Spectrum Utilization and Congestion of IEEE 802.11 Networks in the 2.4 GHz ISM Band

Wi-Fi technology, plays a major role in society thanks to its widespread availability, ease of use and low cost. To assure its long term viability in terms of capacity and ability to share the spectrum efficiently, it is of paramount to study the spectrum utilization and congestion mechanisms in live environments. In this paper the service level in the 2.4 GHz ISM band is investigated with focus on todays IEEE 802.11 WLAN systems with support for the 802.11e extension. Here service level means the overall Quality of Service (QoS), i.e. can all devices fulfill their communication needs? A crosslayer approach is used, since the service level can be measured at several levels of the protocol stack. The focus is on monitoring at both the Physical (PHY) and the Medium Access Control (MAC) link layer simultaneously by performing respectively power measurements with a spectrum analyzer to assess spectrum utilization and packet sniffing to measure the congestion. Compared to traditional QoS analysis in 802.11 networks, packet sniffing allows to study the occurring congestion mechanisms more thoroughly. The monitoring is applied for the following two cases. First the influence of interference between WLAN networks sharing the same radio channel is investigated in a controlled environment. It turns out that retry rate, Clear-ToSend (CTS), Request-To-Send (RTS) and (Block) Acknowledgment (ACK) frames can be used to identify congestion, whereas the spectrum analyzer is employed to identify the source of interference. Secondly, live measurements are performed at three locations to identify this type of interference in real-live situations. Results show inefficient use of the wireless medium in certain scenarios, due to a large portion of management and control frames compared to data content frames (i.e. only 21% of the frames is identified as data frames)

Development of a smart-antenna test-bed, demonstrating software defined digital beamforming

This paper describes a smart-antenna test-bed consisting of ‘common of the shelf’ (COTS) hardware and software defined radio components. The use of software radio components enables a flexible platform to implement and test mobile communication systems as a real-world system. The test-bed is configured to demonstrate the concept of a smart antenna receiver using digital beamforming. The system consists of high-speed analog to digital converters (ADC), a digital signal processor (DSP) and a real-time operating system, combined with radio algorithms in software. Programmable signal generators generate signals at intermediate frequencies (IF), which are sampled by the ADCs. The sampled IF signal is transferred efficiently to the DSP where a software defined digital downconverter translates the signal to the baseband. To demonstrate the test-bed for smart antennas a Constant Modulus (CM) algorithm is implemented. This algorithm recursively computes and updates the weight factors for the signals arriving at different antennas. The resulting optimal weight vector forms a spatial filter that can remove interfering signals arriving at an angle different from the desired signal

Interference Measurements in IEEE 802.11 Communication Links Due to Different Types of Interference Sources

The number of wireless devices (smartphones, laptops, sensors) that use the 2.4 GHz ISM band is rapidly increasing. The most common communication system in this band is Wi-Fi (IEEE 802.11b/g/n). For that reason coexistence between Wi-Fi and other systems becomes more and more important. In this paper we have investigated the influence on Wi-Fi communication for different interference sources, i.e., wireless Audio/Video (A/V) transmitter, microwave and Bluetooth. A measurement tool has been developed to measure this influence both at the Physical (PHY) Layer and at the link layer to assess the overall Quality of Service (QoS). At link layer the tool allows to analyze the received packets types and sub fields; a sophisticated approach to analyze interference mechanisms compared to traditional packet sniffers that focus on throughput and packet error rate only. In addition, this tool allows to identify the type of interference source based on the occurring interference mechanisms at these lower two layers of the OSI protocol stack. The experimental results show severe impact of A/V transmitters which causes significant overall QoS degradation of WiFi communication in contrast to microwave and Bluetooth interference