Abstract: The Internet of Things (IoT) is developed to ensure monitoring and connectivity within different applications. Thus, it is critical to study the channel propagation characteristics in Low Power Wide Area Network (LPWAN), especially LoRaWAN. In this paper, an in-depth investigation of the reciprocity between the uplink and downlink Channel State Information (CSI) is done by performing an outdoor measurement campaign in the area of Campus Beaulieu in Rennes. At each different location, the CSI reciprocity is quantified using the Pearson Correlation Coefficient (PCC) which shows a very high linear correlation between the uplink and downlink CSI. This reciprocity feature could be utilized for the physical layer security between the node and the gateway. On the other hand, most of the CSI shapes from different locations are highly uncorrelated with each other. Hence, it can be anticipated that this could achieve significant localization gain by utilizing the frequency hopping in the LoRa systems to get access to a wider band.
Abstract: This paper explores a detailed procedure of predicting a path loss (PL) model and its application in estimating the coverage probability in a WiMAX network. For this a hybrid approach is followed in predicting an empirical PL model of a 2.65 GHz WiMAX network deployed in a suburban environment. Data collection, statistical analysis, and regression analysis are the phases of operations incorporated in this approach and the importance of each of these phases has been discussed properly. The procedure of collecting data such as received signal strength indicator (RSSI) through experimental set up is demonstrated. From the collected data set, empirical PL and RSSI models are predicted with regression technique. Furthermore, with the aid of the predicted PL model, essential parameters such as PL exponent as well as the coverage probability of the network are evaluated. This research work may assist in the process of deployment and optimisation of any cellular network significantly.
Abstract: The instantaneous and spatial localization for visually impaired people in dynamically changing environments with unexpected hazards and obstacles, is the most demanding and challenging issue faced by the navigation systems today. Since Bluetooth cannot utilize techniques like Time Difference of Arrival (TDOA) and Time of Arrival (TOA), it uses received signal strength indicator (RSSI) to measure Receive Signal Strength (RSS). The measurements using RSSI can be improved significantly by improving the existing methodologies related to RSSI. Therefore, the current paper focuses on proposing an improved method using trilateration for localization of Bluetooth devices for visually impaired people. To validate the method, class 2 Bluetooth devices were used along with the development of a software. Experiments were then conducted to obtain surface plots that showed the signal interferences and other environmental effects. Finally, the results obtained show the surface plots for all Bluetooth modules used along with the strong and weak points depicted as per the color codes in red, yellow and blue. It was concluded that the suggested improved method of measuring RSS using trilateration helped to not only measure signal strength affectively but also highlighted how the signal strength can be influenced by atmospheric conditions such as noise, reflections, etc.
Abstract: Link adaptation is an important strategy for achieving robust wireless multimedia communications based on quality of service (QoS) demand. Scheme switching in multiple-input multiple-output (MIMO) systems is an aspect of link adaptation, and it involves selecting among different MIMO transmission schemes or modes so as to adapt to the varying radio channel conditions for the purpose of achieving QoS delivery. However, finding the most appropriate switching method in MIMO links is still a challenge as existing methods are either computationally complex or not always accurate. This paper presents an intelligent switching method for the MIMO system consisting of two schemes - transmit diversity (TD) and spatial multiplexing (SM) - using fuzzy logic technique. In this method, two channel quality indicators (CQI) namely average received signal-to-noise ratio (RSNR) and received signal strength indicator (RSSI) are measured and are passed as inputs to the fuzzy logic system which then gives a decision – an inference. The switching decision of the fuzzy logic system is fed back to the transmitter to switch between the TD and SM schemes. Simulation results show that the proposed fuzzy logic – based switching technique outperforms conventional static switching technique in terms of bit error rate and spectral efficiency.
Abstract: Conceiving and developing routing protocols for
wireless sensor networks requires considerations on constraints such
as network lifetime and energy consumption. In this paper, we propose
a hybrid hierarchical routing protocol named HHRP combining both
clustering mechanism and multipath optimization taking into account
residual energy and RSSI measures. HHRP consists of classifying
dynamically nodes into clusters where coordinators nodes with extra
privileges are able to manipulate messages, aggregate data and ensure
transmission between nodes according to TDMA and CDMA
schedules. The reconfiguration of the network is carried out
dynamically based on a threshold value which is associated with the
number of nodes belonging to the smallest cluster. To show the
effectiveness of the proposed approach HHRP, a comparative study
with LEACH protocol is illustrated in simulations.
