Design and Deployment of Small Cell Networks最新文献

{"title":"Temporary cognitive small cell networks for rapid and emergency deployments","authors":"A. Al-Hourani, K. Sithamparanathan, S. Arunthavanathan","doi":"10.1017/CBO9781107297333.010","DOIUrl":"https://doi.org/10.1017/CBO9781107297333.010","url":null,"abstract":"This chapter introduces the concept of temporary cognitive small cell networks (TCSCN) as a supplement infrastructure to LTE-Advanced macro networks, and examines how the cognitive capabilities can enable the rapid and temporary nature of such deployments. Temporary networks are suitable for disaster-recovery scenarios where the nominal macro network is severely affected or completely paralyzed. In addition to that, such temporary networks can address the sudden increase in wireless traffic in certain geographic areas due to public events. The approach in realizing the cognitive capabilities is achieved by exploiting the latest LTE-Advanced HetNet features, as well as by presenting novel techniques for intelligently mitigating interference between the macro network base stations and the introduced temporary infrastructure. Simulation results are presented in order to show the enhancement of the wireless service when such femporary networks are deployed together with the proposed cognitive capabilities. At the end of this chapter an overview will be provided about open research directions that are fundamental for further possible realization of temporary cognitive smail cell networks.","PeriodicalId":315180,"journal":{"name":"Design and Deployment of Small Cell Networks","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116358584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Required number of small cell access points in heterogeneous wireless networks","authors":"S. Banani, A. Eckford, R. Adve","doi":"10.1017/CBO9781107297333.008","DOIUrl":"https://doi.org/10.1017/CBO9781107297333.008","url":null,"abstract":"How many small cell (SC) access points (APs) are required to guarantee a chosen quality of service in a heterogeneous network? In this chapter, we answer this question considering two different network models. The first is the downlink of a finite-area SC network where the locations of APs within the chosen area are uniformly distributed. A key step in obtaining the closed-form expressions is to generalize the well-accepted moment matching approximation for the linear combination of lognormal random variables. For the second model, we focus on a two-layer downlink heterogeneous network with frequency reuse-1 hexagonal macro cells (MCs), and SC APs that are placed at locations that do not meet a chosen quality of service from macro base stations (BSs). An important property of this model is that the SC AP locations are coupled with the MC coverage. Here, simple bounds for the average total interference within an MC makes the formulation possible for the percentage of MC area in outage, as well as the required average number of SCs (per MC) to overcome outage, assuming isolated SCs. Introduction Heterogeneous cellular networks (HCNs) are being considered as an efficient way to improve system capacity as well as effectively enhance network coverage [1, 2]. Comprising multiple layers of access points (APs), HCNs encompass a conventional macro cellular network (first layer) overlaid with a diverse set of small cells (SCs) (higher layers). Cell deployment is an important problem in heterogeneous networks, both in terms of the number and positioning of the SCs. Traditional network models are either impractically simple (such as the Wyner model [3]) or excessively complex (e.g., the general case of random user locations in a hexagonal lattice network [4]) to accurately model SC networks. A useful mathematical model that accounts for the randomness in SC locations and irregularity in the cells uses spatial point processes, such as Poisson point process (PPP), to model the location of SCs in the network [5–10]. The independent placement of SCs from the MC layer, has the advantage of analytical tractability and leads to many useful SINR and/or rate expressions. However, even assuming that wireless providers would deploy SCs to support mobile broadband services, the dominant assumption remains that SCs are deployed randomly and independent of the MC layer [11].","PeriodicalId":315180,"journal":{"name":"Design and Deployment of Small Cell Networks","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128917546","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Time- and frequency-domain e-ICIC with single- and multi-flow carrier aggregation in HetNets","authors":"M. Simsek, M. Bennis, Ismail Güvenç","doi":"10.1017/CBO9781107297333.020","DOIUrl":"https://doi.org/10.1017/CBO9781107297333.020","url":null,"abstract":"Multi-layer heterogeneous network (HetNet) deployments