Generate and decode MAC frames of high efficiency single user (HE-SU), high efficiency extended range single user (HE-EXT-SU), very high throughput (VHT), high throughput mixed format (HT-MF) and Non-HT formats. This model is validated against the published calibration results from the TGax Task Group for Box 3 scenarios (Tests 1a, 1b, and 2a) specified in TGax evaluation methodology. Moreover, the runtime figures that help in analyzing/estimating the node-level and network-level performance are also displayed in this model. The model in the example displays various statistics such as the number of transmitted, received, and dropped packets at PHY and MAC layers. Whereas, the virtual carrier sensing uses the RTS/CTS handshake to prevent the hidden node problem. The physical carrier sensing uses the clear channel assessment (CCA) mechanism to determine whether the medium is busy before transmitting. These nodes implement carrier-sense multiple access with collision avoidance (CSMA/CA) with physical carrier sense and virtual carrier sense. This example models a WLAN network with five nodes as shown in this figure. In 802.11ac and 802.11ax, the maximum limits for an A-MPDU length were increased resulting in even better throughput in WLAN networks. This reduces the overhead of channel contention for transmitting multiple frames, resulting in enhanced throughput. When MPDU aggregation is supported, MAC layer aggregates multiple MPDUs into an aggregated MPDU (A-MPDU) for transmission. In 802.11n, MPDU aggregation was introduced to increase the throughput. MAC protocol data unit (MPDU) is the unit of transmission at MAC layer. Medium Access Control (MAC) layer throughput refers to the amount of data successfully transmitted by the MAC layer over a period of time. Throughput is the amount of data transmitted over a period of time. We have not yet found a good solution to speed up the code (the problem is not the implementation of the CRP Toolbox but in some Matlab internal functions related to the object handling).Īt the moment it is strongly recommend to use Matlab versions up to release R2014a and to avoid R2014b (and later).The IEEE® 802.11™ working group is continually adding features to 802.11 specification to improve the throughput and reliability in WLAN networks. However, due to a new but less efficient handling of objects within Matlab R2014b, the speed of some functions of the CRP Toolbox will be lowered by a factor up to 10(!). We have tried to fix several serious issues and provide an updated CRP Toolbox (R29.0) that might be mainly compatible to the Matlab releases starting with R2014b. Note developer: Starting with Release R2014b, Matlab contains significant changes that is causing some problems for running the CRP Toolbox in new Matlab versions. The toolbox can be used by a comfortable graphical user interface as well as on commandline (e.g. Windowed plot of statistical parameters Transformation of the data distribution to a desired distribution Phase space tools (parameters, size, visualisation Fast multi-dimensional histogram estimation AR parameter estimation via Yule-Walker method ACE - estimation of optimal transformations and maximal correlation Moreover, a time scale alignment tool based on CRPs is available.įurther useful tools and methods of nonlinear time series analysis and data preparation are provided: It provides the most up-to-date quantification analysis of RPs, CRPs and JRPs (RQA), which includes the new measures of complexity as LAM and TT. The CRP Toolbox for Matlab® allows for the creation of recurrence plots (RPs) as well as cross and joint recurrence plots (CRPs/ JRPs).
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |