Research has often called for studies that attempt to explain the complex causal chain known as the “black box” between human resource management (HRM) activities and individual-level outcomes. To explore the dynamics within the “black box,” this study investigates the influence of HRM activities (e.g., practices and processes) on individual-level outcomes, taking into consideration psychological empowerment as a mediating mechanism. Furthermore, to investigate how HRM activities affect individual-level outcomes, one must consider how HRM activities interrelate to create synergistic effects. Subsequently, this research contributes to the literature of strategic HRM research by investigating how and why systems of HRM activities influence individual-level outcomes.

This thesis endeavours to model a trip demand function for recreationalangling in Sweden, including the individual expected per-trip utility of regionalattributes. The analysis is conducted with the use of a Random Utility Model (RUM)for the estimation of ‘site-specific’ utility, and a negative binomial logit model fortrip demand. The site quality variable is stated as expected catch-rates (CR) definedin terms of three different specifications: sample mean CR, individually perfectlyforesighted CR, and an econometrically predicted individual CR. Results indicatethat the econometrically estimated individual catch-rate specification performs wellas an explanatory variable both when modelling discrete site choice and trip demand,while the sample mean and perfectly foresighted CR specifications provide withunintuitive and insignificant parameter values. The inclusive value of the regionchosen by the angler, estimated with the RUM, was subsequently found to be asignificant predicting variable for the number of recreational angling trips conductedby Swedish anglers.

<p> Understanding how to balance human well-being and ecological integrity is one of the fundamental challenges in conservation and natural resource management. As our human-footprint on ecosystems expands and deepens, we are increasingly realizing that human well-being is crucial to understanding social-ecological systems and managing them sustainably.</p><p> In my first chapter I add to this literature by extending a theoretical model to examine the effects of two biophysical stressors on a marine species. While this model was developed to understand how harvest and climate change may interact to affect species viability, the model instead emphasized the sensitivity of the results to assumptions about human behavior. This result adds to a small, but growing, body of literature that demonstrates the importance of considering resource-users&rsquo; dynamics when attempting to predict outcomes for biophysical systems.</p><p> Despite conceptual advances in linking human-wellbeing to biophysical dynamics, a major challenge exists in operationalizing these conceptual framings. In my second chapter I use the US West Coast commercial fisheries system as a case study and developed a novel network approach of linking the social system (i.e. fishing communities) to the ecological system (the fish). This approach made use of data collected by management, making it immediately operational for all managed fisheries in the US. Such a conceptual framework represents a major step forward for mapping and quantifying these linkages between social and natural systems. I add to this work by analyzing these resultant networks to show that the topological structure and modularity varied non-randomly, providing additional features that may be useful for mangers seeking to balance human well-being with sustainable populations of fish.</p><p> In my third chapter I analyzed patterns of participation across the US West Coast commercial fisheries before and after a major management change in a single fishery. Using individual- and fishing community-level analyses, using the framework described above, I show that the policy affected how fishermen shift their effort across fisheries at the individual level, but community level attributes remain unchanged. This work demonstrates how such social-ecological system level policy analysis may be conducted.</p><p> Overall this dissertation helps move us towards a set of tools managers can use to evaluate policy efficacy in commercial fisheries in the face of rapid environmental change while balancing ecological integrity and human well-being.</p>

The main topic of this master thesis is a company impacted by the current economic crisis and the role of the human resource management within the crisis. The thesis firstly provides theoretical basis, defines terms and explains associations. It focuses on the company and its goals, then on the economic cycle, recession and crisis and afterwards dedicates to the human resource management and human resource activities including the approach and procedures that are typical for the time of crisis. Then the focus is on the current economic crisis and its origin in the USA, impacts on the Slovak Republic where the analyzed company is located. Afterwards the thesis provides an introduction of the analyzed company and describes and analyzes the human resource management and hr activities in this company. The final part is dedicated to the complex evaluation of the hr area in this firm and of the approach and changes that were implemented as a reaction to the situation caused by the crisis. The thesis also suggests and recommends some steps and changes, that could help the company improve its situation.