including small cell base stations (BSs) are considered to be the key to further enhancements of the spectral efficiency achieved in mobile communication networks [1]. Besides the capacity enhancement due to frequency reuse, a limiting factor in HetNets has been identified as inter-cell interference. The 3rd Generation Partnership Project (3GPP) discussed inter-cell interference coordination (ICIC) mechanisms in long term evolution (LTE) Release 8/9 [2]. LTE Release 8/9 ICIC techniques were introduced to primarily save cell-edge user equipments (UEs). They are based on limited frequency domain interference information exchange via the X2 interface, whereby ICIC related X2 messages are defined in the 3GPP standard [3]. In LTE Release 8/9 ICIC, a BS provides information about set of frequency resources in which it is likely to schedule DL transmissions to cell-edge UEs, for the benefit of a neighboring BS. The neighboring BS in turn avoids scheduling its UEs on these frequency resources. With the growing demand for data services and the introduction of HetNets it has become increasingly difficult to meet a UE's quality of service (QoS) requirements with these mechanisms. To cope with the QoS requirements and growing demand for data services, enhanced ICIC (e-ICIC) solutions have been proposed in LTE Release 10 and further e-ICIC (Fe-ICIC) solutions to reduce cell reference signal (CRS) interference in e-ICIC techniques are discussed in LTE Release 11 [4]. In LTE Release 10 e-ICIC techniques, the focus is on time- and frequency-domain techniques and power-control techniques. While in time-domain techniques, the transmissions of the victim UEs are coordinated in time-domain resources, in frequency-domain techniques, e-ICIC is mainly achieved by frequency-domain orthogonalization. The power-control techniques have been intensively discussed in 3GPP. Hereby, power control is performed by the aggressor cell to reduce inter-cell interference to victim UEs. In 3GPP studies, e-ICIC mechanisms with adaptive resource partitioning, cell range expansion (CRE), and interference coordination/cancellation take a central stage [5]. In the following, the inter-cell interference problem in HetNets is introduced and time- and frequency-domain e-ICIC techniques are discussed based on 3GPP specifications. In addition, single- and multi-flow transmission techniques for e-ICIC and system capacity improvement are described. Inter-cell interference in HetNets One of the major features extensively studied for LTE Release 10, also known as LTE-Advanced, is the HetNet coverage and capacity optimization, e.g., through the use of cell-range expansion (CRE) techniques.","PeriodicalId":315180,"journal":{"name":"Design and Deployment of Small Cell Networks","volume":"137 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132412835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mobility management in small cell heterogeneous networks","authors":"P. Legg, X. Gelabert","doi":"10.1017/CBO9781107297333.014","DOIUrl":"https://doi.org/10.1017/CBO9781107297333.014","url":null,"abstract":"Introduction In cellular networks, handover refers to the mechanism by which the set of radio links between an active mode mobile device and base station cells is modified. Mobility in the idle mode (when the mobile has no data bearers established and is not transmitting or receiving user plane traffic), termed cell selection/reselection, typically ensures that the UE selects the strongest available cell in preparation for an outgoing or incoming call/data session. Handover reliability is a key performance indicator (KPI) since it directly impacts the perceived quality of experience (QoE) of the end user. In contrast, cell reselection is less important since no bearers are established and suboptimal performance is apparent only on call establishment and as a signaling cost to the network operator. For this reason, the remainder of this chapter focuses on handover. In GSM and LTE the mobile supports only a single radio link such that the handover swaps this link from one cell (the serving cell) to another (the target cell). In WCDMA, however, multiple links (on the same frequency) may be established (known as “soft handover”). Handovers can be classified as: • intra-RAT, meaning within the same radio access technology (RAT), for example, LTE to LTE • intra-frequency (serving and target cells are on the same frequency) • inter-frequency (serving and target cells are not on the same frequency) • inter-RAT • between cells of different RATs. Handover may be triggered for a number of reasons: • to maintain the connectivity of the mobile and support data transfer (often called a “coverage handover”) • to balance the loading of cells with overlapping coverage or to handover a mobile between overlapping cells to ensure data rates demanded by an ongoing