Ajmani, Manisha

Boutaleb, Tuleen

Sinanovic, Sinan

English

Manisha Ajmani

Sinan Sinanovic

Tuleen Boutaleb

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Optimal beam radius for LED-based indoor positioning algorithm

Indoor positioning systems have the potential to replicate the success of outdoor positioning systems, but owing to the expensive and less accurate technology currently available for indoor positioning, they have not been able to take-off. LED-based Visible Light Communication (VLC) systems can solve this problem, but owing to complex algorithms and unoptimized parameter values the desired accuracy has not yet been achieved. This research addresses the problem of overlapping light radiation regions, which leads to lower accuracy in a VLC system, and proposes an algorithm to accurately determine the position of a device with respect to pre-positioned LEDs when it is receiving signal from multiple transmitting LEDs. To check the accuracy of this Optimal Beam Radius Indoor Positioning (OBRIP) algorithm numerous possible positions of a device uniformly distributed in a room with an indoor positioning system have been simulated to calculate the error in position estimation. Also, from the simulations, optimal values for beam radius, for a given number of LEDs in an array, separation between adjacent LEDs in an array for different room shapes has been calculated

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Optimal beam radius for LED-based indoor positioning algorithmAjmani, Manisha; Sinanovic, Sinan; Boutaleb, TuleenPublished in:2016 International Conference for Students on Applied Engineering (ICSAE) ProceedingsDOI:10.1109/ICSAE.2016.7810217Publication date:2017Document VersionPeer reviewed versionLink to publication in ResearchOnlineCitation for published version (Harvard):Ajmani, M, Sinanovic, S & Boutaleb, T 2017, Optimal beam radius for LED-based indoor positioning algorithm. inZYA Al-Shibaany & AF Hameed (eds), 2016 International Conference for Students on Applied Engineering(ICSAE) Proceedings. 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Apr. 2020Optimal beam radius for LED-based indoorpositioning algorithmManisha Ajmani*, Sinan Sinanovic´* and Tuleen Boutaleb**School of Engineering and Built Environment, Glasgow Caledonian University, Glasgow, G4 0BA,UKEmail: (manisha.ajmani, sinan.sinanovic, t.boutaleb)@gcu.ac.ukAbstract—Indoor positioning systems have the potential toreplicate the success of outdoor positioning systems, but owingto the expensive and less accurate technology currently availablefor indoor positioning, they have not been able to take-off. LED-based Visible Light Communication (VLC) systems can solvethis problem, but owing to complex algorithms and unoptimizedparameter values the desired accuracy has not yet been achieved.This research addresses the problem of overlapping light radia-tion regions, which leads to lower accuracy in a VLC system, andproposes an algorithm to accurately determine the position of adevice with respect to pre-positioned LEDs when it is receivingsignal from multiple transmitting LEDs. To check the accuracy ofthis Optimal Beam Radius Indoor Positioning (OBRIP) algorithmnumerous possible positions of a device uniformly distributed ina room with an indoor positioning system have been simulatedto calculate the error in position estimation. Also, from thesimulations, optimal values for beam radius, for a given numberof LEDs in an array, separation between adjacent LEDs in anarray for different room shapes has been calculated.Keywords—Visible light communication (VLC); Indoor posi-tioning system (IPS); Light-emitting diode (LED); Infrared (IR);Electromagnetic (EM)I. INTRODUCTIONOutdoor tracking and positioning systems have evolved ex-tensively in the past decade in terms of accuracy and efficiency[1]. GPS has taken the world of outdoor positioning [2] andtracking by storm leading to huge success of applicationslike Google Maps and Apple Maps. Research in the fieldof Indoor tracking and positioning has been going on toproduce the similar results. The existing indoor positioningsystems (IPS) are based on microwave technology or opticaltracking and imaging [3]. Indoor positioning system basedon microwave technology include Bluetooth, ultra-wide band(UWB) or wireless local area network [4] integrated into thesystems. Many IPS devices have been designed using thesetechnologies, but till now there is no clear winner. Some majorchallenges for the design of an Indoor positioning solution are:1. Additional infrastructure is required leading to inflatedcosts, i.e. expensive implementation and installation (IR, Ul-trasound, RFID etc.) [5], [6]2. RF based solutions are not safe for environments likehospitals, airplanes etc. as it may cause, and suffer, fromElectromagnetic (EM) interference [6], [7].3. Indoor positioning requires very high accuracy, whichexisting technologies like GPS fail to provide [6], [7].Optical tracking and imaging methods provide good accuracyup to few millimeters [3], but it involves high cost and complexusage of image processing. Visible Light Communication(VLC) using LEDs has emerged as a new solution for indoorpositioning systems [8]. VLC is a unique method of high-speed data transfer which can operate both as a lightingsource and a communication tool, addressing the problem ofadditional infrastructure. It is based on the wireless opticalcommunication principle in which the data to be transmittedis modulated according to the visible light emitted by theLED [9]. LEDs offer several advantages including a higherbandwidth, high brightness efficiency and longer life [10], [11]in comparison to traditional light sources, and the VLC systemas a whole offers many attractive features such as high accu-racy, high bandwidth capacity, robustness to EM interference,excellent security