Abstract: With the increasing use and application of Wireless Sensor Networks (WSN), need has arisen to explore them in more effective and efficient manner. An important area which can bring efficiency to WSNs is the localization process, which refers to the estimation of the position of wireless sensor nodes in an ad hoc network setting, in reference to a coordinate system that may be internal or external to the network. In this paper, we have done comparison and analysed Sigmoidal Feedforward Artificial Neural Networks (SFFANNs) and Radial Basis Function (RBF) networks for developing localization framework in WSNs. The presented work utilizes the Received Signal Strength Indicator (RSSI), measured by static node on 100 x 100 m2 grid from three anchor nodes. The comprehensive evaluation of these approaches is done using MATLAB software. The simulation results effectively demonstrate that FFANNs based sensor motes will show better localization accuracy as compared to RBF.
Abstract: Many cluster based routing protocols have been
proposed in the field of wireless sensor networks, in which a group of
nodes are formed as clusters. A cluster head is selected from one
among those nodes based on residual energy, coverage area, number
of hops and that cluster-head will perform data gathering from
various sensor nodes and forwards aggregated data to the base station
or to a relay node (another cluster-head), which will forward the
packet along with its own data packet to the base station. Here a
Game Theory based Diligent Energy Utilization Algorithm (GTDEA)
for routing is proposed. In GTDEA, the cluster head selection is done
with the help of game theory, a decision making process, that selects
a cluster-head based on three parameters such as residual energy
(RE), Received Signal Strength Index (RSSI) and Packet Reception
Rate (PRR). Finding a feasible path to the destination with minimum
utilization of available energy improves the network lifetime and is
achieved by the proposed approach. In GTDEA, the packets are
forwarded to the base station using inter-cluster routing technique,
which will further forward it to the base station. Simulation results
reveal that GTDEA improves the network performance in terms of
throughput, lifetime, and power consumption.
Abstract: The localization information is crucial for the
operation of WSN. There are principally two types of localization
algorithms. The Range-based localization algorithm has strict
requirements on hardware, thus is expensive to be implemented in
practice. The Range-free localization algorithm reduces the hardware
cost. However, it can only achieve high accuracy in ideal scenarios.
In this paper, we locate unknown nodes by incorporating the
advantages of these two types of methods. The proposed algorithm
makes the unknown nodes select the nearest anchor using the
Received Signal Strength Indicator (RSSI) and choose two other
anchors which are the most accurate to achieve the estimated
location. Our algorithm improves the localization accuracy compared
with previous algorithms, which has been demonstrated by the
simulating results.
Abstract: Lately, with the increasing number of location-based applications, demand for highly accurate and reliable indoor localization became urgent. This is a challenging problem, due to the measurement variance which is the consequence of various factors like obstacles, equipment properties and environmental changes in complex nature of indoor environments. In this paper we propose low-cost custom-setup infrastructure solution and localization algorithm based on the Weighted Centroid Localization (WCL) method. Localization accuracy is increased by several enhancements: calibration of RSSI values gained from wireless nodes, repetitive measurements of RSSI to exclude deviating values from the position estimation, and by considering orientation of the device according to the wireless nodes. We conducted several experiments to evaluate the proposed algorithm. High accuracy of ~1m was achieved.
Abstract: WiFi has become an essential technology that is widely used nowadays. It is famous due to its convenience to be used with mobile devices. This is especially true for Internet users worldwide that use WiFi connections. There are many location based services that are available nowadays which uses Wireless Fidelity (WiFi) signal fingerprinting. A common example that is gaining popularity in this era would be Foursquare. In this work, the WiFi signal would be used to estimate the user or client’s location. Similar to GPS, fingerprinting method needs a floor plan to increase the accuracy of location estimation. Still, the factor of inconsistent WiFi signal makes the estimation defer at different time intervals. Given so, an adaptive method is needed to obtain the most accurate signal at all times. WiFi signals are heavily distorted by external factors such as physical objects, radio frequency interference, electrical interference, and environmental factors to name a few. Due to these factors, this work uses a method of reducing the signal noise and estimation using the Nearest Neighbour based on past activities of the signal to increase the signal accuracy up to more than 80%. The repository yet increases the accuracy by using Artificial Neural Network (ANN) pattern matching. The repository acts as the server cum support of the client side application decision. Numerous previous works has adapted the methods of collecting signal strengths in the repository over the years, but mostly were just static. In this work, proposed solutions on how the adaptive method is done to match the signal received to the data in the repository are highlighted. With the said approach, location estimation can be done more accurately. Adaptive update allows the latest location fingerprint to be stored in the repository. Furthermore, any redundant location fingerprints are removed and only the updated version of the fingerprint is stored in the repository. How the location estimation of the user can be predicted would be highlighted more in the proposed solution section. After some studies on previous works, it is found that the Artificial Neural Network is the most feasible method to deploy in updating the repository and making it adaptive. The Artificial Neural Network functions are to do the pattern matching of the WiFi signal to the existing data available in the repository.
