Improving RSSI based distance estimation for wireless sensor networks

In modern everyday life we see gradually increasing number of wireless sensor devices. In some cases it is necessary to know the accurate location of the devices. Most of the usual techniques developed to get this information require a lot of resources (power, bandwidth, computation, extra hardware) which small embedded devices cannot afford. Therefore techniques, using small resources without the need for extra hardware, need to be developed. Wireless sensor networks are often used inside buildings. In such environment satellite positioning is not available. As a consequence, the location computation must be done in network-based manner. In this thesis a received signal strength indicator (RSSI) based distance estimation technique for 802.15.4 network based on CC2431 radio is discussed. In this approach we try to differentiate between good and erroneous measurements by imposing limits based on standard deviation of RSSI and the number of lost packets. These limits are included as a part of the model parameter estimation process. These limits are optimized in order to improve the resulting distance estimates with minimum loss of connectivity information. We experimentally evaluated the merits of the proposed method and found it to be useful under certain circumstances.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

Partner selection in indoor-to-outdoor cooperative networks: an experimental study

In this paper, we develop a partner selection protocol for enhancing the network lifetime in cooperative wireless networks. The case-study is the cooperative relayed transmission from fixed indoor nodes to a common outdoor access point. A stochastic bivariate model for the spatial distribution of the fading parameters that govern the link performance, namely the Rician K-factor and the path-loss, is proposed and validated by means of real channel measurements. The partner selection protocol is based on the real-time estimation of a function of these fading parameters, i.e., the coding gain. To reduce the complexity of the link quality assessment, a Bayesian approach is proposed that uses the site-specific bivariate model as a-priori information for the coding gain estimation. This link quality estimator allows network lifetime gains almost as if all K-factor values were known. Furthermore, it suits IEEE 802.15.4 compliant networks as it efficiently exploits the information acquired from the receiver signal strength indicator. Extensive numerical results highlight the trade-off between complexity, robustness to model mismatches and network lifetime performance. We show for instance that infrequent updates of the site-specific model through K-factor estimation over a subset of links are sufficient to at least double the network lifetime with respect to existing algorithms based on path loss information only.Comment: This work has been submitted to IEEE Journal on Selected Areas in Communications in August 201

Experimental characterisation of the off-body wireless channel at 2.4 GHz for dairy cows in barns and pastures

status: publishe

Internet of animals : characterisation of LoRa sub-GHz off-body wireless channel in dairy barns

Advances in wireless sensor technologies and MEMS have made it possible to automatically monitor the health status of dairy cows using Internet of things (IoT) and wireless body area networks. Since on-cow measuring devices are energy constrained, a proper characterisation of the off-body wireless channel between the on-cow sensor nodes and the back-end base station is required for an optimised deployment of these networks in barns. In this Letter, the long range (LoRa) off-body wireless channel has been characterised at 868 MHz, a typical IoT frequency. Both path loss and temporal fading were investigated using LoRa motes. Based on this characterisation, network planning and energy consumption optimisation of the on-body nodes could be performed, which enables the deployment of reliable dairy cow monitoring systems

Lightweight Information Security Methods for Indoor Wireless Body Area Networks: from Channel Modeling to Secret Key Extraction

A group of wirelessly communicating sensors that are placed inside, on or around a human body constitute a Wireless Body Area Network (WBAN). Continuous monitoring of vital signs through WBANs have a potential to revolutionize current health care services by reducing the cost, improving accessibility, and facilitating medical diagnosis. However, sensitive nature of personal health data requires WBANs to integrate appropriate security methods and practices. As limited hardware resources make conventional security measures inadequate in a WBAN context, this work is focused on alternative techniques based on Wireless Physical Layer Security (WPLS). More specifically, we introduce a symbiosis of WPLS and Compressed Sensing to achieve security at the time of sampling. We successfully show how the proposed framework can be applied to electrocardiography data saving significant computational and memory resources. In the scenario when a WBAN Access Point can make use of diversity methods in the form of Switch-and-Stay Combining, we demonstrate that output Signal-to-Noise Ratio (SNR) and WPLS key extraction rate are optimized at different switching thresholds. Thus, the highest key rate may result in significant loss of output SNR. In addition, we also show that the past WBAN off-body channel models are insufficient when the user exhibits dynamic behavior. We propose a novel Rician based off-body channel model that can naturally reflect body motion by randomizing Rician factor K and considering small and large scale fading to be related. Another part of our investigation provides implications of user\u27s dynamic behavior on shared secret generation. In particular, we reveal that body shadowing causes negative correlation of the channel exposing legitimate participants to a security threat. This threat is analyzed from a qualitative and quantitative perspective of a practical secret key extraction algorithm