It is widely acknowledged that discipline at work is a neglected area of study in the context of contemporary employee relations. Within the workplace the handling of discipline is largely prescribed by formal rules that are captured in policies, applied through procedures and then interpreted by the actors who facilitate this process. This thesis argues that an empirical understanding of the disciplinary process can only be achieved if it includes an appreciation of the nature of the relationship that is established during the disciplinary process and that this is crucial for us to develop a full understanding of the dynamics that take place within this activity and between these functions. It contends that throughout the process of disciplinary handling there exists a highly contested terrain (Edwards, 1979) that is constantly contended by the various actors that play out this vital role in relation to aspects of power, control and consent.

Cloud computing represents a distributed computing paradigm that gained notoriety due to its properties related to on-demand elastic and dynamic resource provisioning. These characteristics are highly desirable for the execution of workflows, in particular scientific workflows that required a great amount of computing resources and that handle large-scale data. One of the main questions in this sense is how to manage resources of one or more cloud infrastructures to execute workflows while optimizing resource utilization and minimizing the total duration of the execution of tasks (makespan). The more complex the infrastructure and the tasks to be executed are, the higher the risk of incorrectly estimating the amount of resources to be assigned to each task, leading to both performance and monetary costs. Scenarios which are inherently more complex, such as hybrid and multiclouds, rarely are considered by existing resource management solutions. Moreover, a thorough research of relevant related work revealed that most of the solutions do not address data-intensive workflows, a characteristic that is increasingly evident for modern scientific workflows. In this sense, this proposal presents MPSF, the Multiphase Proactive Scheduling Framework, a cloud resource management solution based on multiple scheduling phases that continuously assess the system to optimize resource utilization and task distribution. MPSF defines models to describe and characterize workflows and resources. MPSF also defines performance and reliability models to improve load distribution among nodes and to mitigate the effects of performance fluctuations and potential failures that might occur in the system. Finally, MPSF defines a framework and an architecture to integrate all these components and deliver a solution that can be implemented and tested in real applications. Experimental results show that MPSF is able to predict with much better accuracy the duration of workflows and workflow phases, as well as providing performance gains compared to greedy approaches. / A computação em nuvem representa um paradigma de computação distribuída que ganhoudestaque devido a aspectos relacionados à obtenção de recursos sob demanda de modo elástico e dinâmico. Estas características são consideravelmente desejáveis para a execução de tarefas relacionadas a fluxos de trabalho científicos, que exigem grande quantidade de recursos computacionais e grande fluxo de dados. Uma das principais questões neste sentido é como gerenciar os recursos de uma ou mais infraestruturas de nuvem para execução de fluxos de trabalho de modo a otimizar a utilização destes recursos e minimizar o tempo total de execução das tarefas. Quanto mais complexa a infraestrutura e as tarefas a serem executadas, maior o risco de estimar incorretamente a quantidade de recursos destinada para cada tarefa, levando a prejuízos não só em termos de tempo de execução como também financeiros. Cenários inerentemente mais complexos como nuvens híbridas e múltiplas nuvens raramente são considerados em soluções existentes de gerenciamento de recursos para nuvens. Além destes fatores, a maioria das soluções não oferece mecanismos claros para tratar de fluxos de trabalho com alta intensidade de dados, característica cada vez mais proeminente em fluxos de trabalho moderno. Neste sentido, esta proposta apresenta MPSF, uma solução de gerenciamento de recursos baseada em múltiplas fases de gerenciamento baseadas em mecanismos dinâmicos de alocação de tarefas. MPSF define modelos para descrever e caracterizar fluxos de trabalho e recursos de modo a suportar cenários simples e complexos, como nuvens híbridas e nuvens integradas. MPSF também define modelos de desempenho e confiabilidade para melhor distribuir a carga e para combater os efeitos de possíveis falhas que possam ocorrer no sistema. Por fim, MPSF define um arcabouço e um arquitetura que integra todos estes componentes de modo a definir uma solução que possa ser implementada e utilizada em cenários reais. Testes experimentais indicam que MPSF não só é capaz de prever com maior precisão a duração da execução de tarefas, como também consegue otimizar a execução das mesmas, especialmente para tarefas que demandam alto poder computacional e alta quantidade de dados.

