15 research outputs found

    Physical Layer Service Integration in 5G: Potentials and Challenges

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    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

    Physical-Layer Security in Wireless Communication Systems

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    The use of wireless networks has grown significantly in contemporary times, and continues to develop further. The broadcast nature of wireless communications, however, makes them particularly vulnerable to eavesdropping. Unlike traditional solutions, which usually handle security at the application layer, the primary concern of this dissertation is to analyze and develop solutions based on coding techniques at the physical-layer. First, in chapter 22, we consider a scenario where a source node wishes to broadcast two confidential messages to two receivers, while a wire-tapper also receives the transmitted signal. This model is motivated by wireless communications, where individual secure messages are broadcast over open media and can be received by any illegitimate receiver. The secrecy level is measured by the equivocation rate at the eavesdropper. We first study the general (non-degraded) broadcast channel with an eavesdropper, and present an inner bound on the secrecy capacity region for this model. This inner bound is based on a combination of random binning, and the Gelfand-Pinsker binning. We further study the situation in which the channels are degraded. For the degraded broadcast channel with an eavesdropper, we present the secrecy capacity region. Our achievable coding scheme is based on Cover's superposition scheme and random binning. We refer to this scheme as the Secret Superposition Scheme. Our converse proof is based on a combination of the converse proof of the conventional degraded broadcast channel and Csiszar Lemma. We then assume that the channels are Additive White Gaussian Noise and show that the Secret Superposition Scheme with Gaussian codebook is optimal. The converse proof is based on Costa's entropy power inequality. Finally, we use a broadcast strategy for the slowly fading wire-tap channel when only the eavesdropper's channel is fixed and known at the transmitter. We derive the optimum power allocation for the coding layers, which maximizes the total average rate. Second, in chapter 33 , we consider the Multiple-Input-Multiple-Output (MIMO) scenario of a broadcast channel where a wiretapper also receives the transmitted signal via another MIMO channel. First, we assume that the channels are degraded and the wiretapper has the worst channel. We establish the capacity region of this scenario. Our achievability scheme is the Secret Superposition Coding. For the outerbound, we use notion of the enhanced channels to show that the secret superposition of Gaussian codes is optimal. We show that we only need to enhance the channels of the legitimate receivers, and the channel of the eavesdropper remains unchanged. We then extend the result of the degraded case to a non-degraded case. We show that the secret superposition of Gaussian codes, along with successive decoding, cannot work when the channels are not degraded. We develop a Secret Dirty Paper Coding scheme and show that it is optimal for this channel. We then present a corollary generalizing the capacity region of the two receivers case to the case of multiple receivers. Finally, we investigate a scenario which frequently occurs in the practice of wireless networks. In this scenario, the transmitter and the eavesdropper have multiple antennae, while both intended receivers have a single antenna (representing resource limited mobile units). We characterize the secrecy capacity region in terms of generalized eigenvalues of the receivers' channels and the eavesdropper's channel. We refer to this configuration as the MISOME case. We then present a corollary generalizing the results of the two receivers case to multiple receivers. In the high SNR regime, we show that the capacity region is a convex closure of rectangular regions. Finally, in chapter 44, we consider a KK-user secure Gaussian Multiple-Access-Channel with an external eavesdropper. We establish an achievable rate region for the secure discrete memoryless MAC. Thereafter, we prove the secrecy sum capacity of the degraded Gaussian MIMO MAC using Gaussian codebooks. For the non-degraded Gaussian MIMO MAC, we propose an algorithm inspired by the interference alignment technique to achieve the largest possible total Secure-Degrees-of-Freedom . When all the terminals are equipped with a single antenna, Gaussian codebooks have shown to be inefficient in providing a positive S-DoF. Instead, we propose a novel secure coding scheme to achieve a positive S-DoF in the single antenna MAC. This scheme converts the single-antenna system into a multiple-dimension system with fractional dimensions. The achievability scheme is based on the alignment of signals into a small sub-space at the eavesdropper, and the simultaneous separation of the signals at the intended receiver. We use tools from the field of Diophantine Approximation in number theory to analyze the probability of error in the coding scheme. We prove that the total S-DoF of K1K\frac{K-1}{K} can be achieved for almost all channel gains. For the other channel gains, we propose a multi-layer coding scheme to achieve a positive S-DoF. As a function of channel gains, therefore, the achievable S-DoF is discontinued

