63 research outputs found

    Performance analysis of 802.11ac with frame aggregation using NS3

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    802.11ac is an interesting standard of IEEE bringing multiple advantages than its predecessor 802.11n. 802.11ac is faster and more scalable version of 802.11n offering the capabilities of wireless Gigabit Ethernet. 802.11ac will enable access points (AP) to support more STAs with a better experience for clients and more channel bonding increasing from a maximum of 40 MHz with 802.11n up to 80 or 160 MHz with 802.11ac standard. In this paper, we analyze and evaluate the 802.11ac performance using NS3 simulator (v3.26) relying on several features like channel bonding, modulation and coding schemes, guard interval and frame aggregation. Then, we present the effect of the variation of distance between STAs and AP on the network performance in term of throughput. Finally, we capture the most relevant simulations outcomes and we indicate some research challenges for the future work

    A New Adaptive Frame Aggregation Method for Downlink WLAN MU-MIMO Channels

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    Accommodating the heterogeneous traffic demand among streams in the downlink MU-MIMO channel is among the challenges that affect the transmission efficiency since users in the channel do not always have the same traffic demand. Consequently, it is feasible to adjust the frame size to maximize the system throughput. The existing adaptive aggregation solutions do not consider the effects of different traffic scenarios and they use a Poison traffic model which is inadequate to represent the real network traffic scenarios, thus leading to suboptimal solutions. In this study, we propose some adaptive aggregation strategies which employ a novel dynamic adaptive aggregation policy selection algorithm in addressing the challenges of heterogenous traffic demand in the downlink MU-MIMO channel. Different traffic models are proposed to emulate real world traffic scenarios in the network and to analyze the proposed aggregation polices with respect to various traffic models. Finally, through simulation, we demonstrate the performance of our adaptive algorithm over the baseline FIFO aggregation approach in terms of system throughput performance and channel utilization in achieving the optimal frame size of the system

    A MAC Throughput in the Wireless LAN

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    An Adaptive Packet Aggregation Algorithm (AAM) for Wireless Networks

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    Packet aggregation algorithms are used to improve the throughput performance by combining a number of packets into a single transmission unit in order to reduce the overhead associated with each transmission within a packet-based communications network. However, the throughput improvement is also accompanied by a delay increase. The biggest drawback of a significant number of the proposed packet aggregation algorithms is that they tend to only optimize a single metric, i.e. either to maximize throughput or to minimize delay. They do not permit an optimal trade-off between maximizing throughput and minimizing delay. Therefore, these algorithms cannot achieve the optimal network performance for mixed traffic loads containing a number of different types of applications which may have very different network performance requirements. In this thesis an adaptive packet aggregation algorithm called the Adaptive Aggregation Mechanism (AAM) is proposed which achieves an aggregation trade-off in terms of realizing the largest average throughput with the smallest average delay compared to a number of other popular aggregation algorithms under saturation conditions in wireless networks. The AAM algorithm is the first packet aggregation algorithm that employs an adaptive selection window mechanism where the selection window size is adaptively adjusted in order to respond to the varying nature of both the packet size and packet rate. This algorithm is essentially a feedback control system incorporating a hybrid selection strategy for selecting the packets. Simulation results demonstrate that the proposed algorithm can (a) achieve a large number of sub-packets per aggregate packet for a given delay and (b) significantly improve the performance in terms of the aggregation trade-off for different traffic loads. Furthermore, the AAM algorithm is a robust algorithm as it can significantly improve the performance in terms of the average throughput in error-prone wireless networks