I en värld som ständigt förändras och utvecklas kan det finnas ett pågående tryck hos organisationer att behålla värdefull kunskap men även att identifiera var kunskap saknas och åtgärda detta. Arbetet med detta hos organisationer kallas ofta för ”kompetensförsörjning”. Syftet med denna studie är att identifiera hur arbetet med kompetensförsörjning i vissa fall kan se ut för HR-medarbetare och chefer i en offentlig verksamhet. Studien är kvalitativ och innehåller tidigare forskning gällande Human Resources och kompetensförsörjning . I studien har fyra halvstrukturerade intervjuer genomförts med fyra respondenter som alla arbetar med HR inom offentlig sektor. Därefter har data blivit tematisk analyserat för att ge form till de olika teman som återfinns i resultatet. Resultatet påvisar att både HR-medarbetare och chefer är delaktiga i arbetet med kompetensförsörjning, men att cheferna ofta tilldelas utvalda ansvarsområden och att HR-medarbetare har det övergripande ansvaret och fungerar som en specialistfunktion. Slutsatsen påvisar att både HRmedarbetare och chefers olika kunskaper är viktiga beståndsdelar i kompetensförsörjningen men även att det finns alternativa arbetssätt som skulle vara önskvärda om tid och möjlighet funnits.

This thesis integrates theory and practice of team coaching into a holistic framework relevant to professional coaches and professional coach educators. I adopt an autoethnographic approach, exploring team coaching via three fieldwork sites; two sites where I am the team coach and thirdly a discussion group of professional coaches. Fieldwork data is collated chronologically and implicit knowledge is surfaced through story telling as a mechanism of sense making to answer the question: What is going on when I am coaching a team? In analysing and interpreting my stories, I take a postmodernist theoretical perspective, adopting a deconstructive approach which seeks to elucidate multiple ways of knowing and seeing. The resulting framework draws on four metaphors. Team as machine that follows a functionalist model of effectiveness that can be managed through behaviours and process. Team as family, which illuminates the interwoven nature of individual relationships and suggests strategies to create safe, mutually respectful collaborative behaviours. Team as living system represents the experience of teams thriving within a dynamic interrelated environment. Finally, the team and coach in Wonderland depicts a coaching assignment as analogous to following the White Rabbit into Wonderland. In a strange environment we may feel uncertain and vulnerable, however, curiosity enables us to remain open to possibilities. Each metaphorical perspective offers a ‘mode of awareness’ from which to operate as a coach. The framework develops our understanding of team coaching by bringing together diverse theoretical streams to inform what is going on in a new and accessible way as the metaphorical devices encapsulate complex ideas with simplicity. I contribute to team coaching practice as professional coaches can use the metaphorical language allied with theory to plan and reflect upon coaching assignments, consider relevant coaching approaches and engage in supervision. A shared language of metaphors provides researchers and practitioners with a new way to describe team coaching, creating a foundation on which to progress development in the future. In addition, the framework provides the basis for a coach development curriculum. I distinguish between team coaching and other team-based interventions and highlight how dyadic coaching practices may be applied within the team context to enable professionals from a variety of backgrounds to engage with the framework. Finally, I offer a transparent insight into a different way of investigating professional coaching practice describing how autoethnography allows us to tell practice stories in ways that are both evocative, insightful and open to analysis.

