rede de duas camadas, com femtocells utilizadas para o backhaul das ligações indoor. A solução conjunta permite ainda a resolução eficaz de problemas de cobertura no interior de edifícios. De acordo com a nossa projecção das necessidades futuras de capacidade concluiu-se que a implementação de uma rede apenas com recurso a femtocells é a melhor opção, do ponto de vista da capacidade, financeiro e ambiental. Também foi apresentada uma metodologia para quantificar a pegada ambiental devida ao consumo de energia, através da qual se estudou e estimou os custos associados à implementação de uma rede com pegada ambiental nula

Optimization models for resource management in two-tier cellular networks

Macro-femtocell network is the most promising two-tier architecture for the cellular network operators because it can improve their current network capacity without additional costs. Nevertheless, the incorporation of femtocells to the existing cellular networks needs to be finely tuned in order to enhance the usage of the limited wireless resources, because the femtocells operate in the same spectrum as the macrocell. In this thesis, we address the resource optimization problem for the OFDMA two-tier networks for scenarios where femtocells are deployed using hybrid access policy. The hybrid access policy is a technique that could provide different levels of service to authorized users and visitors to the femtocell. This method reduces interference received by femtocell subscribers by granting access to nearby public users. These approaches should find a compromise between the level of access granted to public users and the impact on the subscribers satisfaction. This impact should be reduced in terms of performance or through economic compensation. In this work, two specific issues of an OFDMA two-tier cellular network are addressed. The first is the trade-off between macrocell resource usage efficiency and the fairness of the resource distribution among macro mobile users and femtocells. The second issue is the compromise between interference mitigation and granting access to public users without depriving the subscriber downlink transmissions. We tackle these issues by developing several resource allocation models for non-dense and dense femtocell deployment using Linear Programming and one evolutionary optimization method. In addition, the proposed resource allocation models determine the best suitable serving base station together with bandwidth and transmitted power per user in order to enhance the overall network capacity. The first two parts of this work cope with the resource optimization for non-dense deployment using orthogonal and co-channel allocation. Both parts aim at the maximization of the sum of the weighted user data rates. In the first part, several set of weights are introduced to prioritize the use of femtocells for subscribers and public users close to femtocells. In addition, macrocell power control is incorporated to enhance the power distribution among the active downlink transmissions and to improve the tolerance to the environmental noise. The second part enables the spectral reuse and the power adaptation is a three-folded solution that enhances the power distribution over the active downlink transmissions, improves the tolerance to the environmental noise and a given interference threshold, and achieves the target Quality of Service (QoS). To reduce the complexity of the resource optimization problem for dense deployment, the third part of this work divides the optimization problem into subproblems. The main idea is to divide the user and FC sets into disjoint sets taking into account their locations. Thus, the optimization problem can be solved independently in each OFDMA zone. This solution allows the subcarriers reuse among inner macrocell zones and femtocells located in outer macrocell zones and also between femtocells belonging to different clusters if they are located in the same zone. Macrocell power control is performed to avoid the cross-tier interference among macrocell inner zones and inside femtocells located in outer zones. Another well known method used to reduce the complexity of the resource optimization problem is the femtocell clustering. However, finding the optimal cluster configuration together with the resource allocation is a complex optimization problem due to variable number related to the possible cluster configurations. Therefore, the part four of this work deals with a heuristic cluster based resource allocation model and a motivation scheme for femtocell clustering through the allocation of extra resources for subscriber and “visitor user” transmissions. The cluster based resource allocation model maximizes the network throughput while keeping balanced clusters and minimizing the inter-cluster interference. Finally, the proposed solutions are evaluated through extensive numerical simulations and the numerical results are presented to provide a comparison with the related works found in the literature

Optimisation de la capacité et de la consommation énergétique dans les réseaux maillés sans fil

