12,722 research outputs found

    Differentiating Clear Channel Assessment using Transmit Power Variation

    Get PDF
    Clear Channel Assessment (CCA) is a core element of Wireless Sensor Network (WSN) Medium Access Control (MAC) protocols which is used on transmitter and receiver side. Current CCA implementations cannot determine the device type occupying the media, leaving nodes unable to differentiate between WSN traffic and interference. However, this would be valuable as MAC protocols benefit from reacting differently depending on the channel occupier. In this paper we describe a method called Power Differentiating Clear Channel Assessment (P-DCCA). Transmitters vary the output power of the radio while the packet is being sent. Receivers are able to identify signals with this characteristic, enabling a Differentiating Clear Channel Assessment (DCCA) check to reveal if the medium is currently occupied by WSN traffic other interference. We present an implementation and thorough evaluation of P-DCCA. Using ContikiMAC as example we describe how P-DCCA can be integrated within MAC protocols. We show via large-scale testbed experiments and deployments that P-DCCA enabled networks have a significant improved performance. For example, we show that a P-DCCA enabled network can improve Packet Reception Rate (PRR) by up to a factor of 10 while reducing energy usage by over 80% under heavy interference

    Single session imaging of cerebellum at 7 tesla: Obtaining structure and function of multiple motor subsystems in individual subjects

    Get PDF
    The recent increase in the use of high field MR systems is accompanied by a demand for acquisition techniques and coil systems that can take advantage of increased power and accuracy without being susceptible to increased noise. Physical location and anatomical complexity of targeted regions must be considered when attempting to image deeper structures with small nuclei and/or complex cytoarchitechtonics (i.e. small microvasculature and deep nuclei), such as the brainstem and the cerebellum (Cb). Once these obstacles are overcome, the concomitant increase in signal strength at higher field strength should allow for faster acquisition of MR images. Here we show that it is technically feasible to quickly and accurately detect blood oxygen level dependent (BOLD) signal changes and obtain anatomical images of Cb at high spatial resolutions in individual subjects at 7 Tesla in a single one-hour session. Images were obtained using two high-density multi-element surface coils (32 channels in total) placed beneath the head at the level of Cb, two channel transmission, and three-dimensional sensitivity encoded (3D, SENSE) acquisitions to investigate sensorimotor activations in Cb. Two classic sensorimotor tasks were used to detect Cb activations. BOLD signal changes during motor activity resulted in concentrated clusters of activity within the Cb lobules associated with each task, observed consistently and independently in each subject: Oculomotor vermis (VI/VII) and CrusI/II for pro- and anti-saccades; ipsilateral hemispheres IV-VI for finger tapping; and topographical separation of eye- and hand- activations in hemispheres VI and VIIb/VIII. Though fast temporal resolution was not attempted here, these functional patches of highly specific BOLD signal changes may reflect small-scale shunting of blood in the microvasculature of Cb. The observed improvements in acquisition time and signal detection are ideal for individualized investigations such as differentiation of functional zones prior to surgery. Copyright

    Machine learning based lightweight interference mitigation scheme for wireless sensor network

    Get PDF
    The interference issue is most vibrant on low-powered networks like wireless sensor network (WSN). In some cases, the heavy interference on WSN from different technologies and devices result in life threatening situations. In this paper, a machine learning (ML) based lightweight interference mitigation scheme for WSN is proposed. The scheme detects and identifies heterogeneous interference like Wifi, bluetooth and microwave oven using a lightweight feature extraction method and ML lightweight decision tree. It also provides WSN an adaptive interference mitigation solution by helping to choose packet scheduling, Acknowledgement (ACK)-retransmission or channel switching as the best countermeasure. The scheme is simulated with test data to evaluate the accuracy performance and the memory consumption. Evaluation of the proposed scheme’s memory profile shows a 14% memory saving compared to a fast fourier transform (FFT) based periodicity estimation technique and 3% less memory compared to logistic regression-based ML model, hence proving the scheme is lightweight. The validation test shows the scheme has a high accuracy at 95.24%. It shows a precision of 100% in detecting WiFi and microwave oven interference while a 90% precision in detecting bluetooth interference

    Distributed Power Control of Cellular Networks in the Presence of Channel Uncertainties

