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Jida Zhang

Publications and source records attributed to Jida Zhang.

3 recordsLinked to original sources

First-Principles Channel Model and Capacity-Achieving Transmission Scheme in Thermal Noise Backscatter Links

Thermal noise communication systems transmit information by modulating thermal radiation, eliminating the need for a dedicated signal power source and making them attractive solutions for low-power sensor networks. Their efficiency enables long-lived, unobtrusive operation, which is valuable in the Internet of Things, electromagnetic interference-sensitive environments, and RFID tag systems. However, a limited understanding of the wireless channel model and efficient transmission schemes has hindered their practical deployment. Here, we present a wireless channel model that elucidates how systems operating at ambient temperature can modulate thermal noise to convey information. Our results reveal a thermal noise backscatter mechanism that enables significantly higher data rates than previously achieved. We designed and built a thermal noise communication system leveraging this mechanism to achieve data rates in the kilobits-per-second range - over two orders of magnitude higher than prior demonstrations. We also derive the system capacity and show that using polar codes, we are able to achieve this expected capacity. Our channel model and transmission scheme pave the way for new strategies in thermal noise sensing and communication, advancing practical low-power networking for next-generation wireless applications.

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StarLoc: Pinpointing Transmitting LEO Satellites from a Single Passive Array

This paper focuses on 3D localization of transmitting satellites in low Earth orbits (LEO). 3D localization of transmitters in low orbits is an important emerging problem for many applications such as spectrum management, orbit determination, and backup for GPS failures in orbit. We present StarLoc -- a system to geolocate transmitters in space using a combination of orbital modeling and a new interferometric 3D angle-of-arrival estimation technique. StarLoc's design relies on a unique insight -- the motion of satellites is governed by orbital dynamics and is therefore along a 2D manifold in a 3D space. This reduces the degrees of freedom in satellite motion and allows us to 3D-locate and track a satellite with just three antennas in a 2D plane. We evaluate the system using signal transmissions from 81 Starlink satellites. Our results show that StarLoc can estimate the 3D-angle of a satellite within 0.7 degrees and the orbital range within 5 km. Our dataset and implementation are available at: https://connectedsystemslab.github.io/starloc.

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Enhancing Energy Efficiency for Reconfigurable Intelligent Surfaces with Practical Power Models

Reconfigurable intelligent surfaces (RISs) are widely considered a promising technology for future wireless communication systems. As an important indicator of RIS-assisted communication systems in green wireless communications, energy efficiency (EE) has recently received intensive research interest as an optimization target. However, most previous works have ignored the different power consumption between ON and OFF states of the PIN diodes attached to each RIS element. This oversight results in extensive unnecessary power consumption and reduction of actual EE due to the inaccurate power model. To address this issue, in this paper, we first utilize a practical power model for a RIS-assisted multi-user multiple-input single-output (MU-MISO) communication system, which takes into account the difference in power dissipation caused by ON-OFF states of RIS's PIN diodes. Based on this model, we formulate a more accurate EE optimization problem. However, this problem is non-convex and has mixed-integer properties, which poses a challenge for optimization. To solve the problem, an effective alternating optimization (AO) algorithm framework is utilized to optimize the base station and RIS beamforming precoder separately. To obtain the essential RIS beamforming precoder, we develop two effective methods based on maximum gradient search and SDP relaxation respectively. Theoretical analysis shows the exponential complexity of the original problem has been reduced to polynomial complexity. Simulation results demonstrate that the proposed algorithm outperforms the existing ones, leading to a significant increase in EE across a diverse set of scenarios.

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