52 research outputs found
Spatially Selective Artificial-Noise Aided Transmit Optimization for MISO Multi-Eves Secrecy Rate Maximization
Consider an MISO channel overheard by multiple eavesdroppers. Our goal is to
design an artificial noise (AN)-aided transmit strategy, such that the
achievable secrecy rate is maximized subject to the sum power constraint.
AN-aided secure transmission has recently been found to be a promising approach
for blocking eavesdropping attempts. In many existing studies, the confidential
information transmit covariance and the AN covariance are not simultaneously
optimized. In particular, for design convenience, it is common to prefix the AN
covariance as a specific kind of spatially isotropic covariance. This paper
considers joint optimization of the transmit and AN covariances for secrecy
rate maximization (SRM), with a design flexibility that the AN can take any
spatial pattern. Hence, the proposed design has potential in jamming the
eavesdroppers more effectively, based upon the channel state information (CSI).
We derive an optimization approach to the SRM problem through both analysis and
convex conic optimization machinery. We show that the SRM problem can be recast
as a single-variable optimization problem, and that resultant problem can be
efficiently handled by solving a sequence of semidefinite programs. Our
framework deals with a general setup of multiple multi-antenna eavesdroppers,
and can cater for additional constraints arising from specific application
scenarios, such as interference temperature constraints in interference
networks. We also generalize the framework to an imperfect CSI case where a
worst-case robust SRM formulation is considered. A suboptimal but safe solution
to the outage-constrained robust SRM design is also investigated. Simulation
results show that the proposed AN-aided SRM design yields significant secrecy
rate gains over an optimal no-AN design and the isotropic AN design, especially
when there are more eavesdroppers.Comment: To appear in IEEE Trans. Signal Process., 201
Physical Layer Service Integration in 5G: Potentials and Challenges
High transmission rate and secure communication have been identified as the
key targets that need to be effectively addressed by fifth generation (5G)
wireless systems. In this context, the concept of physical-layer security
becomes attractive, as it can establish perfect security using only the
characteristics of wireless medium. Nonetheless, to further increase the
spectral efficiency, an emerging concept, termed physical-layer service
integration (PHY-SI), has been recognized as an effective means. Its basic idea
is to combine multiple coexisting services, i.e., multicast/broadcast service
and confidential service, into one integral service for one-time transmission
at the transmitter side. This article first provides a tutorial on typical
PHY-SI models. Furthermore, we propose some state-of-the-art solutions to
improve the overall performance of PHY-SI in certain important communication
scenarios. In particular, we highlight the extension of several concepts
borrowed from conventional single-service communications, such as artificial
noise (AN), eigenmode transmission etc., to the scenario of PHY-SI. These
techniques are shown to be effective in the design of reliable and robust
PHY-SI schemes. Finally, several potential research directions are identified
for future work.Comment: 12 pages, 7 figure
Optimising multiple antenna techniques for physical layer security
Wireless communications offer data transmission services anywhere and anytime, but with the inevitable cost of introducing major security vulnerabilities. Indeed, an eavesdropper can overhear a message conveyed over the open insecure wireless media putting at risk the confidentiality of the wireless users. Currently, the way to partially prevent eavesdropping attacks is by ciphering the information between the authorised parties through complex cryptographic algorithms. Cryptography operates in the upper layers of the communication model, bit it does not address the security problem where the attack is suffered: at the transmission level.
In this context, physical layer security has emerged as a promising framework to prevent eavesdropping attacks at the transmission level. Physical layer security is based on information-theoretic concepts and exploits the randomness and the uniqueness of the wireless channel. In this context, this thesis presents signal processing techniques to secure wireless networks at the physical layer by optimising the use of multiple-antennas. A masked transmission strategy is used to steer the confidential information towards the intended receiver, and, at the same time, broadcast an interfering signal to confuse unknown eavesdroppers. This thesis considers practical issues in multiple-antenna networks such as limited transmission resources and the lack of accurate information between the authorised transmission parties. The worst-case for the security, that occurs when a powerful eavesdropper takes advantage of any opportunity to put at risk the transmission confidentiality, is addressed. The techniques introduced improve the security by offering efficient and innovative transmission solutions to lock the communication at the physical layer. Notably, these transmission mechanisms strike a balance between confidentiality and quality to satisfy the practical requirements of modern wireless networks
Power Allocation in Multiuser Parallel Gaussian Broadcast Channels With Common and Confidential Messages
We consider a broadcast communication over parallel channels, where the transmitter sends K+1 messages: one common message to all users, and K confidential messages to each user, which need to be kept secret from all unintended users. We assume partial channel state information at the transmitter, stemming from noisy channel estimation. Our main goal is to design a power allocation algorithm in order to maximize the weighted sum rate of common and confidential messages under a total power constraint. The resulting problem for joint encoding across channels is formulated as the cascade of two problems, the inner min problem being discrete, and the outer max problem being convex. Thereby, efficient algorithms for this kind of optimization program can be used as solutions to our power allocation problem. For the special case K=2 , we provide an almost closed-form solution, where only two single variables must be optimized, e.g., through dichotomic searches. To reduce computational complexity, we propose three new algorithms, maximizing the weighted sum rate achievable by two suboptimal schemes that perform per-user and per-channel encoding. By numerical results, we assess the performance of all proposed algorithms as a function of different system parameters
Transmit optimization techniques for physical layer security
PhD ThesisOver the last several decades, reliable communication has received considerable
attention in the area of dynamic network con gurations and
distributed processing techniques. Traditional secure communications
mainly considered transmission cryptography, which has been developed
in the network layer. However, the nature of wireless transmission introduces
various challenges of key distribution and management in establishing
secure communication links. Physical layer security has been
recently recognized as a promising new design paradigm to provide security
in wireless networks in addition to existing conventional cryptographic
methods, where the physical layer dynamics of fading channels
are exploited to establish secure wireless links. On the other hand, with
the ever-increasing demand of wireless access users, multi-antenna transmission
has been considered as one of e ective approaches to improve
the capacity of wireless networks. Multi-antenna transmission applied
in physical layer security has extracted more and more attentions by
exploiting additional degrees of freedom and diversity gains.
