The evolution of 6G networks demands ultra-massive connectivity and intelligent radio environments, yet existing reconfigurable intelligent surface (RIS) technologies face critical limitations in hardware efficiency, dynamic control, and scalability. This paper introduces LLM-RIMSA, a transformative framework that integrates large language models (LLMs) with a novel reconfigurable intelligent metasurface antenna (RIMSA) architecture to address these challenges. Unlike conventional RIS designs, RIMSA employs parallel coaxial feeding and 2D metasurface integration, enabling each individual metamaterial element to independently adjust both its amplitude and phase. While traditional optimization and deep learning (DL) methods struggle with high-dimensional state spaces and prohibitive training costs for RIMSA control, LLM-RIMSA leverages pre-trained LLMs cross-modal reasoning and few-shot learning capabilities to dynamically optimize RIMSA configurations. Simulations demonstrate that LLM-RIMSA achieves state-of-the-art performance, outperforming conventional DL-based methods in sum rate while reducing training overhead. The proposed framework pave the way for LLM-driven intelligent radio environments.

In this paper, we explore the vulnerability of the physical uplink shared channel (PUSCH) to a new smart jamming attack in fifth generation (5G) new radio (NR), where an intelligent adversary first executes its attack by sniffing the downlink control information (DCI)-indicated resource scheduling information and then disrupts the PUSCH data transmission effectively and covertly by the precise jamming. To combat such kind of DCI sniffing based smart jamming (DCIS-SJ), we propose a novel method for effective DCIS-SJ suppression leveraging the DCI-scheduled subset identification and the PUSCH resource reconstruction. Our method fundamentally relies on the differences in the spatial domain feature under available control channel elements and resource block group granularities between legitimate users and the DCIS-SJ attacker, to selectively exclude unwanted elements while safeguarding the authenticity of the targeted transmissions. Numerical results evaluate and confirm the effectiveness of our method.

In this paper, we propose a dynamic agile reconfigurable intelligent surface antenna (DARISA) array integrated into multi-input multi-output (MIMO) transceivers. Each DARISA comprises a number of metasurface elements activated simultaneously via a parallel feed network. The proposed system enables rapid and intelligent phase response adjustments for each metasurface element within a single symbol duration, facilitating a dynamic agile adjustment of phase response (DAAPR) strategy. By analyzing the theoretical degrees of freedom (DoF) of the DARISA MIMO system under the DAAPR framework, we derive an explicit relationship between DoF and critical system parameters, including agility frequentness (i.e., the number of phase adjustments of metasurface elements during one symbol period), cluster angular spread of wireless channels, DARISA array size, and the number of transmit/receive DARISAs. The DoF result reveals a significant conclusion: when the number of receive DARISAs is smaller than that of transmit DARISAs, the DAAPR strategy of the DARISA MIMO enhances the overall system DoF. Furthermore, relying on DoF alone to measure channel capacity is insufficient, so we analyze the effective DoF (EDoF) that reflects the impacts of the DoF and channel matrix singular value distribution on capacity. We show channel capacity monotonically increases with EDoF, and optimize the agile phase responses of metasurface elements by using fractional programming (FP) and semidefinite relaxation (SDR) algorithms to maximize the EDoF. Simulations validate the theoretical DoF gains and reveal that increasing agility frequentness, metasurface element density, and phase quantization accuracy can enhance the EDoF. Additionally, densely deployed elements can compensate for the loss in communication performance caused by lower phase quantization accuracy.

This work is focused on safeguarding the security of a reconfigurable intelligent surface (RIS) based symbiotic radio (SR) system. In the considered system, a primary link coexists with an RIS-based backscatter link. For the primary link, physical layer security is used to ensure the confidentiality of the transmitted data, for which a null-space artificial noise scheme is adopted. For the RIS-based backscatter link, we design the reflection coefficients of the RIS so that it becomes covert to a third-party. Under the condition that the backscatter link is covert and its signal-to-noise ratio is above a pre-given threshold, the secrecy rate of the primary link is maximized by jointly optimizing the beamforming vector of the primary transmitter and the reflection coefficients of the RIS. The considered optimization problem is non-convex, and we present a penalty-based iterative method to handle with it, along with an alternating-optimization based initialization method. Numerical results reveal that even though the backscatter link interferes with the primary link, the secrecy rate of the primary link could still be increased as compared with the case without an RIS, which demonstrates the superiority of the RIS-SR technology.

The utilization of radio frequency (RF) signals for wireless sensing has garnered increasing attention. However, the radio environment is unpredictable and often unfavorable, the sensing accuracy of traditional RF sensing methods is often affected by adverse propagation channels from the transmitter to the receiver, such as fading and noise. In this paper, we propose employing distributed Reconfigurable Intelligent Metasurface Antennas (RIMSA) to detect the presence and location of objects where multiple RIMSA receivers (RIMSA Rxs) are deployed on different places. By programming their beamforming patterns, RIMSA Rxs can enhance the quality of received signals. The RF sensing problem is modeled as a joint optimization problem of beamforming pattern and mapping of received signals to sensing outcomes. To address this challenge, we introduce a deep reinforcement learning (DRL) algorithm aimed at calculating the optimal beamforming patterns and a neural network aimed at converting received signals into sensing outcomes. In addition, the malicious attacker may potentially launch jamming attack to disrupt sensing process. To enable effective sensing in interference-prone environment, we devise a combined loss function that takes into account the Signal to Interference plus Noise Ratio (SINR) of the received signals. The simulation results show that the proposed distributed RIMSA system can achieve more efficient sensing performance and better overcome environmental influences than centralized implementation. Furthermore, the introduced method ensures high-accuracy sensing performance even under jamming attack.

We examine a secure wireless communication system that is enabled by unmanned aerial vehicles (UAVs) in this research. In the wireless communication system with an eavesdropping UAV, we deploy a relay UAV to facilitate the transmission of confidential signals from the source station (denoted asS) to ground users. Additionally, we select an idle relay UAV to act as a cooperative jamming UAV, sending interference signals to the eavesdropping UAV. It is quite feasible that the eavesdropping UAV will leverage its mobility to improve the quality of its eavesdropping, making its trajectory unpredictable. First, to address the worst-case scenario for the ground user’s security performance, we assume the eavesdropping UAV approaches at the closest distance.We aim to maximize the worst secrecy rate under perfect CSI via designing the flight trajectory and transmission power of both the relay UAV and the jamming UAV. Second, we investigated the performance of the system’s secrecy outage probability under imperfect CSI. The presence of eavesdropping UAVs and the unpredictable nature of their environment makes traditional convex optimization methods mathematically complex for solving the trajectory optimization problem of the relay and jamming UAVs. To address this, we propose the Multi-Agent joint design trajectory and power (MAJDTP) algorithm based on the Multi-Agent Deep Deterministic Policy Gradient (MADDPG) algorithm to optimize the flight trajectory and transmission power of both UAVs. During the design and training process, the relay and jamming UAVs are treated as agents to derive their optimal flight paths and transmission energy. Finally, our approach surpasses the benchmark algorithm, as demonstrated by the simulation results.

Dynamic spectrum access (DSA) is a technology proposed to address issues, such as spectrum scarcity, inflexible spectrum management, and spectrum waste in wireless communication. This is crucial in supporting the escalating demands of spectrum particularly for Internet of Things (IoT)-based applications. Modeling the spectrum access problem as a Markov decision process (MDP) and incorporating deep reinforcement learning (DRL) have emerged as a cutting-edge approach to tackle this challenge. However, the application of DRL in spectrum access is vulnerability to malicious attacks, posing significant security threats. We introduce both glass-box adversarial attack and closed-box jamming attack over-the-air to assess the susceptibility of DRL-based spectrum access system. The simulation results demonstrate the destructive effect of these attack methods in disrupting the spectrum access process of DRL models, adversely affecting the overall performance of communication systems. Moreover, we propose effective defense mechanisms to mitigate potential threats posed by adversary on DRL-based spectrum access. By incorporating advanced defense mechanisms, we successfully enhance the robustness of the system, ensuring the secure and stable operation of the spectrum access system.

