Resumen de Localización con señales ofdm en sistemes 5g
Arash Shahmansoori
A key aspect to design an OFDM system for combined positioning and high-data-rate communications is to find optimal data and pilot power allocations. Previously, A capacity maximizing design has been investigated for the case of static channels. However, it is logical to consider channel variation for different OFDM symbols due to movement. Joint design of data and pilots with considering the time variations of the channel and correlation between the corresponding channel taps from different OFDM symbols increases the capacity for a given time-delay estimation accuracy. We propose a method for joint design of data and pilots for the time-varying channels. Numerical results approve the improvement in terms of channel capacity for a desired value of time-delay estimation accuracy.
Next, we consider the power allocations for OFDM WNL. In location-aware wireless networks, mobile nodes (agents) can obtain their positions using range measurements to other nodes with known positions (anchors). Optimal subcarrier power allocation at the anchors reduces positioning error and improves network lifetime and throughput. We present an optimization framework for ergodic and robust subcarrier power allocations in network localization with imperfect knowledge of network parameters based on the fundamental statistical limits. Ergodic and robust power allocations are obtained using semidefinite optimization problems in non-iterative and iterative forms with both unicast and multicast transmissions. Results show that robust and ergodic power allocations provide more accurate localization than non-robust designs under channel and agents positions uncertainty.
Finally, we extend the localization techniques for 5G systems. 5G communications are characterized by large bandwidths, large antenna arrays, and device-to-device communication. We describe why and how these properties are conducive to accurate positioning. We also provide an overview of how 5G technologies have been used for positioning in recent literature. Particularly, millimeter wave and massive MIMO are considered enabling technologies for future 5G networks. While their benefits for achieving high-data rate communications are well-known, their potential advantages for accurate positioning are largely undiscovered. We derive fundamental bounds on the position and rotation angle estimation in the presence of clusters for wideband systems. A detection algorithm based on MMV matching pursuit is used for the coarse estimation of AOA/AOD and TOA that are applied for initialization of the estimation phase based on the EM with a sequential iterative procedure. The results show the convergence of the estimated parameters to the values obtained by the inverse of Fisher information matrix.