    A Critical Review of Physical Layer Security in Wireless Networking

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    Wireless networking has kept evolving with additional features and increasing capacity. Meanwhile, inherent characteristics of wireless networking make it more vulnerable than wired networks. In this thesis we present an extensive and comprehensive review of physical layer security in wireless networking. Different from cryptography, physical layer security, emerging from the information theoretic assessment of secrecy, could leverage the properties of wireless channel for security purpose, by either enabling secret communication without the need of keys, or facilitating the key agreement process. Hence we categorize existing literature into two main branches, namely keyless security and key-based security. We elaborate the evolution of this area from the early theoretic works on the wiretap channel, to its generalizations to more complicated scenarios including multiple-user, multiple-access and multiple-antenna systems, and introduce not only theoretical results but practical implementations. We critically and systematically examine the existing knowledge by analyzing the fundamental mechanics for each approach. Hence we are able to highlight advantages and limitations of proposed techniques, as well their interrelations, and bring insights into future developments of this area

    Secure Multiuser Communications in Wireless Sensor Networks with TAS and Cooperative Jamming

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    In this paper, we investigate the secure transmission in wireless sensor networks (WSNs) consisting of one multiple-antenna base station (BS), multiple single-antenna legitimate users, one single-antenna eavesdropper and one multiple-antenna cooperative jammer. In an effort to reduce the scheduling complexity and extend the battery lifetime of the sensor nodes, the switch-and-stay combining (SSC) scheduling scheme is exploited over the sensor nodes. Meanwhile, transmit antenna selection (TAS) is employed at the BS and cooperative jamming (CJ) is adopted at the jammer node, aiming at achieving a satisfactory secrecy performance. Moreover, depending on whether the jammer node has the global channel state information (CSI) of both the legitimate channel and the eavesdropper's channel, it explores a zero-forcing beamforming (ZFB) scheme or a null-space artificial noise (NAN) scheme to confound the eavesdropper while avoiding the interference to the legitimate user. Building on this, we propose two novel hybrid secure transmission schemes, termed TAS-SSC-ZFB and TAS-SSC-NAN, for WSNs. We then derive the exact closed-form expressions for the secrecy outage probability and the effective secrecy throughput of both schemes to characterize the secrecy performance. Using these closed-form expressions, we further determine the optimal switching threshold and obtain the optimal power allocation factor between the BS and jammer node for both schemes to minimize the secrecy outage probability, while the optimal secrecy rate is decided to maximize the effective secrecy throughput for both schemes. Numerical results are provided to verify the theoretical analysis and illustrate the impact of key system parameters on the secrecy performance.This work was supported by the National Science Foundation of China (No. 61501507), and the Jiangsu Provincial Natural Science Foundation of China (No. BK20150719). The work of Nan Yang is supported by the Australian Research Council Discovery Project (DP150103905)

    Artificial Noise: Transmission Optimization in Multi-Input Single-Output Wiretap Channels

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    We analyze and optimize the secrecy performance of artificial noise (AN) in multi-input single-output wiretap channels with multiple antennas at the transmitter and a single antenna at the receiver and the eavesdropper. We consider two transmission schemes: 1) an on-off transmission scheme with a constant secrecy rate for all transmission periods, and 2) an adaptive transmission scheme with a varying secrecy rate during each transmission period. For the on-off transmission scheme, an easy-to-compute expression is derived for the hybrid outage probability, which allows us to evaluate the transmission outage probability and the secrecy outage probability. For the adaptive transmission scheme where transmission outage does not occur, we derive a closedform expression for the secrecy outage probability. Using these expressions, we determine the optimal power allocation between the information signal and the AN signal and also determine the optimal secrecy rate such that the effective secrecy throughput is maximized for both transmission schemes. We show that the maximum effective secrecy throughput requires more power to be allocated to the AN signal when the quality of the transmitterreceiver channel or the transmitter-eavesdropper channel improves. We also show that both transmission schemes achieve a higher maximum effective secrecy throughput while incurring a lower secrecy outage probability than existing schemes.ARC Discovery Projects Grant DP150103905

    Application of evolutionary computation techniques in emerging optimization problems in 5G and beyond wireless systems

