352 research outputs found

    Scheduling algorithms in broadband wireless networks

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    Scheduling algorithms that support quality of service (QoS) differentiation and guarantees for wireless data networks are crucial to the development of broadband wireless networks. Wireless communication poses special problems that do not exist in wireline networks, such as time-varying channel capacity and location-dependent errors. Although many mature scheduling algorithms are available for wireline networks, they are not directly applicable in wireless networks because of these special problems. This paper provides a comprehensive and in-depth survey on recent research in wireless scheduling. The problems and difficulties in wireless scheduling are discussed. Various representative algorithms are examined. Their themes of thoughts and pros and cons are compared and analyzed. At the end of the paper, some open questions and future research directions are addressed.published_or_final_versio

    Scheduling in CDMA-based wireless packet networks.

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    Thesis (M.Sc. Eng.)-University of Natal, Durban, 2003.Modern networks carry a wide range of different data types, each with its own individual requirements. The scheduler plays an important role in enabling a network to meet all these requirements. In wired networks a large amount of research has been performed on various schedulers, most of which belong to the family of General Processor Sharing (GPS) schedulers. In this dissertation we briefly discuss the work that has been done on a range of wired schedulers, which all attempt to differentiate between heterogeneous traffic. In the world of wireless communications the scheduler plays a very important role, since it can take channel conditions into account to further improve the performance of the network. The main focus of this dissertation is to introduce schedulers, which attempt to meet the Quality of Service requirements of various data types in a wireless environment. Examples of schedulers that take channel conditions into account are the Modified Largest Weighted Delay First (M-LWDF), as well as a new scheduler introduced in this dissertation, known as the Wireless Fair Largest Weighted Delay First (WF-LWDF) algorithm. The two schemes are studied in detail and a comparison of their throughput, delay, power, and packet dropping performance is made through a range of simulations. The results are compared to the performance offour other schedulers. The fairness ofM-LWDF and WFLWDF is determined through simulations. The throughput results are used to establish Chernoff bounds of the fairness of these two algorithms. Finally, a summary is given of the published delay bounds of various schedulers, and the tightness of the resultant bounds is discussed

    Radio resource management and metric estimation for multicarrier CDMA systems

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    Adaptive Capacity Management in Bluetooth Networks

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    Modelling and Analysis of Smart Grids for Critical Data Communication

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    Practical models for the subnetworks of smart grid are presented and analyzed. Critical packet-delay bounds for these subnetworks are determined, with the overall objective of identifying parameters that would help in the design of smart grid with least end-to-end delay. A single-server non-preemptive queueing model with prioritized critical packets is presented for Home Area Network (HAN). Closed-form expressions for critical packet delay are derived and illustrated as a function of: i) critical packet arrival rate, ii) service rate, iii) utilization factor, and iv) rate of arrival of non-critical packets. Next, wireless HANs using FDMA and TDMA are presented. Upper and lower bounds on critical packet delay are derived in closed-form as functions of: i) average of signal-to interference-plus-noise ratio, ii) random channel scale, iii) transmitted power strength, iv) received power strength, v) number of EDs, vi) critical packet size, vii) number of channels, viii) path loss component, ix) distances between electrical devices and mesh client, x) channel interference range, xi) channel capacity, xii) bandwidth of the channel, and xiii) number of time/frequency slots. Analytical and simulation results show that critical packet delay is smaller for TDMA compared to FDMA. Lastly, an Intelligent Distributed Channel-Aware Medium Access Control (IDCA-MAC) protocol for wireless HAN using Distributed Coordination Function (DCF) is presented. The protocol eliminates collision and employs Multiple Input Multiple Output (MIMO) system to enhance system performance. Simulation results show that critical packet delay can be reduced by nearly 20% using MA-Aware protocol compared to IDCA-MAC protocol. However, the latter is superior in terms throughput. A wireless mesh backbone network model for Neighbourhood Area Network (NAN) is presented for forwarding critical packets received from HAN to an identified gateway. The routing suggested is based on selected shortest path using Voronoi tessellation. CSMA/CA and CDMA protocols are considered and closed{form upper and lower bounds on critical packet delay are derived and examined as functions of i) signal-to-noise ratio, ii) signal interference, iii) critical packet size, iv) number of channels, v) channel interference range, vi) path loss components, vii) channel bandwidth, and viii) distance between MRs. The results show that critical packet delay to gateway using CDMA is lower compared to CSMA/CA protocol. A fiber optic Wide Area Network (WAN) is presented for transporting critical packets received from NAN to a control station. A Dynamic Fastest Routing Strategy (DFRS) algorithm is used for routing critical packets to control station. Closed-form expression for mean critical packet delay is derived and is examined as a function of: i) traffic intensity, ii) capacity of fiber links, iii) number of links, iv) variance of inter-arrival time, v) variance of service time, and vi) the latency of links. It is shown that delay of critical packets to control station meets acceptable standards set for smart grid

