SDN-based channel assignment algorithm for interference management in dense Wi-Fi networks

Seyedebrahimi, Mirghiasaldin; Bouhafs, Faycal; Raschellà, Alessandro; Mackay, Michael; Shi, Qi

doi:10.1109/eucnc.2016.7561018

Cited by 33 publications

(33 citation statements)

References 7 publications

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“…As Wi‐Fi networks also operate on unlicensed bands, the popularity of this technology has resulted in dense deployments with a lack of coordination among Wi‐Fi access points, which has resulted in interference and congestion that affects the quality of connectivity for many wireless users. Many research initiatives are currently trying to address the spectrum congestion problem in Wi‐Fi networks by introducing novel interaccess point cooperation solutions based on SDN …”

Section: State Of the Art And Paper Contributionsmentioning

confidence: 99%

Radio resource management framework for energy‐efficient communications in the Internet of Things

Deepak

Bouhafs

Raschellà

et al. 2019

Trans Emerging Tel Tech

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The Internet of Things (IoT) is the vision of a global network that connects various physical world objects to the IT infrastructure through a wireless medium.Despite the availability of a number of mature radio access technologies such as GSM, Long-Term Evolution, Wi-Fi, and due to the current progress made in developing 5G technology, more and more IoT operators are opting to use low-power wide-area (LPWA) technologies due to their low cost and easy deployment. However, recent studies show that the radio resource allocation used in these technologies is not scalable. This limitation often results in packet collisions, retransmission and unnecessary waste of scarce energy resources. In this paper, we propose a radio resource management framework, based on software-defined network (SDN), to overcome the inefficient radio resource allocation of LPWA technologies. This is possible through the centralized nature of SDN, which allows collecting network monitoring information to analyze and calculate the optimal channel assignment configuration across the IoT network.We perform software-defined radio-based spectrum monitoring within the real IoT network platform in 868 MHz bands in which the latest IoT technologies, ie, LoRa and SigFox, operate. We demonstrate, through extensive simulations, that the proposed approach provides a better radio resource allocation for LPWA, reduces the number of packet collisions, and significantly improves the energy efficiency of the IoT communications.Trans Emerging Tel Tech. 2019;30:e3766.wileyonlinelibrary.com/journal/ett

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Section: State Of the Art And Paper Contributionsmentioning

confidence: 99%

Radio resource management framework for energy‐efficient communications in the Internet of Things

Deepak

Bouhafs

Raschellà

et al. 2019

Trans Emerging Tel Tech

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“…The project proposes an architecture [12] that acknowledges the heterogeneity of Wi-Fi networks operators and uses SDWN to provide a coordination platform among operators that could be used to implement cooperative spectrum management algorithms [14], [15], as illustrated in Fig. 1.…”

Section: Sdwn-based Wi-fi Management Frameworkmentioning

confidence: 99%

“…In this section we first revisit our channel assignment optimization problem, which has preliminarily been introduced in [15]. We then extend the analysis of its interference-related quantity, interference impact, as a basis for providing a networkwide quality indicator from the perspective of interference.…”

Section: Network-wide Interference Analysismentioning

confidence: 99%

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Fine-Grained Radio Resource Management to Control Interference in Dense Wi-Fi Networks

Seyedebrahimi

Bouhafs

Raschellà

et al. 2017

2017 IEEE Wireless Communications and Networking Conference (WCNC)

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Abstract-In spite of the enormous popularity of Wi-Fienabled devices, the utilization of Wi-Fi radio resources (e.g. RF spectrum and transmission power levels) at Access Points (APs) is degraded in current decentralized Radio Resource Management (RRM) schemes. Most state of the art central control solutions apply configurations in which the network-wide impacts of the involved parameters and their mutual relationships are ignored. In this paper, we propose an algorithm for jointly adjusting the transmission power levels and optimizing the RF channel assignment of APs by taking into account the flows' required qualities while minimizing their interference impacts throughout the network. The proposed solution is tailored for an operatoragnostic and Software Defined Wireless Networking (SDWN)-based centralised RRM in dense Wi-Fi networks. Our extensive simulation results validate the performance improvement of the proposed algorithm compared to the main state of the art alternative by showing more than 25% higher spectrum efficiency, satisfying the users' demands and further mitigating the networkwide interference through a flow-based and quality-oriented power level adjustment.

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“…On the other hand, there have been also studies about interference management schemes, eg, transmission power control, 9 AP placement optimization, 10 and channel selection. 11 In the work of Seyedebrahimi et al, 12 the authors provided an algorithm for channel assignment functionality in the context of SDN-based centralized resource management, which captures the live status of a WiFi network and is capable of optimizing the Radio Frequency (RF) channel assignment process. In the work of Zhou et al, 11 the authors proposed a heuristic algorithm that assigns a channel to an AP by analyzing the effect of partially overlapping channels on the WiFi network throughput.…”

Section: Introductionmentioning

confidence: 99%

Modelling the impact of interference on the energy efficiency of WLANs

Han

Wang

et al. 2019

Concurrency and Computation

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The high-bandwidth demands from variety of applications drive a dense wireless local access network (WLAN), which results in a complicated wireless network scene with serious co-channel interference and energy waste. In this paper, to reveal the interactions between interference and energy efficiency, we propose an interference-energy efficiency (IFEE) model to quantify the interference impact on the energy efficiency of 802.11 access point (AP) devices. Firstly, we introduce the channel separation and the difference of received signal strength indication (D-RSSI) as two indicators to extend the classical signal to interference plus noise ratio (SINR) notion and rate adaptive mechanism. Then, these two parameters are integrated into the energy consumption model to establish the IFEE model. Lastly, we conduct extensive measurements with five typical WiFi interference scene in real network to validate the effectiveness of our model. The comparisons between simulation results and real data demonstrate that the proposed IFEE model can quantify the interference and energy efficiency with high accuracy, which can be used for wireless network optimization and protocol design.

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SDN-based channel assignment algorithm for interference management in dense Wi-Fi networks

Abstract: Abstract-

Cited by 33 publications

References 7 publications

Radio resource management framework for energy‐efficient communications in the Internet of Things

Radio resource management framework for energy‐efficient communications in the Internet of Things

Fine-Grained Radio Resource Management to Control Interference in Dense Wi-Fi Networks

Modelling the impact of interference on the energy efficiency of WLANs

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