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5G cellular networks are expected to be the key infrastructure to deliver the emerging services. These services bring new requirements and challenges that obstruct the desired goal of forthcoming networks. Mobile operators are rethinking their network design to provide more flexible, dynamic, cost-effective and intelligent solutions. This paper starts with describing the background of the 5G wireless networks then we give a deep insight into a set of 5G challenges and research opportunities for machine learning (ML) techniques to manage these challenges. The first part of the paper is devoted to overview the fifth-generation of cellular networks, explaining its requirements as well as its key technologies, their challenges and its forthcoming architecture. The second part is devoted to present a basic overview of ML techniques that are nowadays applied to cellular networks. The last part discusses the most important related works which propose ML solutions in order to overcome 5G challenges. [ABSTRACT FROM AUTHOR]

Existing and future wireless networks are expected to have multiple Radio Access Technologies (RAT), primarily due to legacy reasons and introduction of newer technologies. However, new technologies, e.g., Self Organizing Networks (SON), tend to focus only on future generations networks, ignoring the existing benefits provided by legacy systems. The motivation behind this work is that, with minimal changes newer functionalities can be extended to legacy systems as well. This paper proposes an Software Defined Networking assisted SON architecture for multi-RAT cellular networks. Using this architecture, a multi-RAT Automatic Neighbour Relation functionality of SON is constructed, and the same can be used to predict mobility of User Equipments (UEs) to a cell. This mobility aspect is modeled using random graphs, and a Mixed Integer Non-Linear Programming problem is formulated, to maximize probability of mobility of UEs to a cell. It is observed that the problem is non-convex and also NP-Hard. Subsequently, a Particle Swarm Optimization (PSO) approach is developed to solve this problem. Results show that PSO output matches with that of exhaustive search for finding the maximum value of UE mobility probability to a cell, thus validating the solution approach. Results also reveal, compatibility of QoS parameters (required by UEs) among source and target cells, increases mobility probability. However, higher arrival rate of UEs towards a cell decreases the same, within target cell capacity limits. Subsequently, implications of UE mobility probability on core SON functionalities, such as load balancing and mobility optimization, are studied. [ABSTRACT FROM AUTHOR]

The paper discusses femtocell identification aspects in mobile networks such as long-term evolution (LTE) and LTE-advanced. Femtocells, or femto access points (FAPs), are new-class of base stations in addition to existing macro, microcells. Unlike these cells, femtocells implement automatic configuration principles. One of the main parameters in the automatic configuration process is among others an physical cell identifier. By considering two FAP deployment models, we discuss collision and confusion issues, which affect the proper physical cell id allocation. The first model represents a random deployment of FAPs within a (rural) macrocell area, whereas the second one, called dense urban model, constitutes placement of FAPs in a built-up area. The given study serves for the better understanding of interrelations between differently placed FAPs in term of collision and confusion events, and the obtained results can be used as a basis when designing an algorithm for automated assignment of physical cell identifier. [ABSTRACT FROM AUTHOR]

Education influences aspects of demographic behaviour and outcomes including a child sex preference. Sex preferences of children have been studied in different societies because of its associated social and demographic implications. Using the 2014 Ghana Demographic and Health Survey, we examined the association between educational attainment and sex preferences of children. Findings from the study indicated that there is preference for sons (26.1%) compared to daughters (17.4%). At higher levels of education, there is a higher likelihood for no preference for a sex of a child. Among the characteristics of respondents that influenced sex preferences are: gender, lineage, religion, occupation and desired family size. Acquisition of knowledge through education to some extent alter fertility preferences and hence the need to motivate individuals to attain some level of education. [ABSTRACT FROM AUTHOR]

Fourth generation networks and beyond (5G) have recently emerged to satisfy the increasing demand for high data bit rates. Cost-effective means such as small cells have been designed in 3GPP LTE-Advanced standard since the Release 10 to significantly enhance coverage and capacity. The deployment of small cells over Macrocells layer introduces a new type of networks called Heterogeneous Networks (HetNets). Another cost saving concept is Self-Organizing Networks (SON) which aims at minimizing human efforts in management and operating processes. The last emerging trend for cost effectiveness is to save energy especially in access networks by turning off the unused stations. In this context, we propose a new green procedure that aims at minimizing the energy consumption in LTE-Advanced/5G access networks using Handover self-optimization SON function. We also introduce a new mathematical model for energy cost calculations. Performance evaluation results show that our proposed algorithm considerably reduces the energy consumption in the network for all scenarios related to user speed. [ABSTRACT FROM AUTHOR]

