1,140 research outputs found
Beamforming Optimization for Full-Duplex Wireless-powered MIMO Systems
We propose techniques for optimizing transmit beamforming in a full-duplex
multiple-input-multiple-output (MIMO) wireless-powered communication system,
which consists of two phases. In the first phase, the wireless-powered mobile
station (MS) harvests energy using signals from the base station (BS), whereas
in the second phase, both MS and BS communicate to each other in a full-duplex
mode. When complete instantaneous channel state information (CSI) is available,
the BS beamformer and the time-splitting (TS) parameter of energy harvesting
are jointly optimized in order to obtain the BS-MS rate region. The joint
optimization problem is non-convex, however, a computationally efficient
optimum technique, based upon semidefinite relaxation and line-search, is
proposed to solve the problem. A sub-optimum zero-forcing approach is also
proposed, in which a closed-form solution of TS parameter is obtained. When
only second-order statistics of transmit CSI is available, we propose to
maximize the ergodic information rate at the MS, while maintaining the outage
probability at the BS below a certain threshold. An upper bound for the outage
probability is also derived and an approximate convex optimization framework is
proposed for efficiently solving the underlying non-convex problem. Simulations
demonstrate the advantages of the proposed methods over the sub-optimum and
half-duplex ones.Comment: 14 pages, accepte
Throughput Analysis and Optimization of Wireless-Powered Multiple Antenna Full-Duplex Relay Systems
We consider a full-duplex (FD) decode-and-forward system in which the
time-switching protocol is employed by the multi-antenna relay to receive
energy from the source and transmit information to the destination. The
instantaneous throughput is maximized by optimizing receive and transmit
beamformers at the relay and the time-split parameter. We study both optimum
and suboptimum schemes. The reformulated problem in the optimum scheme achieves
closed-form solutions in terms of transmit beamformer for some scenarios. In
other scenarios, the optimization problem is formulated as a semi-definite
relaxation problem and a rank-one optimum solution is always guaranteed. In the
suboptimum schemes, the beamformers are obtained using maximum ratio combining,
zero-forcing, and maximum ratio transmission. When beamformers have closed-form
solutions, the achievable instantaneous and delay-constrained throughput are
analytically characterized. Our results reveal that, beamforming increases both
the energy harvesting and loop interference suppression capabilities at the FD
relay. Moreover, simulation results demonstrate that the choice of the linear
processing scheme as well as the time-split plays a critical role in
determining the FD gains.Comment: Accepted for publication in IEEE Transactions on Communication
Wireless Information and Power Transfer in Full-Duplex Systems with Massive Antenna Arrays
We consider a multiuser wireless system with a full-duplex hybrid access
point (HAP) that transmits to a set of users in the downlink channel, while
receiving data from a set of energy-constrained sensors in the uplink channel.
We assume that the HAP is equipped with a massive antenna array, while all
users and sensor nodes have a single antenna. We adopt a time-switching
protocol where in the first phase, sensors are powered through wireless energy
transfer from HAP and HAP estimates the downlink channel of the users. In the
second phase, sensors use the harvested energy to transmit to the HAP. The
downlink-uplink sum-rate region is obtained by solving downlink sum-rate
maximization problem under a constraint on uplink sum-rate. Moreover, assuming
perfect and imperfect channel state information, we derive expressions for the
achievable uplink and downlink rates in the large-antenna limit and approximate
results that hold for any finite number of antennas. Based on these analytical
results, we obtain the power-scaling law and analyze the effect of the number
of antennas on the cancellation of intra-user interference and the
self-interference.Comment: Accepted for the IEEE International Conference on Communications (ICC
2017
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
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