Received signal strength (RSS)-based localization techniques have gained much attention in location-based services (LBSs). However, the coexistence of unknown path loss exponent (PLE), uncertain sensor positions, and impulsive noise poses serious challenges to localization accuracy. To address the problem, we first model the impulsive noise as a Mixture of Gaussian (MoG) distribution with unknown parameters. Thus, the noise model and the channel model can be refined using the observed data under the variational Bayesian inference (VBI) framework, which is defined as the model refinement learning. We then propose a corresponding online target localization procedure with the refined noise distribution, PLE and sensor positions. The Bayesian Cramer-Rao bound (BCRB) is finally derived in terms of all unknown parameters. Simulation results together with real experiment demonstrate that the proposed VBI algorithm can effectively learn the true noise distribution, and the developed localization method exhibits robust localization performance in various scenarios.

Received signal strength (RSS)-based WiFi fingerprint localization has attracted much attention for global positioning system denied-areas. Deep neural network (DNN) has introduced innovative techniques for indoor localization. However, deep learning models are susceptible to adversarial attacks, so the performance of indoor positioning methods is seriously threatened by adversarial attacks. To improve the localization performance, we first investigate the impact of adversarial attacks on indoor localization systems. A secure adversarial location guard framework, adv-LG, is then developed. It consists of a transformer-based generative adversarial network (TransGAN) and a cleaner module. TransGAN is developed to learn the mapping from adversarial samples to clean ones, while the cleaner module aims to remove adversarial perturbations from the adversarial samples using the learned mapping. The cleaned data is finally fed into a deep learning model to achieve online localization. We compare the localization performance of the proposed adv-LG method with adversarial training (AT), Gaussian smoothing (GS), and autoencoder (AE)-based approaches on two publicly available datasets, i.e., UJIIndoorLoc and UTSIndoorLoc. The results show that adv-LG exhibits significant advantages in classification and localization performance under several typical adversarial attack scenarios.

Ensuring signal confidentiality against eavesdroppers is particularly challenging, especially with imperfect channel state information (CSI). To address this, we propose a novel approach leveraging reconfigurable intelligent surfaces (RISs) to enhance security and optimize transmission performance. This paper focuses on secure communication in symbiotic radio (SR) systems by investigating cooperative jamming-assisted transmission with RISs, providing a robust solution to these challenges. RIS-I, acting as a secondary transmitter (STx), multicasts confidential signals from the primary transmitter (Alice) to a primary user (Bob), protecting against eavesdropping by Eve. Additionally, RIS-I transmits its own signals to a secondary user (SU) using backscattering radio technology. Meanwhile, RIS-II serves as a cooperative jammer, converting received confidential signals from Alice into jamming signals by strategically adjusting its reflection coefficients to disrupt Eve’s reception. These RISs can operate cooperatively; when RIS-II transmits as an STx, RIS-I functions as a cooperative jammer. We explore two scenarios: 1. With perfect CSI for the wiretap channel, we propose a joint SDR(Semi-definite relaxation)+MM(Minorization-maximization) optimization algorithm to simultaneously optimize Alice’s beamforming vector and the RISs’ reflection coefficients. 2. With imperfect CSI, we derive the secrecy outage probability formula and evaluate the scheme’s performance across different scenarios. Numerical results demonstrate that RIS-assisted cooperative jamming significantly enhances the secrecy rate and reduces the secrecy outage probability for Bob, outperforming traditional RIS-assisted SR systems.

Intelligent reflection surface (IRS) has been used to assist communication by reflection and beamforming where a direct path is not available. Thus, IRS adjusts the wireless channel to enhance the data transmission efficiency with low power consumption. Recently, deep reinforcement learning (DRL) has been exploited in IRS coefficients optimization. IRS can be controlled by DRL to adapt their phase shift to the propagation environment and an expected reflection pattern can be obtained. However, due to the openness of wireless channel and the unexplainability of DRL, it is vulnerable to adversary attacks lauched through wireless channels. In this paper, we investigate a pilot contamination based backdoor attack against DRL based IRS beamforming, where an IRS controlled by an adversary attacker is used to contaminate the channel state information (CSI) during the training phase. The backdoor attack is covert because the adversary need not to know the legitimate pilot sequence and DRL performs well when the adversary IRS keeps inactive. We show that the backdoor attack can reduce the data rate significantly with the adversary IRS. At last, we propose a retraining method agaist the attack to recover the data rate.

Reconfigurable intelligent surface (RIS), which can manipulate the wireless environment, has recently been integrated into physical-layer key generation (PKG) systems to establish randomness symmetric keys in static environments. However, few studies have jointly considered the optimization and randomization of the RIS elements to simultaneously achieve a high key generation rate (KGR) and communication performance. This study proposes a RIS-assisted communication and security-integrated protocol for dual-function integration of communication enhancement and PKG in static environments. The protocol partitions RIS elements for beamforming and random beams for parallel execution, utilizing a sparsity adaptive matching pursuit-based channel estimation algorithm to obtain individual channel state information. Subsequently, an optimization problem is formulated for KGR maximization while satisfying quality of service (QoS) requirements. The non-convex optimization problem is addressed through monotonicity analysis and triangle inequality. We validate the efficacy of the proposed protocol by developing a 4.9 GHz RIS-assisted PKG prototype system, comprising modular hardware and flexible software. The field trials demonstrate a 30.81 bit/s KGR for static environments with an average received power increase of 10.6 dB, achieving effective simultaneous integration of communication and security.

This paper investigates an intelligent reflecting surface (IRS) aided green multiple-user downlink communication system. In contrast to the existing works that deploy the IRS in a fixed location, the location of the IRS is taken as an optimization variable to minimize the total transmit power by jointly optimizing the location of the IRS, transmit beamformers at the base station (BS), and IRS phase shifts. We point out a critical conclusion that before and after IRS deployment, the channel state information (CSI) of all the communication terminals is different, so an offline-online hybrid-CSI optimization framework is proposed to solve the problem. In the offline stage, we optimize the IRS location with only the statistical CSI (S-CSI) so the ergodic quality of service (QoS) constraints have to be considered, and universal lower bounds associated only with the location variable are derived to decouple all variables. In the online stage, all the instantaneous-CSI (I-CSI) are available. To solve this non-convex problem, an alternating optimization framework is developed. We propose a Riemannian Manifold (RM) algorithm to optimize the IRS phase shifts. Simulation results validate that the proposed algorithm is convergent and effective, and show that the location deployment of IRS is crucial for green communication.

Due to the limited coverage of reflecting-only reconfigurable intelligent surfaces (RIS), the existing RIS-assisted physical-layer key generation (PKG) scheme limits its overall performance in the full space. This paper proposes a novel simultaneously transmitting and reflecting (STAR)-RIS-assisted PKG protocol for multiple-input multiple-output (MIMO) systems, where the closed-form sum secret key rate is derived in the presence of full-space eavesdroppers. Two optimization problems are formulated to maximize the sum secret key rate by designing the transmit beamforming (TBF) and transmitting and reflecting coefficients (TRCs) for energy splitting (ES) with coupled phase-shift and mode switching (MS) mode. For ES mode with coupled phase-shift, a penalty-based alternating optimization (AO) algorithm is proposed to address its non-convexity. For MS mode, the semidefinite relaxation-successive convex approximation-based AO algorithm is utilized to achieve continuous solutions and then quantize to binary value for the MS mode. Simulation results demonstrate that the coupled phase-shift STAR-RIS incurs a slight KGR loss in comparison to the independent phase-shift STAR-RIS. Additionally, the ES mode outperforms the MS mode in terms of KGR performance. Finally, STAR-RIS can achieve a higher sum secret key rate than traditional reflecting-only RIS.