動態頻譜共享(dynamic spectrum sharing) 允許不具有執照的無線電用戶(坎級用戶)擇機使用具有執照的無線電用戶(主用戶)的頻譜，因此被認為是一種有效解決頻譜低效利用問題的方案。本論文研究次級用戶如何智能地實現高效率的動態頻譜共享。我們考慮兩種智能共享模式:社交智能(social intelligence) 以及個體智能(individual intelligence) 。 / 對於社交智能，次級用戶基於社交互動(social interactions) 來協作地共享頻譜。受到電子商務工業的推薦系統(recommendation sYstem) 的啟發，我們提出了一種基於推薦的社交頻譜共享機制。其中，次級用戶相互協作，彼此推薦良好的信道， 并動態接入信道。我們設計了種基於馬爾科夫決策過程( Markovdecision process) 的自適應信道推薦算法。該算法可突現良好的系統通信性能。同時，我們也提出種基於模仿(imitation) 的社交頻譜分享機制。其中，次級用戶根據自身觀察來估計自己的期望通信速率并彼此分享。如果鄰近用戶的期望通信速率更高，該用戶則模仿鄰近用戶的信道接入。我們證明該機制能夠有效地收斂到模仿均衡。如果次級用戶的數目較多，收斂的模仿均衡即是納什均衡(Nashequilibrium) 。該均衡是個次級用戶相互滿意的頻譜共享結果。 / 對於個體智能，次級用戶基於策略互動(strategic interactions) 來競爭地共享頻譜。對於基於空間複用(spatial reuse) 的競爭性頻譜共享，我們提出了種新穎的空間頻譜接入博弈框架。我們研究了不同的干擾圖形結構對於納什均衡的存在性的影響。同時，我們設計了種基於用戶自身觀察的分佈式學習算法。該算法適用於所有空間頻譜接入博弈，并能夠有效地收斂到近似納什均衡(approximateNash equilibrium) 。對於基於數據庫的電視頻譜(white-space spectrum) 無線AP(access point)網絡，我們運用博弈理論方法為分佈式AP 信道選擇問題以及分佈式次級用戶AP 連接問題建立理論模型。我們證明了分佈式AP信道選擇博奔以及分佈式次級用戶AP 連接博弈屬於勢博弈(potential game) 的範疇。基於勢博莽的有限改進性質(finite improvement property) ，我們設計了分佈式算法能夠有效地收斂到納什均衡。 / Dynamic spectrum sharing enables unlicensed secondary wireless users to opportunistically share the spectrum with licensed primary users, and thus is envisioned as a promising solution to address the spectrum under-utilization problem. This thesis explores the intelligence of secondary users for achieving efficient distributed spectrum sharing. We consider two types of intelligences: social intelligence and individual intelligence. / For the social intelligence, secondary users share the spectrum collaboratively based on social interactions. Inspired by the recommendation system in the electronic commerce industry, we propose a recommendation-based social spectrum sharing mechanism, where secondary users collaboratively recommend "good" channels to each other and access accordingly. We devise an adaptive channel recommendation algorithm based on Markov decision process, which achieves a good system communication performance. We then propose an imitation-based social spectrum sharing mechanism, where each secondary user estimates its expected throughput based on local observations, and imitates another neighboring user’s channel selection if neighbor’s estimated throughput is higher. We show that the mechanism can converge to an imitation equilibrium. When the number of users is large, the convergent imitation equilibrium corresponds to a Nash equilibrium, which is a mutually satisfactory spectrum sharing solution. / For the individual intelligence, secondary users share the spectrum competitively based on strategic interactions. To formulate the competitive spectrum sharing with spatial reuse, we propose a framework of spatial spectrum access game on general directed interference graphs. We investigate the impact of the underlying interference graph structure on the existence of a Nash equilibrium. We also design a distributed learning algorithm based on local observations that can converge to an approximate Nash equilibrium for any spatial spectrum access games. We then apply the game theoretic approach for modeling the distributed channel selection problem among the APs and distributed AP association problem among the secondary users in database-assisted white-space AP networks. We show that both the distributed AP channel selection game and the distributed AP association game are potential games. We then design distributed algorithms for achieving Nash equilibria by utilizing the finite improvement property of potential game. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Chen, Xu. