Investigation of the Characteristics of Radio Signal Propagation in Indoor Environment

The success of wireless local area networks (WLANs) has led to an intense interest among wireless engineers in understanding and predicting radio propagation characteristics within buildings. This paper present radio signal propagation measurement and modeling at 2.4GHz, within a building in the Faculty of Engineering, University of Benin. A base station built around SENAO access point, and a PA24 flat panel directional antenna of 19dBi gain and 17.50 beam-widths was setup for the experimentation. Signals were monitored from the fixed BS using LINKSYS, and NET STUMBLER version 4.0 software run on a Laptop. In this report, the effect of multi-path and delay spread was not considered. The result of the investigation revealed a significant attenuation of the radio signal within the small distance. A path loss exponent of 7.8 to 8.9 on the ground floor, and 2.9 to 5.2 for the 2nd floor were obtained for the period of investigation.

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Improved Association and Disassociation Scheme for Enhanced WLAN Handover and VHO

Mobile Information Systems ◽

10.1155/2016/4868479 ◽

2016 ◽

Vol 2016 ◽

pp. 1-6 ◽

Cited By ~ 1

Author(s):

Sungjin Shin ◽

Donghyuk Han ◽

Hyoungjun Cho ◽

Jong-Moon Chung

Keyword(s):

Mobile Devices ◽

Local Area Networks ◽

Access Point ◽

Local Area ◽

Vertical Handover ◽

Base Station ◽

Wireless Local Area Networks ◽

Received Signal Strength Indicator ◽

Wireless Protocol

The number of mobile devices and wireless connections is significantly increasing. Among many wireless protocol types, wireless local area networks (WLANs) are expected to support a significant number of devices. Due to this reason, effective and efficient handover (HO) and vertical handover (VHO) support for WLAN mobile devices is important. A significant improvement in quality of service (QoS) can be obtained by reducing the association and disassociation interruption time for user equipment (UE) servicing real-time applications during WLAN HO and VHO operations. Based on this focus, this paper investigates the problem of using only the received signal strength indicator (RSSI) in HO and VHO decisions, which is what the current IEEE 802.11 based WLAN systems use. Experimental results presented in this paper demonstrate that only using the RSSI results in significant interruption time during HO to another WLAN access point (AP) or to a cellular base station during VHO. Therefore, in this paper, an improved association and disassociation scheme that can reduce the data interruption time (DIT) and improve the throughput performance is proposed.

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Extensions of Access-Point Aggregation Algorithm for Large-scale Wireless Local Area Networks

International Journal of Networking and Computing ◽

10.15803/ijnc.5.1_200 ◽

2015 ◽

Vol 5 (1) ◽

pp. 200-222 ◽

Cited By ~ 7

Author(s):

Md. Ezharul Islam ◽

Nobuo Funabiki ◽

Toru Nakanishi

Keyword(s):

Large Scale ◽

Local Area Networks ◽

Access Point ◽

Local Area ◽

Wireless Local Area Networks ◽

Point Aggregation

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802.11 wireless simulation and anomaly detection using HMM and UBM

SIMULATION ◽

10.1177/0037549720958480 ◽

2020 ◽

Vol 96 (12) ◽

pp. 939-956 ◽

Cited By ~ 1

Author(s):

Anisa Allahdadi ◽

Ricardo Morla ◽

Jaime S Cardoso

Keyword(s):

Anomaly Detection ◽

User Behavior ◽

Local Area Networks ◽

Principal Component ◽

Access Point ◽

Local Area ◽

Wireless Local Area Networks ◽

Network Simulator ◽

Detection Analysis ◽

And Performance

Despite the growing popularity of 802.11 wireless networks, users often suffer from connectivity problems and performance issues due to unstable radio conditions and dynamic user behavior, among other reasons. Anomaly detection and distinction are in the thick of major challenges that network managers encounter. The difficulty of monitoring broad and complex Wireless Local Area Networks, that often requires heavy instrumentation of the user devices, makes anomaly detection analysis even harder. In this paper we exploit 802.11 access point usage data and propose an anomaly detection technique based on Hidden Markov Model (HMM) and Universal Background Model (UBM) on data that is inexpensive to obtain. We then generate a number of network anomalous scenarios in OMNeT++/INET network simulator and compare the detection outcomes with those in baseline approaches—RawData and Principal Component Analysis. The experimental results show the superiority of HMM and HMM-UBM models in detection precision and sensitivity.

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