In recent years, several studies and simulations have been made on changing the current Radio Access Network (RAN) architecture into a more centralized access network where the base band processing is done in a central oce (CO) instead of out by the antenna site. This new architecture is denoted as the mobile fronthaul and is planned to be in use for the coming 5G network. The studies that have been made so far suggest that the new architecture can reduce cost, power usage and latency which are important factors regarding environmental, economical and data transmission issues. Furthermore, the new architecture allows a smarter distribution of data for each sector covered by the antennas, reducing redundant data transmission and thus increases the data eciency. The disadvantage or challenge however is that some of the optical components will be transferred from the currently controlled environment in the CO to an uncontrolled outdoor environment at the antenna site, which may generate risks as these components may be sensitive to especially changes in temperature. In this master thesis, the optical performance of four di erent passive lter setups, using a thin lm lter (TFF), an arrayed waveguide grating (AWG) and an interleaver, has been studied and compared in order to nd the most suitable lter setup for the mobile fronthaul. These optical parameters include insertion loss, isolation, crosstalk, 3 dB passband, center wavelength drift and also bit error-rate (BER) which have all been measured over a temperature interval of -40-85oC. Moreover, the measurement results have been compared with results from simulations done with VPItransmissionmaker. From the measurement results, the TFF had a better optical performance and reliability compared to the AWG mainly due to a higher isolation and a lower BER penalty of 0.2 dB compared to 0.5-1.5 dB for the AWG. Considering data capacity and economical aspects for a more realistic mobile fronthaul scenario with 80 channels using dense wavelength division multiplexing (DWDM) however, the AWG connected to the interleaver is more benecial without risking negative a ects on trac performance. / Under senare år har flera studier och simulationer utförts med syfte att ändra arkitekturen på dagens radioaccess-nätverk till ett mer centraliserat nätverk där basbandsprocesseringen sker i en central nod istället för ute vid antennen och radiomasterna. Denna nya arkitektur kallas mobile fronthaul och planeras att realiseras till 5G-nätet. De studier som har gjorts hittills indikerar på att den nya arkitekturen kan minska ekonomiska kostnader, elanvändningen och latens vilka är viktiga faktorer som bland annat rör miljö-, ekonomi och kapacitetrelaterade områden. Dessutom kan data fördelas på ett smartare sätt över alla delområden som antennerna täcker vilket minskar redundant datatrafik och därmed ökar den effektiva mängden data som skickas ut. Problemet eller utmaningen är att vissa optiska komponenter behöver flyttas från en nuvarande kontrollerad miljö till en okontrollerad utemiljö vid radiomasterna vilket kan medföra risker då dessa komponenter främst kan vara väldigt temperaturkänsliga. Inom detta examensarbete har optisk prestanda studerats, analyserats och jämförts mellan fyra olika filterkonstellationer bestående av ett tunnfilmsfilter, ett AWG-filter och en interleaver med syfte att finna vilken konstellation som passar bäst för mobile fronthaularkitekturen. De optiska parametrarna består av insertionsförluster, isolation, överhörningsinterferens, 3 dB-passband, centervåglängdsdrift samt bitfelsgrad vilka alla har blivit undersökta över ett temperaturintervall på -40-85oC. Utöver detta så har mätresultaten jämförts med simulationer gjorda med VPItransmissionmaker. Utifrån mätresultaten kunde det konstateras att tunnfilmfiltret hade bättre optiska egenskaper och även högre trovärdighet jämfört med AWG-filtret främst på grund av en högre isolation och lägre bitfelsgradsstraff på 0.2 dB jämfört med 0.5-1.5 dB för AWG-filtret. Om en endast avväger datakapacitet och ekonomiska aspekter för ett mer realistiskt scenario för mobile fronthaul med 80 DWDM-kanaler så är AWG-filtret tillsammans med interleavern mer foördelaktig att välja utan att riskera några negativa påverkningar på trafikprestandan.

