3,818 research outputs found
Exploiting Amplitude Control in Intelligent Reflecting Surface Aided Wireless Communication with Imperfect CSI
Intelligent reflecting surface (IRS) is a promising new paradigm to achieve
high spectral and energy efficiency for future wireless networks by
reconfiguring the wireless signal propagation via passive reflection. To reap
the potential gains of IRS, channel state information (CSI) is essential,
whereas channel estimation errors are inevitable in practice due to limited
channel training resources. In this paper, in order to optimize the performance
of IRS-aided multiuser systems with imperfect CSI, we propose to jointly design
the active transmit precoding at the access point (AP) and passive reflection
coefficients of IRS, each consisting of not only the conventional phase shift
and also the newly exploited amplitude variation. First, the achievable rate of
each user is derived assuming a practical IRS channel estimation method, which
shows that the interference due to CSI errors is intricately related to the AP
transmit precoders, the channel training power and the IRS reflection
coefficients during both channel training and data transmission. Then, for the
single-user case, by combining the benefits of the penalty method, Dinkelbach
method and block successive upper-bound minimization (BSUM) method, a new
penalized Dinkelbach-BSUM algorithm is proposed to optimize the IRS reflection
coefficients for maximizing the achievable data transmission rate subjected to
CSI errors; while for the multiuser case, a new penalty dual decomposition
(PDD)-based algorithm is proposed to maximize the users' weighted sum-rate.
Simulation results are presented to validate the effectiveness of our proposed
algorithms as compared to benchmark schemes. In particular, useful insights are
drawn to characterize the effect of IRS reflection amplitude control
(with/without the conventional phase shift) on the system performance under
imperfect CSI.Comment: 15 pages, 10 figures, accepted by IEEE Transactions on Communication
Robust Transceiver Design for MISO Interference Channel with Energy Harvesting
In this paper, we consider multiuser multiple-input single-output (MISO)
interference channel where the received signal is divided into two parts for
information decoding and energy harvesting (EH), respectively. The transmit
beamforming vectors and receive power splitting (PS) ratios are jointly
designed in order to minimize the total transmission power subject to both
signal-to-interference-plus-noise ratio (SINR) and EH constraints. Most joint
beamforming and power splitting (JBPS) designs assume that perfect channel
state information (CSI) is available; however CSI errors are inevitable in
practice. To overcome this limitation, we study the robust JBPS design problem
assuming a norm-bounded error (NBE) model for the CSI. Three different solution
approaches are proposed for the robust JBPS problem, each one leading to a
different computational algorithm. Firstly, an efficient semidefinite
relaxation (SDR)-based approach is presented to solve the highly non-convex
JBPS problem, where the latter can be formulated as a semidefinite programming
(SDP) problem. A rank-one recovery method is provided to recover a robust
feasible solution to the original problem. Secondly, based on second order cone
programming (SOCP) relaxation, we propose a low complexity approach with the
aid of a closed-form robust solution recovery method. Thirdly, a new iterative
method is also provided which can achieve near-optimal performance when the
SDR-based algorithm results in a higher-rank solution. We prove that this
iterative algorithm monotonically converges to a Karush-Kuhn-Tucker (KKT)
solution of the robust JBPS problem. Finally, simulation results are presented
to validate the robustness and efficiency of the proposed algorithms.Comment: 13 pages, 8 figures. arXiv admin note: text overlap with
arXiv:1407.0474 by other author
Joint Transceiver Design Algorithms for Multiuser MISO Relay Systems with Energy Harvesting
In this paper, we investigate a multiuser relay system with simultaneous
wireless information and power transfer. Assuming that both base station (BS)
and relay station (RS) are equipped with multiple antennas, this work studies
the joint transceiver design problem for the BS beamforming vectors, the RS
amplify-and-forward transformation matrix and the power splitting (PS) ratios
at the single-antenna receivers. Firstly, an iterative algorithm based on
alternating optimization (AO) and with guaranteed convergence is proposed to
successively optimize the transceiver coefficients. Secondly, a novel design
scheme based on switched relaying (SR) is proposed that can significantly
reduce the computational complexity and overhead of the AO based designs while
maintaining a similar performance. In the proposed SR scheme, the RS is
equipped with a codebook of permutation matrices. For each permutation matrix,
a latent transceiver is designed which consists of BS beamforming vectors,
optimally scaled RS permutation matrix and receiver PS ratios. For the given
CSI, the optimal transceiver with the lowest total power consumption is
selected for transmission. We propose a concave-convex procedure based and
subgradient-type iterative algorithms for the non-robust and robust latent
transceiver designs. Simulation results are presented to validate the
effectiveness of all the proposed algorithms
Efficiency Maximization for UAV-Enabled Mobile Relaying Systems with Laser Charging
This work studies the joint problem of power and trajectory optimization in
an unmanned aerial vehicle (UAV)-enabled mobile relaying system. In the
considered system, in order to provide convenient and sustainable energy supply
to the UAV relay, we consider the deployment of a power beacon (PB) which can
wirelessly charge the UAV and it is realized by a properly designed laser
charging system. To this end, we propose an efficiency (the weighted sum of the
energy efficiency during information transmission and wireless power
transmission efficiency) maximization problem by optimizing the source/UAV/PB
transmit powers along with the UAV's trajectory. This optimization problem is
also subject to practical mobility constraints, as well as the
information-causality constraint and energy-causality constraint at the UAV.
