176 research outputs found

    Performance Analysis of Bluetooth Network in the Presence of WI-FI System

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    Many wireless technologies used to build local or personal area network (WLANs or WPANs) operate in the 2.4 GHz ISM band. Due to mutual interference, the coexistence of such devices working at the same time in the same area can be troublesome. This paper reports the result of Bluetooth performance  with 802.11b interference in term of BER of Bluetooth network. This study employed Agilent Advance Design system 2011 (ADS 2011) as methodology. The result revealed how Bluetooth network suffered degradation in terms of BER and the IEEE 802.11b interfering power and frequency offset. This study confirm previous finding. Further, the study recommends that the data rate of IEEE 802.11b should be taken into account in the performance evaluation of the Bluetooth network. Keywords: Bluetooth, Performance, and WI-FI syste

    Bluetooth performance in the presence of 802.11b WLAN

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    Wireless Technologies for IoT in Smart Cities

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    [EN] As cities continue to grow, numerous initiatives for Smart Cities are being conducted. The concept of Smart City encompasses several concepts being governance, economy, management, infrastructure, technology and people. This means that a Smart City can have different communication needs. Wireless technologies such as WiFi, ZigBee, Bluetooth, WiMax, 4G or LTE (Long Term Evolution) have presented themselves as solutions to the communication needs of Smart City initiatives. However, as most of them employ unlicensed bands, interference and coexistence problems are increasing. In this paper, the wireless technologies available nowadays for IoT (Internet of Things) in Smart Cities are presented. Our contribution is a review of wireless technologies, their comparison and the problems that difficult coexistence among them. In order to do so, the characteristics and adequacy of wireless technologies to each domain are considered. The problems derived of over-crowded unlicensed spectrum and coexistence difficulties among each technology are discussed as well. Finally, power consumption concerns are addressed.García-García, L.; Jimenez, JM.; Abdullah, MTA.; Lloret, J. (2018). Wireless Technologies for IoT in Smart Cities. Network Protocols and Algorithms. 10(1):23-64. doi:10.5296/npa.v10i1.12798S236410

    On adaptive frequency hopping to combat coexistence interference between bluetooth and IEEE 802.11b with practical resource constraints

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    In contrast to traditional frequency hopping techniques, Adaptive Frequency Hopping (AFH) is a low cost and low power solution to avoid interference dynamically. While each AFH algorithm proposed previously is shown to be efficient, a detailed performance analysis of various AFH mechanisms under realistic resource constraints is yet to be done. In particular, based on our performance study on Bluetooth systems presented in this paper, we have found that the AFH mechanism adopted by IEEE 802.15 Task Group 2 (TG2) is very sensitive to memory and power limitations. We then propose a novel Interference Source Oriented Adaptive Frequency Hopping (ISOAFH) approach based on a cross-layer design, in which the baseband layer of Bluetooth considers not only the instantaneous channels condition but also the physical layer transmission characteristics of potential interference sources in determining the hop sequence. In our simulations using detailed MATLAB Simulink modeling, we find that our proposed method is much more robust in that it is insensitive to memory and energy constraints. Indeed, our approach generally achieves a lower collision rate and higher ISM spectrum utilization.published_or_final_versio

    Wireless communication technologies for the Internet of Things

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    Internet of Things (IoT) is the inter-networking paradigm based on many processes such as identifying, sensing, networking and computation. An IoT technology stack provides seamless connectivity between various physical and virtual objects. The increasing number of IoT applications leads to the issue of transmitting, storing, and processing a large amount of data. Therefore, it is necessary to enable a system capable to handle the growing traffic requirements with the required level of QoS (Quality of Service). IoT devices become more complex due to the various components such as sensors and network interfaces. The IoT environment is often demanding for mobile power source, QoS, mobility, reliability, security, and other requirements. Therefore, new IoT technologies are required to overcome some of these issues. In recent years new wireless communication technologies are being developed to support the development of new IoT applications. This paper provides an overview of some of the most widely used wireless communication technologies used for IoT applications

    WLAN CSMA/CA Performance in a Bluetooth Interference Environment

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    IEEE 802.11 WLANs and Bluetooth piconets both operate in the 2.4 GHz Industrial Scientific and Medical (ISM) radio band. When operating in close proximity, these two technologies interfere with each other. Current literature suggests that IEEE 802.11 (employing direct sequence spread spectrum technology) is more susceptible to this interference than Bluetooth, which uses frequency hopping spread spectrum technology, resulting in reduced throughput. Current research tends to focus on the issue of packet collisions, and not the fact that IEEE 802.11 may also delay its transmissions while the radio channel is occupied by a Bluetooth signal. This research characterizes previously neglected transmission delay effects. Through analytic modeling and simulation, the impact of this interference is determined to identify all facets of the interference issues. Results show that Bluetooth-induced transmission delays improve network performance in many scenarios. When isolating delay effects, the likelihood that WLAN STA signals collide with each other decreases, causing an overall increase in normalized throughput and decrease in expected delay for many network configurations. As wireless communication technologies become an integral part of national defense, it is imperative to understand every performance characteristic. For instance, if the Air Force uses IEEE 802.11 and wants to incorporate a Bluetooth piconet as well, the impact of concurrent operation should be known beforehand. Since IEEE 802.11 and Bluetooth technologies could become vital for the Air Force to maintain its position of air superiority, all the strengths, weaknesses, and limitations of these systems should be understood

    Coexistence and interference mitigation for WPANs and WLANs from traditional approaches to deep learning: a review

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    More and more devices, such as Bluetooth and IEEE 802.15.4 devices forming Wireless Personal Area Networks (WPANs) and IEEE 802.11 devices constituting Wireless Local Area Networks (WLANs), share the 2.4 GHz Industrial, Scientific and Medical (ISM) band in the realm of the Internet of Things (IoT) and Smart Cities. However, the coexistence of these devices could pose a real challenge—co-channel interference that would severely compromise network performances. Although the coexistence issues has been partially discussed elsewhere in some articles, there is no single review that fully summarises and compares recent research outcomes and challenges of IEEE 802.15.4 networks, Bluetooth and WLANs together. In this work, we revisit and provide a comprehensive review on the coexistence and interference mitigation for those three types of networks. We summarize the strengths and weaknesses of the current methodologies, analysis and simulation models in terms of numerous important metrics such as the packet reception ratio, latency, scalability and energy efficiency. We discover that although Bluetooth and IEEE 802.15.4 networks are both WPANs, they show quite different performances in the presence of WLANs. IEEE 802.15.4 networks are adversely impacted by WLANs, whereas WLANs are interfered by Bluetooth. When IEEE 802.15.4 networks and Bluetooth co-locate, they are unlikely to harm each other. Finally, we also discuss the future research trends and challenges especially Deep-Learning and Reinforcement-Learning-based approaches to detecting and mitigating the co-channel interference caused by WPANs and WLANs
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