Beamforming Design for Joint Localization and Data Transmission in Distributed Antenna System

A distributed antenna system is studied whose goal is to provide data communication and positioning functionalities to Mobile Stations (MSs). Each MS receives data from a number of Base Stations (BSs), and uses the received signal not only to extract the information but also to determine its location. This is done based on Time of Arrival (TOA) or Time Difference of Arrival (TDOA) measurements, depending on the assumed synchronization conditions. The problem of minimizing the overall power expenditure of the BSs under data throughput and localization accuracy requirements is formulated with respect to the beamforming vectors used at the BSs. The analysis covers both frequency-flat and frequency-selective channels, and accounts also for robustness constraints in the presence of parameter uncertainty. The proposed algorithmic solutions are based on rank-relaxation and Difference-of-Convex (DC) programming.Comment: 15 pages, 9 figures, and 1 table, accepted in IEEE Transactions on Vehicular Technolog

A Review on suboptimal power allocation schemes for WSN localization

This paper considers a review of two proposed power allocation algorithms for increasing accuracy in localization scenarios, a deeper theoretical analysis and a detailed performance comparison. Appropriate power allocation (PA) among beacons is an effective tool to implement localization with improved precision. At first, a brief review on existing optimal PA strategies is presented. Subsequently, the first PA algorithm is discussed: a function called uncertainty area is defined according to the interaction of beacons in a pair-wise selection procedure. A general selection strategy among allocated transmission powers for each beacon completes the algorithm structure. In the literature, on one hand the commonly made assumption about ranging measures is that their ideal values are equal to their corresponding Cramer-Rao bounds but, on the other hand, at high signal-to-noise ratios, real ranging estimators are characterized by different lower limits on their performance, mainly as a result of maximum sampling rates and computational load available in the sensors. The second PA algorithm develops a type of adaptive PA (APA) directly based on measured SNRs and, consequently, much simpler than other techniques