Ioannis Glaropoulos

Detecting Low-Power Primary Signals via Distributed Sensing to Support Opportunistic Spectrum Access

Cognitive radio operation with opportunistic spectrum access has been proposed to utilize spectrum holes left unused by a primary system owning the spectrum license. The key of cognitive radio operation is the ability to detect weak primary signals and to control the transmission of cognitive users in a way that interference between the two systems is minimized. In this paper we evaluate how a sensor network deployed to provide distributed spectrum sensing can assist cognitive operation. Specifically, we consider sensor networks with regular topology, where a high level of cooperation also means that sensors far from the source of the primary signal are involved in the sensing process. Assuming energy detection and hard-decision combining we derive worst case probabilities of missed detection and false alarm, determine the necessary level of cooperation among the sensors and evaluate how the sensor density and the sensing time affect the performance of distributed sensing.

Enhanced power saving mode for low-latency communication in multi-hop 802.11 networks

The Future Internet of Things (IoT) will connect billions of battery-powered radio-enabled devices. Some of them may need to communicate with each other and with Internet gateways (border routers) over multi-hop links. While most IoT scenarios assume that for this purpose devices use energy-efficient IEEE 802.15.4 radios, there are use cases where IEEE 802.11 is preferred despite its potentially higher energy consumption. We extend the IEEE 802.11 power saving mode (PSM), which allows WLAN devices to enter a low-power doze state to save energy, with a traffic announcement scheme that facilitates multi-hop communication. The scheme propagates traffic announcements along multi-hop paths to ensure that all intermediate nodes remain awake to receive and forward the pending data frames with minimum latency. Our simulation results show that the proposed Multi-Hop PSM (MH-PSM) improves both end-to-end delay and doze time compared to the standard PSM; therefore, it may optimize WLAN to meet the networking requirements of IoT devices. MH-PSM is practical and software-implementable since it does not require changes to the parts of the IEEE 802.11 medium access control that are typically implemented on-chip. We implemented MH-PSM as a part of a WLAN driver for Contiki OS, which is an operating system for resource-constrained IoT devices, and we demonstrated its efficiency experimentally.

Enhanced IEEE 802.11 Power Saving for Multi-hop Toy-to-Toy Communication

In the future Internet of Things (IoT), battery-powered devices equipped with short range radios may need to communicate with each other over multi-hop links. This may significantly increase their energy consumption. Whereas most research on IoT assumes that the devices use energy-efficient IEEE 802.15.4 wireless transceivers, we focus on IEEE 802.11 because of its wide penetration in consumer electronics such as toys. We extend the IEEE 802.11 power saving mode (PSM), which allows the devices to enter the low-power doze state, with a traffic announcement scheme that facilitates multi-hop communication. The scheme propagates traffic announcements along multi-hop paths to ensure that all intermediate nodes remain awake to forward the pending data frames with minimum latency. Simulation results show that the proposed Multi-Hop PSM (MH-PSM) improves both end-to-end delay and doze time compared to the standard PSM. MH-PSM is practical and software-implement able since it does not require changes to the parts of the IEEE 802.11 medium access control that are typically implemented in hardware.

Green sensing and access: energy-throughput trade-offs in cognitive networking

Limited spectrum resources and the dramatic growth of high data rate applications have motivated opportunistic spectrum access exploiting the promising concept of cognitive networks. Although this concept has emerged primarily to enhance spectrum utilization and to allow the coexistence of heterogeneous network technologies, the importance of energy consumption imposes additional challenges, because energy consumption and communication performance can be at odds. In this article the approaches for energy efficient spectrum sensing and spectrum handoff, fundamental building blocks of cognitive networks, are investigated. The trade-offs between energy consumption and throughput, under local as well as under cooperative sensing, are characterized. We also discuss the additional factors that need to be investigated to achieve energy efficient cognitive operation under various application requirements.