Cellular networks have significantly transformed the way we communicate and access data and the data rates have only been increasing for the last 30 years. 5G is the current generation of cellular networks and enables faster data rates and lower latency. One of the cellular network architectures used to enable 5g is centralized radio access networks (C-RAN). C-RAN centralizes all the baseband units (BBU) into one or a few locations in contrast to traditional architectures where BBUs are separated. This centralization causes more demand on the fronthaul to transfer larger amounts of data. To mitigate this demand on the fronthaul, functional splits were developed to distribute the baseband functions dependent on the need. This thesis focuses on simulating several functional splits in C-RAN with packetized fronthaul. The objective is to study the impact the functional split options have on the network by investigating key metrics such as fronthaul link throughput, utilization, and, buffer usage. The thesis includes the development of a digital twin (DT) of C-RAN deployments. This digital twin is implemented in Python using the SimPy library to enable discrete event simulation. The DT was then used to simulate each split option over low, medium, and high traffic loads. The network that was simulated includes one BBU, fronthual link, one switch, and three remote radio units with 64 antennas. The fronthaul link is 1 km long and has a transfer rate of 100 Gbps. The results show that various functional split options have a significant impact on the network’s overall performance. This impact is mostly dependent on the split option choice and not on the load for this configuration. Overall, this thesis contributes to the understanding of functional splits in centralized radio access networks with packetized fronthaul. / Mobilnäten har förändrat hur vi kommunicerar och får tillgång till data, och datahastigheterna har bara ökat under de senaste 30 åren. 5G är den nuvarande generationen av mobilnät och möjliggör snabbare datahastigheter och lägre latens. En av de mobilnät arkitekturer som används för att möjliggöra 5g är centraliserade radioaccessnät (C-RAN). C-RAN centraliserar alla basbandsenheter (BBU) till en eller ett mindre antal platser i motsats till traditionella arkitekturer där BBU är separerade. Denna centralisering leder till att fronthaul länken belastas mer för att överföra större data mängder. För att minska denna belastning på fronthaul länken kan funktionella uppdelningar användas för att distribuera basbandsfunktionerna beroende på behov. Det här arbetet fokuserar på att simulera flera funktionella uppdelningar i centraliserade radio radioaccessnätvärk med paketerad fronthaul. Syftet är att studera vilken påvärkan de funktionella uppdelnings alternativen har på nätverket genom att undersöka och mäta värden som genomströmning, utnyttjande av fronthaul kabel och buffertanvändning i fronthaulen. I arbetet inkluderar utvecklingen av en digital tvilling (DT) av C-RAN. Denna digitala tvilling implementeras i Python med hjälp av SimPy-biblioteket för att möjliggöra discrete event simulation"vilket betyder simulering av diskreta händelser. DT användes sedan för att simulera varje uppdelnings alternativ över låg, medelhög och hög trafikbelastning. Nätverket som simulerades inkluderar en badeband unit (BBH), en fronthual länk, en switch och tre remote radio unit (RRU) med 64 antenner. Fronthaul länken är 1 km lång och har en överföringshastighet på 100 Gbps. Resultaten visar att olika uppdelningar har en betydande påvärkan på nätverkets övergripande prestanda. Denna påverkan beror främst på valet av delningsalternativet och inte av belastningen för denna konfiguration.svis så bidrar detta arbete till förståelsen av funktionella delningar i centraliserade radioaccessnät radioaccessnät med paketerad fronthaul i olika trafikbelastningar.

