This paper discusses causes of the sluggish growth rates of mobile learning in a developing country (Botswana), despite the mobile phone revolution and proposes future directions in application of mobile technology to enhance education in emerging economies.
{"title":"Is Rural Botswana Stuck to the \"Chalkboard Only\" Era while Others Make Strides in Mobile Learning?","authors":"Lydia Maketo, C. Balakrishna","doi":"10.1109/NGMAST.2015.39","DOIUrl":"https://doi.org/10.1109/NGMAST.2015.39","url":null,"abstract":"This paper discusses causes of the sluggish growth rates of mobile learning in a developing country (Botswana), despite the mobile phone revolution and proposes future directions in application of mobile technology to enhance education in emerging economies.","PeriodicalId":217588,"journal":{"name":"2015 9th International Conference on Next Generation Mobile Applications, Services and Technologies","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114332817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mir Lodro, S. Greedy, C. Smartt, David W. P. Thomas, A. Vukovic
Cognitive Radio (CR) dynamically finds the spectrum opportunity i.e. spectrum hole in space-time-frequency and code to do its adaptive transmission without harming the incumbent or the Primary User (PU). TV white spaces (TVWS) are the unused or underutiliised bands in the UHF and VHF part of the band which according to Federal Communication Commission (FCC) can be exploited if the secondary user (SU) with CR capabilities can adequately accommodate the transmission without introducing the harmful interference to incumbent or Primary Users (PU). TV band offers excellent building penetration and less propagation losses when compared to ISM bands of 2.4GHz and 5GHz. The focus of this article is to study cooperative sensing-throughout trade-off for SU with CR capabilities in TVWS. It is shown that with M cognitive users in cooperation we can get increased throughput with increase in sensing time for a fixed probability of false alarm and target probability of detection.
{"title":"Sensing-Throughput Tradeoff for Cognitive Radio in TV White Spaces","authors":"Mir Lodro, S. Greedy, C. Smartt, David W. P. Thomas, A. Vukovic","doi":"10.1109/NGMAST.2015.21","DOIUrl":"https://doi.org/10.1109/NGMAST.2015.21","url":null,"abstract":"Cognitive Radio (CR) dynamically finds the spectrum opportunity i.e. spectrum hole in space-time-frequency and code to do its adaptive transmission without harming the incumbent or the Primary User (PU). TV white spaces (TVWS) are the unused or underutiliised bands in the UHF and VHF part of the band which according to Federal Communication Commission (FCC) can be exploited if the secondary user (SU) with CR capabilities can adequately accommodate the transmission without introducing the harmful interference to incumbent or Primary Users (PU). TV band offers excellent building penetration and less propagation losses when compared to ISM bands of 2.4GHz and 5GHz. The focus of this article is to study cooperative sensing-throughout trade-off for SU with CR capabilities in TVWS. It is shown that with M cognitive users in cooperation we can get increased throughput with increase in sensing time for a fixed probability of false alarm and target probability of detection.","PeriodicalId":217588,"journal":{"name":"2015 9th International Conference on Next Generation Mobile Applications, Services and Technologies","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116953115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The performance of Emergency Management Systems (EMS) in confined spaces is highly dependent on the decision algorithm employed for the safe navigation of the evacuees to the available exits. In the algorithm proposed in this paper, we have considered evacuees under two groups, based on their age and physical condition, and we tailor two routing metrics, one for each group, in finding suitable paths for the evacuees. A dynamic grouping mechanism that can adjust an evacuee's group, and therefore routing metric, according to its on-going health condition is employed during the evacuation. To implement the routing metrics, we have used the Cognitive Packet Network (CPN) with random neural networks (RNN) and reinforcement learning. The CPN is an adaptive routing protocol that is loop-free at all times and easily handles multiple quality of service (QoS) metrics. Simulation results show that allowing the navigation system to be sensitive to the on-going health conditions and mobility of the evacuees, using our proposed dynamic grouping, can achieve higher survival rates.