Cellular radio networks continuously evolve to respond the exponential growth in data traffic volume in mobile communications. Active antenna technology contributes to this evolution by introducing vertical sectorization, which splits the horizontal sector into two subsectors with respect to the elevation plane and doubles the number of cells that can be deployed. However, in order to guarantee a reliable and near-optimal operation of vertical sectorization in a system that applies universal frequency reuse, such as LTE-advanced, co-channel interference mitigation is essentially needed. In this article we propose a decentralized self-optimization method that can be used to mitigate the undesirable inter-cell interference by self-tuning the electrical antenna downtilt toward the optimal antenna elevation angle. The performance evaluations for the proposed self-optimization method are carried out for both coordinated and uncoordinated subsector transmission scenarios within the LTE-advanced framework using a dynamic LTE-advanced compliant system level SON simulator. Based on the extensive performance evaluations carried out for a realistic urban scenario, it is found that self-optimization improves the vertical sectorization performance 25 % in terms of virtual load. Furthermore, the performance gain reaches up to 30 % when vertical vectorization is provided with dynamic point selection and muting feature. Therefore, the article concludes that in LTE-advanced networks vertical sectorization can largely benefit from the antenna self-optimization and outperform the traditional horizontal sectorization approach with low algorithmic complexity . [ABSTRACT FROM AUTHOR]

The reduction in the cost and enhancement in the network coverage and capacity are the main objectives in the establishment of mobile networks. These objectives were the key force behind the idea of femtocells deployment. But, there are many technical issues for the femtocells deployment with already existing macro network. Cross-tier interference is one of the main challenge that must have to be resolved for smooth operation of macro-femto network. This paper gives self-optimizing and self-healing technique that utilizes Q-learning and fuzzy Q-learning algorithm for the objectives of enhancement in the network capacity and spectral efficiency. In our proposed scheme, each macro base station acts as an agent which interacts with its local environment (all the femtocells and mobile stations under its coverage area), gathers the information and takes the suitable actions correspondingly. For the objective of controlling cross-tier interference, macrousers are rescheduled in such an intelligent way that performance of the femtousers, located on the overlapped spectral portion, is not degraded. The simulation results confirm our proposed approach to improve the network capacity and spectral efficiency as well as sharp convergence, which designates its capability to meet the self organizing network requirements set by 3GPP. [ABSTRACT FROM AUTHOR]

To overcome the challenge of large data demanding in future 5G cellular networks, heterogeneous networks (HetNets) take advantage of low power nodes (LPNs) to enhance capacity and coverage. This paper aims at 5G HetNets and presents a novel scheme of adaptive self-organization network (SON) by integrating cognitive radio (CR) with inter-cell interference coordination (ICIC). Particularly, we combine the spectrum sensing function from CR and the radio resource layering function from ICIC. Our work addresses the issues of smart low-power node (SLPN) development, which associates appropriate sectorization with radio resource allocation during the self-organization process. We further develop a Hungarian algorithm based self-organization strategy to improve the SLPN adaptive optimization. Simulation results show that our proposed scheme can achieve considerable gain in terms of throughput and coverage, with extra rewards of high flexibility and low complexity in HetNet SON. [ABSTRACT FROM AUTHOR]

This paper proposes a spectrum sharing scheme based on Stackelberg game exploiting the SON features of 3GPP LTE-A HetNets. In the game, the MeNB controls and prices the available spectrum resource which the PeNBs can purchase and use to serve the Pico-cell as well as offload some macro-users. Both kinds of nodes try to maximize their own utility which is consisted of user data rates, earning and expenditures on spectrum trading. During the dynamic interaction of the game, the interference coordination features of the LTE-A SON, such as almost blank sub-frames (ABS) of enhanced inter-cell interference coordination (eICIC) and cell range expansion (CRE), are employed so that the change of spectrum allocation can be fully exploited. Simulation results show that the proposed approach can significantly improve the throughput of victim users with slight network total throughput degradation. [ABSTRACT FROM AUTHOR]

When put together with the other parts of The Giver Quartet, Son (), Lowry's recently published concluding book, emerges as an odd exception to the focus on young adult protagonists since it foregrounds the mother's perspective and addresses the issue of motherhood. It presents the reader with at least three conceptual models of motherhood: mothers (1) as human egg incubators in the community; (2) as caring and nurturing; and (3) as abusive and neglectful. Unlike the latter familiar models, the first is intended to evoke in young readers the effect called cognitive dissonance (Festinger, A Theory of Dissonance, ). Employing a combination of approaches within a cognitive paradigm (Lakoff and Johnson, Metaphors we live by, ; Schank, Explanation patterns: understanding mechanically and creatively, ; Zunshine, Why we read fiction: theory of mind and the novel, ; Gavins, Text world theory: an introduction, ), this essay in the first place seeks to demonstrate how Lowry creates her vision of maternity through cognitive scripting and how her young audience understands and makes sense of motherhood by resorting to the underlying conceptual metaphor motherhood is maturation. Simultaneously, in line with the contention that people's interpretations of phenomena are largely dependent on societal frames, we intend to confront Lowry's models with some of the cultural scripts of motherhood that prevail in Western Europe. Finally, this essay aims at explaining how young readers potentially recuperate the final meaning of Son by tracking Claire's and Gabe's mental constructions and compressing them into a joint wish text-world. [ABSTRACT FROM AUTHOR]

