219 research outputs found

    A Comprehensive Study of the Enhanced Distributed Control Access (EDCA) Function

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    This technical report presents a comprehensive study of the Enhanced Distributed Control Access (EDCA) function defined in IEEE 802.11e. All the three factors are considered. They are: contention window size (CW), arbitration inter-frame space (AIFS), and transmission opportunity limit (TXOP). We first propose a discrete Markov chain model to describe the channel activities governed by EDCA. Then we evaluate the individual as well as joint effects of each factor on the throughput and QoS performance. We obtain several insightful observations showing that judiciously using the EDCA service differentiation mechanism is important to achieve maximum bandwidth utilization and user-specified QoS performance. Guided by our theoretical study, we devise a general QoS framework that provides QoS in an optimal way. The means of realizing the framework in a specific network is yet to be studied

    Mac-Phy Cross-Layer analysis and design of Mimo-Ofdm Wlans based on fast link adaptation

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    The latestWLAN standard, known as IEEE 802.11n, has notably increased the network capacity with respect to its predecessors thanks to the incorporation of the multipleinput multiple-output (MIMO) technology. Nonetheless, the new amendment, as its previous ones, does not specify how crucial configuration mechanisms, most notably the adaptive modulation and coding (AMC) algorithm should be implemented. The AMC process has proved essential to fully exploit the system resources in light of varying channel conditions. In this dissertation, a closed-loop AMC technique, referred to as fast link adaption (FLA) algorithm, that effectively selects themodulation and coding scheme (MCS) for multicarriermultiantennaWLAN networks is proposed. The FLA algorithm determines the MCS that maximizes the throughput while satisfying a quality of service (QoS) constraint, usually defined in the form of an objective packet error rate (PER). To this end, FLA uses a packet/bit error rate prediction methodology based on the exponential effective SNRmetric (EESM). The FLA algorithm performance has been evaluated under IEEE 802.11n systems that thanks to the incorporation of a feedbackmechanismare able to implement closed- loop AMC mechanisms. Initially, this AMC technique relies only on physical layer information but it is subsequently extended to also take into account themediumaccess control (MAC) sublayer performance. At the physical layer, the FLA algorithm has demonstrated its effectivity by performing very close to optimality in terms of throughput, while satisfying a prescribed PER constraint. The FLA algorithm has also been evaluated using imperfect channel information. It has been observed that the proposed FLA technique is rather robust against imperfect channel information, and only in highly-frequency selective channels, imperfect channel knowledge causes a noticeable degradation in throughput. At the MAC sublayer, the FLA algorithm has been complemented with a timeout strategy that weighs down the influence of the available channel information as this becomes outdated. This channel information outdate is caused by the MAC sublayer whose user multiplexing policy potentially results in large delays between acquiring the instant in which the channel state information is acquired and that in which the channel is accessed. Results demonstrate the superiority of FLA when compared to open-loop algorithms under saturated and non-saturated conditions and irrespective of the packet length, number of users, protocol (CSMA/CA or CDMA/E2CA) and access scheme (Basic Access or RTS/CTS). Additionally, several analytical models have been developed to estimate the system performance at the MAC sublayer. These models account for all operational details of the IEEE 802.11n MAC sublayer, such as finite number of retries, anomalous slot or channel errors. In particular, a semi-analytical model that assesses the MAC layer throughput under saturated conditions, considering the AMC performance is first introduced. Then, an analytical model that allows the evaluation of the QoS performance under non-saturated conditions is presented. This model