{"title":"Emergency Navigation in Confined Spaces Using Dynamic Grouping","authors":"Huibo Bi, Olumide J. Akinwande, E. Gelenbe","doi":"10.1109/NGMAST.2015.12","DOIUrl":"https://doi.org/10.1109/NGMAST.2015.12","url":null,"abstract":"The performance of Emergency Management Systems (EMS) in confined spaces is highly dependent on the decision algorithm employed for the safe navigation of the evacuees to the available exits. In the algorithm proposed in this paper, we have considered evacuees under two groups, based on their age and physical condition, and we tailor two routing metrics, one for each group, in finding suitable paths for the evacuees. A dynamic grouping mechanism that can adjust an evacuee's group, and therefore routing metric, according to its on-going health condition is employed during the evacuation. To implement the routing metrics, we have used the Cognitive Packet Network (CPN) with random neural networks (RNN) and reinforcement learning. The CPN is an adaptive routing protocol that is loop-free at all times and easily handles multiple quality of service (QoS) metrics. Simulation results show that allowing the navigation system to be sensitive to the on-going health conditions and mobility of the evacuees, using our proposed dynamic grouping, can achieve higher survival rates.","PeriodicalId":217588,"journal":{"name":"2015 9th International Conference on Next Generation Mobile Applications, Services and Technologies","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116603338","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Organizations that give out loans to farmers are interested in seeing the farmers farms do well, so farmers can reap a bountiful harvest and repay their loans. In the case under consideration, the organization employs agriculture extension officers who should visit farmers at seven times at key stages during a farming cycle. The city based administrators of the scheme have no way of ensuring that extension officers actually visit the farmers at the appointed times and time intervals. Further, the farmers claims of poor harvests cannot be verified, leading to loan defaults. This project makes use of a multi-language mobile and web application to address these and other challenges faced by the industry in an innovative way. The mobile application can work offline and synchronizes with a cloud database when connectivity is available. The application has been deployed for more than one year. The design of the application, results and lessons from the deployment are presented.
{"title":"Lessons from Addressing Challenges in an Agricultural Extension Scheme Using Mobile Apps","authors":"N. Amanquah, M. Mzyece","doi":"10.1109/NGMAST.2015.69","DOIUrl":"https://doi.org/10.1109/NGMAST.2015.69","url":null,"abstract":"Organizations that give out loans to farmers are interested in seeing the farmers farms do well, so farmers can reap a bountiful harvest and repay their loans. In the case under consideration, the organization employs agriculture extension officers who should visit farmers at seven times at key stages during a farming cycle. The city based administrators of the scheme have no way of ensuring that extension officers actually visit the farmers at the appointed times and time intervals. Further, the farmers claims of poor harvests cannot be verified, leading to loan defaults. This project makes use of a multi-language mobile and web application to address these and other challenges faced by the industry in an innovative way. The mobile application can work offline and synchronizes with a cloud database when connectivity is available. The application has been deployed for more than one year. The design of the application, results and lessons from the deployment are presented.","PeriodicalId":217588,"journal":{"name":"2015 9th International Conference on Next Generation Mobile Applications, Services and Technologies","volume":"193 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131047688","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper describes a model of a smart street light that can work autonomously, save energy and can be seamlessly integrated with the existing grid. The street light incorporates a Light Emitting Diode array and an ARM Cortex M0 based microcontroller, both of which are powered by a combination of a solar panel and battery pack. The microcontroller executes an astronomical time switch based estimation algorithm to determine the sunrise and sunset time daily. This is done using the Real Time Clock running on the controller along with the hard coded coordinates and time zone of any given location. Upon evaluation of the sun times, the controller can routinely regulate the lamp at sunrise and sunset. The algorithm operates with an accuracy of up to 10 seconds in its estimation of sun times. The controller also monitors the voltage from the battery at sunset and switches to mains to power up the LED array in case power is not enough. A coin cell is also connected to the controller to ensure RTC keeps on running in the scenario that battery is completely discharged and there is no power from the mains. The results conclude that the use of such a technology would provide high energy efficiency, increases the operating life and also proves to be cost effective as compared to prevalent lamp technologies. Analysis is performed using HOMER, a microgrid simulation software. The boundary conditions are set for Indian scenarios, however the result applies to many geographical locations.