Enhancement of QoS in PS network as 5G communication network is non trivial endeavour which faces a host of new challenges beyond 3G and 4G communication networks. The number of nodes, the homogeneity of the access technologies, the conflicting network management objectives, resource usage minimization, and the division between limited physical resources and elastic virtual resources is driving a complete change in the vision and methodologies for efficient management of the available network resources. QoS is the measure of the reliability and performance of the networks' nodes and links, particularly as perceived by the end users of the services and application that are transported via PS network. Furthermore, QoS is a composite metric as it based on a number of multiple factors, which indicate the E2E characteristics and performance of the network condition, applications and services. Hence, reductions or improvements in the QoS level can brought about through a number of combined factors. This thesis tries to introduce a vision of Quality of Service (QoS) enhancement and management based on the 5th generation network requirements and solutions by: Firstly: Proposing a traffic flow management policy, which allocates and organises Machine Type Communication (MTC) traffic flow's network resources sharing within Evolved Packet System (EPS), with an access element as a Wireless Sensor Network (WSN) gateway for providing an overlaying access channel between the Machine Type Devices (MTDs) and EPS. This proposal addresses the effect and interaction in the heterogeneity of applications, services and terminal devices and the related QoS issues among them. The introduced work in this proposal overcomes the problems of network resource starvation by preventing deterioration of network performance. The scheme is validated through simulation, which indicates the proposed traffic flow management policy outperforms the current traffic management policy. Specifically, simulation results show that the proposed model achieves an enhancement in QoS performance for the MTC traffic flows, including a decrease of 99.45% in Packet Loss Rate (PLR), a decrease of 99.89% in packet End to End (E2E) delay, a decrease of 99.21% in Packet Delay Variation (PDV). Furthermore, it retains the perceived Quality of Experience (QoE) of the real time application users within high satisfaction levels, such as the Voice over Long Term Evolution (VoLTE) service possessing a Mean Opinion Score (MOS)of 4.349 and enhancing the QoS of a video conference service within the standardised values of a 3GPP body, with a decrease of 85.28% in PLR, a decrease of 85% in packet E2E delay and a decrease of 88.5% in PDV. Secondly: Proposing an approach for allocating existing 4G installed network radio access nodes to multiple Base Band Unit (BBU) pools, which is proposed to deploy 5G Cloud-Radio Access Network (C-RAN) and improve the offered Network QoS (NQoS). The proposed approach involves performing radio access nodes clustering based on the Particle Swarm Optimization (PSO) algorithm, model selection Bayesian Information Criterion (BIC), Measure of spread technique and Voronoi tessellation. The proposed scheme is used to consider a Dynamic C-RAN (DC-RAN) operation, that adaptively adjusts the main Radio Remote Head (RRH) coverage range according to the traffic load requirement as well as considering energy saving. The numerical results of the approach show that the optimized partition of the proposed network model is 41 BBU pools, with an average density of RRHs per pool area, which matches the primary average density of the radio access nodes per network area. Thirdly: Developing mathematical framework that investigates the Power Consumption (PC) profile for the interaction of Internet of Thing (IoT) Application QoS (AQoS) with NQoS in wireless Software Defined Network (SDN) as SDN for WIreless SEnsor network (SDN-WISE). This profile model offers flexibility for managing the structure of the Machine to Machine (M2M) system in IoT. It enables controlling the provided NQoS, precisely the achieved PHY layer transmission link throughput, combined with the AQoS, represented by IoT data stream payload size. The investigation is composed of two essential SDN traffic parts, they are control plane signalling and data plane traffic PCs and their relevance with QoS. The results show that 98% PC in data plane companion with a control plane PC of 2% in overall of the proposed system power, these figures were achieved with control plane signalling Transmission Time Interval (TTI) of 5 sec and a maximum data plane payload size of 92 Bytes as a worst case scenario.