focuses on single MCS and it is able to accurately predict very important system performance metrics such as blocking probability, delay, probability of discard or goodput thanks to the consideration of the finite queues on each station. Finally, the previous non-saturated analytical approach is used to define a semi-analytical model in order to estimate the system performance when considering AMC algorithms (i.e. whenmultiple MCSs are available)La darrera versió de l’estàndard deWLAN, anomenada IEEE 802.11n, ha augmentat la seva capacitat notablement en relació als sistemes anteriors gràcies a la incorporació de la tecnologia de múltiples antenes en transmissió i recepció (MIMO). No obstant això, la nova proposta, al igual que les anteriors, segueix sense especificar com s’han d’implementar elsmecanismes de configuraciómés crucials, un dels quals és l’algoritme de codificació imodulació adaptativa (AMC). Aquests algoritmes ja han demostrat la seva importància a l’hora demaximitzar el rendiment del sistema tenint en compte les condicions canviants del canal. En aquesta tesis s’ha proposat un algoritme AMC de llaç tancat, anomenat adaptació ràpida de l’enllaç (FLA), que selecciona eficientment l’esquema demodulació i codificació adaptativa per xarxes WLAN basades en arquitectures multiportadora multiantena. L’algoritme FLA determina el mode de transmissió capaç de maximitzar el throughput per les condicions de canal actuals, mentre satisfà un requisit de qualitat de servei en forma de taxa d’error per paquet (PER). FLA utilitza una metodologia de predicció de PER basada en l’estimació de la relació senyal renou (SNR) efectiva exponencial (EESM). El rendiment de l’algoritme FLA ha estat avaluat en sistemes IEEE 802.11n, ja que aquests, gràcies a la incorporació d’unmecanisme de realimentació demodes de transmissió, poden adoptar solucions AMC de llaç tancat. En una primera part, l’estudi s’ha centrat a la capa física i després s’ha estès a la subcapa MAC. A la capa física s’ha demostrat l’efectivitat de l’algoritme FLA aconseguint un rendiment molt proper al que ens proporcionaria un esquema AMC òptim en termes de throughput, alhora que es satisfan els requisits de PER objectiu. L’algoritme FLA també ha estat avaluat utilitzant informació imperfecte del canal. S’ha vist que l’algoritme FLA proposat és robust en front dels efectes d’estimació imperfecte del canal, i només en canals altament selectius en freqüència, la informació imperfecte del canal provoca una davallada en el rendiment en termes de throughput. A la subcapa MAC, l’algoritme FLA ha estat complementat amb una estratègia de temps d’espera que disminueix la dependència amb la informació de canal disponible a mesura que aquesta va quedant desfassada respecte de l’estat actual. Aquesta informació de canal desfassada és conseqüència de la subcapa MAC que degut a la multiplexació d’usuaris introdueix grans retards entre que es determina el mode de transmissió més adequat i la seva utilització per a l’accés al canal. Els resultats obtinguts han demostrat la superioritat de FLA respecte d’altres algoritmes de llaç obert en condicions de saturació i de no saturació, i independentment de la longitud de paquet, nombre d’usuaris, protocol (CSMA/CA i CSMA/E2CA) i esquema d’accés (Basic Access i RTS/CTS). Amés, s’han desenvolupat diversosmodels analítics per tal d’estimar el rendiment del sistema a la subcapa MAC. Aquests models consideren tots els detalls de funcionament de la subcapaMAC del 802.11n, comper exemple un nombre finit de retransmissions de cada paquet, l’slot anòmal o els errors introduïts pel canal. Inicialment s’ha proposat unmodel semi-analític que determina el throughtput en condicions de saturació, considerant el rendiment dels algoritmes AMC. Després s’ha presentat un model analític que estima el rendiment del sistema per condicions de no saturació, mitjançat elmodelat de cues finites a cada estació. Aquestmodel consideramodes de transmissió fixes i és capaç de determinar de manera molt precisa mètriques de rendimentmolt importants comsón la probabilitat de bloqueig de cada estació, el retard mitjà del paquets, la probabilitat de descart o la mesura del goodput. Finalment, el model analític de no saturació s’ha utilitzat per definir un model semi-analític per tal d’estimar el rendiment del sistema quan es considera l’ús d’algoritmes AMC

