A PERFORMANCE ANALYSIS OF IEEE 802.11ax NETWORKS

The paper is focused on the forthcoming IEEE 802.11ax standard and its influence on Wi-Fi networks performance. The most important features dedicated to improve transmission effectiveness are presented. Furthermore, the simulation results of a new transmission modes are described. The comparison with the legacy IEEE 802.11n/ac standards shows that even partial implementation of a new standard should bring significant throughput improvements

A PERFORMANCE ANALYSIS OF IEEE 802.11ax NETWORKS

The paper is focused on the forthcoming IEEE 802.11ax standard and its influence on Wi-Fi networks performance. The most important features dedicated to improve transmission effectiveness are presented. Furthermore, the simulation results of a new transmission modes are described. The comparison with the legacy IEEE 802.11n/ac standards shows that even partial implementation of a new standard should bring significant throughput improvements

QUALITY OF SERVICE IMPROVEMENTS IN IEEE 802.11AX WI-FI

IEEE 802.11ax is the latest high rate Wi-Fi technology (also known as high efficiency Wireless) introduces some new features like OFDMA, Uplink multi-user MIMO (UL MU-MIMO) to deliver benefits in reliability, capacity, and speed. 802.11ax is better suited to some new use cases, such as live video streaming and IoT than previous versions of Wi-Fi (802.11n/ac). In this article, we study the Quality of Service (QoS) mechanism to guarantee certain levels of service to various traffic flows with the help of weighted fair queuing (WFQ) hierarchical scheduler. The multi-user mode of enhanced distributed channel access (MU mode EDCA) illustrates the controlling aspects, issues, and possible solutions of EDCA for the 802.11ax standard to satisfy QoS requirements in dense deployment scenarios

A Survey on Multi-AP Coordination Approaches over Emerging WLANs: Future Directions and Open Challenges

Recent advancements in wireless local area network (WLAN) technology include IEEE 802.11be and 802.11ay, often known as Wi-Fi 7 and WiGig, respectively. The goal of these developments is to provide Extremely High Throughput (EHT) and low latency to meet the demands of future applications like as 8K videos, augmented and virtual reality, the Internet of Things, telesurgery, and other developing technologies. IEEE 802.11be includes new features such as 320 MHz bandwidth, multi-link operation, Multi-user Multi-Input Multi-Output, orthogonal frequency-division multiple access, and Multiple-Access Point (multi-AP) coordination (MAP-Co) to achieve EHT. With the increase in the number of overlapping APs and inter-AP interference, researchers have focused on studying MAP-Co approaches for coordinated transmission in IEEE 802.11be, making MAP-Co a key feature of future WLANs. Moreover, similar issues may arise in EHF bands WLAN, particularly for standards beyond IEEE 802.11ay. This has prompted researchers to investigate the implementation of MAP-Co over future 802.11ay WLANs. Thus, in this article, we provide a comprehensive review of the state-of-the-art MAP-Co features and their shortcomings concerning emerging WLAN. Finally, we discuss several novel future directions and open challenges for MAP-Co.Comment: The reason for the replacement of the previous version of the paper is due to a change in the author's list. As a result, a new version has been created, which serves as the final draft version before acceptance. This updated version contains all the latest changes and improvements made to the pape

Desenvolvimento de uma estação meteorológica compacta e de baixo custo para aplicações em energias renováveis