and low cost deployment [12], [13]. VLCtechnology is also suitable for various other applications likenavigation and broadcasting wireless communication [14].Though VLC can lead to highly accurate position estimation,the existing positioning algorithms have not been able to tapinto the potential of this technology in a practical and lowcomplexity manner. These algorithms have proven to be rea-sonably successful at reducing the error in position estimationand also are relatively inexpensive [15], but they still sufferfrom the problem of packet loss due to interference created byoverlapping light beam regions. In this research this problemof overlapping light beams is used to the system’s advantageand a simple and practical positioning algorithm is proposedwhich helps reduce the anomaly in position estimation toenhance the system accuracy. These low-cost, reliable andhighly accurate alternatives to existing indoor position systemscould be utilized in the medical sector for monitoring patients,or in large commercial stores to monitor location of staff.II. OPTIMAL BEAM RADIUS INDOOR POSITIONING (OBRIP)The proposed algorithm employs an array of LEDs installedin a room at fixed locations. These LEDs constantly transmittheir location coordinates in the form of optical signals withinthe room. When a device (or receiver) enters the room, itdetects one or more signals from light beams of differentLEDs. If the signal it receives is only from one LED, thecoordinates of the LED are assigned the device’s referencepoint. If the device receives multiple signals, i.e. if it is in theoverlapping region of two or more LEDs, it finds the centroidof the received coordinates and stores it as the reference point.Thus, the overlap region is used as an advantage to increasethe accuracy in position estimation because more overlappingregion means more reference points. This algorithm has beensimulated in MATLAB to analyze its performance. Variousrandom positions of an object in a room with an indoor posi-tioning system are considered and correspondingly the error inposition estimation is averaged. Also, various parameters likeradius of the beam and number of LEDs in an array have beenvaried and the output is analyzed in order to obtain optimizedvalues for these parameters. Radius vs. Average Error plotfor different radii, Radius vs. Average Error plot for varyingnumber of LEDs have been plotted, and based on these graphsoptimized parameter values are determined.III. SIMULATION SETUP AND RESULTSIn this paper, simulation based procedure is followed tostudy the performance of the LED-based indoor positioningsystem.Fig. 1: Simulation of a room with indoor positioning systemIn this algorithm, a fixed size of room (10*10 sq. units) isassumed, which contains nine pre-positioned LEDs. The beamarea of light radiation of an LED in the array is assumed to bein the form of a circle. This area overlaps for various LEDs inthe array and the beam radius of the LEDs is varied to changethe area of this overlapping region. Based on the positionedLEDs and overlapping region various reference points aregenerated and stored (Fig. 1). These reference points are thepositions of the LEDs and the midpoint of the overlappingregions. The midpoints of overlapping region are calculatedby finding the average of the LEDs positions whose beamarea leads to this overlapping region.To simulate the position of an object in a room 25000uniformly distributed random points are generated withinthe room which can be inside the overlapping region, non-coverage region or within beam area of one LED. This largenumber of random points would cover the entire area of theroom. In the first scenario, when the device will receive signalfrom only one LED, it will be assigned the reference pointas position of that LED. In the second scenario, when itwill receive signal from multiple LEDs, it will be assigned areference point as the mean of all LEDs positions it is gettinga signal from. In the third scenario, when it receives no signalit will be assigned center of the room as its reference point.The same scenarios have been implemented in this simulation.To check the accuracy of this model the difference betweenthe actual position (coordinates of the random point) and itscorresponding reference point was calculated. The averageerror is calculated for the 25000 simulated random points.The same scenario is repeated for a range of values of thebeam radius to find its optimal value. After beam radiusoptimization, number of LEDs in the array and separationbetween LEDs in array are varied for different room shapesto find out optimal values.The following equation is used to calculate the error in positionestimation, by finding the distance between the actual and thereference (or allocated) position.d =√(x1 − x2)2 + (y1 − y2)2 (1)Avg = S/N (2)where d is distance between the assigned reference positionand actual position,(x1, y1) is the reference position and,(x2, y2) is the actual position,Avg is the average error,S is the sum of the distances between each random point andits reference point,N is the number of total random point generated.In our case N = 25000Fig. 2: Beam Radius vs. Average Error in position estimationA. Variation of beam radiusBeam radius is the maximum extent up to which a singleLED can transmit with the required intensity which the deviceTABLE I. Average error v/s Radius for different No. of LEDSNo. of LEDS Optimal Radius Average Error9 2.75 1.008 2.75 1.197 2.75 1.356 2.75 1.785 2.75 2.04can detect. The radius is varied from 0.5 to 8 units at an inter-val of 0.25 for parameter optimization. From the simulations,it is observed that the average error varies significantly withthe radius (Fig. 2). We were also able to determine optimumbeam radius for each LED from the plot between average errorand radius of signal transmission (Fig. 