This dissertation is directed towards improving the performance of 5G Wireless Fronthaul Networks and Wireless Sensor Networks, as measured by reliability, fault recovery time, energy consumption, efficiency, and security of transmissions, beyond what is achievable with conventional error control technology. To achieve these ambitious goals, the research is focused on novel applications of networking techniques, such as Diversity Coding, where a feedforward network design uses forward error control across spatially diverse paths to enable reliable wireless networking with minimal delay, in a wide variety of application scenarios. These applications include Cloud-Radio Access Networks (C-RANs), which is an emerging 5G wireless network architecture, where Remote Radio Heads (RRHs) are connected to the centralized Baseband Unit (BBU) via fronthaul networks, to enable near-instantaneous recovery from link/node failures. In addition, the ability of Diversity Coding to recover from multiple simultaneous link failures is demonstrated in many network scenarios. Furthermore, the ability of Diversity Coding to enable significantly simpler and thus lower-cost routing than other types of restoration techniques is demonstrated. Achieving high throughput for broadcasting/multicasting applications, with the required level of reliability is critical for the efficient operation of 5G wireless infrastructure networks. To improve the performance of C-RAN networks, a novel technology, Diversity and Network Coding (DC-NC), which synergistically combines Diversity Coding and Network Coding, is introduced. Application of DC-NC to several 5G fronthaul networks, enables these networks to provide high throughput and near-instant recovery in the presence of link and node failures. Also, the application of DC-NC coding to enhance the performance of downlink Joint Transmission-Coordinated Multi Point (JT-CoMP) in 5G wireless fronthaul C-RANs is demonstrated. In all these scenarios, it is shown that DC-NC coding can provide efficient transmission and reduce the resource consumption in the network by about one-third for broadcasting/multicasting applications, while simultaneously enabling near-instantaneous latency in recovery from multiple link/node failures in fronthaul networks. In addition, it is shown by applying the DC-NC coding, the number of redundant links that uses to provide the required level of reliability, which is an important metric to evaluate any protection system, is reduced by about 30%-40% when compared to that of Diversity Coding. With the additional goal of further reducing of the recovery time from multiple link/node failures and maximizing the network reliability, DC-NC coding is further improved to be able to tolerate multiple, simultaneous link failures with less computational complexity and lower energy consumption. This is accomplished by modifying Triangular Network Coding (TNC) and synergistically combining TNC with Diversity Coding to create enhanced DC-NC (eDC-NC), that is applied to Fog computing-based Radio Access Networks (F-RAN) and Wireless Sensor Networks (WSN). Furthermore, it is demonstrated that the redundancy percentage for protecting against n link failures is inversely related to the number of source data streams, which illustrates the scalability of eDC-NC coding. Solutions to enable synchronized broadcasting are proposed for different situations. The ability of eDC-NC coding scheme to provide efficient and secure broadcasting for 5G wireless F-RAN fronthaul networks is also demonstrated. The security of the broadcasting data streams can be obtained more efficiently than standardized methods such as Secure Multicasting using Secret (Shared) Key Cryptography.

Next-generation wireless communication systems will need to contend with many active mobile devices, each of which will require a very high data rate. To cope with this growing demand, network deployments are becoming denser, leading to higher interference between active users. Conventional architectures aim to mitigate this interference through careful design of signaling and scheduling protocols. Unfortunately, these methods become less effective as the device density increases. One promising option is to enable cellular basestations (i.e., cell towers) to jointly process their received signals for decoding users’ data packets as well as to jointly encode their data packets to the users. This joint processing architecture is often enabled by a cloud radio access network that links the basestations to a central processing unit via dedicated connections. One of the main contributions of this thesis is a novel end-to-end communications architecture for cloud radio access networks as well as a detailed comparison to prior approaches, both via theoretical bounds and numerical simulations. Recent work has that the following high-level approach has numerous advantages: each basestation quantizes its observed signal and sends it to the central processing unit for decoding, which in turn generates signals for the basestations to transmit, and sends them quantized versions. This thesis follows an integer-forcing approach that uses the fact that, if codewords are drawn from a linear codebook, then their integer-linear combinations are themselves codewords. Overall, this architecture requires integer-forcing channel coding from the users to the central processing unit and back, which handles interference between the users’ codewords, as well as integer-forcing source coding from the basestations to the central processing unit and back, which handles correlations between the basestations’ analog signals. Prior work on integer-forcing has proposed and analyzed channel coding strategies as well as a source coding strategy for the basestations to the central processing unit, and this thesis proposes a source coding strategy for the other direction. Iterative algorithms are developed to optimize the parameters of the proposed architecture, which involve real-valued beamforming and equalization matrices and integer-valued coefficient matrices in a quadratic objective. Beyond the cloud radio setting, it is argued that the integer-forcing approach is a promising framework for interference alignment between multiple transmitter-receiver pairs. In this scenario, the goal is to align the interfering data streams so that, from the perspective of each receiver, there seems to be only a signal receiver. Integer-forcing interference alignment accomplishes this objective by having each receiver recover two linear combinations that can then be solved for the desired signal and the sum of the interference. Finally, this thesis investigates the impact of channel coherence on the integer-forcing strategy via numerical simulations.

