3,605 research outputs found
Simulation Analysis of Medium Access Techniques
This paper presents comparison of Access Techniques used in Medium Access
Control (MAC) protocol for Wireless Body Area Networks (WBANs). Comparison is
performed between Time Division Multiple Access (TDMA), Frequency Division
Multiple Access (FDMA), Carrier Sense Multiple Access with Collision Avoidance
(CSMA/CA), Pure ALOHA and Slotted ALOHA (S-ALOHA). Performance metrics used for
comparison are throughput (T), delay (D) and offered load (G). The main goal
for comparison is to show which technique gives highest Throughput and lowest
Delay with increase in Load. Energy efficiency is major issue in WBAN that is
why there is need to know which technique performs best for energy conservation
and also gives minimum delay.Comment: NGWMN with 7th IEEE International Conference on Broadband and
Wireless Computing, Com- munication and Applications (BWCCA 2012), Victoria,
Canada, 201
Channel estimation and transmit power control in wireless body area networks
Wireless body area networks have recently received much attention because of their application to assisted living and remote patient monitoring. For these applications, energy minimisation is a critical issue since, in many cases, batteries cannot be easily replaced or recharged. Reducing energy expenditure by avoiding unnecessary high transmission power and minimising frame retransmissions is therefore crucial. In this study, a transmit power control scheme suitable for IEEE 802.15.6 networks operating in beacon mode with superframe boundaries is proposed. The transmission power is modulated, frame-by-frame, according to a run-time estimation of the channel conditions. Power measurements using the beacon frames are made periodically, providing reverse channel gain and an opportunistic fade margin, set on the basis of prior power fluctuations, is added. This approach allows tracking of the highly variable on-body to on-body propagation channel without the need to transmit additional probe frames. An experimental study based on test cases demonstrates the effectiveness of the scheme and compares its performance with alternative solutions presented in the literature
Spectrum Utilization and Congestion of IEEE 802.11 Networks in the 2.4 GHz ISM Band
Wi-Fi technology, plays a major role in society thanks to its widespread availability, ease of use and low cost. To assure its long term viability in terms of capacity and ability to share the spectrum efïŹciently, it is of paramount to study the spectrum utilization and congestion mechanisms in live environments. In this paper the service level in the 2.4 GHz ISM band is investigated with focus on todays IEEE 802.11 WLAN systems with support for the 802.11e extension. Here service level means the overall Quality of Service (QoS), i.e. can all devices fulïŹll their communication needs? A crosslayer approach is used, since the service level can be measured at several levels of the protocol stack. The focus is on monitoring at both the Physical (PHY) and the Medium Access Control (MAC) link layer simultaneously by performing respectively power measurements with a spectrum analyzer to assess spectrum utilization and packet snifïŹng to measure the congestion. Compared to traditional QoS analysis in 802.11 networks, packet snifïŹng allows to study the occurring congestion mechanisms more thoroughly. The monitoring is applied for the following two cases. First the inïŹuence of interference between WLAN networks sharing the same radio channel is investigated in a controlled environment. It turns out that retry rate, Clear-ToSend (CTS), Request-To-Send (RTS) and (Block) Acknowledgment (ACK) frames can be used to identify congestion, whereas the spectrum analyzer is employed to identify the source of interference. Secondly, live measurements are performed at three locations to identify this type of interference in real-live situations. Results show inefïŹcient use of the wireless medium in certain scenarios, due to a large portion of management and control frames compared to data content frames (i.e. only 21% of the frames is identiïŹed as data frames)
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