Les réseaux maillés sans fil sont une solution efficace, de plus en plus mise en œuvre en tant qu infrastructure, pour interconnecter les stations d accès des réseaux radio. Ces réseaux doivent absorber une croissance très forte du trafic généré par les terminaux de nouvelle génération. Cependant, l augmentation du prix de l énergie, ainsi que les préoccupations écologiques et sanitaires, poussent à s intéresser à la minimisation de la consommation énergétique de ces réseaux. Ces travaux de thèse s inscrivent dans les problématiques d optimisation de la capacité et de la minimisation de la consommation énergétique globale des réseaux radio maillés. Nous définissons la capacité d un réseau comme la quantité de trafic que le réseau peut supporter par unité de temps. Ces travaux s articulent autour de quatre axes. Tout d abord, nous abordons le problème d amélioration de la capacité des réseaux radio maillés de type WIFI où l accès au médium radio se base sur le protocole d accès CSMA/CA. Nous mettons en lumière, les facteurs déterminants qui impactent la capacité du réseau, et l existence d un goulot d étranglement qui limite cette capacité du réseau. Ensuite, nous proposons une architecture de communication basée sur l utilisation conjointe de CSMA/CA et de TDMA afin de résoudre ce problème de goulot d étranglement. Dans la deuxième partie de cette thèse, nous nous intéressons aux réseaux maillés sans fil basés sur un partage des ressources temps-fréquence. Afin de calculer des bornes théoriques sur les performances du réseau, nous développons des modèles d optimisation basés sur la programmation linéaire et la technique de génération de colonnes. Ces modèles d optimisation intègrent un modèle d interférence SINR avec contrôle de puissance continue et variation de taux de transmission. Ils permettent, en particulier, de calculer une configuration optimale du réseau qui maximise la capacité ou minimise la consommation d énergie. Ensuite, dans le troisième axe de recherche, nous étudions en détail le compromis entre la capacité du réseau et la consommation énergétique. Nous mettons en évidence plusieurs résultats d ingénierie nécessaires pour un fonctionnement optimal d un réseau maillé sans fil. Enfin, nous nous focalisons sur les réseaux cellulaires hétérogènes. Nous proposons des outils d optimisation calculant une configuration optimale des stations de base qui maximise la capacité du réseau avec une consommation efficace d énergie. Ensuite, afin d économiser l énergie, nous proposons une heuristique calculant un ordonnancement des stations et leur mise en mode d endormissement partiel selon deux stratégies différentes, nommées LAFS et MAFS.Wireless mesh networks (WMN) are a promising solution to support high data rate and increase the capacity provided to users, e.g. for meeting the requirements of mobile multimedia applications. However, the rapid growth of traffic load generated by the terminals is accompanied by an unsustainable increase of energy consumption, which becomes a hot societal and economical challenges. This thesis relates to the problem of the optimization of network capacity and energy consumption of wireless mesh networks. The network capacity is defined as the maximum achievable total traffic in the network per unit time. This thesis is divided into four main parts. First, we address the problem of improvement of the capacity of 802.11 wireless mesh networks. We highlight some insensible properties and deterministic factors of the capacity, while it is directly related to a bottleneck problem. Then, we propose a joint TDMA/CSMA scheduling strategy for solving the bottleneck issue in the network. Second, we focus on broadband wireless mesh networks based on time-frequency resource management. In order to get theoretical bounds on the network performances, we formulate optimization models based on linear programming and column generation algorithm. These models lead to compute an optimal offline configuration which maximizes the network capacity with low energy consumption. A realistic SINR model of the physical layer allows the nodes to perform continuous power control and use a discrete set of data rates. Third, we use the optimization models to provide practical engineering insights on WMN. We briefly study the tradeoff between network capacity and energy consumption using a realistic physical layer and SINR interference model. Finally, we focus on capacity and energy optimization for heterogeneous cellular networks. We develop, first, optimization tools to calculate an optimal configuration of the network that maximizes the network capacity with low energy consumption. We second propose a heuristic algorithm that calculates a scheduling and partial sleeping of base stations in two different strategies, called LAFS and MAFS.VILLEURBANNE-DOC'INSA-Bib. elec. (692669901) / SudocSudocFranceF

Spectral and Energy Efficiency in Cellular Mobile Radio Access Networks

Driven by the widespread use of smartphones and the release of a wide range of online packet data services, an unprecedented growth in the mobile data usage has been observed over the last decade. Network operators recently realised that the traditional approach of deploying more macrocells could not cope with this continuous growth in mobile data traffic and if no actions are taken, the energy demand to run the networks, which are able to support such traffic volumes risks to become unmanageable. In this context, comprehensive investigations of different cellular network deployments, and various algorithms have been evaluated and compared against each other in this thesis, to determine the best deployment options which are able to deliver the required capacity at a minimum level of energy consumption. A new scalable base station power consumption model was proposed and a joint evaluation framework for the relative improvements in throughput, energy consumption,and energy efficiency is adopted to avoid the inherent ambiguity of using only the bit/J energy efficiency metric. This framework was applied to many cellular network cases studies including macro only, small cell only and heterogeneous networks to show that pure small cell deployments outperform the macro and heterogeneous networks in terms of the energy consumption even if the backhaul power consumption is included in the analysis. Interestingly, picocell only deployments can attain up to 3 times increase in the throughput and 2.27 times reduction in the energy consumed when compared with macro only RANs at high target capacities, while it offers 2 times more throughput and reduces the energy consumption by 12% when compared with the macro/pico HetNet deployments. Further investigations have focused on improving the macrocell RAN by adding more sectors and more antennas. Importantly, the results have shown that adding small cells to the macrocell RAN is more energy efficient than adding more sectors even if adaptive sectorisation techniques are employed. While dimensioning the network by using MIMO base stations results in less consumed energy than using SISO base stations. The impact of traffic offloading to small cell, sleep mode, and inter-cell interference coordination techniques on the throughput and energy consumption in dense heterogeneous network deployments have been investigated. Significant improvements in the throughput and energy efficiency in bit/J were observed. However, a decrease in the energy consumption is obtained only in heterogeneous networks with small cells deployed to service clusters of users. Finally, the same framework is used to evaluate the throughput and energy consumption of massive MIMO deployments to show the superiority of massive MIMOs versus macrocell RANs, small cell deployments and heterogeneous networks in terms of achieving the target capacity with a minimum level of energy consumption. 1.6 times reduction in the energy consumption is achieved by massive MIMOs when compared with picocell only RAN at the same target capacity and when the backhaul power consumption is included in the analysis