本文描述了一种智能路灯的模型，它可以自主工作，节约能源，并可以与现有电网无缝集成。路灯采用了发光二极管阵列和基于ARM Cortex M0的微控制器，两者都由太阳能电池板和电池组组合供电。微控制器执行基于天文时间开关的估计算法来确定每天的日出和日落时间。这是使用控制器上运行的Real Time Clock以及任何给定位置的硬编码坐标和时区来完成的。根据太阳时间的评估，控制器可以在日出和日落时常规调节灯。该算法对太阳时间的估计精度可达10秒。控制器还监测日落时电池的电压，并在电源不足的情况下切换到电源上为LED阵列供电。一个硬币电池也连接到控制器，以确保RTC在电池完全放电和没有电源的情况下继续运行。结果表明，使用这种技术将提供高能效，增加使用寿命，并且与流行的灯技术相比，也被证明具有成本效益。使用微电网仿真软件HOMER进行分析。边界条件是为印度设定的，但结果适用于许多地理位置。
{"title":"Efficient Control Algorithm for a Smart Solar Street Light","authors":"Abhilasha Jain, C. Nagarajan","doi":"10.1109/NGMAST.2015.40","DOIUrl":"https://doi.org/10.1109/NGMAST.2015.40","url":null,"abstract":"This paper describes a model of a smart street light that can work autonomously, save energy and can be seamlessly integrated with the existing grid. The street light incorporates a Light Emitting Diode array and an ARM Cortex M0 based microcontroller, both of which are powered by a combination of a solar panel and battery pack. The microcontroller executes an astronomical time switch based estimation algorithm to determine the sunrise and sunset time daily. This is done using the Real Time Clock running on the controller along with the hard coded coordinates and time zone of any given location. Upon evaluation of the sun times, the controller can routinely regulate the lamp at sunrise and sunset. The algorithm operates with an accuracy of up to 10 seconds in its estimation of sun times. The controller also monitors the voltage from the battery at sunset and switches to mains to power up the LED array in case power is not enough. A coin cell is also connected to the controller to ensure RTC keeps on running in the scenario that battery is completely discharged and there is no power from the mains. The results conclude that the use of such a technology would provide high energy efficiency, increases the operating life and also proves to be cost effective as compared to prevalent lamp technologies. Analysis is performed using HOMER, a microgrid simulation software. The boundary conditions are set for Indian scenarios, however the result applies to many geographical locations.","PeriodicalId":217588,"journal":{"name":"2015 9th International Conference on Next Generation Mobile Applications, Services and Technologies","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117189943","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
WiFi offloading is a cost-effective way of alleviating the problem of highly congested cellular networks. In this paper, we consider WiFi offloading problem in an integrated cellular WiFi system consisting of mobile base station (MBS) and WiFi access point (AP). We propose a probabilistic offloading scheme, where cellular packets that arrive at the queue of MBS are offloaded to the queue of WiFi AP with an offload probability. The offload probability is determined to minimize the average delay experienced by the cellular packets while guaranteeing stability of both cellular and WiFi system. We model the arrivals and fulfillments of data services of a cellular operator as an M/M/1 queue. We investigate two priority disciplines: First-In-First-Out (FIFO) and Non-Preemptive Priority Rule (NPPR). We provide an exact optimal offload probability for FIFO, but present an upper bound on the optimal probability for NPPR. Numerical investigation is used to verify the optimality of the proposed solutions, to examine the effect of packet arrival rate of MBS and compare the average delays for FIFO and NPPR.
{"title":"Probabilistic Offload Scheme in Integrated Cellular WiFi Systems","authors":"Insook Kim, Dongwoo Kim","doi":"10.1109/NGMAST.2015.18","DOIUrl":"https://doi.org/10.1109/NGMAST.2015.18","url":null,"abstract":"WiFi offloading is a cost-effective way of alleviating the problem of highly congested cellular networks. In this paper, we consider WiFi offloading problem in an integrated cellular WiFi system consisting of mobile base station (MBS) and WiFi access point (AP). We propose a probabilistic offloading scheme, where cellular packets that arrive at the queue of MBS are offloaded to the queue of WiFi AP with an offload probability. The offload probability is determined to minimize the average delay experienced by the cellular packets while guaranteeing stability of both cellular and WiFi system. We model the arrivals and fulfillments of data services of a cellular operator as an M/M/1 queue. We investigate two priority disciplines: First-In-First-Out (FIFO) and Non-Preemptive Priority Rule (NPPR). We provide an exact optimal offload probability for FIFO, but present an upper bound on the optimal probability for NPPR. Numerical investigation is used to verify the optimality of the proposed solutions, to examine the effect of packet arrival rate of MBS and compare the average delays for FIFO and NPPR.","PeriodicalId":217588,"journal":{"name":"2015 9th International Conference on Next Generation Mobile Applications, Services and Technologies","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127541969","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Iwailo Denisow, Sebastian Zickau, Felix Beierle, Axel Küpper
Attribute-based encryption (ABE) allows users to encrypt (cloud) data with fine-grained Boolean access control policies. To be able to decrypt the ciphertext, users need to have a private key with the associated attributes. If the attributes satisfy the formula, the plaintext can be recovered. In this paper, ABE is extended with dynamic attributes. This allows attributes to be added to an existing private key. A server component named Attribute Authority is introduced. By using these dynamic attributes, it is now possible to have the decryption depend on data that changes often, such as location information of a mobile device. Two schemes were developed that convert location data into usable ABE attributes. To demonstrate our results, an Android application was implemented and evaluated in a field test.