Modeling and estimation of partially observed WLAN activity for cognitive WSNs

Efficient communication in the crowded ISM band requires the communication networks to be aware of the networking environment and to control their communication protocols accordingly. In this paper we address the issue of efficient WSN communication under WLAN interference. We propose analytic models to describe the WLAN idle time distributions as observed by the WSN nodes, together with efficient methods for parameter estimation. We evaluate how the spectrum sensing capability of the sensors affects the performance of the idle period distribution estimation and conclude that the proposed solutions are accurate enough to support cognitive WSNs.

Energy Efficient COGnitive-MAC for Sensor Networks Under WLAN Co-existence

Energy efficiency has been the driving force behind the design of communication protocols for battery-constrained wireless sensor networks (WSNs). The energy efficiency and the performance of the proposed protocol stacks, however, degrade dramatically in case the low-powered WSNS are subject to interference from high-power wireless systems such as WLANs. In this paper we propose COG-MAC, a novel cognitive medium access control scheme (MAC) for IEEE 802.15.4-compliant WSNS that minimizes the energy cost for multihop communications, by deriving energy-optimal packet lengths and single-hop transmission distances based on the experienced interference from IEEE 802.11 WLANs. We evaluate COG-MAC by deriving a detailed analytic model for its performance and by comparing it with previous access control schemes. Numerical and simulation results show that a significant decrease in packet transmission energy cost, up to 66%, can be achieved in a wide range of scenarios, particularly under severe WLAN interference. COG-MAC is, also, lightweight and shows high robustness against WLAN model estimation errors and is, therefore, an effective, implementable solution to reduce the WSN performance impairment when coexisting with WLANs.

Contiki80211: An IEEE 802.11 Radio Link Layer for the Contiki OS

We believe that the existing 802.11 MAC layer can be optimized (especially for energy-efficiency) to make Wi-Fi suitable for a wide range of IoT applications. However, there is a lack of low-cost embedded platforms to be used for experimentation with 802.11 MAC. The majority of low-power Wi-Fi modules for embedded systems has closed source firmware and protocol stack implementations, which prevents implementation and testing of new protocol features. Here we describe Contiki80211, an open source 802.11 radio link layer implementation for Contiki OS, optimized for resource constrained embedded platforms, whose purpose is to enable experimentation with 802.11 MAC layer management mechanisms on embedded devices.

Closing the gap between traffic workload and channel occupancy models for 802.11 networks

The modeling of wireless network traffic is necessary to evaluate the possible gains of spectrum sharing and to support the design of new cognitive protocols that can use spectrum efficiently in network environments where diverse technologies coexist. In this paper we focus on IEEE 802.11 wireless local area networks and close the gap between two popular levels of modeling, macroscopic traffic workload modeling and microscopic channel occupancy modeling. We consider traffic streams generated by established traffic workload models and characterize the networking scenarios where a simple, semi-Markovian channel occupancy model accurately predicts the wireless channel usage. Our results demonstrate that the proposed channel occupancy model can capture the channel idle time distribution in most of the scenarios, while the Markovian assumption cannot be validated in all cases.

Performance of deterministic local sensing aggregation under interference

In this paper we evaluate the delay and sensing performance of distributed cooperative sensing in wireless sensor networks assisting cognitive secondary operation. We propose a time division multiple access protocol to exchange sensing information among neighboring sensors, that is tunable in terms of sensing cooperation range and frequency reuse distance. Our evaluation shows that short frequency reuse distance may cause significant packet loss in the sensing aggregation process. This loss however affects mainly transmissions with less significant information, and therefore low delay aggregation with efficient spatial time division multiplexing is possible.

Spectrum sharing with low power primary networks

Access to unused spectrum bands of primary networks requires a careful optimization of the secondary cooperative spectrum sensing, if the transmission powers in the two networks are comparable. In this case the reliability of the sensing depends significantly on the spatial distribution of the cooperating nodes. In this paper we study the efficiency of cooperative sensing over multiple bands, sensed and shared by a large number of secondary users. We show that the per user cognitive capacity is maximized, if both the number of bands sensed by the secondary network as a whole, and the subsets of these bands sensed by the individual nodes are optimized. We derive the fundamental limits under different sensing duty allocation schemes. We show that with some coordination the per user cognitive capacity can be kept nearly independent from the network density.