We take the viewpoint of wireless attackers, and investigate the use of the reconfigurable intelligent surface (RIS) in degrading the communications performance of a time-division duplex system, in which a multiple-antenna base station (BS) transmits independent data streams to multiple user terminals (UTs). Each channel coherent time block consists of a channel training (CT) phase followed by a data transmission (DT) phase. During the CT phase, the UTs broadcast pilots to enable the BS to estimate the wireless channels, and the RIS manipulates the wireless environment so that the channel estimations obtained by the BS are incorrect. During the DT phase, the BS generates beamforming vectors, which are based on the channel estimations obtained during the CT phase, to transmit data to the UTs, and the RIS adopts a randomly time-varying reflection pattern to distort the signals received by the UTs. The mean square errors (MSEs) of the UTs are used as the performance metric, for which, analytical expressions are derived in large system limit. Based on the theoretic results, an efficient method is proposed to optimize the time-varying reflection pattern of the RIS to enhance the attack performance. Numerical simulations are presented to validate our theoretical results and to demonstrate the superiority of the proposed attack scheme over an existing attack scheme wherein the reflection pattern is time-invariant.

In this paper, we design a novel two-phase unsourced random access (URA) scheme in massive multiple input multiple output (MIMO). In the first phase, we collect a sequence of information bits to jointly acquire the user channel state information (CSI) and the associated information bits. In the second phase, the residual information bits of all the users are partitioned into sub-blocks with a very short length to exhibit a higher spectral efficiency and a lower computational complexity than the existing transmission schemes in massive MIMO URA. By using the acquired CSI in the first phase, the sub-block recovery in the second phase is cast as a compressed sensing (CS) problem. From the perspective of the statistical physics, we provide a theoretical framework for our proposed URA scheme to analyze the induced problem based on the replica method. The analytical results show that the performance metrics of our URA scheme can be linked to the system parameters by a single-valued free entropy function. An AMP-based recovery algorithm is designed to achieve the performance indicated by the proposed theoretical framework. Simulations verify that our scheme outperforms the most recent counterparts.

In this paper, we propose a novel dynamic unsourced random access (URA) framework for massive multiple-input multiple-output (MIMO) uplink access. Unlike the existing studies, where the quasi-static channel models and the unchanged user states (active or idle) are assumed, we take the dynamics in both the channels and the states of user devices into consideration. Such a framework supports the high mobility of user devices, and facilitates their abrupt terminates and accesses during the whole transmission process. To model the dynamics, we adopt steady-state Gaussian Markov processes for all the channel coefficients of user devices, and introduce a series of latent variables to indicate the user states. We design a two-step algorithm, including the approximate message passing (AMP)-based inner decoding algorithm and the variational message passing (VMP)-based outer decoding algorithm, to decode the information sequences for all the user devices that have accessed the network. Simulation results show that our proposed method outperforms all the baselines when there are dynamics in the channels of user devices, and our proposed method has robustness to deal with the abrupt changes of user states by equipping the large number of antennas at the base station.

Device-to-device (D2D) communication is able to enhance the spectrum efficiency and coverage of wireless networks but its transmission secrecy is vulnerable since D2D terminals are usually resource/power constrained. Various existing endeavors propose physical-layer security (PLS) means to protect D2D transmissions, under the default prerequisite that D2D transmissions always improve the secrecy performance. In this article, we show that this assumption/conclusion is invalid. We investigate a so-called cellular transmission mode assisted by the base station (cellular mode) and compare its secrecy performance with that of the D2D direct transmission (D2D mode). In both modes, subject to the secrecy outage probability constraints, we optimize the transceiver parameters, such as the signal power, secrecy rates, and transmission thresholds, to maximize the secrecy throughputs. All of the optimal solutions are obtained by closed-form expressions in both modes. Numerical results show that neither of the two transmission modes is always the better but highly depends on the system parameters, such as the locations of nodes, transmit power, and secrecy requirements, and consequently provides the answer that D2D communication is not always beneficial for PLS. This immediately suggests that an adaptive switching transmission mode could achieve an enhanced secrecy performance, which is also validated by simulations.

In this paper, we propose a novel fully Bayesian approach for the massive multiple-input multiple-output (MIMO) massive unsourced random access (URA). The payload of each user device is coded by the sparse regression codes (SPARCs) without redundant parity bits. A Bayesian model is established to capture the probabilistic characteristics of the overall system. Particularly, we adopt the core idea of the model-based learning approach to establish a flexible Bayesian channel model to adapt the complex environments. Different from the traditional divide-and-conquer or pilot-based massive MIMO URA strategies, we propose a three-layer message passing (TLMP) algorithm to jointly decode all the information blocks, as well as acquire the massive MIMO channel, which adopts the core idea of the variational message passing and approximate message passing. We verify that our proposed TLMP significantly enhances the spectral efficiency compared with the state-of-the-arts baselines, and is more robust to the possible codeword collisions.

For mission-critical massive machine-type communications (mMTC) applications, the messages are required to be delivered in real-time. However, due to the weak security protection capabilities of the low-cost and low-complexity machine-type devices, active jamming attack in the uplink access is a serious threat. Uplink access jamming (UAJ) can increase the number of dropped/retransmitted packets and restrict or prevent the normal device access. To tackle this vital and challenging problem, we propose a novel UAJ detection method based on the joint space-time sparsity (JSTS). Our key insight is that the JSTS-based feature will be significantly impacted if UAJ happens, since only a small fraction of the devices are active and the traffic pattern for each device is sporadic in the normal state. Unlike the existing detection methods under batch mode (i.e., all sample observations are collected before making a decision), the JSTS-based detection is performed in a sequential manner by processing the received signals one by one, which can detect UAJ as quickly as possible. Moreover, the proposed JSTS-based method does not rely on the prior knowledge of the attackers, since it only cares the abrupt change in the JSTS-based feature on each frame. Numerical results evaluate and confirm the effectiveness of our method.

With the development of multi-access edge computing (MEC), the cloudlet at the edge of the network can provide nearby high-performance computing services, thus reducing the computational consumption of user equipments (UEs). To provide more real-time computing services to UEs, service providers face the challenge of optimizing the assignment of requests and the allocation of cloudlets’ computing resources to achieve low latency while dealing with the large number of offloaded requests from UEs. Therefore, in this paper, we study the problem of minimizing the total latency to complete the requests in the MEC network by jointly optimizing request assignment and computing resource allocation. The problem is formulated as a mixed integer nonlinear programming (MINLP) problem which is NP-hard. To solve the problem, we decompose the problem into two subproblems which respectively optimize the request assignment and the computing resource allocation. We first deal with the computing resource allocation problem by utilizing the Lagrangian multiplier method, and the resulting solution is applied for the request assignment problem. Then a novel primal-dual based approximation algorithm is devised to address the request assignment problem. Finally, to verify the efficiency of the proposed algorithm, we provide an upper bound on the approximation ratio. The experiment results show that the proposed algorithm outperforms baseline algorithms in terms of total latency, loading balancing, and computational speed.