Abstract: RFID system is used to identify objects such as passenger identification in public transportation, instead of linear or 2-dimensional barcodes. Key advantages of RFID system are to identify objects without physical contact, and to write arbitrary information into RFID tag. These advantages may help to improve maritime safety and efficiency of activity on the sea. However, utilization of RFID system for maritime scenes has not been considered. In this paper, we evaluate the availability of a generic RFID system operating on the sea. We measure RSSI between RFID tag floating on the sea and RFID antenna, and check whether a RFID reader can access a tag or not, while the distance between a floating buoy and the ship, and the angle are changed. Finally, we discuss the feasibility and the applicability of RFID system on the sea through the results of our preliminary experiment.
Abstract: In this work we present a solution for DAGC (Digital
Automatic Gain Control) in WLAN receivers compatible to IEEE 802.11a/g standard. Those standards define communication in 5/2.4
GHz band using Orthogonal Frequency Division Multiplexing OFDM modulation scheme. WLAN Transceiver that we have used
enables gain control over Low Noise Amplifier (LNA) and a
Variable Gain Amplifier (VGA). The control over those signals is
performed in our digital baseband processor using dedicated hardware block DAGC. DAGC in this process is used to automatically control the VGA and LNA in order to achieve better
signal-to-noise ratio, decrease FER (Frame Error Rate) and hold the
average power of the baseband signal close to the desired set point.
DAGC function in baseband processor is done in few steps: measuring power levels of baseband samples of an RF signal,accumulating the differences between the measured power level and
actual gain setting, adjusting a gain factor of the accumulation, and
applying the adjusted gain factor the baseband values. Based on the measurement results of RSSI signal dependence to input power we have concluded that this digital AGC can be implemented applying
the simple linearization of the RSSI. This solution is very simple but also effective and reduces complexity and power consumption of the
DAGC. This DAGC is implemented and tested both in FPGA and in ASIC as a part of our WLAN baseband processor. Finally, we have integrated this circuit in a compact WLAN PCMCIA board based on MAC and baseband ASIC chips designed from us.
Abstract: Using Internet communication, new home electronics
have functions of monitoring and control from remote. However in
many case these electronics work as standalone, and old electronics
are not followed. Then, we developed the total remote system include
not only new electronics but olds. This systems node is a adapter of
electrical power plug that embed relay switch and some sensors, and
these nodes communicate with each other. the system server was build
on the Internet, and users access to this system from web browsers.
To reduce the cost to set up of this system, communication between
adapters are used ZigBee wireless network instead of wired LAN
cable[3]. From measured RSSI(received signal strength indicator)
information between each nodes, the system can estimate roughly
adapters were mounted on which room, and where in the room. So
also it reduces the cost of mapping nodes. Using this system, energy
saving and house monitoring are expected.
Abstract: These days wireless local area networks has become
very popular, when the initial IEEE802.11 is the standard for
providing wireless connectivity to automatic machinery, equipment
and stations that require rapid deployment, which may be portable,
handheld or which may be mounted on moving vehicles within a
local area. IEEE802.11 Wireless local area network is a sharedmedium
communication network that transmits information over
wireless links for all IEEE802.11 stations in its transmission range to
receive. When a user is moving from one location to another, how
the other user knows about the required station inside WLAN. For
that we designed and implemented a system to locate a mobile user
inside the wireless local area network based on RSSI with the help of
four specially designed architectures. These architectures are based
on statistical or we can say manual configuration of mapping and
radio map of indoor and outdoor location with the help of available
Sniffer based and cluster based techniques. We found a better
location of a mobile user in WLAN. We tested this work in indoor
and outdoor environments with different locations with the help of
Pamvotis, a simulator for WLAN.