No / Next-generation 5G networks is the future of information networks and it will experience a tremendous growth in traffic. To meet such traffic demands, there is a necessity to increase the network capacity, which requires the deployment of ultra dense heterogeneous base stations (BSs). Nevertheless, BSs are very expensive and consume a significant amount of energy. Meanwhile, cloud radio access networks (C-RAN) has been proposed as an energy-efficient architecture that leverages the cloud computing technology where baseband processing is performed in the cloud. In addition, the BS sleeping is considered as a promising solution to conserving the network energy. This paper integrates the cloud technology and the BS sleeping approach. It also proposes an energy-efficient scheme for reducing energy consumption by switching off remote radio heads (RRHs) and idle BBUs using a greedy and first fit decreasing (FFD) bin packing algorithms, respectively. The number of RRHs and BBUs are minimized by matching the right amount of baseband computing load with traffic load. Simulation results demonstrate that the proposed scheme achieves an enhanced energy performance compared to the existing distributed long term evolution advanced (LTE-A) system.

Current mobile network architecture is facing a big challenge as the traffic demands have been increasing dramatically these years. Explosive mobile data demands are driving a significant growth in energy consumption in mobile networks, as well as the cost and carbon footprints [1]. In 2010, China Mobile Research Institute proposed Cloud Radio Access Network (C-RAN) [2], which has been regarded as one of the most promising architecture to solve the challenge of operators. In C-RAN, the baseband units (BBU) are decoupled from the remote radio units (RRH) and centralized in one or more locations. The feasibility of combination of implementing the very tight radio coordination schemes and sharing baseband processing and cooling system resources proves to be the two main advantages of C-RAN compared to traditional RAN. More importantly, mobile operators can quickly deploy RRHs to expand and make upgrades to their networks. Therefore, the C-RAN has been advocated by both operators and equipment vendors as a means to achieve the significant performance gains required for 5G [3]. However, one of the biggest barriers has shown up in the deployment of C-RAN as the novel architecture imposes very high capacity requirement on the transport network between the RRHs and BBUs, which is been called fronthaul network. With the implementation of 5G wireless system using advanced multi-antenna transmission (MIMO), the capacity requirement would go further up, as well as the power consumption. One solution has been proposed to solve the problem is to have the baseband functions divided, partially staying with RRHs and other functions would be centralized in BBU pool. Different splitting solutions has been proposed in [4] [5] and [6]. In this thesis work, we choose four different splitting solutions to build four CRAN architecture models. Under one specific case scenario with the fixed number of LTE base stations, we calculate the transport capacity requirement for fronthaul and adopt three different fronthaul technology. The power consumption is calculated by adding up the power utilized by RRHs, fronthaul network and baseband processing. By comparing the numerical results, split 1 and 2 shows the best results while split 2 is more practical for dense cell area, since split 1 requires large fronthaul capacity. The fronthaul transport technology can be decided according to different density of base stations. TWDM-PON shows better energy performance as fronthaul network when the capacity requirement is high, compared to EPON. However, for larger number of BSs, mm-Wave fronthaul is a better solution in terms of energy efficiency, fiber saving and flexibility.

