666 research outputs found
Resource Allocation for Secure Communication in Systems with Wireless Information and Power Transfer
This paper considers secure communication in a multiuser multiple-input
single-output (MISO) downlink system with simultaneous wireless information and
power transfer. We study the design of resource allocation algorithms
minimizing the total transmit power for the case when the receivers are able to
harvest energy from the radio frequency. In particular, the algorithm design is
formulated as a non-convex optimization problem which takes into account
artificial noise generation to combat potential eavesdroppers, a minimum
required signal-to-interference-plus-noise ratio (SINR) at the desired
receiver, maximum tolerable SINRs at the potential eavesdroppers, and a minimum
required power delivered to the receivers. We adopt a semidefinite programming
(SDP) relaxation approach to obtain an upper bound solution for the considered
problem. The tightness of the upper bound is revealed by examining a sufficient
condition for the global optimal solution. Inspired by the sufficient
condition, we propose two suboptimal resource allocation schemes enhancing
secure communication and facilitating efficient energy harvesting. Simulation
results demonstrate a close-to-optimal performance achieved by the proposed
suboptimal schemes and significant transmit power savings by optimization of
the artificial noise generation.Comment: 7 pages, 5 figures, and 1 table. Submitted for possible conference
publicatio
Max-min Fair Wireless Energy Transfer for Secure Multiuser Communication Systems
This paper considers max-min fairness for wireless energy transfer in a
downlink multiuser communication system. Our resource allocation design
maximizes the minimum harvested energy among multiple multiple-antenna energy
harvesting receivers (potential eavesdroppers) while providing quality of
service (QoS) for secure communication to multiple single-antenna information
receivers. In particular, the algorithm design is formulated as a non-convex
optimization problem which takes into account a minimum required
signal-to-interference-plus-noise ratio (SINR) constraint at the information
receivers and a constraint on the maximum tolerable channel capacity achieved
by the energy harvesting receivers for a given transmit power budget. The
proposed problem formulation exploits the dual use of artificial noise
generation for facilitating efficient wireless energy transfer and secure
communication. A semidefinite programming (SDP) relaxation approach is
exploited to obtain a global optimal solution of the considered problem.
Simulation results demonstrate the significant performance gain in harvested
energy that is achieved by the proposed optimal scheme compared to two simple
baseline schemes.Comment: 5 pages, invited paper, IEEE Information Theory Workshop 2014,
Hobart, Tasmania, Australia, Nov. 201
Secure Layered Transmission in Multicast Systems with Wireless Information and Power Transfer
This paper considers downlink multicast transmit beamforming for secure
layered transmission systems with wireless simultaneous information and power
transfer. We study the power allocation algorithm design for minimizing the
total transmit power in the presence of passive eavesdroppers and energy
harvesting receivers. The algorithm design is formulated as a non-convex
optimization problem. Our problem formulation promotes the dual use of energy
signals in providing secure communication and facilitating efficient energy
transfer. Besides, we take into account a minimum required power for energy
harvesting at the idle receivers and heterogeneous quality of service (QoS)
requirements for the multicast video receivers. In light of the intractability
of the problem, we reformulate the considered problem by replacing a non-convex
probabilistic constraint with a convex deterministic constraint. Then, a
semidefinite programming relaxation (SDR) approach is adopted to obtain an
upper solution for the reformulated problem. Subsequently, sufficient
conditions for the global optimal solution of the reformulated problem are
revealed. Furthermore, we propose two suboptimal power allocation schemes based
on the upper bound solution. Simulation results demonstrate the excellent
performance and significant transmit power savings achieved by the proposed
schemes compared to isotropic energy signal generation.Comment: 7 pages, 3 figures, accepted for presentation at the IEEE
International Conference on Communications (ICC), Sydney, Australia, 201
Power Efficient MISO Beamforming for Secure Layered Transmission
This paper studies secure layered video transmission in a multiuser
multiple-input single-output (MISO) beamforming downlink communication system.
The power allocation algorithm design is formulated as a non-convex
optimization problem for minimizing the total transmit power while guaranteeing
a minimum received signal-to-interference-plus-noise ratio (SINR) at the
desired receiver. In particular, the proposed problem formulation takes into
account the self-protecting architecture of layered transmission and artificial
noise generation to prevent potential information eavesdropping. A
semi-definite programming (SDP) relaxation based power allocation algorithm is
proposed to obtain an upper bound solution. A sufficient condition for the
global optimal solution is examined to reveal the tightness of the upper bound
solution. Subsequently, two suboptimal power allocation schemes with low
computational complexity are proposed for enabling secure layered video
transmission. Simulation results demonstrate significant transmit power savings
achieved by the proposed algorithms and layered transmission compared to the
baseline schemes.Comment: Accepted for presentation at the IEEE Wireless Communications and
Networking Conference (WCNC), Istanbul, Turkey, 201
Multiuser Precoding and Channel Estimation for Hybrid Millimeter Wave MIMO Systems
In this paper, we develop a low-complexity channel estimation for hybrid
millimeter wave (mmWave) systems, where the number of radio frequency (RF)
chains is much less than the number of antennas equipped at each transceiver.
The proposed channel estimation algorithm aims to estimate the strongest
angle-of-arrivals (AoAs) at both the base station (BS) and the users. Then all
the users transmit orthogonal pilot symbols to the BS via these estimated
strongest AoAs to facilitate the channel estimation. The algorithm does not
require any explicit channel state information (CSI) feedback from the users
and the associated signalling overhead of the algorithm is only proportional to
the number of users, which is significantly less compared to various existing
schemes. Besides, the proposed algorithm is applicable to both non-sparse and
sparse mmWave channel environments. Based on the estimated CSI, zero-forcing
(ZF) precoding is adopted for multiuser downlink transmission. In addition, we
derive a tight achievable rate upper bound of the system. Our analytical and
simulation results show that the proposed scheme offer a considerable
achievable rate gain compared to fully digital systems, where the number of RF
chains equipped at each transceiver is equal to the number of antennas.
Furthermore, the achievable rate performance gap between the considered hybrid
mmWave systems and the fully digital system is characterized, which provides
useful system design insights.Comment: 6 pages, accepted for presentation, ICC 201
- …