220 research outputs found
Effect of adjacent-channel interference in IEEE 802.11 WLANs
Frequency channels are a scarce resource in the ISM bands used by IEEE 802.11 WLANs. Current radio resource management is often limited to a small number of nonoverlapping
channels, which leaves only three possible channels in the 2.4GHz band used in IEEE 802.11b/g networks. In this paper we study and quantify the effect of adjacent channel
interference, which is caused by transmissions in partially overlapping channels. We propose a model that is able to
determine under what circumstances the use of adjacent channels is justified. The model can also be used to assist different radio resource management mechanisms (e.g.
transmitted power assignments
SDN-Based Channel Assignment Algorithm for Interference Management in Dense Wi-Fi Networks
The popularity of Wi-Fi-enabled devices alongside the growing demand for non-licensed spectrum, has made the Wi-Fi networks exceedingly congested. This endangers the efficiency of Wi-Fi and negatively affect the users' experience. The problem is especially pressing in dense areas (e.g. shopping centers) where Wi-Fi channel assignment is more likely to be uncoordinated and the working environment of Wi-Fi Access Points (APs) has become increasingly time-variant. As a result, the availability of Software-Defined Networking (SDN) and network virtualization technologies has motivated the use of centralized resource management as a solution. This paper provides an algorithm for channel assignment functionality in the context of SDN-based centralized resource management, which captures the live status of a Wi-Fi network and is capable of optimising the Radio Frequency (RF) channel assignment process. The APs' network arrangement, the current assignment of the channels and the characteristics of the RF channels in IEEE 802.11 have all been taken into account in the proposed model. The performance of the proposed model in terms of the level of the interference, the spectral efficiency at each AP and the Signal to Interference plus Noise Ratio (SINR) at the user-side is evaluated through simulation and compared against state of the art solutions
Fine-Grained Radio Resource Management to Control Interference in Dense Wi-Fi Networks
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
On the Benefits of Channel Bonding in Dense, Decentralized Wi-Fi 4 Networks
Channel bonding is a technique first defined in the IEEE 802.11n standard to increase the throughput in wireless networks by means of using wider channels. In IEEE 802.11n (nowadays also known as Wi-Fi 4), it is possible to use 40 MHz channels instead of the classical 20 MHz channels. Although using channel bonding can increase the throughput, the classic 802.11 setting only allows for two orthogonal channels in the 2.4 GHz frequency band, which is not enough for proper channel assignment in dense settings. For that reason, it is commonly accepted that channel bonding is not suitable for this frequency band. However, to the best of our knowledge, there is not any accurate study that deals with this issue thoroughly. In this work, we study in depth the effect of channel bonding in Wi-Fi 4 dense, decentralized networks operating in the 2.4 GHz frequency band. We confirm the negative effect of using channel bonding in the 2.4 GHz frequency band with 11 channels which are 20 MHz wide (as in North America), but we also show that when there are 13 or more channels at hand (as in many other parts of the world, including Europe and Japan), the use of channel bonding yields consistent throughput improvements. For that reason, we claim that the common assumption of not considering channel bonding in the 2.4 GHz band should be revised
An Interface Setup Optimization Method Using a Throughput Estimation Model for Concurrently Communicating Access Points in a Wireless Local Area Network
The IEEE 802.11 wireless local-area network (WLAN) has been deployed around the globe as a major Internet access medium due to its low cost and high flexibility and capacity. Unfortunately, dense wireless networks can suffer from poor performance due to high levels of radio interference resulting from adjoining access points (APs). To address this problem, we studied the AP transmission power optimization method, which selects the maximum or minimum power supplied to each AP so that the average signal-to-interference ratio (SIR) among the concurrently communicating APs is maximized.However, this method requires measurements of receiving signal strength (RSS) under all the possible combinations of powers. It may need intolerable loads and time as the number of APs increases. It also only considers the use of channel bonding (CB), although non-CB sometimes achieves higher performance under high levels of interference. In this paper, we present an AP interface setup optimization method using the throughput estimation model for concurrently communicating APs. The proposed method selects CB or non-CB in addition to the maximum or minimum power for each AP. This model approach avoids expensive costs of RSS measurements under a number of combinations. To estimate the RSS at an AP from another AP or a host, the model needs the distance and the obstacles between them, such as walls. Then, by calculating the estimated RSS with the model and calculating the SIR from them, the AP interface setups for a lot of APs in a large-scale wireless network can be optimized on a computer in a very short time. For evaluation, we conducted extensive experiments using Raspberry Pi for APs and Linux PCs for hosts under 12 network topologies in three buildings at Okayama University, Japan, and Jatiya Kabi Kazi Nazrul Islam University, Bangladesh. The results confirm that the proposed method selects the best AP interface setup with the highest total throughput in any topology
Development of a Planning and Analysis Tool for Wireless Mesh Network
The aim of this project, "Development of Wireless Mesh Network Planning and Analysis Tool", is to create a GUI-oriented modeler for wireless mesh network planning and analysis. The main purpose of network planning is to provide a costeffective solution in term of two objectives which are coverage and capacity. Network planning covers a wide range of issues from coverage (base station or access point) to core network system. It will develop a tool, using Java programming language, which provides functions to help users do planning setting up a desired wireless mesh network and also techniques to analyze the system
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