In this paper, we investigate the design of a burst jamming detection method for delay-sensitive Internet-of-Things (IoT) applications. In order to obtain a timely detection of burst jamming, we propose an online principal direction anomaly detection (OPDAD) method. We consider the one-ring scatter channel model, where the base station equipped with a large number of antennas is elevated at a high altitude. In this case, since the angular spread of the legitimate IoT transmitter or the jammer is restricted within a narrow region, there is a distinct difference of the principal direction of the signal space between the jamming attack and the normal state. Most of existing binary hypothesis test based works cannot apply to detect burst jamming, because the attackers’ target time window does not match with the legitimate transmission. Unlike existing statistical features based batching methods, the proposed OPDAD method adopts an online iterative processing mode, which can quickly detect the exact attack time block instance by analyzing the newly coming signal. In addition, our detection method does not rely on the prior knowledge of the attacker, because it only cares the abrupt change in the principal direction of the signal space. Moreover, based on the high spatial resolution and the narrow angular spread, we provide the convergence rate estimate and derive a nearly optimal finite sample error bound for the proposed OPDAD method. Numerical results show the excellent real time capability and detection performance of our proposed method.

Due to the weak security protection capabilities of the low-cost and low-complexity massive access of machine-type devices, massive machine-type communications (mMTC) networks are extremely vulnerable to the access jamming, which can affect the correctness of activity and data detection of legitimate devices and even leads to the paralysis of the mission-critical mMTC applications. This paper studies detection problem of the access jamming in the uplink of mMTC (AJ-UM), and we propose to exploit the characteristics of the joint low-rank factor and sparsity (JLFS) to detect the AJ-UM. Our detection method is motivated by the fact that the JLFS-based feature will be significantly impacted if the AJ-UM happens. We first extract the JLFS-based feature by solving a low-rank maximum likelihood factor analysis problem with sparsity constraint, and then perform the AJ-UM detection in a sequential manner. Moreover, the proposed JLFS-based method does not need to know the accurate prior information of the JLFS-based feature in the presence or absence of the AJ-UM, which can determine the AJ-UM exists as long as there is an abrupt change in the JLFS-based feature. Numerical results are finally presented to confirm the effectiveness of the proposed JLFS-based method.

The full-duplex millimeter-wave communication has drawn significant attention for its rich spectrum resources and high spectrum efficiency characteristics. However, due to the information leakage during transmission, secure threats in the full-duplex systems still exist. In this paper, we propose a full-duplex jamming based secure transmission scheme, where the instantaneous channel state information of eavesdropping channel is unknown. We study the optimal design of hybrid beamforming and power allocation jointly with secrecy outage probability constraint. Our results reveal that joint optimization highly facilitates the secrecy performance of full-duplex mmWave communication, without any self-interference limitations in the multiple-antenna scenarios.

In this paper we propose a joint Radar and Communications waveform for next-generation wireless networks (e.g., 6G, next-generation Wi-Fi). The proposed waveform is a multiple carrier signal with each carrier a chirp-like wave instead of a sinusoid in OFDM. The signal is a parameterized waveforms with two adjustable parameters, and could be generated by affine Fourier transform once the parameters are given. We analyze the communications and ranging performances of the waveform by deriving the transmitting-receiving model and the ambiguity function and compare them with an OFDM signal. Further, we investigate the secrecy of the waveform in both communications and ranging and show the sensitivity of the waveform to the mismatch of these parameters. When these parameters are kept secret from the potential adversary, the legitimate signal cannot be demodulated correctly by the eavesdropper and the waveform spoofing attack is also invalided. Simulations demonstrate that the proposed multiple-carrier chirp waveform has better performance than OFDM signal in both communications and ranging, which has lower BER in fading channel and higher resolution in ranging. We also evaluate the performance under eavesdropping and spoofing attack1.

Physical layer authentication (PLA) is a promising complement for the cryptographic-based authentication scheme, especially for Internet of Things (IoT) scenarios with massive devices. Traditional PLA schemes exploiting channel state information (CSI) face significant challenges in mobile communication scenarios due to the unknown variation of wireless channels. To address this challenge, we propose a PLA scheme based on Gaussian process (GP) channel prediction, where the variation of channel characteristics is tracked and predicted. Specifically, historical CSI attributes together with the transmitter’s geographical information are exploited to establish a mapping to predict the next legitimate CSI for authentication. Furthermore, to overcome the impracticality of applying conventional PLA framework for authentication, where an unrealistic assumption that either the prior knowledge of the adversary’s statistical channel model or even the real observations of its CSI data is required, we propose the so-called one-class authentication (OCA) scheme, which does not require any attacker’s channel information. We exploit the quasideterministic radio channel generator (QuaDRiGa) simulation platform as the generator of CSI for experimental verifications. Simulation tests are performed to demonstrate that our method improves authentication performance significantly in time-varying scenarios.

In this paper, we propose a robust secrecy transmission scheme for intelligent reflecting surface (IRS) aided communication systems. Different from all the existing works where IRS has already been deployed at a fixed location, we take the location of IRS as a variable to maximize the secrecy rate (SR) under the outage probability constraint by jointly optimizing the location of IRS, transmit beamformer and IRS phase shifts with imperfect channel state information (CSI) of Eve, where we consider two cases: a) the location of Eve is known; b) only a suspicious area of Eve is available. We show a critical observation that CSI models are different before and after IRS deployment, thus the optimization problem could be decomposed and solved via a two-stage framework. For case a), in the first stage, universal upper bounds of outage probabilities only related to the location of IRS are derived which can be optimized via successive convex approximation (SCA) method. In the second stage, we develop an alternative optimization (AO) algorithm to optimize beamformer and phase shifts iteratively. For case b), we propose a Max-Min SR scheme based on two-stage framework, where the location of IRS is optimized based on the worst location of Eve. Simulation results indicate the importance of the location of IRS optimization.

Exploiting short packets for communications is one of the key technologies for realizing emerging application scenarios such as massive machine type communications (mMTC) and ultra-reliable low-latency communications (uRLLC). In this paper, we investigate short-packet communications to provide both reliability and security guarantees simultaneously with an eavesdropper. In particular, an outage probability considering both reliability and secrecy is defined according to the characteristics of short-packet transmission, while the effective throughput in the sense of outage is established as the performance metric. Specifically, a general analytical framework is proposed to approximate the outage probability and effective throughput. Furthermore, closed-form expressions for these quantities are derived for the high signal-to-noise ratio (SNR) regime. Both effective throughput obtained via a general analytical framework and a high-SNR approximation are maximized under an outage-probability constraint by searching for the optimal blocklength. Numerical results verify the feasibility and accuracy of the proposed analytical framework, and illustrate the influence of the main system parameters on the blocklength and system performance under the outage-probability constraint.

This paper considers an uplink massive machine-type communication scenario with a massive number of antennas, where a large number of user devices are connected to a base station (BS) and the user traffic is sporadic. We propose a novel hybrid message passing (HMP) algorithm to achieve joint active detection and channel estimation (JADCE) by exploiting the channel characteristics in both the angular domain and user domain, which is expected to enhance the performance of JADCE compared with the conventional approaches without the knowledge of such a consideration. The user grouping is performed simultaneously with JADCE, which provides the prerequisites of the joint spatial division and multiplexing to achieve significant savings both in the downlink training and feedback of channel state information at the transmitter. Based on the acquired knowledge of user grouping, we further propose a per-group processing based JADCE (PGP-JADCE) approach. It significantly reduces the computational overhead for JADCE and the BS is capable to process all the user groups in parallel. Further, the analysis of detection error probabilities and channel estimation error of PGP-JADCE is provided.

