647 research outputs found
Probabilistic QoS Constrained Robust Downlink Multiuser MIMO Transceiver Design with Arbitrarily Distributed Channel Uncertainty
We study the robust transceiver optimization in downlink multiuser multiple-input multiple-output (MU-MIMO) systems aiming at minimizing transmit power under probabilistic quality-of-service (QoS) requirements. Owing to the unknown distributed interference, the channel estimation error obtained from the linear minimum mean square error (LMMSE) estimator can be arbitrarily distributed. Under this situation, the QoS requirements should account for the worst-case channel estimation error distribution. While directly finding the worst-case distribution is challenging, two methods are proposed to solve the robust transceiver design problem. One is based on the Markov’s inequality, while the other is based on a novel duality method. Two convergence-guaranteed iterative algorithms are proposed to solve the transceiver design problems. Furthermore, for the special case of MU multiple-input single-output (MISO) systems, the corresponding robust transceiver design problems are shown to be convex. Simulation results show that, compared to the non-robust method, the QoS requirement is satisfied by both proposed algorithms. Among the two proposed methods, the duality method shows a superior performance in transmit power, while the Markov method demonstrates a lower computational complexity. Furthermore, the proposed duality method results in less conservative QoS performance than the Gaussian approximated probabilistic robust method and bounded robust method.published_or_final_versio
Robust Transmissions in Wireless Powered Multi-Relay Networks with Chance Interference Constraints
In this paper, we consider a wireless powered multi-relay network in which a
multi-antenna hybrid access point underlaying a cellular system transmits
information to distant receivers. Multiple relays capable of energy harvesting
are deployed in the network to assist the information transmission. The hybrid
access point can wirelessly supply energy to the relays, achieving multi-user
gains from signal and energy cooperation. We propose a joint optimization for
signal beamforming of the hybrid access point as well as wireless energy
harvesting and collaborative beamforming strategies of the relays. The
objective is to maximize network throughput subject to probabilistic
interference constraints at the cellular user equipment. We formulate the
throughput maximization with both the time-switching and power-splitting
schemes, which impose very different couplings between the operating parameters
for wireless power and information transfer. Although the optimization problems
are inherently non-convex, they share similar structural properties that can be
leveraged for efficient algorithm design. In particular, by exploiting
monotonicity in the throughput, we maximize it iteratively via customized
polyblock approximation with reduced complexity. The numerical results show
that the proposed algorithms can achieve close to optimal performance in terms
of the energy efficiency and throughput.Comment: 14 pages, 8 figure
Robust Linear Precoder Design for Multi-cell Downlink Transmission
Coordinated information processing by the base stations of multi-cell
wireless networks enhances the overall quality of communication in the network.
Such coordinations for optimizing any desired network-wide quality of service
(QoS) necessitate the base stations to acquire and share some channel state
information (CSI). With perfect knowledge of channel states, the base stations
can adjust their transmissions for achieving a network-wise QoS optimality. In
practice, however, the CSI can be obtained only imperfectly. As a result, due
to the uncertainties involved, the network is not guaranteed to benefit from a
globally optimal QoS. Nevertheless, if the channel estimation perturbations are
confined within bounded regions, the QoS measure will also lie within a bounded
region. Therefore, by exploiting the notion of robustness in the worst-case
sense some worst-case QoS guarantees for the network can be asserted. We adopt
a popular model for noisy channel estimates that assumes that estimation noise
terms lie within known hyper-spheres. We aim to design linear transceivers that
optimize a worst-case QoS measure in downlink transmissions. In particular, we
focus on maximizing the worst-case weighted sum-rate of the network and the
minimum worst-case rate of the network. For obtaining such transceiver designs,
we offer several centralized (fully cooperative) and distributed (limited
cooperation) algorithms which entail different levels of complexity and
information exchange among the base stations.Comment: 38 Pages, 7 Figures, To appear in the IEEE Transactions on Signal
Processin
Robust Transceiver Design for Covert Integrated Sensing and Communications With Imperfect CSI
We propose a robust transceiver design for a covert integrated sensing and
communications (ISAC) system with imperfect channel state information (CSI).
Considering both bounded and probabilistic CSI error models, we formulate
worst-case and outage-constrained robust optimization problems of joint
trasceiver beamforming and radar waveform design to balance the radar
performance of multiple targets while ensuring communications performance and
covertness of the system. The optimization problems are challenging due to the
non-convexity arising from the semi-infinite constraints (SICs) and the coupled
transceiver variables. In an effort to tackle the former difficulty,
S-procedure and Bernstein-type inequality are introduced for converting the
SICs into finite convex linear matrix inequalities (LMIs) and second-order cone
constraints. A robust alternating optimization framework referred to
alternating double-checking is developed for decoupling the transceiver design
problem into feasibility-checking transmitter- and receiver-side subproblems,
transforming the rank-one constraints into a set of LMIs, and verifying the
feasibility of beamforming by invoking the matrix-lifting scheme. Numerical
results are provided to demonstrate the effectiveness and robustness of the
proposed algorithm in improving the performance of covert ISAC systems
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