# High-Efficiency Device Positioning and Location-Aware Communications in Dense 5G Networks

arXiv: https://arxiv.org/abs/1608.03775 · HTML: https://mlsanity.com/paper/1608.03775/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 Aug 2016.

## Built on by (most cited first, 3 of 3)

- [Synesthesia of Machines (SoM)-Enhanced ISAC Precoding for Vehicular Networks with Double Dynamics](https://mlsanity.com/paper/2408.13546/) (2024)
- [Channel-Feedback-Free Transmission for Downlink FD-RAN: A Radio Map based Complex-valued Precoding Network Approach](https://mlsanity.com/paper/2312.02184/) (2023)
- [Doubly-Dynamic ISAC Precoding for Vehicular Networks: A Constrained Deep Reinforcement Learning (CDRL) Approach](https://mlsanity.com/paper/2405.14347/) (2024)

## Abstract (arXiv)

In this article, the prospects and enabling technologies for high-efficiency device positioning and location-aware communications in emerging 5G networks are reviewed. We will first describe some key technical enablers and demonstrate by means of realistic ray-tracing and map based evaluations that positioning accuracies below one meter can be achieved by properly fusing direction and delay related measurements on the network side, even when tracking moving devices. We will then discuss the possibilities and opportunities that such high-efficiency positioning capabilities can offer, not only for location-based services in general, but also for the radio access network itself. In particular, we will demonstrate that geometric location-based beamforming schemes become technically feasible, which can offer substantially reduced reference symbol overhead compared to classical full channel state information (CSI)-based beamforming. At the same time, substantial power savings can be realized in future wideband 5G networks where acquiring full CSI calls for wideband reference signals while location estimation and tracking can, in turn, be accomplished with narrowband pilots.