{"title":"Dynamic Location Information in Attribute-Based Encryption Schemes","authors":"Iwailo Denisow, Sebastian Zickau, Felix Beierle, Axel Küpper","doi":"10.1109/NGMAST.2015.63","DOIUrl":"https://doi.org/10.1109/NGMAST.2015.63","url":null,"abstract":"Attribute-based encryption (ABE) allows users to encrypt (cloud) data with fine-grained Boolean access control policies. To be able to decrypt the ciphertext, users need to have a private key with the associated attributes. If the attributes satisfy the formula, the plaintext can be recovered. In this paper, ABE is extended with dynamic attributes. This allows attributes to be added to an existing private key. A server component named Attribute Authority is introduced. By using these dynamic attributes, it is now possible to have the decryption depend on data that changes often, such as location information of a mobile device. Two schemes were developed that convert location data into usable ABE attributes. To demonstrate our results, an Android application was implemented and evaluated in a field test.","PeriodicalId":217588,"journal":{"name":"2015 9th International Conference on Next Generation Mobile Applications, Services and Technologies","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126845154","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, we propose a low-complexity quality of service (QoS)-oriented resource and power allocation framework. The aim of our scheme is to adjust the power expenditure of mobile stations (MSs) according to their QoS demands, which are imposed by the applications on the MS ranging from conversational and video-conference to telemetry and bulk data, for instance. Users are scheduled based on their QoS requirements and interference levels. Furthermore, we apply a power allocation method which is based on non-cooperative game theory, thus users are forced to transmit in a power regime allowing them to meet their specific QoS constraints. We develop a centralized signal-to-interference-plus-noise ratio (SINR) balancing scheme as well as a maximum power allocation mechanism to provide a performance bound. The results show that our framework allows the system to achieve important energy savings. Furthermore, it allows a higher percentage of users to meet their QoS requirements, when compared with a signal-to-interference-plus-noise ratio balancing scheme and a maximum transmission power method. Additionally, we show that our method only requires minimal channel knowledge to perform its optimization process.
{"title":"A QoS-oriented Power and Resource Allocation Framework for Wireless Networks","authors":"R. A. V. Ramírez, V. Ramos","doi":"10.1109/NGMAST.2015.54","DOIUrl":"https://doi.org/10.1109/NGMAST.2015.54","url":null,"abstract":"In this paper, we propose a low-complexity quality of service (QoS)-oriented resource and power allocation framework. The aim of our scheme is to adjust the power expenditure of mobile stations (MSs) according to their QoS demands, which are imposed by the applications on the MS ranging from conversational and video-conference to telemetry and bulk data, for instance. Users are scheduled based on their QoS requirements and interference levels. Furthermore, we apply a power allocation method which is based on non-cooperative game theory, thus users are forced to transmit in a power regime allowing them to meet their specific QoS constraints. We develop a centralized signal-to-interference-plus-noise ratio (SINR) balancing scheme as well as a maximum power allocation mechanism to provide a performance bound. The results show that our framework allows the system to achieve important energy savings. Furthermore, it allows a higher percentage of users to meet their QoS requirements, when compared with a signal-to-interference-plus-noise ratio balancing scheme and a maximum transmission power method. Additionally, we show that our method only requires minimal channel knowledge to perform its optimization process.","PeriodicalId":217588,"journal":{"name":"2015 9th International Conference on Next Generation Mobile Applications, Services and Technologies","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116053556","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In cognitive radio networks, unlicensed users are allowed to use underutilized licensed spectrum until licensed users' transmission quality of service is not compromised. As soon as the conflict goes beyond a certain limit, SU must leave the spectrum and move to the other nearby free band. At the time of interruption, sensing the nearby free channels and switching to them will take some time, hence the ongoing data will be interrupted, which will delay the data transmission. To minimize this delay, creating cache of the SU signal at multiple nodes in a cluster has shown significant improvement in reducing the transmission delay if cache placement is done systematically. This systematic and accurate placement of cache is possible if the data accumulated is accessed and processed quickly. Taking into account the vastness of cluster networks, a huge amount of data will be required to be accessed and processed. Cognitive Radio networks are very complex structures when it comes to the information sharing amongst the secondary users and with the cluster head. Taking into account, whether unlicensed users share their information with other secondary users, and in case if they do, how much proportion of it they allow the fusion center to process, several big data scenarios exist. This paper discusses the possible information sharing scenarios in cognitive radio network systems and their possible Big Data Solutions.
