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.
In bi-static Ambient Backscatter Communications (AmBC) systems, the receiver needs to operate at a large dynamic range because the direct path from the ambient source to the receiver can be several orders of magnitude stronger than the scattered path modulated by the AmBC device. In this paper, we propose a novel analog-digital hybrid null-steering beamformer which allows the backscatter receiver to detect and decode the weak AmBC-modulated signal buried in the strong direct path signals and the noise without requiring the instantaneous channel state information. The analog cancellation of the strong signal components allows the receiver automatic gain control to adjust to the level of the weak AmBC signals. This hence allows common analog-to-digital converters to be used for sampling the signal. After cancelling the strong components, the ambient source signal appears as zero mean fast fading from the AmBC system point of view. We use the direct path signal component to track the phase of the unknown ambient signal. In order to avoid channel estimation, we propose AmBC to use orthogonal channelization codes. The results show that the design allows the AmBC receiver to detect the backscatter binary phase shift keying signals without decoding the ambient signals and requiring knowledge of the instantaneous channel state information.Index Terms-Ambient backscatter, low-power receiver, hybrid analog-digital beamformer.
Backscatter communication is expected to help in revitalizing the domain of healthcare through its myriad applications. From on-body sensors to in-body implants and miniature embeddable devices, there are many potential use cases that can leverage the miniature and low-powered nature of backscatter devices. However, the existing literature lacks a comprehensive study that provides a distilled review of the latest studies on backscatter communications from the healthcare perspective. Thus, with the objective to promote the utility of backscatter communication in healthcare, this paper aims to identify specific applications of backscatter systems. A detailed taxonomy of recent studies and gap analysis for future research directions are provided in this work. Finally, we conduct measurements at 590 MHz in different propagation environments with the in-house designed backscatter device. The link budget results show the promise of backscatter devices to communicate over large distances for indoor environments which demonstrates its potential in the healthcare system. Index TermsBackscatter communication, Healthcare, In-body implants, Link budget, On-body sensors I. INTRODUCTIONThe medical industry today is seeking new solutions for in-body and on-body devices that transfer the data over a wireless channel [1], [2]. This includes pacemakers for generating electric pulses, micro-scale robots that operate in the bloodstream, and smart pills for identifying abnormalities in the gastrointestinal tract. However, the modern deep tissue systems consume a significant amount of energy by generating their own radio signals. For instance, wireless capsules for endoscopy consume up to 10 times more power than the sensors [1]. Due to these reasons, the large battery of the capsule consumes 40-50% of the total space of the capsule [2]. Reduction in this form-factor (i.e., the size, shape, and other physical specifications of electronic components) of these capsules can not only improve the likelihood of completion of endoscopy but also make them easy to swallow and excrete. Similar challenges are faced in the case of on-body sensors. The premise of on-body sensor networks is to build a network of devices capable of operating in a battery-free manner by means of smart networking, and power management at the granularity of individual bits and instructions. This is challenging to achieve through conventional networking approaches due to the need for active radio circuits, large form-factors, and their energy constraint nature. Thus, we expect that it is important to divorce the healthcare from conventional wireless solutions and move towards innovative systems for seamlessly connecting the in-body and on-body wireless devices.Backscatter communication is an emerging paradigm and a key enabler for pervasive connectivity of low-powered wireless devices [3]. It is primarily beneficial in situations where computing and connectivity capabilities expand to sensors and miniature devices that exchange data on a low power budget. Due to this in...
Abstract-Fifth generation of cellular systems is expected to widely enable machine-type communications (MTC). The envisioned applications and services for MTC have diverse requirements which are not fully supported with current wireless systems. Ultra-reliable communications (URC) with low-latency is an essential feature for mission-critical applications, such as industrial automation, public safety, and vehicular safety applications. This feature guarantees a communication service with a high level of reliability. This paper investigates the feasibility and efficiency of URC over wireless links. It also analyzes the effectiveness of different transmission methods, including spatial diversity and support of hybrid automatic repeat request (HARQ). Finally, the importance of reliable feedback information is highlighted.
Ambient backscatter communication (AmBC), a green communication technology, is hampered by the continuously and extremely fast varying, strong and unknown ambient radio frequency (RF) signals. This paper presents a machine learning-assisted method for extracting the information of the AmBC device. The information is modulated on top of the unknown Gaussian-distributed ambient RF signals. The proposed approach can decode the binary phase shift keying backscatter signals encoded using Hadamard codes. This method extracts the learnable features for the tag signal by first eliminating the direct path signal and then correlating the residual signal with the coarse estimate of ambient signal. Thereafter, the tag signals are recovered by using the k-nearest neighbors classification algorithm. The recovered signals are decoded by a Hadamard decoder to retrieve the original information bits. We validate the performance using simulations to corroborate the proposed approach.
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