Yijun Mo

Indoor Localization Based on Curve Fitting and Location Search Using Received Signal Strength

Indoor localization based on received signal strength (RSS) has attracted considerable attention in both academia and industry due to the wide deployment of wireless local area networks. In this paper, we propose a novel indoor localization scheme based on curve fitting (CF) and location search. In the offline phase, we divide the whole environment into some subareas and create a fingerprint for each subarea. We then apply the CF technique to construct a fitted RSS-distance function for each transmitter in each subarea. The online positioning phase consists of two steps. In the first step, we determine a subarea to which a mobile device belongs. In the second step, we propose two location search algorithms, namely exhaustive search and gradient descent search, to find a location within the selected subarea such that the sum of distance errors can be minimized. We conduct field experiments to examine the proposed algorithms. The results show that our algorithms can obtain approximately 20% improvement in localization accuracy compared with the classical fingerprinting-based and lateration-based localization algorithms.

Indoor positioning via subarea fingerprinting and surface fitting with received signal strength

The fingerprinting technique based on received signal strength (RSS) has been intensively researched for indoor localization in the last decade. Instead of using discrete reference points to build fingerprint database, this paper applies the surface fitting technique to construct RSS spatial distribution functions and proposes two location search methods to find the target location. We also propose to use subarea division and determination scheme to improve the fitting accuracy and search efficiency. In the offline phase, we divide the whole indoor environment into several subareas, construct a fingerprint for each subarea, and build a RSS distribution fitting function for each access point in each subarea. In the online phase, we first determine to which subarea a target belongs, and then search its location according to the proposed exhaustive location search or gradient descent based search algorithm. We conduct both extensive simulations and field experiments to verify the proposed scheme. The experiment results show that for the same reference point granularity, the proposed localization scheme can achieve about 22 % localization accuracy improvement, compared with the classical nearest neighbor-based fingerprinting method.

Sensor scheduling for confident information coverage in wireless sensor networks

Many applications in wireless sensor networks have strict coverage accuracy requirements and need to operate as long as possible. In this paper, based on the new confident information coverage model proposed in our previous study (Wang et al., 2012), we design a novel sensor scheduling algorithm to prolong the network lifetime. This algorithm organizes the sensors into a maximal number of set covers, each capable of providing required coverage. The task of reconstructing the physical phenomena will be accomplished only by the sensors from one working set cover, while all the other sensors are in sleep mode. And we rotate the working set cover to prolong the network lifetime. Our simulation results show that the proposed algorithm outperforms two typical peer algorithms in terms of longer network lifetime.

Rechargeable router placement based on efficiency and fairness in green wireless mesh networks

The wireless mesh networks are currently emerging as a promising solution for broadband access, while their deployment and operational costs are also ever increasing significantly due to the continuous electrical power consumption. The alternative is to deploy rechargeable mesh routers using renewable energy sources. In this paper, we study the rechargeable router placement problem for a green mesh network. The problem is formulated as an optimization with the objective of minimizing the number of deployed routers, while fulfilling QoS requirements on wireless coverage, traffic demand, energy efficiency and user fairness. Specifically, we introduce the network failure rate to evaluate the network performance and adopt the proportional fairness-based approach to do the cell association between users and routers. We first propose two cell association algorithms from two perspectives: the Nearest Cell Association Algorithm (NCA) for energy efficiency consideration and the Proportional Fairness Cell Association Algorithm (PFCA) to achieve a balance between the network performance and the user fairness. We then design two heuristic placement algorithms embedded with the proposed cell association methods to find approximate solutions for the rechargeable router placement problem. Simulation results verify that the proposed PFCA algorithm can guarantee the user fairness with a slight increase of deployment cost. Furthermore, compared with the optimal placement achieved by exhaustive search, ours can achieve good performance with greatly reduced computation complexity.

Occurrence-Based Fingerprint Clustering for Fast Pattern-Matching Location Determination

Fingerprint clustering is an efficient approach to address the scalability problem of the pattern-matching localization system in large-scale environments. In this letter, we propose an occurrence-based fingerprint clustering algorithm that exploits the useful information embedded in the statistics of received signal strength measurements. Our algorithm allows that a reference point can have more than one fingerprint according to the highest received signal strength, and can be grouped into several clusters according to its highest and second highest received signal strengths. Simulation and experimental results show that our algorithm performs consistently a little better than the peer one without clustering in terms of improved localization accuracy and reduced fingerprint comparisons. Compared with two other clustering algorithms, our algorithm also achieves higher localization accuracy and reduces false cluster selection.