No / The healthcare sector is now blending with Information and Communications Technology (ICT) using Internet of Things (IoT) to potentially minimise medical errors and reduce healthcare cost. Patients are now embedded with smart devices like body sensors and wearable devices which can monitor their health without the need for a doctor in physical contact. Such smart devices have the downside of low battery power and are unable to transmit their data to the medical personnel when the patient is on the move away from the smart home/smart clinic fixed gateway. A mobile gateway is required which moves with the patient to process the smart device data without depleting the smartphone battery. This paper proposes an Intelligent and Energy Efficient SG based smartphone Gateway for healthcare smart devices (IEE5GG). In IEE5GG, the 5G architecture is adopted and the patient's smartphone is used as a gateway where multiple smart devices are connected e.g. via Bluetooth. To save energy, requests to the smartphone can either be executed on the smartphone gateway or offloaded and executed in the Mobile Edge Computing (MEC) cloud at close proximity to the smartphone in the 5G Base Station (BS) central Unit (gNB-CU) while considering the transmission power, Quality of Service (QoS), smartphone battery level and Central Processing Unit (CPU) load. Results show that the proposed IEE5GG framework saves up to 38% of energy in the healthcare mobile gateway smartphone and reduces healthcare application service time by up to 41%. / British Council Institutional Links grant under the BEIS-managed Newton Fund.

Future mobile networks are anticipated to not only enhance communication performance but also facilitate new sensing-based applications. This highlights the essential role of integrated sensing and communication (ISAC) in sixth-generation (6G) and beyond mobile networks. The seamless integration of sensing and communication poses challenges in deployment and resource allocation. Cell-free massive multiple-input multiple-output (MIMO) networks, characterized by multiple distributed access points, offer a promising infrastructure for ISAC implementation. However, the effective realization of ISAC necessitates joint design and resource allocation optimization. In this thesis, we study ISAC within cell-free massive MIMO systems, with a particular emphasis on developing power allocation algorithms under various scenarios. In this thesis, we explore two scenarios: utilizing existing communication signals and incorporating additional sensing signals. We propose power allocation algorithms aiming to maximize the sensing performance while meeting communication and power constraints. In addition, we develop two maximum a posteriori ratio test (MAPRT) target detectors under clutter-free and cluttered scenarios. Results indicate that employing additional sensing signals enhances sensing performance, particularly in scenarios where the target has low reflectivity. Moreover, although the clutter-aware detector requires more advanced processing, it leads to better sensing performance. Furthermore, we introduced sensing spectral efficiency (SE) to measure the effect of resource block utilization, highlighting the integration advantages of ISAC over orthogonal resource sharing approaches.  In the next part of the thesis, we study the energy efficiency aspects of ISAC in cell-free massive MIMO systems with ultra-reliable low-latency communications (URLLC) users. We propose a power allocation algorithm aiming to maximize energy efficiency of the system while meeting communication and sensing requirements. We conduct a comparative analysis between the proposed power allocation algorithms and a URLLC-only approach which takes into account only URLLC and power requirements. The results reveal that while the URLLC-only algorithm excels in energy efficiency, it is not able to support sensing requirements.   Moreover, we study the impact of ISAC on end-to-end (including radio and processing) energy consumption. Particularly, we present giga-operations per second (GOPS) analysis for both communication and sensing tasks. Two optimization problems are formulated and solved to minimize transmission and end-to-end energy through blocklength and power optimization. Results indicate that while end-to-end energy minimization offers substantial energy savings, its efficacy diminishes with sensing integration due to processing energy requirements. / Framtida mobila nätverk förväntas inte bara förbättra kommunikations-prestanda utan även mögliggöra nya applikationer baserade på sensorer. Dettaunderstryker den avgörande rollen för Integrerad avkänning och kommunika-tion (ISAC) i sjätte generationens (6G) och