    Analytical modeling of HSUPA-enabled UMTS networks for capacity planning

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    In recent years, mobile communication networks have experienced significant evolution. The 3G mobile communication system, UMTS, employs WCDMA as the air interface standard, which leads to quite different mobile network planning and dimensioning processes compared with 2G systems. The UMTS system capacity is limited by the received interference at NodeBs due to the unique features of WCDMA, which is denoted as `soft capacity'. Consequently, the key challenge in UMTS radio network planning has been shifted from channel allocation in the channelized 2G systems to blocking and outage probabilities computation under the `cell breathing' effects which are due to the relationship between network coverage and capacity. The interference characterization, especially for the other-cell interference, is one of the most important components in 3G mobile networks planning. This monograph firstly investigates the system behavior in the operation of UMTS uplink, and develops the analytic techniques to model interference and system load as fully-characterized random variables, which can be directly applicable to the performance modeling of such networks. When the analysis progresses from single-cell scenario to multi-cell scenario, as the target SIR oriented power control mechanism is employed for maximum capacity, more sophisticated system operation, `feedback behavior', has emerged, as the interference levels at different cells depend on each other. Such behaviors are also captured into the constructed interference model by iterative and approximation approaches. The models are then extended to cater for the features of the newly introduced HSUPA, which provides enhanced dedicated channels for the packet switched data services such that much higher bandwidth can be achieved for best-effort elastic traffic, which allows network operators to cope with the coexistence of both circuit-switched and packet-switched traffic and guarantee the QoS requirements. During the derivation, we consider various propagation models, traffic models, resource allocation schemes for many possible scenarios, each of which may lead to different analytical models. All the suggested models are validated with either Monte-Carlo simulations or discrete event simulations, where excellent matches between results are always achieved. Furthermore, this monograph studies the optimization-based resource allocation strategies in the UMTS uplink with integrated QoS/best-effort traffic. Optimization techniques, both linear-programming based and non-linear-programming based, are used to determine how much resource should be assigned to each enhanced uplink user in the multi-cell environment where each NodeB possesses full knowledge of the whole network. The system performance under such resource allocation schemes are analyzed and compared via Monte-Carlo simulations, which verifies that the proposed framework may serve as a good estimation and optimal reference to study how systems perform for network operators

    Analytical modeling of HSUPA-enabled UMTS networks for capacity planning

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    In recent years, mobile communication networks have experienced significant evolution. The 3G mobile communication system, UMTS, employs WCDMA as the air interface standard, which leads to quite different mobile network planning and dimensioning processes compared with 2G systems. The UMTS system capacity is limited by the received interference at NodeBs due to the unique features of WCDMA, which is denoted as `soft capacity'. Consequently, the key challenge in UMTS radio network planning has been shifted from channel allocation in the channelized 2G systems to blocking and outage probabilities computation under the `cell breathing' effects which are due to the relationship between network coverage and capacity. The interference characterization, especially for the other-cell interference, is one of the most important components in 3G mobile networks planning. This monograph firstly investigates the system behavior in the operation of UMTS uplink, and develops the analytic techniques to model interference and system load as fully-characterized random variables, which can be directly applicable to the performance modeling of such networks. When the analysis progresses from single-cell scenario to multi-cell scenario, as the target SIR oriented power control mechanism is employed for maximum capacity, more sophisticated system operation, `feedback behavior', has emerged, as the interference levels at different cells depend on each other. Such behaviors are also captured into the constructed interference model by iterative and approximation approaches. The models are then extended to cater for the features of the newly introduced HSUPA, which provides enhanced dedicated channels for the packet switched data services such that much higher bandwidth can be achieved for best-effort elastic traffic, which allows network operators to cope with the coexistence of both circuit-switched and packet-switched traffic and guarantee the QoS requirements. During the derivation, we consider various propagation models, traffic models, resource allocation schemes for many possible scenarios, each of which may lead to different analytical models. All the suggested models are validated with either Monte-Carlo simulations or discrete event simulations, where excellent matches between results are always achieved. Furthermore, this monograph studies the optimization-based resource allocation strategies in the UMTS uplink with integrated QoS/best-effort traffic. Optimization techniques, both linear-programming based and non-linear-programming based, are used to determine how much resource should be assigned to each enhanced uplink user in the multi-cell environment where each NodeB possesses full knowledge of the whole network. The system performance under such resource allocation schemes are analyzed and compared via Monte-Carlo simulations, which verifies that the proposed framework may serve as a good estimation and optimal reference to study how systems perform for network operators

    Cross-layer QoS Analysis of Opportunistic OFDM-TDMA and OFDMA Networks

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