9,335 research outputs found
Principles of Physical Layer Security in Multiuser Wireless Networks: A Survey
This paper provides a comprehensive review of the domain of physical layer
security in multiuser wireless networks. The essential premise of
physical-layer security is to enable the exchange of confidential messages over
a wireless medium in the presence of unauthorized eavesdroppers without relying
on higher-layer encryption. This can be achieved primarily in two ways: without
the need for a secret key by intelligently designing transmit coding
strategies, or by exploiting the wireless communication medium to develop
secret keys over public channels. The survey begins with an overview of the
foundations dating back to the pioneering work of Shannon and Wyner on
information-theoretic security. We then describe the evolution of secure
transmission strategies from point-to-point channels to multiple-antenna
systems, followed by generalizations to multiuser broadcast, multiple-access,
interference, and relay networks. Secret-key generation and establishment
protocols based on physical layer mechanisms are subsequently covered.
Approaches for secrecy based on channel coding design are then examined, along
with a description of inter-disciplinary approaches based on game theory and
stochastic geometry. The associated problem of physical-layer message
authentication is also introduced briefly. The survey concludes with
observations on potential research directions in this area.Comment: 23 pages, 10 figures, 303 refs. arXiv admin note: text overlap with
arXiv:1303.1609 by other authors. IEEE Communications Surveys and Tutorials,
201
Robust Lattice Alignment for K-user MIMO Interference Channels with Imperfect Channel Knowledge
In this paper, we consider a robust lattice alignment design for K-user
quasi-static MIMO interference channels with imperfect channel knowledge. With
random Gaussian inputs, the conventional interference alignment (IA) method has
the feasibility problem when the channel is quasi-static. On the other hand,
structured lattices can create structured interference as opposed to the random
interference caused by random Gaussian symbols. The structured interference
space can be exploited to transmit the desired signals over the gaps. However,
the existing alignment methods on the lattice codes for quasi-static channels
either require infinite SNR or symmetric interference channel coefficients.
Furthermore, perfect channel state information (CSI) is required for these
alignment methods, which is difficult to achieve in practice. In this paper, we
propose a robust lattice alignment method for quasi-static MIMO interference
channels with imperfect CSI at all SNR regimes, and a two-stage decoding
algorithm to decode the desired signal from the structured interference space.
We derive the achievable data rate based on the proposed robust lattice
alignment method, where the design of the precoders, decorrelators, scaling
coefficients and interference quantization coefficients is jointly formulated
as a mixed integer and continuous optimization problem. The effect of imperfect
CSI is also accommodated in the optimization formulation, and hence the derived
solution is robust to imperfect CSI. We also design a low complex iterative
optimization algorithm for our robust lattice alignment method by using the
existing iterative IA algorithm that was designed for the conventional IA
method. Numerical results verify the advantages of the proposed robust lattice
alignment method
MISO Capacity with Per-Antenna Power Constraint
We establish in closed-form the capacity and the optimal signaling scheme for
a MISO channel with per-antenna power constraint. Two cases of channel state
information are considered: constant channel known at both the transmitter and
receiver, and Rayleigh fading channel known only at the receiver. For the first
case, the optimal signaling scheme is beamforming with the phases of the beam
weights matched to the phases of the channel coefficients, but the amplitudes
independent of the channel coefficients and dependent only on the constrained
powers. For the second case, the optimal scheme is to send independent signals
from the antennas with the constrained powers. In both cases, the capacity with
per-antenna power constraint is usually less than that with sum power
constraint.Comment: 7 pages double-column, 3 figure
Exploiting Multi-Antennas for Opportunistic Spectrum Sharing in Cognitive Radio Networks
In cognitive radio (CR) networks, there are scenarios where the secondary
(lower priority) users intend to communicate with each other by
opportunistically utilizing the transmit spectrum originally allocated to the
existing primary (higher priority) users. For such a scenario, a secondary user
usually has to trade off between two conflicting goals at the same time: one is
to maximize its own transmit throughput; and the other is to minimize the
amount of interference it produces at each primary receiver. In this paper, we
study this fundamental tradeoff from an information-theoretic perspective by
characterizing the secondary user's channel capacity under both its own
transmit-power constraint as well as a set of interference-power constraints
each imposed at one of the primary receivers. In particular, this paper
exploits multi-antennas at the secondary transmitter to effectively balance
between spatial multiplexing for the secondary transmission and interference
avoidance at the primary receivers. Convex optimization techniques are used to
design algorithms for the optimal secondary transmit spatial spectrum that
achieves the capacity of the secondary transmission. Suboptimal solutions for
ease of implementation are also presented and their performances are compared
with the optimal solution. Furthermore, algorithms developed for the
single-channel transmission are also extended to the case of multi-channel
transmission whereby the secondary user is able to achieve opportunistic
spectrum sharing via transmit adaptations not only in space, but in time and
frequency domains as well.Comment: Extension of IEEE PIMRC 2007. 35 pages, 6 figures. Submitted to IEEE
Journal of Special Topics in Signal Processing, special issue on Signal
Processing and Networking for Dynamic Spectrum Acces
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