Time Synchronization for the IEEE 802.11a/g WLAN Standard

Canet, M. J.; Almenar, Vicenç; Marín-Roig, José; Valls, Javier

doi:10.1109/pimrc.2007.4394066

Cited by 9 publications

(26 citation statements)

References 14 publications

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“…Synchronization algorithms can be classified in two categories. One is related to redundant information (NDA) (see, e.g., [4,6]) and the other to training sequences (DA) (see, e.g., [16,18,19]). In [6], the OFDM CP symbol is exploited.…”

Section: State Of the Art On Time And Frequency Synchronizationmentioning

confidence: 99%

“…In [18,19], the proposed DA algorithms have been adapted to the IEEE 802.11a standard. To estimate the symbol timing, these algorithms proceed in two main stages: (i) CTS, then (ii) FTS.…”

Section: State Of the Art On Time And Frequency Synchronizationmentioning

confidence: 99%

“…Since the RtS/CtS control frames are sent with higher power levels than the nominal transmission power level of the DATA frames to guarantee that all stations in the same network should hear these control sequences (see [25]), we use the synchronization algorithm developed in [19] to estimate the symbol timing and CFO parameters based on the specified training sequences of the frames. Indeed, this algorithm provides reasonable performance for relatively higher signal to noise ratio compared to DATA frames.…”

Section: Initialization Stage: Extraction Of New Information Source Tmentioning

confidence: 99%

“…These parameters are estimated according to [19]. If the stations have been synchronized, then the exchange control information can continue.…”

Section: Initialization Stage: Extraction Of New Information Source Tmentioning

confidence: 99%

“…Fine frequency synchronization (FFS) and fine time synchronization (FTS) employ the ACF of the LTF. However, in [19], the FTS is performed with the CCF between the received signal and a part of the LTF. In [20], the FTS is performed jointly with channel estimation.…”

Section: Introductionmentioning

confidence: 99%

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Improved time and frequency synchronization in presence of imperfect channel state information

Nguyen

Mokraoui

Duhamel

et al. 2015

J Wireless Com Network

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This paper addresses altogether time and frequency synchronization in IEEE 802.11a orthogonal frequency division multiplexing (OFDM) wireless communication systems. The proposed algorithms have two main features: (i) they make use of an additional source of information available at IEEE 802.11a physical layer, on top of the usual ones typically adopted for synchronization such as training sequences. This additional source of information is provided by the higher layers of the communication protocol. In fact, when the carrier sense multiple access with collision avoidance (CSMA/CA) protocol is activated, the receiver is able to predict some parts of the SIGNAL field that are classically assumed unknown. Moreover, during the negotiation of the transmission medium reservation, the exchanged frames not only help the receiver to predict the SIGNAL field but also to obtain information about the channel state. (ii) Based on this property, we propose a joint MAP time and frequency synchronization algorithm using all available information. Finally, the time synchronization is fine tuned by means of a specific metric in the frequency domain that allows us to minimize the expectation of the transmission error function over all channel estimate errors. Simulation results compliant with the IEEE 802.11a standard in both indoor and outdoor environments show that the proposed algorithm drastically improves the performance in terms of synchronization failure probability and bit error ratio, compared to state-of-the-art algorithms.

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Section: State Of the Art On Time And Frequency Synchronizationmentioning

confidence: 99%

“…In [18,19], the proposed DA algorithms have been adapted to the IEEE 802.11a standard. To estimate the symbol timing, these algorithms proceed in two main stages: (i) CTS, then (ii) FTS.…”

Section: State Of the Art On Time And Frequency Synchronizationmentioning

confidence: 99%

Section: Initialization Stage: Extraction Of New Information Source Tmentioning

confidence: 99%

“…These parameters are estimated according to [19]. If the stations have been synchronized, then the exchange control information can continue.…”

Section: Initialization Stage: Extraction Of New Information Source Tmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Improved time and frequency synchronization in presence of imperfect channel state information

Nguyen

Mokraoui

Duhamel

et al. 2015

J Wireless Com Network

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Improving fog computing performance via Fog-2-Fog collaboration

Al-Khafajiy

Baker

Al-Libawy

et al. 2019

Future Generation Computer Systems

115

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In the Internet of Things (IoT) era, a large volume of data is continuously emitted from a plethora of connected devices. The current network paradigm, which relies on centralized data centers (aka Cloud computing), has become inefficient to respond to IoT latency concern. To address this concern, fog computing allows data processing and storage "close" to IoT devices. However, fog is still not efficient due to spatial and temporal distribution of these devices, which leads to fog nodes' unbalanced loads. This paper proposes a new Fog-2-Fog (F2F) collaboration model that promotes offloading incoming requests among fog nodes, according to their load and processing capabilities, via a novel load balancing known as Fog Resource manAgeMEnt Scheme (FRAMES). A formal mathematical model of F2F and FRAMES has been fomulated, and a set of experiments has been carried out demonstrating the technical doability of F2F collaboration. The performance of the proposed fog load balancing model is compared to other load balancing models.

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