Localization Of Sensors In Presence Of Fading And Mobility

The objective of this dissertation is to estimate the location of a sensor through analysis of signal strengths of messages received from a collection of mobile anchors. In particular, a sensor node determines its location from distance measurements to mobile anchors of known locations. We take into account the uncertainty and fluctuation of the RSS as a result of fading and take into account the decay of the RSS which is proportional to the transmitter-receiver distance power raised to the PLE. The objective is to characterize the channel in order to derive accurate distance estimates from RSS measurements and then utilize the distance estimates in locating the sensors. To characterize the channel, two techniques are presented for the mobile anchors to periodically estimate the channel\u27s PLE and fading parameter. Both techniques estimate the PLE by solving an equation via successive approximations. The formula in the first is stated directly from MLE analysis whereas in the second is derived from a simple probability analysis. Then two distance estimates are proposed, one based on a derived formula and the other based on the MLE analysis. Then a location technique is proposed where two anchors are sufficient to uniquely locate a sensor. That is, the sensor narrows down its possible locations to two when collects RSS measurements transmitted by a mobile anchor, then uniquely determines its location when given a distance to the second anchor. Analysis shows the PLE has no effect on the accuracy of the channel characterization, the normalized error in the distance estimation is invariant to the estimated distance, and accurate location estimates can be achieved from a moderate sample of RSS measurements

On Application of Wireless Sensor Networks for Healthcare Monitoring

With the recent advances in embedded systems and very low power ,wireless tech­ nologies, there has been a great interest in the development and application of a new class of distributed Wireless body area network for health monitoring. The first part of the thesis presents a remote patient monitoring system within the scope of Body Area Network standardization. In this regime, wireless sensor networks are used to continuously acquire the patient’s Electrocardiogram signs and transmit data to the base station via IEEE.802.15. The personal Server (PS) which is responsible to provide real-time displaying, storing, and analyzing the patient’s vital signs is developed in MATLAB. It also transfers ECG streams in real-time to a remote client such as a physician or medical center through internet. The PS has the potential to be integrated with home or hospital computer systems. A prototype of this system has been developed and implemented. Tlie developed system takes advantage of two important features for healthcare monitoring: (i) ECG data acqui­ sition using wearable sensors and (ii) real-time data remote through internet. The fact that our system is interacting with sensor network nodes using MATLAB makes it distinct from other previous works. The second part is devoted to the study of indoor body-area channel model for 2.4 GHz narrowband communications. To un­ derstand the narrowband radio propagation near the body, several measurements are carried out in two separate environments for different on body locations. On the basis of these measurements, we have characterized the fading statistics on body links and we have provided a physical interpretation of our results

A Self-organizing Hybrid Sensor System With Distributed Data Fusion For Intruder Tracking And Surveillance

A wireless sensor network is a network of distributed nodes each equipped with its own sensors, computational resources and transceivers. These sensors are designed to be able to sense specific phenomenon over a large geographic area and communicate this information to the user. Most sensor networks are designed to be stand-alone systems that can operate without user intervention for long periods of time. While the use of wireless sensor networks have been demonstrated in various military and commercial applications, their full potential has not been realized primarily due to the lack of efficient methods to self organize and cover the entire area of interest. Techniques currently available focus solely on homogeneous wireless sensor networks either in terms of static networks or mobile networks and suffers from device specific inadequacies such as lack of coverage, power and fault tolerance. Failing nodes result in coverage loss and breakage in communication connectivity and hence there is a pressing need for a fault tolerant system to allow replacing of the failed nodes. In this dissertation, a unique hybrid sensor network is demonstrated that includes a host of mobile sensor platforms. It is shown that the coverage area of the static sensor network can be improved by self-organizing the mobile sensor platforms to allow interaction with the static sensor nodes and thereby increase the coverage area. The performance of the hybrid sensor network is analyzed for a set of N mobile sensors to determine and optimize parameters such as the position of the mobile nodes for maximum coverage of the sensing area without loss of signal between the mobile sensors, static nodes and the central control station. A novel approach to tracking dynamic targets is also presented. Unlike other tracking methods that are based on computationally complex methods, the strategy adopted in this work is based on a computationally simple but effective technique of received signal strength indicator measurements. The algorithms developed in this dissertation are based on a number of reasonable assumptions that are easily verified in a densely distributed sensor network and require simple computations that efficiently tracks the target in the sensor field. False alarm rate, probability of detection and latency are computed and compared with other published techniques. The performance analysis of the tracking system is done on an experimental testbed and also through simulation and the improvement in accuracy over other methods is demonstrated