A Sink-Oriented Layered Clustering Protocol for Wireless Sensor Networks

Clustering is an effective technique to prolong network lifetime for energy-constrained wireless sensor networks. Due to the many-to-one traffic pattern in a multi-hop network, the nodes closer to the sink also help to relay data for those farther away from the sink, and hence they consume much more energy and tend to die faster. This paper proposes a sink-oriented layered clustering (SOLC) protocol to better balance energy consumption among nodes with different distances to the sink. In SOLC, the sensor field is divided into concentric rings, and the SOLC protocol consists of intra-ring clustering and inter-ring routing. We compute the optimal ring width and the numbers of cluster heads in different rings to balance energy consumption between intra-cluster data processing and inter-cluster data relaying. Cluster heads in a ring closer to the sink has smaller sizes than those in the rings farther away from the sink, and hence they can spend less energy for intra-cluster data processing and more energy for inter-cluster data relay. Simulation results show that the SOLC protocol can outperform several existing clustering protocols in terms of improved network lifetime.

Placement of Access Points for Indoor Wireless Coverage and Fingerprint-Based Localization

In the past, indoor wireless access systems had been designed mainly from the radio coverage perspective. Recently, fingerprint-based localization has also been proposed as another popular application for such access systems. However, few has been studied in the network design for both coverage and localization at the same time. This paper proposes a novel network design for guaranteeing radio coverage and maximizing fingerprint difference. The proposed scheme consists of two stages: The first stage finds the minimum number of access points and their locations to guarantee the desired coverage ratio by using an iterative search algorithm, The second stage uses the simulated annealing to further optimize the deployment so that the fingerprint difference can be maximized without compromising the coverage requirement. Our simulation results show that the proposed scheme can guarantee coverage requirement and provide higher localization accuracy.

Indoor multi-resolution subarea localization based on received signal strength fingerprint

Fingerprint-based localization technology has been intensively studied for point localization in indoor environments. Subarea localization, which is to localize a mobile target into some subarea, is also a practical issue in indoor localization. In this paper, we propose the concept of multi-resolution subarea localization based on received signal strength fingerprinting technique. Different levels of subarea fingerprints are first obtained by constructing coverage range-based fingerprints, and by received signal mean values or probability distribution based fingerprints. We also propose two subarea localization schemes that consists of a two-step localization. At first, the radio coverage range fingerprints are used for localization, and when this method fails, we perform a deterministic-based or probabilistic-based fingerprint comparison to finally locate a mobile target. The field testing results show that the hit rate of the proposed schemes can achieve 0.95 or better in room level.

Improving WLAN throughput via reactive jamming in the presence of hidden terminals

In the area of performance analysis of wireless networks, one critical issue is the hidden terminal problem, which is considered as one of the severest reasons for the degradation of network performance. In this paper, we incorporate reactive jamming scheme with distributed coordination function (DCF) in IEEE 802.11 based wireless local area networks (WLANs) to improve network throughput in the presence of hidden terminals. In the proposed protocol, we schedule access point (AP) to broadcast jamming signal reactively to hinder the simultaneous transmission of hidden terminals. Both analytical and numerical results show that our reactive jamming based protocol can constantly improve WLAN throughput for a wide range of conditions, compared with the traditional RTS/CTS.

Hybrid Placement of Internet Gateways and Rechargeable Routers with Guaranteed QoS for Green Wireless Mesh Networks

To solve the challenges of ever-increasing energy consumption, wireless mesh networks (WMNs) consisting of routers using renewable energy sources have been emerging as a promising solution. In this paper, we jointly consider the node placement and energy management in a hybrid WMN consisting of electricity-powered Internet gateways and solar-powered rechargeable routers. We introduce a new metric of failure rate to evaluate network performance and formulate the problem as a constrained optimization problem with the objective of minimizing both capital expenses on installation and operational expenses related to energy consumption. The network Quality of Service (QoS) requirements include meeting the failure rate requirement, the users’ dynamic traffic demand requirements in both downlink and uplink, the gateways’ and routers’ capacity constraints, the maximal transmission power constraints, and the rechargeable routers’ energy consumption constraints. Furthermore, we propose a minimum cost association algorithm to connect mesh clients to the Internet in different slots and a greedy placement algorithm to find approximate solutions for hybrid node placement. Simulation results show that the hybrid placement with rechargeable routers reveals its advantage for large scale networks in terms of more energy saving. Compared with the optimal placement achieved by the exhaustive search, our proposed algorithm can achieve good performance with the significantly reduced computation complexity.