Federated UKF algorithm for mobile location estimation with TDOA/Doppler measurements

In order to enhance the location estimation performance of mobile station（MS）tracking and positioning, a new method of mobile location optimal estimation based on the federated filtering structure and the simplified unscented Kalman filter （UKF） is presented. The proposed algorithm uses the Singer mobile statement model as the reference system, and the simplified UKF as the subfilters. The subfilters receive the two groups of independently detected time difference of arrival （TDOA） measurement inputs and Doppler measurement inputs, and produce local estimation outputs to the main estimator. Then the main estimator performs the optimal fusion of the local estimation outputs according to the scalar weighted rule, and a global optimal or suboptimal estimation result is achieved. Finally the main estimator gives feedback and reset information to the subfilters and the reference system for next step estimation. In the simulations, the estimation performance of the proposed algorithm is evaluated and compared with the simplified UKF method with TDOA or Doppler measurement alone. The simulation results demonstrate that the proposed algorithm can effectively reduce the location estimation error and variance of the MS, and has favorable performance in both root mean square error（RMSE） and mean error cumulative distribution function（CDF）.

SUPPORTING SALESPERSONS’ CRM EFFORTS THROUGH LOCATION-BASED MOBILE SUPPORT SYSTEMS

This paper aims at assessing how location-based mobile support systems can support salespersons′ CRM efforts when they are operating within a highly mobile work environment. After briefly discussing the state-of-the-art issues associated with mobile location technologies, the paper conceptualizes key dimensions for location-based mobile support systems. The paper then discusses the dual role of salespersons in CRM. A fourth section suggests a categorization of salespersons′ CRM tasks based on both properties of location-based mobile support and the areas of salespersons’ CRM-related tasks that may be affected by mobile location technologies. Finally, the paper suggests potential mobile location services and applications that can help salespersons perform effectively their everyday CRM tasks and link such applications to the determinant of salespersons′ performance. The paper concludes with a discussion of some critical issues and suggests areas for further research.

AN ADVANCED DYNAMIC FEEDBACK AND RANDOM DISPATCHING LOAD-BALANCING ALGORITHM FOR GMLC IN 3G

Based on the system architecture and software structure of GMLC (Gateway Mobile Location Center) in 3G (third generation), a new dynamic load-balancing algorithm is proposed. It bases on dynamic feedback and imports the increment for admitting new request into the load forecast. It dynamically adjusts the dispatching probability according to the remainder process capability of each node. Experiments on the per- formance of algorithm have been carried out in GMLC and the algorithm is compared with Pick-KX algorithm and DFB (Dynamic FeedBack) algorithm in average throughput and average response time. Experiments re- sults show that the average throughput of the proposed algorithm is about five percents higher than that of the other two algorithms and the average response time is four percents higher under high system loading condi- tion.

A Service Discovery Approach Based on a Quantitative Similarity Measure for M-Tourism Platforms

This paper presents a localization architecture for an m-tourism services delivery platform. The aim of the system is to deliver services for nomads (e-tourists) according to their localization and according to the results given by the search engine. This engine is based on a quantitative similarity measure. The discovered services are presented via a Web Map Service. Moreover, the platform integrates an adaptation sub-system for heterogeneous environments and an e-negotiation module.

A TDOA location algorithm based on data fusion

A new positioning method in mobile networks is presented.Based on the data fusion technology,it processes multi-layer information fusion for the location estimates achieved by the Chan algorithm,which increases mobile positioning accuracy effectively by only using measured difference of arriving(TDOA)signals.The method is simple and practical,especially when the location estimates are corrupted by the non-line-of-sight(NLOS)error.It not only has high positioning accuracy,but also reduces the location failure probability.Results from computer simulation show that the proposed method is effective in various environments.

Architecture for mobile group communication in campus environment

The demand for group communication using smart devices in campus environment is increasing rapidly. In this paper, we design an architecture for a mobile group communication system （MGCS） on campus by using Wi-Fi networks and smart devices. The architecture is composed of a web-based system and a smart device based mobile system. Through the systems, users on campus create community/mobile group, maintain dynamic group membership, and reliably deliver the message to other users. We use the common features of many smart devices to develop a prototype that works on off-the-shelf hardware. In the experimental section, we demonstrate our system using various real scenarios which can occur in university campuses.