service are met (often called a “vertical handover”). Vertical handovers target stationary mobiles, implying that the radio conditions of links to serving and target cells are relatively stable. More challenging are coverage handovers that result from the motion of the mobile, leaving the coverage of the serving cell and entering that of the target cell. Since indoor users are usually stationary, the focus of coverage handovers is on outdoor users, on foot or in vehicles.","PeriodicalId":315180,"journal":{"name":"Design and Deployment of Small Cell Networks","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134408385","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"3GPP RAN standards for small cells","authors":"W. Xiao, Jialing Liu, A. Soong","doi":"10.1017/CBO9781107297333.005","DOIUrl":"https://doi.org/10.1017/CBO9781107297333.005","url":null,"abstract":"","PeriodicalId":315180,"journal":{"name":"Design and Deployment of Small Cell Networks","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124941126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Self-organized ICIC for SCN","authors":"L. Giupponi, A. Imran, A. Galindo","doi":"10.1017/CBO9781107297333.017","DOIUrl":"https://doi.org/10.1017/CBO9781107297333.017","url":null,"abstract":"In recent years the use of data services in mobile networks has notably increased, which requires a higher quality of services and data throughput capacity from operators. These requirements become much more demanding in indoor environments, where, due to the wall-penetration losses, communications suffer a higher detriment. As a solution, short-range base stations (BSs), known as femto cells [1], are proposed. Femto cells are installed by the end consumer and communicate with the macro cell system through the internet by means of a digital subscriber line (DSL), fiber, or cable connection. Due to this deployment model, the number and location of femto cells are unknown for the operators and therefore there is no possibility for centralized network planning. In the case of co-channel operation, which is the more rewarding option for operators in terms of spectral efficiency, an aggregated interference problem may arise due to multiple, simultaneous, and uncoordinated femto cell transmissions. On the other hand, the macro cell network can also cause significant interference to the femto cell system due to a lack of control of position of the femto nodes and their users. In this chapter we focus then on the challenging problem in the area of small cell networks, the inter-cell interference coordination among different layers of the network. We propose two different self-organizing solutions, based on two smart techniques that operate on the most appropriate configuration parameters of the network for each situation. In particular, we address femto–macro and macro–femto problems. On the one hand, for the femto–macro case, we propose in Section 16.1 a machine learning (ML) approach to optimize the transmission power levels by modeling the multiple femto BSs as a multi-agent system [2], where each femto cell is able to learn transmission power policy in such a way that the interference it is generating, added to the whole femto cell network interference, does not jeopardize the macro cell system performance. To do this, we propose a reinforcement learning (RL) category of solutions [3], known as time-difference learning. On the other hand, for the macro–femto problem, we propose in Section 16.2 a solution based on interference minimization through self-organization of antenna parameters. In homogeneous macro cell networks, BS antenna parameters are configured in the planning and deployment phase and left unchanged for a long time. This approach works well for homogeneous networks, as the topology of the system remains unchanged over a long time. However, this is not the case in heterogeneous networks where different layers of the networks are deployed and configured in an impromptu manner and based on the timely conditions of the environment. Consequently, the density, locations, and activity levels of the small cells may change over space and time. Hence","PeriodicalId":315180,"journal":{"name":"Design and Deployment of Small Cell Networks","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133080842","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Energy efficient strategies with BS sleep mode in green small cell networks","authors":"Hong Zhang, Jun Cai","doi":"10.1017/CBO9781107297333.013","DOIUrl":"https://doi.org/10.1017/CBO9781107297333.013","url":null,"abstract":"","PeriodicalId":315180,"journal":{"name":"Design and Deployment of Small Cell Networks","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132183654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Large-scale deployment and scalability","authors":"Iris