In this thesis, di erent multi-antenna transmit optimization techniques
are developed for physical layer secure transmission. The secrecy rate
optimization problems (i.e., power minimization and secrecy rate maximization)
are formulated to guarantee the optimal power allocation.
First, transmit optimization for multiple-input single-output (MISO) secrecy
channels are developed to design secure transmit beamformer that
minimize the transmit power to achieve a target secrecy rate. Besides,
the associated robust scheme with the secrecy rate outage probability
constraint are presented with statistical channel uncertainty, where the
outage probability constraint requires that the achieved secrecy rate
exceeds certain thresholds with a speci c probability. Second, multiantenna
cooperative jammer (CJ) is presented to provide jamming services
that introduces extra interference to assist a multiple-input multipleoutput
(MIMO) secure transmission. Transmit optimization for this CJaided
MIMO secrecy channel is designed to achieve an optimal power
allocation. Moreover, secure transmission is achieved when the CJ introduces
charges for its jamming service based on the amount of the
interference caused to the eavesdropper, where the Stackelberg game
is proposed to handle, and the Stackelberg equilibrium is analytically
derived. Finally, transmit optimization for MISO secure simultaneous
wireless information and power transfer (SWIPT) is investigated, where
secure transmit beamformer is designed with/without the help of arti -
cial noise (AN) to maximize the achieved secrecy rate such that satisfy
the transmit power budget and the energy harvesting (EH) constraint.
The performance of all proposed schemes are validated by MATLAB
simulation results
Transmitter Optimization Techniques for Physical Layer Security
Information security is one of the most critical issues in wireless networks as the signals transmitted through wireless medium are more vulnerable for interception. Although the existing conventional security techniques are proven to be safe, the broadcast nature of wireless communications introduces different challenges in terms of key exchange and distributions. As a result, information theoretic physical layer security has been proposed to complement the conventional security techniques for enhancing security in wireless transmissions. On the other hand, the rapid growth of data rates introduces different challenges on power limited mobile devices in terms of energy requirements. Recently, research work on wireless power transfer claimed that it has been considered as a potential technique to extend the battery lifetime of wireless networks. However, the algorithms developed based on the conventional optimization approaches often require iterative techniques, which poses challenges for real-time processing. To meet the demanding requirements of future ultra-low latency and reliable networks, neural network (NN) based approach can be employed to determine the resource allocations in wireless communications.
This thesis developed different transmission strategies for secure transmission in wireless communications. Firstly, transmitter designs are focused in a multiple-input single-output simultaneous wireless information and power transfer system with unknown eavesdroppers. To improve the performance of physical layer security and the harvested energy, artificial noise is incorporated into the network to mask the secret information between the legitimate terminals. Then, different secrecy energy efficiency designs are considered for a MISO underlay cognitive radio network, in the presence of an energy harvesting receiver. In particular, these designs are developed with different channel state information assumptions at the transmitter. Finally, two different power allocation designs are investigated for a cognitive radio network to maximize the secrecy rate of the secondary receiver: conventional convex optimization framework and NN based algorithm
Achievable Secrecy Rates of an Energy Harvesting Device with a Finite Battery
In this paper, we investigate the achievable secrecy rates in an Energy Harvesting communication system composed of one transmitter and multiple receivers. In particular, because of the energy constraints and the channel conditions, it is important to understand when a device should transmit or not and how much power should be used. We introduce the Optimal Secrecy Policy in several scenarios. We show that, if the receivers demand high secrecy rates, then it is not always possible to satisfy all their requests. Thus, we introduce a scheme that chooses which receivers should be discarded. Also, we study how the system is influenced by the Channel State Information and, in particular, how the knowledge of the eavesdropper's channel changes the achievable rates
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