Abstract
Millimeter wave (mmWave) technology is expected to be a major component of 5G wireless networks. Ultra-wide bandwidths of mmWave signals and the possibility of utilizing large number of antennas at the transmitter and the receiver allow accurate identification of multipath components in temporal and angular domains, making mmWave systems advantageous for localization applications. In this paper, we analyze the performance of a two-step mmWave localization approach that can utilize time-of-arrival, angle-of-arrival, and angle-of-departure from multiple nodes in an urban environment with both line-of-sight (LOS) and non-LOS (NLOS) links. Networks with/without radio-environmental mapping (REM) are considered, where a network with REM is able to localize nearby scatterers. Estimation of a UE location is challenging due to large numbers of local optima in the likelihood function. To address this problem, a gradient-assisted particle filter (GAPF) estimator is proposed to accurately estimate a user equipment (UE) location as well as the locations of nearby scatterers. Monte-Carlo simulations show that the GAPF estimator performance matches the Cramer-Rao bound (CRB). The estimator is also used to create a REM. It is seen that significant localization gains can be achieved by increasing beam directionality or by utilizing REM.
Highlights
1 Introduction The demand for wireless broadband communication has been growing rapidly, which has been the driving force for the emergence of 5G cellular networks. It has recently been shown in the literature that millimeter wave technology is feasible for dynamic outdoor cellular networks, but can facilitate a thousand fold increase in data capacity [1,2,3,4]
Communication performance in 5G networks will be limited by the amount of time required to align the highly directional beams of the communicating nodes, for exhaustive beam searches, which are costly to capacity [5]
Instead of a full exhaustive grid search in each dimension for the initial particles θ i0, an alternative initialization is proposed as seen in Algorithm 2 that performs a separate grid search that significantly reduces the number of grid points required for scenarios with many NLOS paths
Summary
The demand for wireless broadband communication has been growing rapidly, which has been the driving force for the emergence of 5G cellular networks. It has recently been shown in the literature that millimeter wave (mmWave) technology is feasible for dynamic outdoor cellular networks, but can facilitate a thousand fold increase in data capacity [1,2,3,4]. The mmWave cellular networks are expected to first be deployed in dense urban environments where the Global Positioning System (GPS) signal may typically be unavailable, and the demand for large data rates is high. It is important to characterize the performance of mmWave network localization for urban scenarios
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