efterföljande mobila nätverk. Densömlösa integrationen av sensorer och kommunikation medför utmaningar iutrullning och resursallokering. Cellfria massiva flerantennsystem (MIMO-nätverk), kännetecknade av flera distribuerade åtkomstpunkter, erbjuder enlovande infrastruktur för implementering av ISAC. Dock kräver den effektivarealiseringen av ISAC samverkande design och optimering av resursallokering.I denna avhandling studerar vi ISAC inom cellfria massiva MIMO-system,med särskild tonvikt på att utveckla effektallokeringsalgoritmer under olikascenarier.Vi utforskar två scenarier: att utnyttja befintliga kommunikationssignaleroch att inkludera ytterligare sensorssignaler. Vi föreslår effektallokeringsalgo-ritmer med målet att maximera sensorsprestandan samtidigt som kommunika-tions och effektbegränsningar uppfylls. Dessutom utvecklar vi två detektorerbaserade på maximum a posteriori ratio test (MAPRT) under störningsfriaoch störda scenarier. Resultaten visar att användning av ytterligare sensors-signaler förbättrar sensorsprestandan, särskilt i scenarier där målet har lågreflektivitet. Dessutom, även om den störkänsliga detektorn kräver mer avan-cerad bearbetning, leder den till bättre sensorsprestanda. Vidare introducerarvi sensorerspektral effektivitet (SE) för att mäta effekten av resursblocksan-vändning och framhäva integrationsfördelarna med ISAC över ortogonala re-sursdelningsmetoder.I den andra delen av avhandlingen studerar vi energieffektivitetsaspek-terna av ISAC i cellfria massiva MIMO-system med användare med ultra-tillförlitlig låg-latens (URLLC) kommunikation. Vi föreslår en effektalloke-ringsalgoritm med syfte att maximera systemets energieffektivitet samtidigtsom kommunikations- och sensorskraven uppfylls. Vi utför en jämförande ana-lys mellan de föreslagna effektallokeringsalgoritmerna och ett URLLC-ensamttillvägagångssätt som tar hänsyn enbart till URLLC- och effektkrav. Resul-taten avslöjar att medan URLLC-ensamma algoritmen utmärker sig i energi-effektivitet, kan den inte stödja sensorskraven. Dessutom studerar vi effektenav ISAC på slut till slut (inklusive radios och bearbetning) energiförbruk-ning. Särskilt presenterar vi giga-operationer per sekund (GOPS) analys förbåde kommunikations- och sensorsuppgifter. Två optimeringsproblem formu-leras och löses för att minimera överförings- och slut till slut energi genomblocklängd- och effektoptimering. Resultaten indikerar att medan slut till slutenergiminimering erbjuder betydande energibesparingar, minskar dess effek-tivitet med sensorintegrationen på grund av bearbetningsenergikrav. / <p>QC 20240513</p>

There is a prolific increase in the penetration of user devices such as smartphones and tablets. In addition, user expectations for higher Quality of Service (QoS), enhanced data rates and lower latencies are relentless. In this context, network densification through the dense deployment of small cell networks, underlaying the currently existing macrocell networks, is the most appealing approach to handle the aforementioned requirements. Small cell networks are capable of reusing the spectrum locally and providing most of the capacity while macrocell networks provide a blanket coverage for mobile user equipment (UEs). However, such setup imposes a lot of issues, among which, co-tier and cross-tier interference are the most challenging. To handle co-tier interference, I have proposed a semi-distributed (hierarchical) interference management scheme based on joint clustering and resource allocation (RA) for small cells. I have formulated the problem as a Mixed Integer Non-Linear Program (MINLP), whose solution was obtained by dividing the problem into two sub-problems, where the related tasks were shared between the Femto Gateway (FGW) and small cells. As for cross-tier interference, I have formulated RA problems for both the macrocell and small cells as optimization problems. In particular, I have introduced the idea of ``Tier-Awareness'' and studied the impact of the different RA policies in the macrocell tier on the small cells performance. I have shown that the RA policy in one tier should be carefully selected. In addition, I have formulated the RA problem for small cells as an optimization problem with an objective function that accounts for both RA and admission control (AC). Finally, I have studied cloud radio access network (C-RAN) of small cells which has been considered as a typical realization of a mobile network which is capable of supporting soft and green technologies in Fifth Generation (5G) networks, as well as a platform for the practical implementation of network multiple-input multiple-output (MIMO) and coordinated multi-point (CoMP) transmission concepts. / February 2016