9 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
Sum Throughput Maximization in Multi-Tag Backscattering to Multiantenna Reader
Backscatter communication (BSC) is being realized as the core technology for
pervasive sustainable Internet-of-Things applications. However, owing to the
resource-limitations of passive tags, the efficient usage of multiple antennas
at the reader is essential for both downlink excitation and uplink detection.
This work targets at maximizing the achievable sum-backscattered-throughput by
jointly optimizing the transceiver (TRX) design at the reader and
backscattering coefficients (BC) at the tags. Since, this joint problem is
nonconvex, we first present individually-optimal designs for the TRX and BC. We
show that with precoder and {combiner} designs at the reader respectively
targeting downlink energy beamforming and uplink Wiener filtering operations,
the BC optimization at tags can be reduced to a binary power control problem.
Next, the asymptotically-optimal joint-TRX-BC designs are proposed for both low
and high signal-to-noise-ratio regimes. Based on these developments, an
iterative low-complexity algorithm is proposed to yield an efficient
jointly-suboptimal design. Thereafter, we discuss the practical utility of the
proposed designs to other application settings like wireless powered
communication networks and BSC with imperfect channel state information.
Lastly, selected numerical results, validating the analysis and shedding novel
insights, demonstrate that the proposed designs can yield significant
enhancement in the sum-backscattered throughput over existing benchmarks.Comment: 17 pages, 5 figures, accepted for publication in IEEE Transactions on
Communication
On Energy Allocation and Data Scheduling in Backscatter Networks with Multi-antenna Readers
In this paper, we study the throughput utility functions in buffer-equipped
monostatic backscatter communication networks with multi-antenna Readers. In
the considered model, the backscatter nodes (BNs) store the data in their
buffers before transmission to the Reader. We investigate three utility
functions, namely, the sum, the proportional and the common throughput. We
design online admission policies, corresponding to each utility function, to
determine how much data can be admitted in the buffers. Moreover, we propose an
online data link control policy for jointly controlling the transmit and
receive beamforming vectors as well as the reflection coefficients of the BNs.
The proposed policies for data admission and data link control jointly optimize
the throughput utility, while stabilizing the buffers. We adopt the
min-drift-plus-penalty (MDPP) method in designing the control policies.
Following the MDPP method, we cast the optimal data link control and the data
admission policies as solutions of two independent optimization problems which
should be solved in each time slot. The optimization problem corresponding to
the data link control is non-convex and does not have a trivial solution. Using
Lagrangian dual and quadratic transforms, we find a closed-form iterative
solution. Finally, we use the results on the achievable rates of finite
blocklength codes to study the system performance in the cases with short
packets. As demonstrated, the proposed policies achieve optimal utility and
stabilize the data buffers in the BNs
Ambient backcom in beyond 5G NOMA networks: A multi-cell resource allocation framework
The research of Non-Orthogonal Multiple Access (NOMA) is extensively used to improve the capacity of networks
beyond the fifth-generation. The recent merger of NOMA with ambient Backscatter Communication (BackCom),
though opening new possibilities for massive connectivity, poses several challenges in dense wireless networks.
One of such challenges is the performance degradation of ambient BackCom in multi-cell NOMA networks under
the effect of inter-cell interference. Driven by providing an efficient solution to the issue, this article proposes a
new resource allocation framework that uses a duality theory approach. Specifically, the sum rate of the multi-cell
network with backscatter tags and NOMA user equipments is maximized by formulating a joint optimization
problem. To find the efficient base station transmit power and backscatter reflection coefficient in each cell, the
original problem is first divided into two subproblems, and then the closed form solution is derived. A comparison
with the Orthogonal Multiple Access (OMA) ambient BackCom and pure NOMA transmission has been provided.
Simulation results of the proposed NOMA ambient BackCom indicate a significant improvement over the OMA
ambient BackCom and pure NOMA in terms of sum-rate gains