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2012. / Includes bibliographical references (leaves 180-188). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese. / Abstract --- p.i / Acknowledgement --- p.v / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Motivation and Overview --- p.1 / Chapter 1.2 --- Thesis Outline --- p.5 / Chapter I --- Social Intelligence For Distributed Spectrum Sharing --- p.7 / Chapter 2 --- Recommendation-based Social Spectrum Sharing --- p.8 / Chapter 2.1 --- Introduction --- p.8 / Chapter 2.2 --- System Model --- p.12 / Chapter 2.3 --- Introduction To Channel Recommendation --- p.13 / Chapter 2.3.1 --- Review of Static Channel Recommendation --- p.14 / Chapter 2.3.2 --- Motivations For Adaptive Channel Recommendation --- p.16 / Chapter 2.4 --- Adaptive Channel Recommendation With Channel Homogeneity --- p.18 / Chapter 2.4.1 --- MDP Formulation For Adaptive Channel Recommendation --- p.19 / Chapter 2.4.2 --- Existence of Optimal Stationary Policy --- p.21 / Chapter 2.5 --- Model Reference Adaptive Search For Optimal Spectrum Access Policy --- p.22 / Chapter 2.5.1 --- Model Reference Adaptive Search Method --- p.23 / Chapter 2.5.2 --- Model Reference Adaptive Search For Optimal Spectrum Access Policy --- p.24 / Chapter 2.5.3 --- Convergence of Model Reference Adaptive Search --- p.29 / Chapter 2.6 --- Adaptive Channel Recommendation With Channel Heterogeneity --- p.30 / Chapter 2.7 --- Numerical Results --- p.33 / Chapter 2.7.1 --- Simulation Setup --- p.33 / Chapter 2.7.2 --- Homogeneous Channel Recommendation --- p.34 / Chapter 2.7.3 --- Heterogenous Channel Recommendation --- p.35 / Chapter 2.8 --- Chapter Summary --- p.38 / Chapter 2.9 --- Appendix --- p.39 / Chapter 2.9.1 --- Proof of Lemma 2.1 --- p.39 / Chapter 2.9.2 --- Derivation of Transition Probability --- p.40 / Chapter 2.9.3 --- Proof of Theorem 2.1 --- p.41 / Chapter 2.9.4 --- Proof of Theorem 2.2 --- p.42 / Chapter 2.9.5 --- Proof of Theorem 2.3 --- p.47 / Chapter 2.9.6 --- Proof of Theorem 2.4 --- p.50 / Chapter 3 --- Imitation-based Social Spectrum Sharing --- p.52 / Chapter 3.1 --- Introduction --- p.52 / Chapter 3.2 --- Spectrum Sharing System Model --- p.55 / Chapter 3.3 --- Imitative Spectrum Access Mechanism --- p.58 / Chapter 3.3.1 --- Expected Throughput Estimation --- p.59 / Chapter 3.3.2 --- Information Sharing Graph --- p.63 / Chapter 3.3.3 --- Imitative Spectrum Access --- p.63 / Chapter 3.4 --- Convergence of Imitative Spectrum Access --- p.65 / Chapter 3.4.1 --- Cluster-based Representation of Information Sharing Graph --- p.65 / Chapter 3.4.2 --- Dynamics of Imitative Spectrum Access --- p.67 / Chapter 3.4.3 --- Convergence of Imitative Spectrum Access --- p.71 / Chapter 3.5 --- Imitative Spectrum Access with Innovation --- p.73 / Chapter 3.6 --- Imitative Spectrum Access With User Heterogeneity --- p.75 / Chapter 3.7 --- Simulation Results --- p.77 / Chapter 3.7.1 --- Large User Population --- p.78 / Chapter 3.7.2 --- Small User Population --- p.82 / Chapter 3.7.3 --- Markovian Channel Environment --- p.85 / Chapter 3.7.4 --- Imitative Spectrum Access With User Heterogeneity --- p.88 / Chapter 3.8 --- Chapter Summary --- p.88 / Chapter 3.9 --- Appendix --- p.89 / Chapter 3.9.1 --- Proof of Theorem 3.1 --- p.89 / Chapter 3.9.2 --- Proof of Theorem 3.2 --- p.91 / Chapter II --- Individual Intelligence For Distributed Spectrum Sharing --- p.93 / Chapter 4 --- Spatial Spectrum Access Game --- p.94 / Chapter 4.1 --- Introduction --- p.94 / Chapter 4.2 --- System Model --- p.97 / Chapter 4.3 --- Spatial