    Contributions to IEEE 802.11-based long range communications

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    The most essential part of the Internet of Things (IoT) infrastructure is the wireless communication system that acts as a bridge for the delivery of data and control messages between the connected things and the Internet. Since the conception of the IoT, a large number of promising applications and technologies have been developed, which will change different aspects in our daily life. However, the existing wireless technologies lack the ability to support a huge amount of data exchange from many battery-driven devices, spread over a wide area. In order to support the IoT paradigm, IEEE 802.11ah is an Internet of Things enabling technology, where the efficient management of thousands of devices is a key function. This is one of the most promising and appealing standards, which aims to bridge the gap between traditional mobile networks and the demands of the IoT. To this aim, IEEE 802.11ah provides the Restricted Access Window (RAW) mechanism, which reduces contention by enabling transmissions for small groups of stations. Optimal grouping of RAW stations requires an evaluation of many possible configurations. In this thesis, we first discuss the main PHY and MAC layer amendments proposed for IEEE 802.11ah. Furthermore, we investigate the operability of IEEE 802.11ah as a backhaul link to connect devices over possibly long distances. Additionally, we compare the aforementioned standard with previous notable IEEE 802.11 amendments (i.e. IEEE 802.11n and IEEE 802.11ac) in terms of throughput (with and without frame aggregation) by utilizing the most robust modulation schemes. The results show an improved performance of IEEE 802.11ah (in terms of power received at long range while experiencing different packet error rates) as compared to previous IEEE 802.11 standards. Additionally, we expose the capabilities of future IEEE 802.11ah in supporting different IoT applications. In addition, we provide a brief overview of the technology contenders that are competing to cover the IoT communications framework. Numerical results are presented showing how the future IEEE 802.11ah specification offers the features required by IoT communications, thus putting forward IEEE 802.11ah as a technology to cater the needs of the Internet of Things paradigm. Finally, we propose an analytical model (named e-model) that provides an evaluation of the RAW onfiguration performance, allowing a fast adaptation of RAW grouping policies, in accordance to varying channel conditions. We base the e-model in known saturation models, which we adapted to include the IEEE 802.11ah’s PHY and MAC layer modifications and to support different bit rate and packet sizes. As a proof of concept, we use the proposed model to compare the performance of different grouping strategies,showing that the e-model is a useful analysis tool in RAW-enabled scenarios. We validate the model with existing IEEE 802.11ah implementation for ns-3.La clave del concepto Internet de las cosas (IoT) es que utiliza un sistema de comunicación inalámbrica, el cual actúa como puente para la entrega de datos y mensajes de control entre las "cosas" conectadas y el Internet. Desde la concepción del IoT, se han desarrollado gran cantidad de aplicaciones y tecnologías prometedoras que cambiarán distintos aspectos de nuestra vida diaria.Sin embargo, las tecnologías de redes computacionales inalámbricas existentes carecen de la capacidad de soportar las características del IoT, como las grandes cantidades de envío y recepción de datos desde múltiples dispositivos distribuidos en un área amplia, donde los dispositivos IoT funcionan con baterías. Para respaldar el paradigma del IoT, IEEE 802.11ah, la cual es una tecnología habilitadora del Internet de las cosas, para el cual la gestión eficiente de miles de dispositivos es una función clave. IEEE 802.11ah es uno de los estándares más prometedores y atractivos, desde su concepción orientada para IoT, su objetivo principal es cerrar la brecha entre las redes móviles tradicionales y la demandada por el IoT. Con este objetivo en mente, IEEE 802.11ah incluye entre sus características especificas el mecanismo de ventana de acceso restringido (RAW, por sus siglas en ingles), el cual define un nuevo período de acceso al canal libre de contención, reduciendo la misma al permitir transmisiones para pequeños grupos de estaciones. Nótese que para obtener una agrupación óptima de estaciones RAW, se requiere una evaluación de las distintas configuraciones posibles. En esta tesis, primero discutimos las principales mejoras de las capas PHY y MAC propuestas para IEEE 802.11ah. Además, investigamos la operatividad de IEEE 802.11ah como enlace de backhaul para conectar dispositivos a distancias largas. También, comparamos el estándar antes mencionado con las notables especificaciones IEEE 802.11 anteriores (es decir, IEEE 802.11n y IEEE 802.11ac), en términos de rendimiento (incluyendo y excluyendo la agregación de tramas de datos) y utilizando los esquemas de modulación más robustos. Los resultados muestran mejores resultados en cuanto al rendimiento de IEEE 802.11ah (en términos de potencia recibida a largo alcance, mientras se experimentan diferentes tasas de error de paquetes de datos) en comparación con los estándares IEEE 802.11 anteriores.Además, exponemos las capacidades de IEEE 802.11ah para admitir diferentes aplicaciones de IoT. A su vez, proporcionamos una descripción general de los competidores tecnológicos, los cuales contienden para cubrir el marco de comunicaciones IoT. También se presentan resultados numéricos que muestran cómo la especificación IEEE 802.11ah ofrece las características requeridas por las comunicaciones IoT, presentando así a IEEE 802.11ah como una tecnología que puede satisfacer las necesidades del paradigma de Internet de las cosas.Finalmente, proponemos un modelo analítico (denominado e-model) que proporciona una evaluación del rendimiento utilizando la característica RAW con múltiples configuraciones, el cual permite una rápida adaptación de las políticas de agrupación RAW, de acuerdo con las diferentes condiciones del canal de comunicación. Basamos el e-model en modelos de saturación conocidos, que adaptamos para incluir las modificaciones de la capa MAC y PHY de IEEE 802.11ah y para poder admitir diferentes velocidades de transmisión de datos y tamaños de paquetes. Como prueba de concepto, utilizamos el modelo propuesto para comparar el desempeño de diferentes estrategias de agrupación, mostrando que el e-model es una herramienta de análisis útil en escenarios habilitados para RAW. Cabe mencionar que también validamos el modelo con la implementación IEEE 802.11ah existente para ns-3

    Video QoS/QoE over IEEE802.11n/ac: A Contemporary Survey

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    The demand for video applications over wireless networks has tremendously increased, and IEEE 802.11 standards have provided higher support for video transmission. However, providing Quality of Service (QoS) and Quality of Experience (QoE) for video over WLAN is still a challenge due to the error sensitivity of compressed video and dynamic channels. This thesis presents a contemporary survey study on video QoS/QoE over WLAN issues and solutions. The objective of the study is to provide an overview of the issues by conducting a background study on the video codecs and their features and characteristics, followed by studying QoS and QoE support in IEEE 802.11 standards. Since IEEE 802.11n is the current standard that is mostly deployed worldwide and IEEE 802.11ac is the upcoming standard, this survey study aims to investigate the most recent video QoS/QoE solutions based on these two standards. The solutions are divided into two broad categories, academic solutions, and vendor solutions. Academic solutions are mostly based on three main layers, namely Application, Media Access Control (MAC) and Physical (PHY) which are further divided into two major categories, single-layer solutions, and cross-layer solutions. Single-layer solutions are those which focus on a single layer to enhance the video transmission performance over WLAN. Cross-layer solutions involve two or more layers to provide a single QoS solution for video over WLAN. This thesis has also presented and technically analyzed QoS solutions by three popular vendors. This thesis concludes that single-layer solutions are not directly related to video QoS/QoE, and cross-layer solutions are performing better than single-layer solutions, but they are much more complicated and not easy to be implemented. Most vendors rely on their network infrastructure to provide QoS for multimedia applications. They have their techniques and mechanisms, but the concept of providing QoS/QoE for video is almost the same because they are using the same standards and rely on Wi-Fi Multimedia (WMM) to provide QoS
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