{"title":"Improving Data Extraction Efficiency of Cache Nodes in Cognitive Radio Networks Using Big Data Analysis","authors":"Ankur Omar","doi":"10.1109/NGMAST.2015.15","DOIUrl":"https://doi.org/10.1109/NGMAST.2015.15","url":null,"abstract":"In cognitive radio networks, unlicensed users are allowed to use underutilized licensed spectrum until licensed users' transmission quality of service is not compromised. As soon as the conflict goes beyond a certain limit, SU must leave the spectrum and move to the other nearby free band. At the time of interruption, sensing the nearby free channels and switching to them will take some time, hence the ongoing data will be interrupted, which will delay the data transmission. To minimize this delay, creating cache of the SU signal at multiple nodes in a cluster has shown significant improvement in reducing the transmission delay if cache placement is done systematically. This systematic and accurate placement of cache is possible if the data accumulated is accessed and processed quickly. Taking into account the vastness of cluster networks, a huge amount of data will be required to be accessed and processed. Cognitive Radio networks are very complex structures when it comes to the information sharing amongst the secondary users and with the cluster head. Taking into account, whether unlicensed users share their information with other secondary users, and in case if they do, how much proportion of it they allow the fusion center to process, several big data scenarios exist. This paper discusses the possible information sharing scenarios in cognitive radio network systems and their possible Big Data Solutions.","PeriodicalId":217588,"journal":{"name":"2015 9th International Conference on Next Generation Mobile Applications, Services and Technologies","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131433840","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Global positioning technologies such as the Global Positioning System (GPS) are ubiquitously available for different positioning applications. Within indoor environments, coverage of the explicit sensors based on GPS is limited. Developing an indoor location tracking system based on the Received Signal Strength Indicator (RSSI) of the Wireless Local Area Network (WLAN) is considered cost effective method. The widely used technique for estimating the position out of the RSSI measurements is the Extended Kalman Filter (EKF). However, EKF has high computational complexity due to the calculation of Jacobian matrices and suffers from filer instability. In this paper, we propose the Scaled Unscented Kalman Filter (SUKF), which is one of the Sigma Point Kalman Filters (SPKF) family, to overcome the limitations of the EKF. SUKF shall work over the WLAN IEEE 802.11n networks to exploit the RSSI range measurements for localizing and tracking of a mobile node. For performance evaluation, SUKF is compared with the EKF. Results are illustrated using Monte Carlo simulation in MATLAB.
{"title":"Scaled Unscented Kalman Filter for RSSI-based Indoor Positioning and Tracking","authors":"L. Khalil, P. Jung","doi":"10.1109/NGMAST.2015.20","DOIUrl":"https://doi.org/10.1109/NGMAST.2015.20","url":null,"abstract":"Global positioning technologies such as the Global Positioning System (GPS) are ubiquitously available for different positioning applications. Within indoor environments, coverage of the explicit sensors based on GPS is limited. Developing an indoor location tracking system based on the Received Signal Strength Indicator (RSSI) of the Wireless Local Area Network (WLAN) is considered cost effective method. The widely used technique for estimating the position out of the RSSI measurements is the Extended Kalman Filter (EKF). However, EKF has high computational complexity due to the calculation of Jacobian matrices and suffers from filer instability. In this paper, we propose the Scaled Unscented Kalman Filter (SUKF), which is one of the Sigma Point Kalman Filters (SPKF) family, to overcome the limitations of the EKF. SUKF shall work over the WLAN IEEE 802.11n networks to exploit the RSSI range measurements for localizing and tracking of a mobile node. For performance evaluation, SUKF is compared with the EKF. Results are illustrated using Monte Carlo simulation in MATLAB.","PeriodicalId":217588,"journal":{"name":"2015 9th International Conference on Next Generation Mobile Applications, Services and Technologies","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131511958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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