In this paper, we investigate physical-layer security of the uplink millimeter wave communications for a cellular vehicle-to-everything (C-V2X) network comprised of a large number of base stations (BSs) and different categories of V2X nodes, including vehicles, pedestrians, and road side units. Considering the dynamic change and randomness of the topology of the C-V2X network, we model the roadways, the V2X nodes on each roadway, and the BSs by a Poisson line process, a 1D Poisson point process (PPP), and a 2D PPP, respectively. We propose two uplink association schemes for a typical vehicle, namely, the smallest-distance association (SDA) scheme and the largest-power association (LPA) scheme, and we establish a tractable analytical framework to comprehensively assess the security performance of the uplink transmission, by leveraging the stochastic geometry theory. Specifically, for each association scheme, we first obtain new expressions for the association probability of the typical vehicle, and then derive the overall connection outage probability and secrecy outage probability by calculating the Laplace transform of the aggregate interference power. Numerical results are presented to validate our theoretical analysis, and we also provide interesting insights into how the security performance is influenced by various system parameters, including the densities of V2X nodes and BSs. Moreover, we show that the LPA scheme outperforms the SDA scheme in terms of secrecy throughput.

Intelligent reflecting surface (IRS) has been proposed as a very promising technique for beyond 5G and 6G communications. In this paper, we apply IRS to enhance the secure transmission of secondary user in a multi-input multioutput (MIMO) cognitive radio (CR) wiretap channel. Since the study of secure IRS-assisted CR communication is still an open problem, all the existing numerical solutions for enhancing secure communications in non-CR setting as well as non-secure communications in CR setting in the literature fail to this work due to the complicated structure of objective functions as well as the constraints. Therefore, to maximize the secrecy rate of secondary user, an efficient alternating optimization (AO) algorithm is proposed to jointly optimize the transmit covariance at base station and phase shift coefficients at IRS. Simulation results show that our proposed algorithm have fast monotonic convergence as well as better performance on enhancing the secrecy rate than the benchmark schemes.

This paper studies covert communications between a pair of legitimate transmitter-receiver against a watchful warden over fading channels. There coexist multiple friendly helper nodes who are willing to protect the covert communication from being detected by the warden. An uncoordinated jammer selection scheme is proposed where those helpers whose instantaneous channel gains to the legitimate receiver fall below a pre-established selection threshold will be chosen as jammers radiating jamming signals to defeat the warden. Afterwards, we jointly design the optimal selection threshold and transmission rate for maximizing covert throughput under the premise that the detection error of the warden exceeds a certain level. Numerical results demonstrate that the maximal covert throughput improves significantly as the total number of helpers increases.

Model-based method and data-based method are two basic approaches for the design of wireless communication systems. Model-based methods suffer from inaccurate modeling assumptions due to excessively complex environment. Recently, data-based methods have achieved remarkable performances in the communication system design without the knowledge of accurate model but encounter some challenges such as, lack of available labelled training data and explainability. In this paper, we propose a novel hybrid idea to integrate the strengths of both data and model-based methods, named model refinement learning, which is training affordable, theoretically interpretable and self-adapting. To show the idea more concretely, a novel channel estimation algorithm is proposed in the multiple-input single-output (MISO) system in the case where the noise model is unknown. In particular, we utilize a universal mixture of Gaussian (MoG) model, which can adaptively adjust the involved parameters to fit the true noise distribution by using observed data. We propose a novel variational inference framework to achieve automatical noise model refinement and design the corresponding online channel estimator. To reduce the online algorithm overhead, we propose a decoupled variational Bayesian method to achieve linear computational complexity. Simulations show that our proposed method outperforms both the model-based and data-based counterparts.

In this paper, an intelligent reflecting surface (IRS) assisted spectrum sharing underlay cognitive radio (CR) wiretap channel (WTC) is studied, and we aim at enhancing the secrecy rate of secondary user in this channel subject to total power constraint at secondary transmitter (ST), interference power constraint (IPC) at primary receiver (PR) as well as unit modulus constraint at IRS. Due to extra IPC and eavesdropper (Eve) are considered, all the existing solutions for enhancing secrecy rate of IRS-assisted non-CR WTC as well as enhancing transmission rate in IRS-assisted CR channel without eavesdropper fail in this work. Therefore, we propose new numerical solutions to optimize the secrecy rate of this channel under full primary, secondary users’ channel state information (CSI) and three different cases of Eve’s CSI: full CSI, imperfect CSI with bounded estimation error, and no CSI. To solve the difficult non-convex optimization problem, an efficient alternating optimization (AO) algorithm is proposed to jointly optimize the beamformer at ST and phase shift coefficients at IRS. In particular, when optimizing the phase shift coefficients during each iteration of AO, a Dinkelbach based solution in combination with successive approximation and penalty based solution is proposed under full CSI and a penalty convex-concave procedure solution is proposed under imperfect Eve’s CSI. For no Eve’s CSI case, artificial noise (AN) aided approach is adopted to help enhancing the secrecy rate. Simulation results show that our proposed solutions for the IRS-assisted design greatly enhance the secrecy performance compared with the existing numerical solutions with and without IRS under full and imperfect Eve’s CSI. And positive secrecy rate can be achieved by our proposed AN aided approach given most channel realizations under no Eve’s CSI case so that secure communication also can be guaranteed. All of the proposed AO algorithms are guaranteed to monotonic convergence.

We investigate covert communication under a sequential change-point detection (SCPD) framework, where a transmitter, Alice, attempts to communicate reliably with a receiver, Bob, over an additive white Gaussian noise channel, while simultaneously ensuring covertness (low probability of detection) with respect to an adversary, Willie. Different from the binary hypothesis test based detection framework considered in prior works where Willie collects all signal samples together and makes a decision in a batch manner, we view Willie’s detection process as an SCPD process that works in a real-time manner. We establish a new criterion to evaluate the covertness of the communication between Alice and Bob, and investigate the performance of covert communication accordingly. Subject to the proposed constraint on covertness, we investigate the feasible transmit power and transmission duration under three SCPD algorithms, namely, the Shewhart test, the finite moving average chart (FMAC), and the cumulative sum (CUSUM) test, and characterize how the covert communication throughput scales with the average run length to false alarm (ARL2FA) of Willie’s detector as the ARL2FA increases without bound. Our theoretical results can be viewed as upper bounds on the covert communication throughput that can be achieved, and we show that compared with the case where Willie performs the CUSUM test, Alice and Bob achieve a higher covert communication throughput if Willie performs the Shewhart test or the FMAC.

We consider that a transmitter covertly communicates with multiple receivers under the help of a friendly jammer. The messages intended for different receivers are transmitted in mutually orthogonal frequency bands. An adversary observes all these frequency bands aiming at detecting whether or not communication occurs, while the friendly jammer broadcasts jamming signals to degrade the detection performance of the adversary. We consider a block Rayleigh fading channel model and evaluate the performance of covert communication in two situations: 1) the wireless channels vary slowly such that the transmission ends within one channel coherent time block, and 2) the wireless channels vary fast such that the wireless channels have changed several times before the whole transmission is finished. In the former case, subject to a covertness constraint, we maximize the sum of the effective rates by optimizing the transmit power allocation and the transmission rate for each receiver. In the latter case, we take the channel training process into consideration, and subject to a covertness constraint, we maximize the sum of the ergodic rates by optimizing the power allocation and the pilot length. Though both of the two optimization problems are non-convex, we presented methods to find their global optimal solutions. Besides, we also present methods to find sub-optimal solutions with lower computational complexities. Numerical results are presented to evaluate the performance under the two situations.