Barcia, S. Chapman, Chris Beale","doi":"10.1017/CBO9781107297333.018","DOIUrl":"https://doi.org/10.1017/CBO9781107297333.018","url":null,"abstract":"Combined with a technology upgrade to LTE/LTE-A, small cells are presented by many industry players (from operators to equipment vendors to analysts) as the most cost-effective solution to the known increase in mobile data demand [1–3]. As small cells (e.g., femto and pico) become the broadly adopted solution for adding capacity to modern, smart phone-dominated cellular networks, their numbers, and the areas where they will be deployed, will increase dramatically (Figure 17.1). This reduction in cell size and the growth in cell numbers has required many new approaches to be developed to ensure that the next generation of networks are built to exploit costly, limited spectrum resources while maximizing capacity. Such new methods consider the network design process in a holistic manner and ensure sufficient computational power is available to remove any accuracy compromises inherent with the traditional design processes. The set of techniques used to accomplish this we call large-scale network design, or L-SND for short. The US cellular market has many good examples of planned small cell deployments that are to occur at a national level [1]. Results and data from such small cell designs are included in this chapter to illustrate the L-SND accuracy and scalability difficulties that have been overcome when compared to the limitations found with traditional methods.","PeriodicalId":315180,"journal":{"name":"Design and Deployment of Small Cell Networks","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114168264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Centralized self-optimization of interference management in LTE-A HetNets","authors":"Yasir Khan, B. Sayraç, É. Moulines","doi":"10.1017/CBO9781107297333.016","DOIUrl":"https://doi.org/10.1017/CBO9781107297333.016","url":null,"abstract":"In this chapter we address interference mitigation in LTE-A co-channel Het-Net deployments, a major issue for reaching substantial capacity enhancements. We provide an extensive literature survey of the existing co-channel interference mitigation methods involving optimization of the related network parameters, resulting in corresponding improvements in quality of service (QoS). Since the number of base stations (macro, micro, pico, and femto) increases considerably in a HetNet deployment, optimization of network parameters with such a high number of nodes becomes complex and costly, calling for the inevitable need for self-optimization. We propose a self-optimization framework based on efficient statistical modeling combined with robust sequential optimization, which is very suitable for implementation in a centralized manner at the operator’s management plane. In particular, the proposed methodology is based on the following two concepts, which will be described in detail.","PeriodicalId":315180,"journal":{"name":"Design and Deployment of Small Cell Networks","volume":"266 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123263902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The art of deploying small cells: field trial experiments, system design, performance prediction, and deployment feasibility","authors":"D. Calin, A. O. Kaya, Amine Abouliatim, G. Ferrada, Ionel Petrut","doi":"10.1017/CBO9781107297333.015","DOIUrl":"https://doi.org/10.1017/CBO9781107297333.015","url":null,"abstract":"We disseminate a set of small cells’ field trial experiments conducted at 2.6 GHz and focused on coverage/capacity within multi-floor office buildings. LTE pico cells deployed indoors as well as LTE small cells deployed outdoors are considered. The latter rely on small emission power levels coupled with intelligent ways of generating transmission beams with various directivity levels by means of adaptive antenna arrays. Furthermore, we introduce an analytical three-dimensional (3D) performance prediction framework, which we calibrate and validate against field measurements. The framework provides detailed performance levels at any point of interest within a building; it allows us to determine the minimum number of small cells required to deliver desirable coverage and capacity levels, their most desirable location subject to deployment constraints, transmission power levels, antenna characteristics (beam shapes), and antenna orientation (azimuth, tilt) to serve a targeted geographical area. In addition, we disseminate specialized solutions for LTE small cells’ deployment within hotspot traffic venues, such as stadiums, through design and deployment feasibility analysis.","PeriodicalId":315180,"journal":{"name":"Design and Deployment of Small Cell Networks","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133878757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}