    Improved multi-point communication for data and voice over IEEE 802.11b

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    There is a growing demand for faster, improved data and voice services in rural areas without modern telecom infrastructure. A wireless network is often the only feasible solution for providing network access in this environment, due to the sparse populations and difficult natural conditions. A system solution that incorporates the Multipoint Communication System (MCS) algorithm created by TRLabs into the available IEEE 802.11b Wireless Local Area Network (WLAN) devices was proposed and studied in this thesis. It combines the advantages of both systems, that is, the MCS’ capability of integrating Voice over Internet Protocol (VoIP) and data services and the IEEE 802.11b standard, currently the most widely used in WLAN products. A system test bed was set up inside Network Simulator-2 (NS-2). The data and VoIP performance was tested. Modifications to the original MCS algorithm to improve system performance were made throughout this thesis. In a constant rate radio channel, data performance (throughput and transmission efficiency) was measured using the original MCS algorithm, which was comparable to the standard Distribution Coordination Function (DCF) operation of IEEE 802.11b when both were simulated at similar conditions. On an 802.11b platform, the Automatic Rate Fallback (ARF) feature was incorporated into the original MCS algorithm. However, when clients with different data rates were present in the same channel, all the clients involved received unacceptably low and equal data throughput, dragged down by the low rate clients. A modified MCS data polling algorithm was proposed with the capability of repeated polling, which eliminated the negative effect of low rate clients in a multi-rate channel. In addition, the original MCS algorithm was modified to be more efficient in the voice polling process. The voice performance and data throughput were tested at various conditions. However, the one-by-one polling still resulted in very low voice transmission efficiency. The time wasted became more severe with increasing relay distance and channel rate (only 8.5% in an 11 Mbps channel at 30 km). A new voice handling process similar to Time Division Multiple Access (TDMA) mode was implemented and simulated. Its voice efficiency can be kept at 25% at any setting of relay distance and channel rate. Data transmission in the same channel can also benefit from using the new voice scheme. The normalized saturation throughput could be improved by 13.5% if there were 40 voice clients involved in an 11 Mbps channel at the relay distance of 15 km, compared to the original MCS algorithm. More improvement in voice efficiency, voice capacity, and data throughput can be achieved at longer relay distance, or with more voice calls set up

    Quality of service differentiation for multimedia delivery in wireless LANs

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    Delivering multimedia content to heterogeneous devices over a variable networking environment while maintaining high quality levels involves many technical challenges. The research reported in this thesis presents a solution for Quality of Service (QoS)-based service differentiation when delivering multimedia content over the wireless LANs. This thesis has three major contributions outlined below: 1. A Model-based Bandwidth Estimation algorithm (MBE), which estimates the available bandwidth based on novel TCP and UDP throughput models over IEEE 802.11 WLANs. MBE has been modelled, implemented, and tested through simulations and real life testing. In comparison with other bandwidth estimation techniques, MBE shows better performance in terms of error rate, overhead, and loss. 2. An intelligent Prioritized Adaptive Scheme (iPAS), which provides QoS service differentiation for multimedia delivery in wireless networks. iPAS assigns dynamic priorities to various streams and determines their bandwidth share by employing a probabilistic approach-which makes use of stereotypes. The total bandwidth to be allocated is estimated using MBE. The priority level of individual stream is variable and dependent on stream-related characteristics and delivery QoS parameters. iPAS can be deployed seamlessly over the original IEEE 802.11 protocols and can be included in the IEEE 802.21 framework in order to optimize the control signal communication. iPAS has been modelled, implemented, and evaluated via simulations. The results demonstrate that iPAS achieves better performance than the equal channel access mechanism over IEEE 802.11 DCF and a service differentiation scheme on top of IEEE 802.11e EDCA, in terms of fairness, throughput, delay, loss, and estimated PSNR. Additionally, both objective and subjective video quality assessment have been performed using a prototype system. 3. A QoS-based Downlink/Uplink Fairness Scheme, which uses the stereotypes-based structure to balance the QoS parameters (i.e. throughput, delay, and loss) between downlink and uplink VoIP traffic. The proposed scheme has been modelled and tested through simulations. The results show that, in comparison with other downlink/uplink fairness-oriented solutions, the proposed scheme performs better in terms of VoIP capacity and fairness level between downlink and uplink traffic