Spectrum Access Game --- p.101 / Chapter 4.4 --- Existence of Nash Equilibria --- p.102 / Chapter 4.4.1 --- Existence of Pure Nash Equilibria on Directed Interference Graphs --- p.103 / Chapter 4.4.2 --- Existence of Pure Nash Equilibria on Undirected Interference Graphs --- p.108 / Chapter 4.5 --- Distributed Learning For Spatial Spectrum Access --- p.113 / Chapter 4.5.1 --- Expected Throughput Estimation --- p.114 / Chapter 4.5.2 --- Distributed Learning Algorithm --- p.115 / Chapter 4.5.3 --- Convergence of Distributed Learning Algorithm --- p.117 / Chapter 4.6 --- Numerical Results --- p.121 / Chapter 4.7 --- Chapter Summary --- p.126 / Chapter 4.8 --- Appendix --- p.127 / Chapter 4.8.1 --- Proof of Theorem 4.2 --- p.127 / Chapter 4.8.2 --- Proof of Theorem 4.3 --- p.129 / Chapter 4.8.3 --- Proof of Lemma 4.4 --- p.131 / Chapter 4.8.4 --- Proof of Lemma 4.5 --- p.133 / Chapter 4.8.5 --- Proof of Theorem 4.5 --- p.136 / Chapter 4.8.6 --- Proof of Theorem 4.6 --- p.139 / Chapter 5 --- Distributed AP Channel Selection Game --- p.141 / Chapter 5.1 --- Introduction --- p.141 / Chapter 5.2 --- Distributed AP Channel Selection --- p.144 / Chapter 5.2.1 --- Problem Formulation --- p.144 / Chapter 5.2.2 --- Distributed AP Channel Selection Game --- p.146 / Chapter 5.3 --- Distributed AP Channel Selection Algorithms --- p.149 / Chapter 5.3.1 --- Distributed AP Channel Selection Algorithm With Information Exchange --- p.149 / Chapter 5.3.2 --- Distributed AP Channel Selection Algorithm Without Information Exchange --- p.151 / Chapter 5.4 --- Numerical Results --- p.157 / Chapter 5.4.1 --- Distributed AP Channel Selection With Information Exchange --- p.157 / Chapter 5.4.2 --- Distributed AP Channel Selection Without Information Exchange --- p.159 / Chapter 5.5 --- Chapter Summary --- p.161 / Chapter 5.6 --- Appendix --- p.162 / Chapter 5.6.1 --- Proof of Theorem 5.2 --- p.162 / Chapter 6 --- Distributed AP Association Game --- p.165 / Chapter 6.1 --- Introduction --- p.165 / Chapter 6.2 --- Distributed AP Association --- p.166 / Chapter 6.2.1 --- Channel Contention Within an AP --- p.167 / Chapter 6.2.2 --- Distributed AP Association Game --- p.168 / Chapter 6.2.3 --- Distributed AP Association Algorithm --- p.170 / Chapter 6.3 --- Numerical Results --- p.172 / Chapter 6.4 --- Chapter Summary --- p.175 / Chapter 7 --- Conclusions and Future Work --- p.176 / Bibliography --- p.180

Next-generation wireless cellular networks are morphing into a massive Internet of Things (IoT) environment that integrates a heterogeneous mix of wireless-enabled devices such as unmanned aerial vehicles (UAVs) and connected vehicles. This unprecedented transformation will not only drive an exponential growth in wireless traffic, but it will also lead to the emergence of new wireless service applications that substantially differ from conventional multimedia services. To realize the fifth generation (5G) mobile networks vision, a new wireless radio technology paradigm shift is required in order to meet the quality of service requirements of these new emerging use cases. In this respect, one of the major components of 5G is self-organized networks. In essence, future cellular networks will have to rely on an autonomous and self-organized behavior in order to manage the large scale of wireless-enabled devices. Such an autonomous capability can be realized by integrating fundamental notions of artificial intelligence (AI) across various network devices. In this regard, the main objective of this thesis is to propose novel self-organizing and AI-inspired