Abstract
Millimeter-Wave (mmWave) communication is a promising solution for achieving high data rate and low latency in 5G wireless networks. Since directional beamforming and antenna arrays are exploited in the mmWave networks, accurate angle-of-arrival (AOA) measurements can be obtained and utilized for localization purposes. In this work, we consider the AOA-based positioning for the mmWave networks using stochastic geometry and analyze how the Cramér-Rao lower bound (CRLB) is affected by the spatial distribution of nodes, including the target and participating anchors. In order to apply the CRLB on a network setting with random node locations, we propose an accurate approximation of the CRLB using the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\lceil L/4 \rceil $ </tex-math></inline-formula> -th value of the ordered distances where <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$L$ </tex-math></inline-formula> is the number of participating anchors. These findings provide us deep insight into optimum network design that meets specified localization requirements.
Highlights
P OSITIONING techniques received considerable attention due to the emergency of internet-of-things, which can be utilized to ameliorate the user experience of locationbased services, including indoor navigation, asset tracking, and simultaneous localization and mapping (SLAM) [1]–[3]
We assumed that the anchors√are randomly distributed by a homogeneous Poisson point process (HPPP) with density = 2/ 3 × 5002 2, bandwidth TOT = 1 GHz, transmit power = 1 Watt, antenna spacing = /4, path-loss intercept = ( /4 )2, and antenna gain 1 = 1 and 2 = 0.2 with its associate probability 1 = 0.4 and 2 = 0.6, respectively
The LOS channel becomes more deterministic while the NLOS channel condition remains fixed, which results in a higher signal-tointerference-plus-noise ratio (SINR) in (9) and better ( ) in (10)
Summary
P OSITIONING techniques received considerable attention due to the emergency of internet-of-things, which can be utilized to ameliorate the user experience of locationbased services, including indoor navigation, asset tracking, and simultaneous localization and mapping (SLAM) [1]–[3]. In the 5G wireless networks, accurate angle-of-arrival (AOA) information can be obtained by leveraging the massive antenna array and highly directional transmission [4]. AOA-based localization is regarded as a promising candidate to achieve high-precision localization for 5G networks. A. MOTIVATION Millimeter-Wave (mmWave) is a promising technology for 5G wireless networks to meet the requirements of large bandwidth and high carrier frequency [5]. Due to its high transmission rate, mmWave signals enable us to efficiently detect and resolve the multipath components, which provide us an opportunity to achieve submeter level localization accuracy [6], [7]. The cost of the mmWave-based system is exorbitant due to the deployment of the massive antenna array and a large number of mmWave anchors. The experimental verification for the mmWave-based system is complicated and time-consuming, which brings challenges to examining the localization performance for the mmWave-based system
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