Dissertação de mestrado integrado em Engenharia Eletrónica Industrial e ComputadoresNos últimos anos cada vez mais são utilizados painéis fotovoltaicos para produção de energia. Estes permitem utilizar a energia proveniente do sol em forma de radiação e transformar em energia elétrica. Muitos destes painéis têm como elemento fundamental na sua composição o silício, podendo este ter várias variações. Dependendo da variação de silício usado, o custo de produção de um painel fotovoltaico e a sua eficiência irá variar. Nesta dissertação foi desenvolvida uma estação meteorológica capaz de medir diversas variáveis meteorológicas, integrando também três módulos fotovoltaicos de diferentes variações de silício na sua composição, com o objetivo de fazer uma correlação entre as condições meteorológicas e a potência produzida pelos módulos. O sistema desenvolvido permite que os dados medidos pela estação sejam guardados localmente, através de um cartão de memória. A transferência dos dados para o utilizador é feita através da rede sem fios Bluetooth Low Energy (BLE), sendo uma solução em que não são acrescentados custos associados. Os dados transferidos são visualizados através de uma aplicação Android, sendo estes guardados numa base de dados desenvolvida em SQLite. Nesta aplicação podem ser definidas as horas de início e fim de aquisição de dados, bem como o período de amostragem. A aquisição de dados é feita recorrendo a um microcontrolador integrado num módulo com um transceiver BLE. Foi concebida e simulada uma solução para a maximização da produção de energia pelos módulos fotovoltaicos, através do uso de um conversor com capacidades de MPPC (Maximum Power Point Control). O sistema é todo alimentado através de uma bateria LiPo (Lithium Polymer), podendo esta ser recarregada através de um módulo fotovoltaico. O sistema desenvolvido foi testado através da aquisição de dados no exterior em dois dias diferentes. Foi possível a transferência e visualização de todos os dados através da aplicação Android desenvolvida. Os resultados obtidos permitem concluir que o módulo de silício monocristalino apresenta a melhor eficiência de entre as três tecnologias de silício para as condições meteorológicas da localização.In recent years more and more photovoltaic panels are used for energy production. These allow the use of energy from the sun in the form of radiation and transform it into electrical energy. Many of these panels have silicon as their fundamental element in their composition, which may have several variations. Depending on the form of silicon used, the cost of producing a photovoltaic panel and its efficiency will vary. In this dissertation a weather station capable of measuring various weather variables was developed, integrating three photovoltaic modules of different silicon variations in its composition. The developed system allows the data measured by the station to be stored locally using a memory card. Data is transferred to the user device through a Bluetooth Low Energy (BLE) wireless network, which is a solution with no transfer costs associated. The transferred data is viewed through an Android application, and the data is stored in a database developed in SQLite. In this application it can be set the start and end times of data acquisition, as well as the sampling period. Data acquisition is done using a microcontroller integrated in a module with a BLE transceiver. A solution for maximizing the power output of photovoltaic modules was designed and simulated using a converter with maximum power point control (MPPC) capabilities. The entire system is powered by a LiPo (Lithium Polymer) battery, which can be recharged using a photovoltaic module. The developed system was tested by acquiring outdoor data in two different days. It was possible to transfer and view all data through the developed Android application. It is concluded through the obtained results that the monocrystalline silicon module has the best efficiency among the three silicon technologies for the localization weather conditions

Avaliação de cenários 5G

A procura de aplicações de multimédia e voz nas comunicações sem fio tem vindo a crescer imenso nos últimos anos. Além disso, há novas classes de aplicações tais como as comunicações entre móveis de banda larga (eMBB), as comunicações ultra fiáveis e de baixa latência (URLLC), as comunicações massivas entre máquinas (mMTC) e a internet das coisas (IoT) ganharam recentemente muito interesse dentro das redes de comunicação de rádio móvel da quinta geração (5G). Nesta dissertação exploram-se alguns cenários de comunicações 5G. Analisam-se três cenários, um com ligações D2D device-to-device, outro com acesso assistido por Drones além do cenário comum das comunicações celulares como parte dos cenários 5G. As aplicações associadas incluem Automação industrial, Conetividade Automóvel e Comunicações Urbanas. Tomando como base a tecnologia e a estrutura de rede celular Long Term EvolutionAdvanced (LTE-A), nesta dissertação alterou-se o simulador de sistema celular existente para incluir os três cenários representativos da multi-conetividade da rede 5G. São apresentados os resultados obtidos em termos de throughput médio, distribuição do throughput, distribuição da relação sinal interferência, potência transmitida dos Drones, sua velocidade e alturaThe demand for wireless access in voice and multimedia applications has increased tremendously. In addition to these, new application classes, such as enhanced mobile broadband (eMBB) communication, ultra-reliable low latency communications (URLLC), massive machine type communications (mMTC), and the Internet of Things (IoT), have gained significant interest recently for 5G wireless networks. In this dissertation some 5G scenarios are explored. Three different scenarios, one with device-to-device (D2D) connections, another with Drone assisted communications beside the common mobile cellular network communications, as part of the 5G scenarios. The applications associated include industrial automation, automatic driving connection and urban area communications. In this dissertation, it was taken as reference the structure of the cellular network with LTE-Advanced technology. The previous version of the cellular system level simulator was updated with two additional scenarios, the Drone based and D2D connections to achieve the multi-connectivity of 5G. The obtained results include average throughput, distribution of throughput, distribution of signal to interference plus noise ratio, Drone transmitted power its velocity and altitude

Multi-Drone-Cell 3D Trajectory Planning and Resource Allocation for Drone-Assisted Radio Access Networks

