96 research outputs found
Symbol-Level Precoding Design Based on Distance Preserving Constructive Interference Regions
In this paper, we investigate the symbol-level precoding (SLP) design problem
in the downlink of a multiuser multiple-input single-output (MISO) channel. We
consider generic constellations with any arbitrary shape and size, and confine
ourselves to one of the main categories of constructive interference regions
(CIR), namely, distance preserving CIR (DPCIR). We provide a comprehensive
study of DPCIRs and derive some properties for these regions. Using these
properties, we first show that any signal in a given DPCIR has a norm greater
than or equal to the norm of the corresponding constellation point if and only
if the convex hull of the constellation contains the origin. It is followed by
proving that the power of the noiseless received signal lying on a DPCIR is a
monotonic strictly increasing function of two parameters relating to the
infinite Voronoi edges. Using the convex description of DPCIRs and their
properties, we formulate two design problems, namely, the SLP power
minimization with signal-to-interference-plus-noise ratio (SINR) constraints,
and the SLP SINR balancing problem under max-min fairness criterion. The SLP
power minimization based on DPCIRs can straightforwardly be written as a
quadratic program (QP). We provide a simplified reformulation of this problem
which is less computationally complex. The SLP max-min SINR, however, is
non-convex in its original form, and hence difficult to tackle. We propose
several alternative optimization approaches, including semidefinite program
(SDP) formulation and block coordinate descent (BCD) optimization. We discuss
and evaluate the loss due to the proposed alternative methods through extensive
simulation results.Comment: 19 pages, 12 figures, Submitted to IEEE Transactions in Signal
Processin
Symbol-Level Precoding Design Based on Distance Preserving Constructive Interference Regions
In this paper, we investigate the symbol-level precoding (SLP) design problem in the downlink of a multiuser multiple-input single-output (MISO) channel. We consider generic two-dimensional constellations with any shape and size, and confine ourselves to one of the main categories of constructive interference regions (CIR), namely, distance preserving CIR (DPCIR). We provide a comprehensive study of DPCIRs and derive several properties for these regions. Using these properties, we first show that any signal in a given DPCIR has a norm greater than or equal to the norm of the corresponding constellation point if and only if the convex hull of the constellation contains the origin. It is followed by proving that the power of the noise-free received signal in a DPCIR is a monotonic strictly increasing function of two parameters relating to the infinite Voronoi edges. Using the convex description of DPCIRs and their characteristics, we formulate two design problems, namely, the SLP power minimization with signal-to-interference-plus-noise ratio (SINR) constraints, and the SLP SINR balancing problem under max-min fairness criterion. The SLP power minimization based on DPCIRs can straightforwardly be written as a quadratic programming (QP). We derive a simplified reformulation of this problem which is less computationally complex. The SLP max-min SINR, however, is non-convex in its original form, and hence difficult to tackle. We propose alternative optimization approaches, including semidefinite programming (SDP) formulation and block coordinate descent (BCD) optimization. We discuss and evaluate the loss due to the proposed alternative methods through extensive simulation results
Power Minimizer Symbol-Level Precoding: A Closed-Form Sub-Optimal Solution
In this letter, we study the optimal solution of the multiuser symbol-level
precoding (SLP) for minimization of the total transmit power under given
signal-to-interference-plus-noise ratio (SINR) constraints. Adopting the
distance preserving constructive interference regions (DPCIR), we first derive
a simplified reformulation of the problem. Then, we analyze the structure of
the optimal solution using the Karush-Kuhn-Tucker (KKT) optimality conditions,
thereby we obtain the necessary and sufficient condition under which the power
minimizer SLP is equivalent to the conventional zero-forcing beamforming
(ZFBF). This further leads us to a closed-form sub-optimal SLP solution
(CF-SLP) for the original problem. Simulation results show that CF-SLP provides
significant gains over ZFBF, while performing quite close to the optimal SLP in
scenarios with rather small number of users. The results further indicate that
the CF-SLP method has a reduction of order in computational time
compared to the optimal solution.Comment: 7 pages, 1 figure, 1 table, submitted to IEEE signal processing
letter
Symbol-Level Precoding Design for Max-Min SINR in Multiuser MISO Broadcast Channels
In this paper, we address the symbol level precoding (SLP) design problem
under max-min SINR criterion in the downlink of multiuser multiple-input
single-output (MISO) channels. First, we show that the distance preserving
constructive interference regions (DPCIR) are always polyhedral angles (shifted
pointed cones) for any given constellation point with unbounded decision
region. Then we prove that any signal in a given unbounded DPCIR has a norm
larger than the norm of the corresponding vertex if and only if the convex hull
of the constellation contains the origin. Using these properties, we show that
the power of the noiseless received signal lying on an unbounded DPCIR is an
strictly increasing function of two parameters. This allows us to reformulate
the originally non-convex SLP max-min SINR as a convex optimization problem. We
discuss the loss due to our proposed convex reformulation and provide some
simulation results.Comment: Submitted to SPAWC 2018, 7 pages, 2 figure
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Rethinking Secure Precoding via Interference Exploitation: A Smart Eavesdropper Perspective
Based on the concept of constructive interference (CI), multiuser
interference (MUI) has recently been shown to be beneficial for communication
secrecy. A few CI-based secure precoding algorithms have been proposed that use
both the channel state information (CSI) and knowledge of the instantaneous
transmit symbols. In this paper, we examine the CI-based secure precoding
problem with a focus on smart eavesdroppers that exploit statistical