Pilot contamination attack (PCA) in a time division duplex wireless communication system is considered, where an eavesdropper (Eve) attacks the reverse pilot transmission phase in order to wiretap the data transmitted from a transmitter, Alice, to a receiver, Bob. We propose a new PCA scheme for Eve, wherein Eve does not emit any signal by itself but uses an intelligent reflecting surface (IRS) to reflect the pilot sent by Bob to Alice. The proposed new PCA scheme, referred to as IRS-PCA, increases the signal leakage from Alice to the IRS during the data transmission phase, which is then reflected by the IRS to Eve in order to improve the wiretapping capability of Eve. The proposed IRS-PCA scheme disables many existing countermeasures on PCA due to the fact that with IRS-PCA, Eve no longer needs to know the pilot sequence of Bob, and therefore, poses severe threat to the security of the legitimate wireless communication system. In view of this, the problems of 1) IRS-PCA detection and 2) secure transmission under IRS-PCA are considered in this paper. For IRS-PCA detection, a generalized cumulative sum (GCUSUM) detection procedure is proposed based on the framework of quickest detection, aiming at detecting the occurrence of IRS-PCA as soon as possible once it occurs. For secure transmission under IRS-PCA, a cooperative channel estimation scheme is proposed to estimate the channel of the IRS, based on which zero-forcing beamforming is designed to reduce signal leakage.

In this paper, we study millimeter wave (mmWave) communications of an uplink cellular vehicle-to-everything (C-V2X) network consisting of vehicles, pedestrians, road side units (RSUs), and cellular base stations (BSs). We propose an association scheme that a vehicle delivers messages to either the V2X nodes, including vehicles, pedestrians, and RSUs, or the BSs, based on the distance and the bias factor. Subsequently, we provide a tractable analytical framework to comprehensively assess the reliability performance of the considered uplink transmission, in terms of success probability. By leveraging the stochastic geometry theory, we model the locations of vehicles, pedestrians, and RSUs as independent cox process and model the locations of BSs as a Poisson point process (PPP), and derive new expressions for the association probability, the success probability of different associating types, and the overall success probability of the C-V2X network. Numerical results are presented to validate the theoretical analyses and provide interesting insights into how the success probability is influenced by various parameters, including the signal-to-interference-plus-noise ratio (SINR) threshold, the densities of V2X nodes and BSs, the blockage density, and the bias factor.

Passive radio frequency identification (RFID) systems raise new transmission secrecy protection challenges against the special proactive eavesdropper, since it is able to both enhance the information wiretap and interfere with the information detection at the RFID reader simultaneously by broadcasting its own continuous wave (CW) signal. To defend against proactive eavesdropping attacks, we propose an artificial noise (AN) aided secure transmission scheme for the RFID reader, which superimposes an AN signal on the CW signal to confuse the proactive eavesdropper. The power allocation between the AN signal and the CW signal are optimized to maximize the secrecy rate. Furthermore, we model the attack and defense process between the proactive eavesdropper and the RFID reader as a hierarchical security game, and prove it can achieve the equilibrium. Simulation results show the superiority of our proposed scheme in terms of the secrecy rate and the interactions between the RFID reader and the proactive eavesdropper.

In this study, the authors propose a generalisedswitching protocol (GSP) for increasing the flexibility of energy harvesting (EH) protocol and enhancing the security of amplify‐and‐forward (AF) multi‐antenna relaying system. The proposed GSP‐based relaying [generalised switching relaying (GSR)] system is established with target node assisted interference and EH technologies. In phase I, while the source transmits certain signal to the relay, the destination transmits an artificial noise to interfere the passive eavesdropper. In this phase, the relay harvests energy from the two nodes. In phase II, the relay node processes the two different received signals, which are from the source and destination, then AF them by utilising the harvested energy. The authors also derive a new analytical formula for the proposed protocol on ergodic secrecy capacity. The effect of the number of relay antennas N , the source transmitted power , the destination transmitted power and EH efficiency factors and on ergodic secrecy capacity are investigated. The simulation results show that as N , , , and increase, the ergodic secrecy capacity of GSR system increases accordingly. Moreover, the GSR protocol can provide higher ergodic secrecy capacity than both time switching relaying and powersplitting relaying protocols.

To enable the low-cost ubiquitous Internet of Things, passive backscatter communication is envisioned as one of the most prominent and promising techniques; however, the underlying security issues associated with practical finite-alphabet signaling from the perspective of physical-layer security (PLS) have not been well studied. Despite several preliminary efforts on improving the eavesdropper's decoding error probability through PLS approaches, this article comprehensively investigates the secrecy rate performance of a secure multiantenna radio-frequency identification (RFID) system with a finite-alphabet input at the RFID tag. Unlike conventional noise-injection schemes, a randomized continuous wave (CW) signal is exploited at the RFID reader for security enhancement, and an analytical framework is proposed to evaluate the impact of exploiting either full or only statistical knowledge of the randomized CW signal at the reader and the eavesdropper, respectively. The secrecy rate is maximized by designing the transmitted randomized CW signal to tackle the stability-variance tradeoff between balancing legitimate signal reception and eavesdropper mitigation. In particular, we show that the proposed scheme also poses a tradeoff between the received additive and multiplicative noise at the eavesdropper for the special case of a single-antenna eavesdropper. Moreover, the more practical case where the eavesdropper's instantaneous channel state information is unavailable is studied under different fading conditions. The numerical results verify the accuracy of the proposed approximations and show that introducing a small variance into the CW signal can greatly improve the system secrecy.

Passive radio-frequency identification (RFID) communication raises new transmission secrecy protection challenges, since passive tags stored information lack effective information protection mechanisms. Due to constraints of passive tags, such as limited computation and storage capabilities, security solutions based on the physical-layer security (PLS) are promising candidates compared to those based on conventional lightweight cryptography. Unlike existing endeavors on PLS of RFID wireless communication, we consider an RFID system in the presence of a special proactive eavesdropper, which is able to both enhance the information wiretap and interfere with the information detection at the RFID reader simultaneously by broadcasting its own continuous-wave (CW) signal. To defend against proactive eavesdropping attacks, we propose a wiretap-channel-conscious artificial-noise (AN)-aided secure transmission scheme for the RFID reader, which first estimates both legitimate and wiretap channels and then superimposes an AN signal on the CW signal to confuse the proactive eavesdropper. The transmit power and power allocation between the AN signal and the CW signal are optimized to maximize the secrecy rate. Furthermore, we model the attack and defense process between the proactive eavesdropper and the RFID reader as a hierarchical security game and prove it can achieve the equilibrium. The simulation results show the superiority of our proposed scheme in terms of the secrecy rate and the interactions between the RFID reader and the proactive eavesdropper.

In this letter, improving the security of an intelligent reflecting surface (IRS) assisted multiple-input single-output (MISO) communication system is studied. Different from the ideal assumption in existing literatures that full eavesdropper's (Eve's) channel state information (CSI) is available, we consider a more practical scenario without Eve's CSI. To enhance the security of this system given a total transmit power at transmitter (Alice), we propose a joint beamforming and jamming approach, in which a minimum transmit power is firstly optimized at Alice so as to meet the quality of service (QoS) at legitimate user (Bob), and then artificial noise (AN) is emitted to jam the eavesdropper by using the residual power at Alice. Two efficient algorithms exploiting oblique manifold (OM) and minorization-maximization (MM) algorithms, respectively, are developed for solving the resulting non-convex optimization problem. Simulation results have been provided to validate the performance and convergence of the proposed algorithms.

In this paper, we establish a framework for low probability of detection (LPD) communication from a sequential change-point detection (SCPD) perspective, where a transmitter, Alice, wants to hide her transmission to a receiver, Bob, from an adversary, Willie. The new framework facilitates modeling LPD communication and further evaluating its performance under the condition that Willie has no prior knowledge about when the transmission from Alice might start and that Willie wants to determine the existence of the communication as quickly as possible in a real-time manner. We consider three different sequential tests, i.e., the Shewhart, the cumulative sum (CUSUM), and the Shiryaev-Roberts (SR) tests, to model Willie's detection process. Communication is said to be covert if it ceases before being detected by Willie with high probability. Covert probability defined as the probability that Willie is not alerted during Alice's transmission is investigated. We formulate an optimization problem aiming at finding the transmit power and transmission duration so as to maximize the total amount of information that can be transmitted subject to a high covert probability. Under the Shewhart test, closed-form approximations of the optimal solutions are derived, which will approximate the solutions obtained from exhaustive search. As for the CUSUM and SR tests, we provide effective algorithms to search for the optimal solutions. Numeric results are presented to show the performance of LPD communication.

