Middleware for Positioning in Cellular Networks

Peer ReviewedPostprint (published version

Middleware-Controlled Resource consumption for Location Traffic in Cellular Networks

Location is valuable information for services implemented in wireless networks. Location systems often use the infrastructure of cellular networks that have already been deployed. Accordingly, location systems spend resources of the network they use. This paper proposes a middleware to reduce the consumption of network resources and optimize the location traffic that is being carried. This middleware, called MILCO (Middleware for Location Cost Optimization), selects the optimum location technique depending on the request, i.e. the location technique that satisfies the quality of service (QoS) required and minimizes the resource operating expense. In addition, MILCO takes advantage of ongoing and carried location processes to reduce the overall expenditure of resources. Our results show that MILCO can reduce location-process failures and improve latency figures for location provisioning and resource use in cellular networks such as UMTS

A New Time-Based Algorithm for Positioning Mobile Terminals in Wireless Networks

This paper presents a positioning algorithm, named time of arrival to time difference of arrival (TOAD), which computes time-difference-of-arrival (TDOA) measurements from the messages that time-of-arrival (TOA) stations in sight exchange while their positioning processes are running. This study addresses the accuracy of the TOAD algorithm in two different environments: line-of-sight (LOS) and non-line-of-sight (NLOS). Simulation is used to set up a wireless network. The Gauss-Newton nonlinear least squares algorithm is used to compute the positions in both TOA and TOAD stations. Results indicate that the TOAD algorithm increases the root mean square error (RMSE) of the positioning error in LOS scenarios by 10 to 20% compared with the RMSE achieved by TOA. This drop in accuracy contrasts with the results for the NLOS scenarios. The RMSE of TOAD in such scenarios is at least 10% lower than that achieved by TOA. This result is specially important since this latter scenario is the most common. Consequently, this novel technique therefore improves the scalability and integrity of TOA techniques based on RTT, making it possible for the stations to position themselves without injecting traffic and with QoS figures close and most times better than that achieved by TOA