algorithms for optimizing the available radio resources in next-generation wireless cellular networks. First, heterogeneous networks that encompass licensed and unlicensed spectrum are studied. In this context, a deep reinforcement learning (RL) framework based on long short-term memory cells is introduced. The proposed scheme aims at proactively allocating the licensed assisted access LTE (LTE-LAA) radio resources over the unlicensed spectrum while ensuring an efficient coexistence with WiFi. The proposed deep learning algorithm is shown to reach a mixed-strategy Nash equilibrium, when it converges. Simulation results using real data traces show that the proposed scheme can yield up to 28% and 11% gains over a conventional reactive approach and a proportional fair coexistence mechanism, respectively. In terms of priority fairness, results show that an efficient utilization of the unlicensed spectrum is guaranteed when both technologies, LTE-LAA and WiFi, are given equal weighted priorities for transmission on the unlicensed spectrum. Furthermore, an optimization formulation for LTE-LAA holistic traffic balancing across the licensed and the unlicensed bands is proposed. A closed form solution for the aforementioned optimization problem is derived. An attractive aspect of the derived solution is that it can be applied online by each LTE-LAA small base station (SBS), adapting its transmission behavior in each of the bands, and without explicit communication with WiFi nodes. Simulation results show that the proposed traffic balancing scheme provides a better tradeoff between maximizing the total network throughput and achieving fairness among all network ows compared to alternative approaches from the literature. Second, UAV-enabled wireless networks are investigated. In particular, the problems of interference management for cellular-connected UAVs and the use of UAVs for providing backhaul connectivity to SBSs are studied. Speci cally, a deep RL framework based on echo state network cells is proposed for optimizing the trajectories of multiple cellular-connected UAVs while minimizing the interference level caused on the ground network. The proposed algorithm is shown to reach a subgame perfect Nash equilibrium upon convergence. Moreover, an upper and lower bound for the altitude of the UAVs is derived thus reducing the computational complexity of the proposed algorithm. Simulation results show that the proposed path planning scheme allows each UAV to achieve a tradeoff between minimizing energy efficiency, wireless latency, and the interference level caused on the ground network along its path. Moreover, in the context of UAV-enabled wireless networks, a UAV-based on-demand aerial backhaul network is proposed. For this framework, a network formation algorithm, which is guaranteed to reach a pairwise stable network upon convergence, is presented. Simulation results show that the proposed scheme achieves substantial performance gains in terms of both rate and delay reaching, respectively, up to 3.8 and 4-fold increase compared to the formation of direct communication links with the gateway node. Overall, the results of the different proposed schemes show that these schemes yield significant improvements in the total network performance as compared to current existing literature. In essence, the proposed algorithms can also provide self-organizing solutions for several resource management problems in the context of new emerging use cases in 5G networks, such as connected autonomous vehicles and virtual reality headsets.