In ambient re-scatter 1 communications, devices convey information by modulating and re-scattering the radio frequency signals impinging on their antennas. In this correspondence, we consider a system consisting of a legacy modulated continuous carrier multiple-input-multiple-output (MIMO) link and a multi-antenna modulated re-scatter (MRS) node, where the MRS node modulates and re-scatters the signal generated by the legacy transmitter. The receiver seeks to decode both the original message and the information added by the MRS. We show that the achievable sum rate of this system exceeds that which the legacy system could achieve alone. We further consider the impact of channel estimation errors under the least squares channel estimation and study the achievable rate of the legacy and MRS systems, where a linear minimum mean square error receiver with successive interference cancellation is utilized for joint decoding.
Abstract-Quantum illumination (QI) is a revolutionary photonic quantum sensing paradigm that enhances the sensitivity of photodetection in noisy and lossy environments. In this paper, we propose to use QI in a quantum backscatter communication (QBC), with the aim of increasing the receiver sensitivity beyond the limits of its classical counterpart. One of the practical challenges in microwave QI is the slow rate at which the entangled microwave modes can be generated. Here, we propose to mitigate this problem by using a multiple-input multipleoutput antenna system to synthetically increase the number of efficiently-distinguishable modes in the QBC context.
Cellular systems are undergoing a transformation toward the fifth generation (5G). Envisioned applications in 5G include intelligent transport system (ITS), autonomous vehicles, and robots as a part of future roads, factories, and society. These applications rely to a great extent on accurate and timely location information of connected devices. This paper proposes a practical scheme for acquiring precise and timely position information by means of a user-centric ultra-dense network (UDN) architecture based on an edge cloud. The considered solution consists of estimating and tracking the azimuth angle-of-arrival (AoA) of the line-of-sight (LoS)-path between a device and multiple transmission-reception points (TRPs), each having a uniform linear antenna array (ULA). AoA estimates from multiple TRPs are fused into position estimates at the edge cloud to obtain timely position information. The extensive measurements have been carried out using a proof-of-concept software-defined-radio (SDR) testbed in order to experimentally assess the achievable positioning accuracy of the proposed architecture. A realistic UDN deployment scenario has been considered in which TRPs consist of antenna arrays mounted on lamp posts. Our results show that practical UDNs can provide sub-meter positioning accuracy of mobile users by employing ULAs with at least four antennas per TRP and by taking into account the non-idealities of the ULAs' phase and magnitude response.
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