The explosive growth of cellular networks makes their deployment and maintenance more and more complex, time consuming, and expensive. Self-Organizing Networks have been recognized as a promising way to alleviate this problem by minimizing human intervention in such processes. This paper introduces a novel multiobjective framework, based on evolutionary optimization, aiming at improving network performance and users Quality of Service. By tuning the transmitted power at each cell, average intercell interference levels are minimized. The design of the proposed scheme is feasible for distributed implementations in Long Term Evolution (LTE) and LTE-Advanced networks and its operation is compatible with current specifications. The framework is able to provide effective network-specific optimization and obtained results show that gains in terms of network capacity and cell edge performance are 5 and 10 %, respectively. Energy savings always accompanied such enhancements with reductions up to 35 %. [ABSTRACT FROM AUTHOR]

This paper presents a distributed, dynamic self-organizing network (SON) solution for downlink resources in an LTE network, triggered by support vector regression instances predicting various traffic loads on the nodes in the network. The proposed SON algorithm pro-actively allocates resources to nodes which are expected to experience traffic spikes before the higher traffic load occurs, as opposed to overloaded nodes reacting to a resource-exhaustion condition. In addition, the solution ensures inter-cell interference coordination is maintained across the LTE cells/sectors. [ABSTRACT FROM AUTHOR]

The commercial success of cellular networks, combined with advances in digital electronics, signal processing, and telecommunications research have lead to the design of next generation 4G-based long term evolution (LTE) wireless systems. The key essence of these emerging, LTE cellular systems lie in deployment of multiple femtocells for improved coverage and higher data rates. However, the arbitrary deployment of a wide number of femtocells makes the configuration, management and planning of LTE systems quite complex and challenging. In order to support dynamic and efficient network configuration, every cell needs to be assigned a particular Physical Cell ID (PCID). In this paper we show that the dynamic, optimal PCID allocation problem in LTE systems is NP-complete. Subsequently we provide a near-optimal solution using Self-Organizing Networks which models the problem using new merge operations and explores the search space using a suitable randomized algorithmic approach. We also discuss two feasible options for dynamic auto-configuration of the system and analyze the algorithm to prove its convergence. Simulation results point out that our proposed near-optimal solution dynamically achieves ∼85−90 % of global optimal auto-configuration in computationally feasible time. [ABSTRACT FROM AUTHOR]

In wireless communications the demand for wide range of services is leading to a rapid increase in network performance requirements. Hence, today's cellular radio technologies are designed to operate closer to Shannon capacity bound which sets the ultimate upper limit for the wireless channel capacity. Yet, good link level performance does not necessarily mean that network resources are used efficiently as the cellular capacity and coverage performance may not be optimal resulting from dynamic conditions in radio network environment such as urbanization, insertion or deletion of base stations, and malfunctioning nodes. Due to the fact that reacting on those inherent problems manually is very expensive and time consuming, automated optimization of cellular coverage and capacity by means of self-optimization of adaptive antenna system parameters could be an attractive solution from the network operator's point of view. Furthermore, suboptimal antenna parameter selection in long term evolution (LTE) network planning or the reuse of the sites and antenna parameters of a preceding access technology requires optimization of adaptive antenna system parameters. In this article we propose a novel centralized self-optimization approach that can be used for adapting antenna system parameters in order to automatically control network capacity and coverage in a macro-cellular deployment. In the proposed approach we present case-based reasoning (CBR) based self-optimization aided by an exemplary rule-based scheme which is required during the training phase of CBR. Dynamic system level downlink simulator is developed to validate the performance of the proposed approach in a realistic macro-cellular scenario. In performance evaluations the 3 rd generation partnership project LTE system framework is assumed and propagation is modeled in three dimensions. [ABSTRACT FROM AUTHOR]