Device-to-device (D2D) communication is a promising solution to meet rapidly growing demands for data services via spectrum reuse. This paper studies the physical layer security in a D2D underlay cellular network from a network-wide perspective, where the locations of D2D and cellular users are modeled as Poisson cluster processes (PCPs) to characterize the clustering feature of D2D users, the locations of eavesdroppers (Eves) and base stations (BSs) are modeled as a PCP and Poisson point process (PPP), respectively. We establish an analytical framework to assess the coverage and security performance of the network. Two scenarios are considered, i.e., one D2D pair scenario and multiple D2D pairs scenario, where in each cell there is one or multiple D2D users (DUs) sharing the frequency spectrum with the cellular users (CUs) in each time slot of the TDMA scheme adopted by BSs. In each considered scenario, we derive exact expressions for the coverage outage probabilities (COPs) and secrecy outage probabilities (SOPs), respectively, for both the CUs and DUs. Furthermore, the exact expression for the network-wide secrecy throughput (ST) is derived. Numerical results are presented to verify our theoretical derivations and reveal some insights into the impact of various parameters on the system performance.

Secrecy transmission is investigated for a cooperative jamming scheme, where a multi-antenna jammer generates artificial noise (AN) to confuse eavesdroppers. Two kinds of eavesdroppers are considered: passive eavesdroppers who only overhear the legitimate information, and active eavesdroppers who not only overhear the legitimate information but also jam the legitimate signal. Existing works only treat the passive and active eavesdroppers separately. Different from the existing works, we investigate the achievable secrecy rate in presence of both active and passive eavesdroppers. For the considered system model, we assume that the instantaneous channel state information (CSI) of the active eavesdroppers is available at the jammer, while only partial CSI of the passive eavesdroppers is available at the jammer. A new zero-forcing beamforming scheme is proposed in the presence of both active and passive eavesdroppers. For both the perfect and imperfect CSI cases, the total transmission power allocation between the information and AN signals is optimized to maximize the achievable secrecy rate. Numerical results show that imperfect CSI between the jammer and the legitimate receiver will do more harm to the achievable secrecy rate than imperfect CSI between the jammer and the active eavesdropper.

This paper proposes a secure downlink multi-user transmission scheme enabled by a flexible unmanned aerial vehicle base station (UAV-BS) and non-orthogonal multiple access (NOMA). According to their heterogeneous service requirements, multiple legitimate users are categorized as security-required users (SUs) and quality of service (QoS)-required users (QUs), while these QUs can potentially act as internal eavesdroppers which are curious about the secrecy transmissions of SUs. In such a context, our goal is to maximize the achievable minimum secrecy rate among SUs through the joint optimization of user scheduling, power allocation, and trajectory design, subject to the QoS requirements of QUs and the mobility constraint of UAV-BS. Due to the non-convexity of the problem, an efficient iterative algorithm is firstly proposed, based on the alternative optimization (AO) and successive convex approximation (SCA) methods and along with a penalty-based algorithm to deal with the introduced binary integer variables, to obtain a sub-optimal solution. Then, we propose an SUs-oriented low-complexity algorithm by taking advantage of the inherent characteristics of the optimization problem, which can efficiently reduce the computational complexity and can act as a reasonable initial solution for the previous iterative algorithm to achieve better performance. Finally, the superiority of our proposed scheme compared with the conventional orthogonal multiple access (OMA) one is validated by numerical simulation results.

The deployment of unmanned aerial vehicle (UAV) for surveillance and monitoring gives rise to the confidential information leakage challenge in both civilian and military environments. The security and covert communication problems for a pair of terrestrial nodes against UAV surveillance are considered in this paper. To overcome the information leakage and increase the transmission reliability, a multi-hop relaying strategy is deployed. We aim to optimize the throughput by carefully designing the parameters of the multi-hop network, including the coding rates, transmit power, and required number of hops. In the secure transmission scenario, the expressions of the connection probability and secrecy outage probability of an end-to-end path are derived and the closed-form expressions of the optimal transmit power, transmission and secrecy rates under a fixed number of hops are obtained. In the covert communication problem, under the constraints of the detection error rate and aggregate power, the sub-problem of transmit power allocation is a convex problem and can be solved numerically. Simulation shows the impact of network settings on the transmission performance. The trade-off between secrecy/covertness and efficiency of the multi-hop transmission is discussed which leads to the existence of the optimal number of hops.

In this article, we consider an intelligent reflecting surface (IRS) assisted Guassian multiple-input multiple-output (MIMO) wiretap channel (WTC), and focus on enhancing its secrecy rate. Due to MIMO setting, all the existing solutions for enhancing the secrecy rate over multiple-input single-output WTC completely fall to this work. Furthermore, all the existing studies are simply based on an ideal assumption that full channel state information (CSI) of eavesdropper (Ev) is available. Therefore, we propose numerical solutions to enhance the secrecy rate of this channel under both full and no Ev's CSI cases. For the full CSI case, we propose a barrier method and one-by-one (OBO) optimization combined alternating optimization (AO) algorithm to jointly optimize the transmit covariance R at transmitter (Tx) and phase shift coefficient Q at IRS. For the case of no Ev's CSI, we develop an artificial noise (AN) aided joint transmission scheme to enhance the secrecy rate. In this scheme, a bisection search (BS) and OBO optimization combined AO algorithm is proposed to jointly optimize R and Q. Such scheme is also applied to enhance the secrecy rate under a special scenario in which the direct link between Tx and receiver (Rx)/Ev is blocked due to obstacles. In particular, we propose a BS and minorization-maximization (MM) combined AO algorithm with slightly faster convergence to optimize R and Q for this scenario. Simulation results have validated the monotonic convergence of the proposed algorithms, and it is shown that the proposed algorithms for the IRS-assisted design achieve significantly larger secrecy rate than the other benchmark schemes under full CSI. When Ev's CSI is unknown, the secrecy performance of this channel also can be enhanced by the proposed AN aided scheme, and there is a trade-off between increasing the quality of service at Rx and enhancing the secrecy rate.

This paper studies physical-layer secure transmissions from a transmitter to a legitimate receiver against an eavesdropper over slow fading channels, taking into account the impact of finite blocklength secrecy coding. A comprehensive analysis and optimization framework is established to investigate secrecy throughput for both single- and multi-antenna transmitter scenarios. Both adaptive and non-adaptive design schemes are devised, in which the secrecy throughput is maximized by exploiting the instantaneous and statistical channel state information of the legitimate receiver, respectively. Specifically, optimal transmission policy, blocklength, and code rates are jointly designed to maximize the secrecy throughput. Additionally, null-space artificial noise is employed to improve the secrecy throughput for the multi-antenna setup with the optimal power allocation derived. Various important insights are developed. In particular, 1) increasing blocklength benefits both reliability and secrecy under the proposed transmission policy; 2) secrecy throughput monotonically increases with blocklength; 3) secrecy throughput initially increases but then decreases as secrecy rate increases, and the optimal secrecy rate maximizing the secrecy throughput should be carefully chosen in order to strike a good balance between rate and decoding correctness. Numerical results are eventually presented to verify theoretical findings.