    Get PDF
    A novel distributed power control (DPC) scheme for cellular networks in the presence of radio channel uncertainties such as path loss shadowing, and Rayleigh fading is presented. Since these uncertainties can attenuate the received signal strength and can cause variations in the received Signal-to-lnterference ratio (SIR), the proposed DPC scheme maintains a target SIR at the receiver provided the uncertainty is slowly varying with time. The DPC estimates the time varying nature of the channel quickly and uses the information to arrive at a suitable transmitter power value . Further, the standard assumption of a constant interference during a link\u27s power update used in other work in the literature is relaxed. A CDMA-hased celluar network environment is used to compare the proposed scheme with earlier approaches. The results show that our DPC scheme can converge faster than others by adapting to the channel variations. The proposed DPC scheme can render outage prohability of 5 to 30% in the presence of uncertainties compared with other schemes of 50 to 90% while consuming law power per active mobile user. In other words, the proposed DPC scheme allows significant increase in network capacity while consuming low- power values even when the channel is uncertain

    Measurement-based feasibility exploration on detecting and localizing multiple humans using MIMO radio channel properties

    Get PDF
    This paper explores the feasibility of using the multiple-input multiple-output (MIMO) radio channel properties to passively detect and localize multiple humans in indoor environments. We propose to utilize the unique reverberation characteristics of indoor channels for the purpose of detecting, and the power angular delay profile (PADP) for localizing humans. On the one hand, the reverberation time corresponds with the decay rate of multipath in a closed or partially closed cavity, and varies with the change of the number of humans or the moving of humans relative to the antennas at link ends. On the other hand, the PADP is proposed to be calculated by the Multiple Signal Classification (MUSIC) super resolution algorithm with frequency smoothing preprocessing. The proposed approach is evaluated based on real-world MIMO radio channel measurements obtained from a meeting room. Measurements with and without the presence of humans have been conducted, where the maximum number of humans considered is four. Humans facing different directions, either in parallel or orthogonal to the direct line between the transmit and the receive antennas have been taken into account. In term of the detection feasibility, it is found that the change of the number of humans as well as the change of their facing/moving directions inside the partial reverberant region can be reflected on the change of the reverberation time estimated from the power delay profile of channel. In term of the localization feasibility, it is found that single human location can be well associated to the peak of the variation of the PADP during his/her movement, while multiple humans' movements result in obvious power variation in the very vicinity of some of them, and also in the vicinity of some background objects that is far from target humans

    LINK ADAPTATION IN WIRELESS NETWORKS: A CROSS-LAYER APPROACH

    Get PDF
    Conventional Link Adaptation Techniques in wireless networks aim to overcome harsh link conditions caused by physical environmental properties, by adaptively regulating modulation, coding and other signal and protocol specific parameters. These techniques are essential for the overall performance of the networks, especially for environments where the ambient noise level is high or the noise level changes rapidly. Link adaptation techniques answer the questions of What to change? and When to change? in order to improve the present layer performance. Once these decisions are made, other layers are expected to function perfectly with the new communication channel conditions. In our work, we have shown that this assumption does not always hold; and provide two mechanisms that lessen the negative outcomes caused by these decisions. Our first solution, MORAL, is a MAC layer link adaptation technique which utilizes the physical transmission information in order to create differentiation between wireless users with different communication capabilities. MORAL passively collects information from its neighbors and re-aligns the MAC layer parameters according to the observed conditions. MORAL improves the fairness and total throughput of the system through distributing the mutually shared network assets to the wireless users in a fairer manner, according to their capabilities. Our second solution, Data Rate and Fragmentation Aware Ad-hoc Routing protocol, is a network layer link adaptation technique which utilizes the physical transmission information in order to differentiate the wireless links according to their communication capabilities. The proposed mechanism takes the physical transmission parameters into account during the path creation process and produces energy-efficient network paths. The research demonstrated in this dissertation contributes to our understanding of link adaptation techniques and broadens the scope of such techniques beyond simple, one-step physical parameter adjustments. We have designed and implemented two cross-layer mechanisms that utilize the physical layer information to better adapt to the varying channel conditions caused by physical link adaptation mechanisms. These mechanisms has shown that even though the Link Adaptation concept starts at the physical layer, its effects are by no means restricted to this layer; and the wireless networks can benefit considerably by expanding the scope of this concept throughout the entire network stack
    • …
    corecore