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    Tese (doutorado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Engenharia Elétrica, Florianópolis, 2021.Os sistemas comunicação sem fio 5G e além (B5G, do inglês Beyong 5G) permitirão a plena implantação de aplicações existentes, como carros autônomos, redes de sensores massivas e casas inteligentes. Para tornar essas aplicações possíveis, requisitos rigorosos, como alta eficiência espectral e ultra baixa latência de comunicação, devem ser atendidos. Para atender a esses requisitos, diferentes tecnologias-chave estão em desenvolvimento, como comunicações de Ondas Milimétricas (mmWave, do inglês Millimeter Wave) e Superfícies Refletivas Inteligentes (IRS, do inglês Intelligent Reflecting Surfaces). As comunicações mmWave têm atraído grande interesse devido ao abundante espectro de frequência disponível, ao contrário das bandas congestionadas adotadas nas redes 4G. No entanto, as bandas mmWave apresentam características de propagação desfavoráveis. Para superar tais problemas de propagação, o uso de beamforming altamente direcional é uma solução eficaz. Além disso, recentemente, uma tecnologia de baixo custo e alta eficiência energética denominada IRS, uma meta-superfície equipada com um grande número de elementos passivos de baixo custo, capaz de refletir o sinal incidente com uma dada mudança de fase/amplitude, foi desenvolvida para otimizar a capacidade da rede. Implantando densamente IRSs em redes de comunicação sem fio e coordenando seus elementos de maneira inteligente, os canais sem fio entre o transmissor e o receptor podem ser intencional e deterministicamente controlados para melhorar a qualidade do sinal no receptor. Embora essas tecnologias tenham inúmeros benefícios para o desempenho do sistema, elas apresentam muitos desafios em sua implantação. Mais especificamente, embora as bandas mmWave permitam considerar o uso de beamforming altamente direcional tanto na BS quanto no UE, isto pode representar um desafio para o processo de Acesso Inicial (IA, do inglês Initial Access) pois, uma vez que a transmissão omnidirecional não pode ser aplicada, devido ao seu baixo ganho de potência e SNR recebido, a duração geral do IA pode ser muito longa. O atraso causado pela busca direcional deve ser pequeno para atender a alguns dos requisitos das redes B5G como baixa latência de ponta-a-ponta. Além disso, apesar da capacidade das IRSs de controlar os canais sem fio, o projeto do beamforming na BS e na IRS é um problema desafiador devido à necessidade de estimar a informação de estado do canal (CSI, do inglês Channel State Information) de todos os links do sistema. No entanto, para estimar o CSI entre a IRS e a BS ou entre a IRS e o UE, cada elemento da IRS precisa ser equipado com uma cadeia de radiofrequência (RF, do inglês Radio Frequency), o que aumenta consideravelmente o custo e o consumo de energia do sistema e vai contra algumas das principais vantagens de utilizar IRSs em sistemas de comunicação sem fio. Portanto, motivados pelos problemas emergentes acima, nesta tese, pretendemos desenvolver novos métodos baseados em técnicas de Computação Evolutiva tais como, Algoritmos Genéticos (GA, do inglês Genetic Algorithm) e Otimização por Enxame de Partículas (PSO, do inglês Particle Swarm Optimization), visando resolver o problema de IA e realizar o projeto do beamforming na BS e IRS sem conhecimento prévio do CSI na BS. Os resultados obtidos nesta tese mostram que os métodos desenvolvidos podem reduzir consideravelmente o atraso e alcançar um desempenho próximo ao ótimo no problema de projeto do beamforming na BS e IRS com sobrecarga de treinamento reduzida.Abstract: Beyond 5G (B5G) wireless systems will enable the deployment of demanding applications such as autonomous cars, massive sensor networks, and smart homes. To make these applications possible, stringent requirements such as improved spectrum efficiency and low communication latency must be fulfilled. In order to meet these requirements, different key technologies are in development such as millimeter Wave (mmWave) communications and Intelligent Reflecting Surfaces (IRS). The mmWave communications have attracted great interest due to the abundant available spectrum, unlike the congested bands adopted in the 4G networks. However, the mmWave bands present poor propagation characteristics. To overcome these propagation issues, the use of highly directional beamforming is an effective solution. In addition, recently, an energy-efficient and low-cost technology named IRS, which is a meta-surface equipped with a large number of low-cost passive elements, capable of reflecting the incident signal with a given phase/amplitude shift, was developed to increase the network capacity. By densely deploying IRSs in wireless communication networks and intelligently coordinating their elements, the wireless channels between the transmitter and receiver can be intentionally and deterministically controlled to improve the signal quality at the receiver. Although these technologies have uncountable benefits for the system performance, they present many challenges in their deployment. More specifically, although the mmWave bands allow to consider highly directional beamforming at the BS and UE, this can be challenging for the Initial Access (IA) process. Since omnidirectional transmission may not be applied, due to its low power gain and received SNR, the overall duration of IA can be very long. The delay caused by directional search must be small to meet some of the B5G requirements for low end-to-end latency. Moreover, despite the capacity of controlling the wireless channels of the IRSs, designing the beamforming at the BS and at the IRS is a challenging problem due to the necessity of estimating the channel state information (CSI) of all system links. However, to estimate the CSI between IRS and BS or between IRS and UE, each element of the IRS needs to be equipped with one radio-frequency (RF) chain which greatly increases the cost and energy consumption of the system and goes against some of the original advantages of using an IRS. Therefore, motivated by the above emerging problems, in this thesis, we intend to develop new methods based on Evolutionary Computation techniques, i.e., Genetic Algorithms (GA) and Particle Swarm Optimization (PSO), to solve the IA problem and to design the beamforming at the BS and IRS without CSI. Results show that the developed methods can reduce the IA delay and achieve a close-to-optimal performance in the IRS beamforming problem with reduced training overhead
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