Different from the commonly used alternating optimization (AO) algorithm, two
joint design algorithms, namely: the concave-convex procedure (CCCP) and
penalty dual decomposition (PDD)-based algorithms, are presented to address the
resulting non-convex problem, which features complex objective function with
multiple-ratio terms and coupling constraints. These two very different
algorithms are both able to achieve a stationary solution of the original
efficiency maximization problem. Simulation results validate the effectiveness
of the proposed algorithms.Comment: 33 pages, 8 figures, accepted for publication in IEEE Transactions on
Wireless Communication
Fast List Decoding of High-Rate Polar Codes
Due to the ability to provide superior error-correction performance, the
successive cancellation list (SCL) algorithm is widely regarded as one of the
most promising decoding algorithms for polar codes with short-to-moderate code
lengths. However, the application of SCL decoding in low-latency communication
scenarios is limited due to its sequential nature. To reduce the decoding
latency, developing tailored fast and efficient list decoding algorithms of
specific polar substituent codes (special nodes) is a promising solution.
Recently, fast list decoding algorithms are proposed by considering special
nodes with low code rates. Aiming to further speedup the SCL decoding, this
paper presents fast list decoding algorithms for two types of high-rate special
nodes, namely single-parity-check (SPC) nodes and sequence rate one or
single-parity-check (SR1/SPC) nodes. In particular, we develop two classes of
fast list decoding algorithms for these nodes, where the first class uses a
sequential decoding procedure to yield decoding latency that is linear with the
list size, and the second further parallelizes the decoding process by
pre-determining the redundant candidate paths offline. Simulation results show
that the proposed list decoding algorithms are able to achieve up to 70.7\%
lower decoding latency than state-of-the-art fast SCL decoders, while
exhibiting the same error-correction performance.Comment: 13 pages, 8 figure
Intelligent Reflecting Surface Enhanced Wireless Network: Two-timescale Beamforming Optimization
Intelligent reflecting surface (IRS) has drawn a lot of attention recently as
a promising new solution to achieve high spectral and energy efficiency for
future wireless networks. By utilizing massive low-cost passive reflecting
elements, the wireless propagation environment becomes controllable and thus
can be made favorable for improving the communication performance. Prior works
on IRS mainly rely on the instantaneous channel state information (I-CSI),
which, however, is practically difficult to obtain for IRS-associated links due
to its passive operation and large number of elements. To overcome this
difficulty, we propose in this paper a new two-timescale (TTS) transmission
protocol to maximize the achievable average sum-rate for an IRS-aided multiuser
system under the general correlated Rician channel model. Specifically, the
passive IRS phase-shifts are first optimized based on the statistical CSI
(S-CSI) of all links, which varies much slowly as compared to their I-CSI,
while the transmit beamforming/precoding vectors at the access point (AP) are
then designed to cater to the I-CSI of the users' effective channels with the
optimized IRS phase-shifts, thus significantly reducing the channel training
overhead and passive beamforming complexity over the existing schemes based on
the I-CSI of all channels. For the single-user case, a novel penalty dual
decomposition (PDD)-based algorithm is proposed, where the IRS phase-shifts are
updated in parallel to reduce the computational time. For the multiuser case,
we propose a general TTS optimization algorithm by constructing a quadratic
surrogate of the objective function, which cannot be explicitly expressed in
closed-form. Simulation results are presented to validate the effectiveness of
our proposed algorithms and evaluate the impact of S-CSI and channel
correlation on the system performance.Comment: 15 pages, 12 figures, accepted for publication in IEEE Transactions
on Wireless Communication
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