Capacity Analysis of IEEE 802.11ah WLANs for M2M Communications

Focusing on the increasing market of the sensors and actuators networks, the IEEE 802.11ah Task Group is currently working on the standardization of a new amendment. This new amendment will operate at the sub-1GHz band, ensure transmission ranges up to 1 Km, data rates above 100 kbps and very low power operation. With IEEE 802.11ah, the WLANs will offer a solution for applications such as smart metering, plan automation, eHealth or surveillance. Moreover, thanks to a hierarchical signalling, the IEEE 802.11ah will be able to manage a higher number of stations (STAs) and improve the 802.11 Power Saving Mechanisms. In order to support a high number of STAs, two different signalling modes are proposed, TIM and Non-TIM Offset. In this paper we present a theoretical model to predict the maximum number of STAs supported by both modes depending on the traffic load and the data rate used. Moreover, the IEEE 802.11ah performance and energy consumption for both signalling modes and for different traffic patterns and data rates is evaluated. Results show that both modes achieve similar Packet Delivery Ratio values but the energy consumed with the TIM Offset is, in average, a 11.7% lower.Comment: Multiple Access Communications 201

Modeling and Predictability Analysis on Channel Spectrum Status Over Heavy Wireless LAN Traffic Environment

Using the real wireless spectrum occupancy status in 2.4 and 5 GHz bands collected at a railway station as representative of a heavy wireless LAN (WLAN) traffic environment, this paper studies the modeling of durations of busy/idle (B/I) status and its predictability based on predictability theory. We first measure and model the channel status in the heavy traffic environment over almost all of the WLAN channels at 2.4 GHz and 5 GHz bands in a busy (rush hour) period and non-busy period. Then, using two selected channels at 2.4 GHz and 5 GHz bands, we analyze the upper bound (UB) and lower bound (LB) of predictability of the busy/idle durations based on predictability theory. The analysis shows that the LB predictability of durations can be easily increased by changing their probability distribution. Based on this property, we introduce the data categorization (DC) method. By categorizing the busy/idle durations into different streams, the proposed data categorization can improve the prediction performance of some streams with large LB predictability, even if it employs a simple low-complexity auto-regressive (AR) predictor

Survey of Spectrum Sharing for Inter-Technology Coexistence

Increasing capacity demands in emerging wireless technologies are expected to be met by network densification and spectrum bands open to multiple technologies. These will, in turn, increase the level of interference and also result in more complex inter-technology interactions, which will need to be managed through spectrum sharing mechanisms. Consequently, novel spectrum sharing mechanisms should be designed to allow spectrum access for multiple technologies, while efficiently utilizing the spectrum resources overall. Importantly, it is not trivial to design such efficient mechanisms, not only due to technical aspects, but also due to regulatory and business model constraints. In this survey we address spectrum sharing mechanisms for wireless inter-technology coexistence by means of a technology circle that incorporates in a unified, system-level view the technical and non-technical aspects. We thus systematically explore the spectrum sharing design space consisting of parameters at different layers. Using this framework, we present a literature review on inter-technology coexistence with a focus on wireless technologies with equal spectrum access rights, i.e. (i) primary/primary, (ii) secondary/secondary, and (iii) technologies operating in a spectrum commons. Moreover, we reflect on our literature review to identify possible spectrum sharing design solutions and performance evaluation approaches useful for future coexistence cases. Finally, we discuss spectrum sharing design challenges and suggest future research directions

Measuring the service level in the 2.4 GHz ISM band

In this report we provide the findings of the 2.4 GHz service level research. Here service level means the following: can all devices in the 2.4 GHz band fulfill their communication needs. In other words this corresponds to the overall Quality of Service (QoS). The project is a short research exploratory project of about 400 hours in collaboration with Agentschap Telecom, the Dutch Radiocommunications Agency. First of all a survey has been made to investigate which measurement methods can be used to assess the service level in the 2.4 GHz. Here the focus is on IEEE 802.11b/g/n (WiFi) systems. The service level can be measured at several levels of the OSI model: spectrum sensing (physical layer) and packet sniffers (datalink layer). Power level measurements are used to assess the utilization of the 2.4 GHz ISM band. On the other hand packet sniffers are an appropriate method to measure congestion and to pinpoint problems. Secondly, in this project the interferer mechanisms of several sources (microwave, wireless A/V transmitter, Bluetooth, second WiFi network) have been measured in a controlled environment. It turns out that interferers not only increase retry rate, but also trigger unwanted WiFi mechanisms; especially the hidden node mechanism (Request To Send (RTS)/Clear To Send (CTS) packets). So this means that the CTS/RTS control packets, but also the retry rate can be used to identify congestion. The spectrum measurement results allow to identify which interferer source causes congestion. Finally, also a measurement setup is presented that allows to measure the service level. In addition, initial measurements are provided of live environments (college room, office room, city centre). The results show inefficient use of the wireless medium in certain scenarios, due to a large frame rate of management and control packets compared to the data frame rate. In a busy WiFi environment (college room) only 20% of all frames are data frames. Of these data frames only 1/10 are actual data frames as most data frames are so-called null frames; used to keep a WiFi connection alive in power save mode. From all frames about 70% are control frames of which most are ACK frames and in less extend CTS/RTS frames. More research is required to identify the reasons for the high number of control frames. It is likely that there is significant interference, probably due to the many WiFi devices. This is also depicted by the retry frame rate (7%). Combining spectrum sensing with packet sniffing seems to be a good method to assess the service level in the 2.4 GHz ISM band. However, the interferer mechanisms that occur between WiFi networks, WiFi devices and other technologies are complex. More research is needed to enhance the developed proof-of-concept demonstrator and to have a better understanding of the interferer mechanisms in WiFi systems