information gleaned from the precoded data for symbol detection. Moreover, the
impact of correlation between the main and eavesdropper channels is taken into
account. We first modify an existing CI-based preocding scheme to better
utilize the destructive impact of the interference. Then, we point out the
drawback of both the existing and the new modified CI-based precoders when
faced with a smart eavesdropper. To address this deficiency, we provide a
general principle for precoder design and then give two specific design
examples. Finally, the scenario where the eavesdropper's CSI is unavailable is
studied. Numerical results show that although our modified CI-based precoder
can achieve a better energy-secrecy trade-off than the existing approach, both
have a limited secrecy benefit. On the contrary, the precoders developed using
the new CI-design principle can achieve a much improved trade-off and
significantly degrade the eavesdropper's performance
Boosting SWIPT via Symbol-Level Precoding
In this paper, we investigate a simultaneous wireless information and power transmission (SWIPT) system, wherein a single multi-antenna transmitter serves multiple single-antenna users which employ the power-splitting (PS) receiver architecture. We formulate a Symbol-Level Precoding (SLP) based transmit power minimization problem dependent on the minimum signal-to-interference-plus-noise ratio (SINR) and energy harvesting (EH) thresholds. We solve the corresponding non-negative convex quadratic optimization problem per time frame of transmitted symbols and study the benefits of proposed design under Zero-Forcing (ZF) Precoding, Direct Demand SLP (DD-SLP), and Squared-Root Demand SLP (RD-SLP) techniques. A static PS-ratio is fixed according to the SINR and EH demands to enable the segregation of intended received signals for information decoding (ID) and EH, respectively. Numerical results show the property conservation of SINR-enhancement via SLP at the ID unit while increasing the harvested energy at each of the end-users
Robust SINR-Constrained Symbol-Level Multiuser Precoding with Imperfect Channel Knowledge
In this paper, we address robust design of symbol-level precoding for the
downlink of multiuser multiple-input multiple-output wireless channels, in the
presence of imperfect channel state information (CSI) at the transmitter. In
particular, we consider two common uncertainty models for the CSI imperfection,
namely, spherical (bounded) and stochastic (Gaussian). Our design objective is
to minimize the total (per-symbol) transmission power subject to constructive
interference (CI) constraints as well as users' quality-of-service requirements
in terms of signal-to-interference-plus-noise ratio. Assuming bounded channel
uncertainties, we obtain a convex CI constraint based on the worst-case robust
analysis, whereas in the case of Gaussian uncertainties, we define
probabilistic CI constraints in order to achieve robustness to
statistically-known CSI errors. Since the probabilistic constraints of actual
interest are difficult to handle, we resort to their convex approximations,
yielding tractable (deterministic) robust constraints. Three convex
approximations are developed based on different robust conservatism approaches,
among which one is introduced as a benchmark for comparison. We show that each
of our proposed approximations is tighter than the other under specific
robustness conditions, while both always outperform the benchmark. Using the
developed CI constraints, we formulate the robust precoding optimization as a
convex conic quadratic program. Extensive simulation results are provided to
validate our analytic discussions and to make comparisons with existing robust
precoding schemes. We also show that the robust design increases the
computational complexity by an order of the number of users in the large system
limit, compared to its non-robust counterpart.Comment: 19 pages, 9 figures, Submitted to IEEE Transactions in Signal
Processin
Robust SINR-Constrained Symbol-Level Multiuser Precoding With Imperfect Channel Knowledge
In this paper, we address robust design of symbol-level precoding (SLP) for the downlink of multiuser multiple-input single-output wireless channels, when imperfect channel state information (CSI) is available at the transmitter. In particular, we consider a well known model for the CSI imperfection, namely, stochastic Gaussian-distributed uncertainty. Our design objective is to minimize the total (per-symbol) transmission power subject to constructive interference (CI) constraints as well as the users’ quality-of-service requirements in terms of signal-to-interference-plus-noise ratio. Assuming stochastic channel uncertainties, we first define probabilistic CI constraints in order to achieve robustness to statistically known CSI errors. Since these probabilistic constraints are difficult to handle, we resort to their convex approximations in the form of tractable (deterministic) robust constraints. Three convex approximations are obtained based on different conservatism levels, among which one is introduced as a benchmark for comparison. We show that each of our proposed approximations is tighter than the other under specific robustness settings, while both of them always outperform the benchmark. Using the proposed CI constraints, we formulate the robust SLP optimization problem as a second-order cone program. Extensive simulation results are provided to validate our analytic discussions and to make comparisons with conventional block-level robust precoding schemes. We show that the robust design of symbol-level precoder leads to an improved performance in terms of energy efficiency at the cost of increasing the computational complexity by an order of the number of users in the large system limit, compared to its non-robust counterpart
NOMA Made Practical: Removing the SIC through Constructive Interference
In this paper a novel constructive multiple access (CoMA) scheme is proposed. The new CoMA technique aligns the superimposed signals to the users constructively to the signal of interest. Accordingly, there is no need to remove it at the receiver using successive interference cancellation (SIC) technique. In this regard, optimal CoMA precoders are designed for user paring NOMA multiple-input-single-output (MISO) systems. The results in this paper show that CoMA is an attractive solution for NOMA systems with low number of antennas, and transmission power
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