Energy efficiency is a significant requirement for the design and management of mobile networks and has recently gained substantial attention from both network operators and the research community. The general concept of energy saving management aims to match the capacity offered by operators to the actual demand at given times and geographic areas. This paper introduces the notion of energy partition, an association of powered-on and powered-off BSs to deliver network-level energy saving. It then elaborates how such concept is applied to perform energy re-configuration to flexibly re-act to load variations encouraging none or minimal extra energy consumption. A simulation-based study evaluates the performance of the proposed algorithms under different network topologies and traffic conditions, highlights the benefits and drawbacks, and provides recommendations for deployment scenarios. [ABSTRACT FROM AUTHOR]

The femto-access-point, a low-cost and small-size cellular base-station, is envisioned to be widely deployed in subscribers homes, as to provide high data-rate communications with improved quality of service. As femtocellular networks will co-exist with macrocellular networks, mitigation of the interference between these two network types is a key challenge for successful integration of these two technologies. In particular, there are several interference mechanisms between the femtocellular and the macrocellular networks, and the effects of the resulting interference depend on the density of femtocells and the overlaid macrocells in a particular coverage area. While improper interference management can cause a significant reduction in the system capacity and can increase the outage probability, effective and efficient frequency allocation among femtocells and macrocells can result in a successful co-existence of these two technologies. Furthermore, highly dense femtocellular deployments-the ultimate goal of the femtocellular technology-will require significant degree of self-organization in lieu of manual configuration. In this paper, we present various femtocellular network deployment scenarios, and we propose a number of frequency-allocation schemes to mitigate the interference and to increase the spectral efficiency of the integrated network. These schemes include: shared frequency band, dedicated frequency band, sub-frequency band, static frequency-reuse, and dynamic frequency-reuse. We derive an analytical model, which allows us to analyze in details the users outage probability, and we compare the performance of the proposed schemes using numerical analysis. [ABSTRACT FROM AUTHOR]

Equilibrium carbon stock is the result of a balance between inputs and outflows to the pool. Changes in land-use are likely to alter such balance, resulting in different carbon stores under different land-use types in addition to the impacts of global climate change. In an agro-pastoral ecotone of Inner Mongolia, northern China, we investigated productivity and belowground carbon and nitrogen stores under six different types of land-uses, namely free grazing (FG), grazing exclusion (GE), mowing (MW), corn plantation (CP), fallow (FL), and alfalfa pasture (AP), and their impacts on litter and fine roots in semiarid grassland ecosystems. We found that there were great variations in aboveground net primary production (ANPP) across the six land-use types, with CP having markedly high ANPP; the FG had significantly reduced soil organic carbon (SOC) and nitrogen stores (SON) to 100 cm depth compared with all other types of land uses, while very little litter accumulation was found on sites of the FG and CP. The top 20 cm of soils accounted for about 80% of the root carbon and nitrogen, with very little roots being found below 50 cm. About 60% of SOC and SON were stored in the top 30 cm layer. Land-use change altered the inputs of organic matters, thus affecting SOC and SON stores accordingly; the MW and GE sites had 59 and 56% more SOC and 61% more SON than the FG. Our estimation suggested that restoring severely degraded and overgrazed grasslands could potentially increase SOC and SON stores by more than 55%; conversion from the native grasses to alfalfa could potentially double the aboveground biomass production, and further increase SOC and SON stores by more than 20%. Our study demonstrated significant carbon and nitrogen storage potential of the agro-pastoral ecotone of northern China through land-use changes and improved management in the context of mitigating global climate change. [ABSTRACT FROM AUTHOR]

Soil soluble organic N (SON) plays an important role in N biogeochemical cycling. In this study, 22 surface forest soils (0–10 cm) were collected from southeast Queensland, Australia, to investigate the size of SON pools extracted by water and salt solutions. Approximately 5–45 mg SON kg−1, 2–42 mg SON kg−1 and 1–24 SON mg kg−1 were extracted by 2 M KCl, 0.5 M K2SO4 and water, on average, corresponding to about 21.1, 13.5 and 7.0 kg SON ha−1 at the 0–10 cm forest soils, respectively. These SON pools, on average, accounted for 39% (KCl extracts), 42% (K2SO4 extracts) and 43% (water extracts) of total soluble N (TSN), and 2.3% (KCl extracts), 1.3% (K2SO4 extracts) and 0.7% (water extracts) of soil total N, respectively. Large variation in SON pools observed across the sites in the present study may be attributed to a combination of factors including soil types, tree species, management practices and environmental conditions. Significant relationships were observed among the SON pools extracted by water, KCl and K2SO4 and microbial biomass N (MBN). In general, KCl and K2SO4 extracted more SON than water from the forest soils, while KCl extracted more SON than K2SO4. The SON and soluble organic C (SOC) in KCl, K2SO4 and water extracts were all positively related to soil organic C, total N and clay contents. This indicates that clay and soil organic matter play a key role in the retention of SON in soil. [ABSTRACT FROM AUTHOR]