    Cross-Layer Optimal Rate Allocation for Heterogeneous Wireless Multicast

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    Heterogeneous multicast is an efficient communication scheme especially for multimedia applications running over multihop networks. The term heterogeneous refers to the phenomenon when multicast receivers in the same session require service at different rates commensurate with their capabilities. In this paper, we address the problem of resource allocation for a set of heterogeneous multicast sessions over multihop wireless networks. We propose an iterative algorithm that achieves the optimal rates for a set of heterogeneous multicast sessions such that the aggregate utility for all sessions is maximized. We present the formulation of the multicast resource allocation problem as a nonlinear optimization model and highlight the cross-layer framework that can solve this problem in a distributed ad hoc network environment with asynchronous computations. Our simulations show that the algorithm achieves optimal resource utilization, guarantees fairness among multicast sessions, provides flexibility in allocating rates over different parts of the multicast sessions, and adapts to changing conditions such as dynamic channel capacity and node mobility. Our results show that the proposed algorithm not only provides flexibility in allocating resources across multicast sessions, but also increases the aggregate system utility and improves the overall system throughput by almost 30% compared to homogeneous multicast

    A Framework for Service Differentiation and Optimization in Multi-hop Wireless Networks

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    In resource-constrained networks such as multi-hop wireless networks (MHWNs), service differentiation algorithms designed to address end users' interests (e.g. user satisfaction, QoS, etc.) should also consider efficient utilization of the scarce network resources in order to maximize the network's interests (e.g. revenue). For this very reason, service differentiation in MHWNs is quite different from the wired network scenario. We propose a service differentiation tool called the ``Investment Function'', which essentially captures the network's cumulative resource investment in a given packet at a given time. This investment value can be used by the network algorithm to implement specific service differentiation principles. As proof-of-concept, we use the investment function to improve fairness among simultaneous flows that traverse varying number of hops in a MHWN (multihop flow fairness). However, to attain the optimal value of a specific service differentiation objective, optimal service differentiation and investment function parameters may need to be computed. The optimal parameters can be computed by casting the service differentiation problem as a network flow problem in MHWNs, with the goal of optimizing the service differentiation objective. The capacity constraints for these problems require knowledge of the adjacent-node interference values, and constructing these constraints could be very expensive based on the transmission scheduling scheme used. As a result, even formulating the optimization problem may take unacceptable computational effort or memory or both. Under optimal scheduling, the adjacent node interference values (and thus the capacity constraints) are not only very expensive to compute, but also cannot be expressed in polynomial form. Therefore, existing optimization techniques cannot be directly applied to solve optimization problems in MHWNs. To develop an efficient optimization framework, we first model the MHWN as a Unit Disk Graph (UDG). The optimal transmission schedule in the MHWN is related to the chromatic number of the UDG, which is very expensive to compute. However, the clique number, which is a lower bound on the chromatic number, can be computed in polynomial time in UDGs. Through an empirical study, we obtain tighter bounds on the ratio of the chromatic number to clique number in UDGs, which enables us to leverage existing polynomial time clique-discovery algorithms to compute very close approximations to the chromatic number value. This approximation not only allows us to quickly formulate the capacity constraints in polynomial form, but also allows us to significantly deviate from the traditional approach of discovering all or most of the constraints \textit{a priori}; instead, we can discover the constraints as needed. We have integrated this approach of constraint-discovery into an active-set optimization algorithm (Gradient Projection method) to solve network flow problems in multi-hop wireless networks. Our results show significant memory and computational savings when compared to existing methods
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