257 research outputs found
Channel Estimation for Ambient Backscatter Communication Systems with Massive-Antenna Reader
Ambient backscatter, an emerging green communication technology, has aroused
great interest from both academia and industry. One open problem for ambient
backscatter communication (AmBC) systems is channel estimation for a
massive-antenna reader. In this paper, we focus on channel estimation problem
in AmBC systems with uniform linear array (ULA) at the reader which consists of
large number of antennas. We first design a two-step method to jointly estimate
channel gains and direction of arrivals (DoAs), and then refine the estimates
through angular rotation. Additionally, Cramer-Rao lower bounds (CRLBs) are
derived for both the modulus of the channel gain and the DoA estimates.
Simulations are then provided to validate the analysis, and to show the
efficiency of the proposed approach.Comment: 5 figures, submitted to IEEE Transactions on Vehicular Technology, 29
March, 201
Optimal Channel Estimation for Reciprocity-Based Backscattering with a Full-Duplex MIMO Reader
Backscatter communication (BSC) technology can enable ubiquitous deployment
of low-cost sustainable wireless devices. In this work we investigate the
efficacy of a full-duplex multiple-input-multiple-output (MIMO) reader for
enhancing the limited communication range of monostatic BSC systems. As this
performance is strongly influenced by the channel estimation (CE) quality, we
first derive a novel least-squares estimator for the forward and backward links
between the reader and the tag, assuming that reciprocity holds and K
orthogonal pilots are transmitted from the first K antennas of an N antenna
reader. We also obtain the corresponding linear minimum-mean square-error
estimate for the backscattered channel. After defining the transceiver design
at the reader using these estimates, we jointly optimize the number of
orthogonal pilots and energy allocation for the CE and information decoding
phases to maximize the average backscattered signal-to-noise ratio (SNR) for
efficiently decoding the tag's messages. The unimodality of this SNR in
optimization variables along with a tight analytical approximation for the
jointly global optimal design is also discoursed. Lastly, the selected
numerical results validate the proposed analysis, present key insights into the
optimal resource utilization at reader, and quantify the achievable gains over
the benchmark schemes.Comment: accepted for publication in IEEE Transactions on Signal Processing,
16 pages, 15 figures, 1 tabl
Multi-BD Symbiotic Radio-Aided 6G IoT Network: Energy Consumption Optimization with QoS Constraint Approach
The commensal symbiotic radio (CSR) system is proposed as a novel solution for connecting systems through green
communication networks. This system enables us to establish
secure, ubiquitous, and unlimited connectivity, which is a goal of 6G. The base station uses MIMO antennas to transmit its signal. Passive IoT devices, called symbiotic backscatter devices (SBDs), receive the signal and use it to charge their power supply. When the SBDs have data to transmit, they modulate the information onto the received ambient RF signal and send it to the symbiotic user equipment, which is a typical active device. The main purpose is to enhance energy efficiency in this network by minimizing energy consumption (EC) while ensuring the minimum required throughput for SBDs. To achieve this, we propose a new scheduling scheme called Timing-SR that optimally allocates resources to SBDs. The main optimization problem involves non-convex objective functions and constraints. To solve this, we use mathematical techniques and introduce a new approach called sequential quadratic and conic quadratic representation to relax and discipline the problem, leading to reducing its complexity and convergence time. The simulation results demonstrate that the proposed approach outperforms other outlined schemes in reducing EC
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