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Golmie, Nada; Dyck, R.E. Van; Soltanian, A.; Tonnerre, A.; Rébala, O.

doi:10.1023/a:1022821110023

Cited by 88 publications

(8 citation statements)

References 11 publications

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“…Header Payload Table III describes action taken when errors occur in the access code, the header and the payload for the different voice packets [24]. For all simulations, we use two types of Bluetooth voice packets (i.e.…”

Section: Bits 54 Bits 240 Bits Access Codementioning

confidence: 99%

Non-coherent detection of GFSK using Extended Kalman Filtering for Non-Gaussian noise

Nsour

Abdallah

Zohdy

2014

2014 Wireless Telecommunications Symposium

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Gaussian Frequency Shift Keying (GFSK), a special case of Continuous Phase Modulation (CPM) schemes, is the modulation scheme chosen for achieving basic data rate of 1 Mbps with Bluetooth receivers. In this article, we present a new non-coherent demodulation technique based on the Extended Kalman Filter (EKF) that does not require the knowledge of the modulation index to detect the GFSK modulated signal in Bluetooth receivers. The paper examines the performance of our proposed receiver in the presence of Non-Gaussian impulsive noise since this type of noise is considered to be a severe noise for wireless technologies including Bluetooth. Bit Error Rate (BER) was used as the measurement metric for the performance for our proposed receiver at the physical level while Packet Error Rate (PER) and Residual Bit Error Rate (RBER) were used as the measurement metrics at the system level. Experimental results obtained for the Extended Kalman Filter detector for Non-Gaussian noise are provided.

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Section: Bits 54 Bits 240 Bits Access Codementioning

confidence: 99%

Non-coherent detection of GFSK using Extended Kalman Filtering for Non-Gaussian noise

Nsour

Abdallah

Zohdy

2014

2014 Wireless Telecommunications Symposium

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“…For WBAN, we choose a 0 = 35.6901 and n = 1.81199 , which are derived from realworld measurements (Miniutti, 2008). For WiFi, we choose a 0 = 20.0542 and n = 2 when d 1 < 8 m; and a 0 = 4.5020 and n = 3.3 when d 1 8 ³ m. This is a common model for WiFi evaluation (Golmie, 2001).…”

Section: Simulation Scenariomentioning

confidence: 99%

“…For example, if WiFi uses carrier sense CCA, it will only back off to IEEE 802.11 compatible signals. Under such assumptions, Golmie et al (2001) model WiFi interference d 1 is the distance between WiFi jamming source and WBAN receiver; d 2 is the distance between WBAN transmitter and WBAN receiver ( Figure 5).…”

Section: Related Workmentioning

confidence: 99%

Evaluating the IEEE 802.15.6 2.4GHz WBAN Proposal on Medical Multi-Parameter Monitoring under WiFi/Bluetooth Interference

Wang

2011

International Journal of E-Health and Medical Communications

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Wireless body area networks (WBAN) play a key role in the future of e-Health. In response, IEEE sets up working group 802.15.6 to standardize WBAN schemes. Of all existing standard proposals, the 2.4GHz proposal is the most mature and ready for mass production. However, as e-Health WBAN applications are often mission/life critical, people are concerned with the reliability (particularly, coexistence reliability) of this proposal. This study evaluates the 2.4GHz proposal under WiFi/Bluetooth interference in the context of medical multi-parameter monitoring. The authors conclude that WiFi poses a major threat to such application scenario, while Bluetooth does not.severe challenge of aging, as a consequence of long-lasting one-child policy (Kaneda, 2006).To curb the healthcare crisis, medical devices and systems must be upgraded to expand capabilities, increase efficiency, improve safety, and enhance convenience. One enabling technology to these goals is wireless body area networks (WBAN).A key application of WBAN is multi-parameter monitoring (i.e., monitoring multiple vital signs). For instance, during operation or

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“…For instance, the IEEE 802.11b and g standards are allowed to operate in the unlicensed and crowded 2.4 GHz industrial scientific medical (ISM) band, in which several different devices may operate simultaneously, like, for instance, IEEE 802. 15.4 (Zig-Bee) [7] and IEEE 802. 15.1 (Bluetooth) [8] apparatuses, microwave ovens, cordless phones, baby monitors, security cameras, and so forth, [9].…”

Section: Introductionmentioning

confidence: 99%

“…15.4 (Zig-Bee) [7] and IEEE 802. 15.1 (Bluetooth) [8] apparatuses, microwave ovens, cordless phones, baby monitors, security cameras, and so forth, [9]. All these sources may add significant interference 2 EURASIP Journal on Wireless Communications and Networking to a Wi-Fi network supporting video streaming, provoking various classes of effects such as: collisions, delays, jitter and loss of data packets, reduced signal-to-interference ratio, final video quality degradation, and so forth.…”

Section: Introductionmentioning

confidence: 99%

Cross-Layer Measurement on an IEEE 802.11g Wireless Network Supporting MPEG-2 Video Streaming Applications in the Presence of Interference

Angrisani

Napolitano

Sona

2010

J Wireless Com Network

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The performance of wireless local area networks supporting video streaming applications, based on MPEG-2 video codec, in the presence of interference is here dealt with. IEEE 802.11g standard wireless networks, that do not support QoS in according with IEEE 802.11e standard, are, in particular, accounted for and Bluetooth signals, additive white Gaussian noise, and competitive data traffic are considered as sources of interference. The goal is twofold: from one side, experimentally assessing and correlating the values that some performance metrics assume at the same time at different layers of an IEEE 802.11g WLAN delivering video streaming in the presence of in-channel interference; from the other side, deducing helpful and practical hints for designers and technicians, in order to efficiently assess and enhance the performance of an IEEE 802.11g WLAN supporting video streaming in some suitable setup conditions and in the presence of interference. To this purpose, an experimental analysis is planned following a cross-layer measurement approach, and a proper testbed within a semianechoic chamber is used. Valuable results are obtained in terms of signal-to-interference ratio, packet loss ratio, jitter, video quality, and interference data rate; helpful hints for designers and technicians are finally gained.

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Untitled

Cited by 88 publications

References 11 publications

Non-coherent detection of GFSK using Extended Kalman Filtering for Non-Gaussian noise

Non-coherent detection of GFSK using Extended Kalman Filtering for Non-Gaussian noise

Evaluating the IEEE 802.15.6 2.4GHz WBAN Proposal on Medical Multi-Parameter Monitoring under WiFi/Bluetooth Interference

Cross-Layer Measurement on an IEEE 802.11g Wireless Network Supporting MPEG-2 Video Streaming Applications in the Presence of Interference

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