2). We note that theerror varies asymmetrically around the optimum point witherror increasing significantly for smaller radii and only slightlyfor larger than optimal radius. The optimum radius result canbe equivalently represented as a ratio between the light beamcoverage area and the area of the room which corresponds to0.2 in a considered scenario. Average error is minimum i.e.1.001 when the radius of beam is 2.5Fig. 3: Beam Radius vs. Average Error in position estimationfor different number of LEDsB. Variation of number of LEDsThe effect of number of LEDs in an array is observed whennumber of LEDs are varied from 5 to 9. Initially 9 LEDs areplaced in a way that the distance between adjacent LEDs issame, and then LEDs are removed in such a way that theirdistance from their adjacent LEDs are 3 units horizontally andvertically and 3√2 units diagonally. For each LED count, 5 to9, the beam radius of each LED is also varied from 0.25 unitsto 8 units. From the graph (Fig. 3) and TABLE I, it is observedthat average error increases as the number of LEDs decreasesfor each value of beam radius. The best value for number ofLEDs is found to be 9, which is expected for this case. Asthe number of LEDs increases, the number of reference pointswill increase because the number of overlapping region willbe more. This would lead to further decrease in average errorin position estimation.Fig. 4: Beam Radius vs. Average Error in position estimationfor different room shapeTABLE II. Average error v/s Radius for different Room ShapesRoom shape Optimal Radius Average ErrorSquare 2.75 1.00Hexagon 2.75 1.02Circle 2.75 1.05Rectangle 2.75 1.23Pentagon 3.5 1.66C. Variation of room shapeFor the following room shapes: square (10 units x 10 units),rectangle (11.1 units x 9 units), circle (radius = 5.64 units),hexagon (radius = 6.21 units) and pentagon (radius = 7.6 units)the algorithm was implemented while keeping the room areaconstant (100 sq. units). The number of LEDs in the array iskept at 9 and the position of the array is such that the positionof the middle LED coincides with the geometric center ofthe shape. It is observed that for each room shape averageerror in position estimation varies along with the beam radius.From the graph (Fig. 4) and TABLE II, it can be seen that theminimum average error occurs when the shape of the room issquare followed by hexagon, circle, rectangle and pentagon.This is the order of effectiveness of the algorithm for differentroom shapes. It can be seen that regular room shapes likecircle, square and hexagon have almost identical low averageerror, whereas pentagon and rectangle, which are irregularshapes have a higher average error.D. Variation of the LEDs grid sizeSeparation between adjacent LEDs is also an importantparameter to be optimized. In this simulation we vary theseparation from 1.5 units to 5.5 units for different room shapes,keeping the position of the center LED fixed i.e. (3,0) (Fig. 5)and observe the change in average error in position estimation.From the graphs (Fig. 6, 8, 10, 12), we can observe that asseparation is increased, average error decreases for each roomshape.From the observations (Fig. 7, 9, 11, 13), when theseparation between adjacent LEDs in the array is increasedfrom 3.5 units to 5.5 units, it can be concluded that theminimum average error obtained is almost same for eachseparation distance, but for different values of beam radius.Fig. 5: Simulation of a room for different grid sizeFig. 6: Average error vs. radius for different grid size (Circle)Fig. 7: Average error vs. Radius, Separation (Circle)IV. CONCLUSIONThe algorithm explained above provides solution to theproblem of overlapping light radiation regions and uses it asan advantage to increase accuracy in position estimation. FromFig. 8: Average error vs. radius for different grid size(Hexagon)Fig. 9: Average error vs. Radius, Separation (Hexagon)Fig. 10: Average error vs. radius for different grid size(Pentagon)Fig. 11: Average error vs. Radius, Separation (Pentagon)Fig. 12: Average error vs. radius for different grid size (Square)Fig. 13: Average error vs. Radius, Separation (Square)the simulation experiment we studied scenario with differentvalues for number of LEDs, separation between LEDs andradius of LED beam for various room shapes. These bestvalues are obtained for a fixed room size. Thus, their ratiowith the room size can be used as a constant parameter whendeciding on values for different room sizes. High accuracy isachieved using this algorithm in the simulations and the samecan be tested in practical experiments. To increase the accuracyof this algorithm multiple receivers, instead of one, can beused on one device. This way each receiver would have itsown reference point which might further improve the accuracyof this algorithm. Using this algorithm as a foundation, acheap and accurate alternative to indoor navigation can alsobe implemented.ACKNOWLEDGMENTThe authors would like to thank Glasgow CaledonianUniversity for funding the research, without their help thisresearch would not have been possible. We would also take thisopportunity to thank the staff of the School of Engineering andBuilt Environment at Glasgow Caledonian University for beingvery cooperative and providing excellent research environmentand equipment. We would also like to thank the GraduateSchool department for conducting ‘Research Workshop’ whichwas extremely helpful in writing this research paper. Theauthors would like to dedicate this research to the peopleaffected by dementia, for whom this research was initiated,and hopefully we would be able to make a difference in theirlives with our research.REFERENCES[1] D. Dardari, P. 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Optimal beam radius for LED-based indoor positioning algorithm

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