Equipped with communication modules, drones can perform as drone-cells (DCs) that provide on-demand communication services to users in various scenarios, such as traffic monitoring, Internet of things (IoT) data collections, and temporal communication provisioning. As the aerial relay nodes between terrestrial users and base stations (BSs), DCs are leveraged to extend wireless connections for uncovered users of radio access networks (RAN), which forms the drone-assisted RAN (DA-RAN). In DA-RAN, the communication coverage, quality-of-service (QoS) performance and deployment flexibility can be improved due to the line-of-sight DC-to-ground (D2G) wireless links and the dynamic deployment capabilities of DCs. Considering the special mobility pattern, channel model, energy consumption, and other features of DCs, it is essential yet challenging to design the flying trajectories and resource allocation schemes for DA-RAN. In specific, given the emerging D2G communication models and dynamic deployment capability of DCs, new DC deployment strategies are required by DA-RAN. Moreover, to exploit the fully controlled mobility of DCs and promote the user fairness, the flying trajectories of DCs and the D2G communications must be jointly optimized. Further, to serve the high-mobility users (e.g. vehicular users) whose mobility patterns are hard to be modeled, both the trajectory planning and resource allocation schemes for DA-RAN should be re-designed to adapt to the variations of terrestrial traffic. To address the above challenges, in this thesis, we propose a DA-RAN architecture in which multiple DCs are leveraged to relay data between BSs and terrestrial users. Based on the theoretical analyses of the D2G communication, DC energy consumption, and DC mobility features, the deployment, trajectory planning and communication resource allocation of multiple DCs are jointly investigated for both quasi-static and high-mobility users. We first analyze the communication coverage, drone-to-BS (D2B) backhaul link quality, and optimal flying height of the DC according to the state-of-the-art drone-to-user (D2U) and D2B channel models. We then formulate the multi-DC three-dimensional (3D) deployment problem with the objective of maximizing the ratio of effectively covered users while guaranteeing D2B link qualities. To solve the problem, a per-drone iterated particle swarm optimization (DI-PSO) algorithm is proposed, which prevents the large particle searching space and the high violating probability of constraints existing in the pure PSO based algorithm. Simulations show that the DI-PSO algorithm can achieve higher coverage ratio with less complexity comparing to the pure PSO based algorithm. Secondly, to improve overall network performance and the fairness among edge and central users, we design 3D trajectories for multiple DCs in DA-RAN. The multi-DC 3D trajectory planning and scheduling is formulated as a mixed integer non-linear programming (MINLP) problem with the objective of maximizing the average D2U throughput. To address the non-convexity and NP-hardness of the MINLP problem due to the 3D trajectory, we first decouple the MINLP problem into multiple integer linear programming and quasi-convex sub-problems in which user association, D2U communication scheduling, horizontal trajectories and flying heights of DBSs are respectively optimized. Then, we design a multi-DC 3D trajectory planning and scheduling algorithm to solve the sub-problems iteratively based on the block coordinate descent (BCD) method. A k-means-based initial trajectory generation scheme and a search-based start slot scheduling scheme are also designed to improve network performance and control mutual interference between DCs, respectively. Compared with the static DBS deployment, the proposed trajectory planning scheme can achieve much lower average value and standard deviation of D2U pathloss, which indicate the improvements of network throughput and user fairness. Thirdly, considering the highly dynamic and uncertain environment composed by high-mobility users, we propose a hierarchical deep reinforcement learning (DRL) based multi-DC trajectory planning and resource allocation (HDRLTPRA) scheme for high-mobility users. The objective is to maximize the accumulative network throughput while satisfying user fairness, DC power consumption, and DC-to-ground link quality constraints. To address the high uncertainties of environment, we decouple the multi-DC TPRA problem into two hierarchical sub-problems, i.e., the higher-level global trajectory planning sub-problem and the lower-level local TPRA sub-problem. First, the global trajectory planning sub-problem is to address trajectory planning for multiple DCs in the RAN over a long time period. To solve the sub-problem, we propose a multi-agent DRL based global trajectory planning (MARL-GTP) algorithm in which the non-stationary state space caused by multi-DC environment is addressed by the multi-agent fingerprint technique. Second, based on the global trajectory planning results, the local TPRA (LTPRA) sub-problem is investigated independently for each DC to control the movement and transmit power allocation based on the real-time user traffic variations. A deep deterministic policy gradient based LTPRA (DDPG-LTPRA) algorithm is then proposed to solve the LTPRA sub-problem. With the two algorithms addressing both sub-problems at different decision granularities, the multi-DC TPRA problem can be resolved by the HDRLTPRA scheme. Simulation results show that 40% network throughput improvement can be achieved by the proposed HDRLTPRA scheme over the non-learning-based TPRA scheme. In summary, we have investigated the multi-DC 3D deployment, trajectory planning and communication resource allocation in DA-RAN considering different user mobility patterns in this thesis. The proposed schemes and theoretical results should provide useful guidelines for future research in DC trajectory planning, resource allocation, as well as the real deployment of DCs in complex environments with diversified users