Abstract: This paper presents a studyof the impact of reference
node locations on the accuracy of the indoor positioning systems. In
particular, we analyze the localization accuracy of the RSSI database
mapping techniques, deploying on the IEEE 802.15.4 wireless
networks. The results show that the locations of the reference nodes
used in the positioning systems affect the signal propagation
characteristics in the service area. Thisin turn affects the accuracy of the wireless indoor positioning system. We found that suitable
location of reference nodes could reduce the positioning error upto 35 %.
Abstract: This report aims to utilize existing and future Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing Wireless Local Area Network (MIMO-OFDM WLAN) systems characteristics–such as multiple subcarriers, multiple antennas, and channel estimation characteristics–for indoor location estimation systems based on the Direction of Arrival (DOA) and Radio Signal Strength Indication (RSSI) methods. Hybrid of DOA-RSSI methods also evaluated. In the experimental data result, we show that location estimation accuracy performances can be increased by minimizing the multipath fading effect. This is done using multiple subcarrier frequencies over wideband frequencies to estimate one location. The proposed methods are analyzed in both a wide indoor environment and a typical room-sized office. In the experiments, WLAN terminal locations are estimated by measuring multiple subcarriers from arrays of three dipole antennas of access points (AP). This research demonstrates highly accurate, robust and hardware-free add-on software for indoor location estimations based on a MIMO-OFDM WLAN system.
Abstract: The adaptive power control of Code Division Multiple
Access (CDMA) communications using Remote Radio Head
(RRH) between multiple Unmanned Aerial Vehicles (UAVs) with
a link-budget based Signal-to-Interference Ratio (SIR) estimate is
applied to four inner loop power control algorithms. It is concluded
that Base Station (BS) can calculate not only UAV distance using
linearity between speed and Consecutive Transmit-Power-Control
Ratio (CTR) of Adaptive Step-size Closed Loop Power Control (ASCLPC),
Consecutive TPC Ratio Step-size Closed Loop Power Control
(CS-CLPC), Fixed Step-size Power Control (FSPC), but also UAV
position with Received Signal Strength Indicator (RSSI) ratio of
RRHs.
Abstract: Radio frequency identification (RFID) applications have grown rapidly in many industries, especially in indoor location identification. The advantage of using received signal strength indicator (RSSI) values as an indoor location measurement method is a cost-effective approach without installing extra hardware. Because the accuracy of many positioning schemes using RSSI values is limited by interference factors and the environment, thus it is challenging to use RFID location techniques based on integrating positioning algorithm design. This study proposes the location estimation approach and analyzes a scheme relying on RSSI values to minimize location errors. In addition, this paper examines different factors that affect location accuracy by integrating the backpropagation neural network (BPN) with the LANDMARC algorithm in a training phase and an online phase. First, the training phase computes coordinates obtained from the LANDMARC algorithm, which uses RSSI values and the real coordinates of reference tags as training data for constructing an appropriate BPN architecture and training length. Second, in the online phase, the LANDMARC algorithm calculates the coordinates of tracking tags, which are then used as BPN inputs to obtain location estimates. The results show that the proposed scheme can estimate locations more accurately compared to LANDMARC without extra devices.
Abstract: Wireless LAN (WLAN) access in public hotspot areas
becomes popular in the recent years. Since more and more multimedia
information is available in the Internet, there is an increasing demand
for accessing multimedia information through WLAN hotspots.
Currently, the bandwidth offered by an IEEE 802.11 WLAN cannot
afford many simultaneous real-time video accesses. A possible way to
increase the offered bandwidth in a hotspot is the use of multiple access
points (APs). However, a mobile station is usually connected to the
WLAN AP with the strongest received signal strength indicator (RSSI).
The total consumed bandwidth cannot be fairly allocated among those
APs. In this paper, we will propose an effective load-balancing scheme
via the support of the IAPP and SNMP in APs. The proposed scheme is
an open solution and doesn-t need any changes in both wireless stations
and APs. This makes load balancing possible in WLAN hotspots,
where a variety of heterogeneous mobile devices are employed.