Recently, a promising technology called WiMAX is providing wireless last-mile connectivity due to its high speed data rates, low cost of deployment, and large coverage area. Both MAC and Physical layer of this technology refer to the IEEE 802.16e standard, which defines five different data delivery service classes that can be used in order to satisfy Quality of Service (QoS) requirements of different applications, such as VoIP, FTP, videoconference, Web, etc. The main aim of this paper is to examine a case of QoS large cell deployment over a cellular WiMAX network. In particular, the paper compares the performance obtained using ertPS service class for voice application in static and mobile conditions. Results indicate that on WiMAX connection statistics, traffic contract was made correctly by considering the overheads, and the performance of voice in mobile environment showed an acceptable level for Mean Opinion Score at around 3.55 until 100 seconds.
The IEEE 802.16 technology (WiMAX) is a promising technology for providing last-mile connectivity by radio link due to its large coverage area, low cost of deployment and high speed data rates. However, the maximum number of channels defined in the current system may cause a potential bottleneck and limit the overall system capacity. The aim of this paper is to compare the impact on system performance of different solutions used to mitigate the impairments due to the radio channel. In particular, taking into account the WiMAX system capacity as well as application delays, the paper presents the simulation results obtained when a static QPSK 1/2 Modulation and Coding Scheme (MCS) is adopted. Then, the study is aimed at evaluating the improvements introduced by the adoption of an adaptive modulation and coding (AMC) and an AMC jointly with Hybrid Automatic Repeat reQuest (HARQ). Results indicate that the best strategy is to use an aggressive AMC table with HARQ
One of the reasons why it is vital to forecast fisher production data in coastal regions is to increase fish resource management efficiency. By calculating the number of fishing boats, the amount of fish that must be caught, and the amount of raw materials required for fish processing based on the anticipated amount of fishermen's production in the following period, decision-makers can determine the amount of fish that must be caught and the amount of raw materials required for fish processing. So that the objective of the research is to forecast fishermen's production data using the Single Exponential Smoothing method, this method is effectively used to perform forecasting of time series data with short period data intervals to produce forecasts for the next period, and it can measure the rate of change of fishermen's production data each period. The results of forecasting data on fishermen's production utilizing time series data intervals from October 2022 to January 2023 to make forecasts for February 2023, namely a MAPE error rate of 2.85%, indicate that the forecasting results are within the "good" category.
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