Recently, device-to-device (D2D) communication has emerged as a promising solution to meet rapidly growing demands for data services. This paper studies the physical layer security of D2D underlay cellular network, where the D2D and cellular communications coexist in the network, in the presence of randomly distributed eavesdroppers (Eves). We establish an analytical framework to assess the security performance of the network of interest. To be specific, by modeling the D2D underlay cellular network as a Poisson cluster process (PCP), we derive exact expressions for the coverage outage probabilities (COP) and secrecy outage probabilities (SOP), respectively, for both the cellular users (CU) and D2D users (DU). The numerical results are finally presented to verify our theoratical derivations and reveal some interesting insights into the effects of various parameters on the system performance.

This paper studies multi-antenna covert communications coexisting with randomly located wardens and interferers. We analyze and optimize the covert throughput under a stochastic geometry framework. We first introduce covert outage probability and connectivity probability to respectively characterize covertness and reliability, and derive analytically tractable expressions for them. We then consider a worst-case covert communication, where the wardens can invariably maximize the covert outage probability by adjusting the detection thresholds of their detectors. Afterwards, we jointly design the optimal transmit power and transmission rate to maximize the covert throughput while satisfying the covertness requirement. Interestingly, it is found that the maximal covert throughput is invariant to either the density of interferers or the interfering power, regardless of the number of transmit antennas.

We propose a downlink beamforming scheme that combines spatial division and orthogonal space-time block coding (OSTBC) in multi-user massive multiple-input and multiple-output systems. The beamformer is divided into two parts: a pre-beamforming matrix to separate the users into different beams with no interference between each other, which is designed based on the low-rank covariance matrix of the downlink channel, and a linear precoding matrix using partial or even no channel state information (CSI) concatenated by an OSTBC. To construct the pre-beamforming matrix, a simple method that selects columns from DFT matrix is presented. To design the linear precoding matrix with partial CSI of the effective channel after the pre-beamforming, we solve an optimization problem to minimize the pairwise error probability (PEP) of the users under an individual power or sum power constraint, respectively. For the individual power constraint, a semi-definite relaxing method with a sufficient condition achieving the globally optimal solution is proposed to provide a performance benchmark. In addition, an efficient iterative successive convex approximation (SCA) method is provided to achieve a suboptimal solution. Furthermore, closed-form solutions are derived under some special cases. For the sum power constraint, we consider two different designs, i.e., minimizing the average PEP and minimizing the maximum PEP of all users. We find that both non-convex problems have a similar structure and proposed a unified SCA-alternating direction method of multipliers (ADMM) algorithm to handle them. The SCA-ADMM method can be implemented in a parallel manner and, thus, with great efficiency. Simulation results show the efficiency of our proposed JSDD scheme and the optimization method.

Device-to-device (D2D) communication raises new transmission secrecy protection challenges, since conventional physical layer security approaches, such as multiple antennas and cooperation techniques, are invalid due to its resource/size constraints. The full-duplex (FD) jamming receiver, which radiates jamming signals to confuse eavesdroppers when receiving the desired signal simultaneously, is a promising candidate. Unlike existing endeavors that assume the FD jamming receiver always improves the secrecy performance compared with the half-duplex (HD) receiver, we show that this assumption highly depends on the instantaneous residual self-interference cancellation level and may be invalid. We propose an adaptive jamming receiver operating in a switched FD/HD mode for a D2D link in random networks. Subject to the secrecy outage probability constraint, we optimize the transceiver parameters, such as signal/jamming powers, secrecy rates, and mode switch criteria, to maximize the secrecy throughput. Most of the optimization operations are taken off-line and only very limited on-line calculations are required to make the scheme with low complexity. Furthermore, some interesting insights are provided, such as the secrecy throughput is a quasi-concave function. Numerical results are demonstrated to verify our theoretical findings, and to show its superiority compared with the receiver operating in the FD or HD mode only.

Exploiting relays in millimeter wave (mmWave) systems is an effective way to extend the communication coverage and overcome the blockage problem. This paper comprehensively studies secure transmissions in mmWave decode-and-forward (DF) relay systems. Depending on the overlapped resolvable paths between the main channel and the wiretap channel in each transmission stage, we consider three eavesdropping scenarios, namely two-stage eavesdropping (TSE), single-stage eavesdropping (SSE) and no eavesdropping (NE). We investigate secrecy performance and optimal parameter design of these eavesdropping scenarios under the same codeword transmission (SCT) scheme and the different codewords transmission (DCT) scheme, where source and relay utilize same codeword or different codewords. Specifically, we derive closed-form expressions for connection probability and secrecy outage probability, and then give solution to the secrecy throughput maximization problem. Furthermore, we investigate the effectiveness of the artificial noise (AN) by evaluating the secrecy performance of AN assisted transmissions. Numerical results are provided to verify our theoretical analysis. Our results give insights into the secure transmission scheme selection and the impact of various parameters, such as number of antennas, power allocation between source and relay, number of overlapped paths, and distances between different nodes, on the secrecy performance of the mmWave relay system.

In applications of the Internet of Things (IoT), the use of short packets is expected to meet the stringent latency requirement in ultra-reliable low-latency communications; however, the incurred security issues and the impact of finite blocklength coding on the physical-layer security are not well understood. This paper investigates the performance of secure short-packet communications in a mission-critical IoT system with an external multi-antenna eavesdropper. An analytical framework is proposed to approximate the average achievable secrecy throughput of the system with finite blocklength coding. To gain more insight, a simple case with a single-antenna access point (AP) is considered first, in which the secrecy throughput is approximated in a closed form. Based on that result, the optimal blocklengths to maximize the secrecy throughput with and without the reliability and latency constraints, respectively, are derived. For the case with a multi-antenna AP, following the proposed analytical framework, closed-form approximations for the secrecy throughput are obtained under both beamforming and artificial-noise-aided transmission schemes. The numerical results verify the accuracy of the proposed approximations and illustrate the impact of the system parameters on the tradeoff between transmission latency and reliability under a secrecy constraint.

This paper studies multi-antenna-aided covert communications coexisting with randomly located wardens and interferers, considering both centralized and distributed antenna systems (CAS/DAS). The throughput performance of the covert communication is analyzed and optimized under a stochastic geometry framework, where the joint impact of the small-scale channel fading and the large-scale path loss is examined. To be specific, two probabilistic metrics, namely, the covert outage probability and the connectivity probability, are adopted to characterize the covertness and reliability of the transmission, respectively, and analytically tractable expressions for the two metrics are derived. The worst-case covert communication scenario is then investigated, where the wardens invariably can maximize the covert outage probability by adjusting the detection thresholds for their detectors. Afterward, the optimal transmit power and transmission rate are jointly designed to maximize the covert throughput subject to a covertness constraint. Interestingly, it is found that the maximal covert throughput for both the CAS and DAS is invariant to the density of interferers and the interfering power, regardless of the number of transmit antennas. The numerical results demonstrate that the CAS outperforms the DAS in terms of the covert throughput for the random network of interest, and the throughput gap between the two systems increases dramatically when the number of transmit antennas becomes higher.

This paper explores physical-layer security in a small cell network with cooperative cache-enabled small base stations (SBSs) in the presence of randomly distributed eavesdroppers. We put forward a hybrid caching placement strategy where a proportion of the cache space in each SBS is assigned to store the most popular files (MPFs), while the remaining is used to cache the disjoint subfiles (DSFs) of less popular files in different SBSs as a means to improve secrecy and content diversity. We then propose two coordinated multi-point techniques, namely, joint transmission and orthogonal transmission, to deliver the MPFs and DSFs, respectively. We jointly design the optimal transmission rate and caching assignment proportion to maximize the secure content delivery probability, and provide various insights into the optimal results. Numerical results are also presented to verify the theoretical findings and to demonstrate the superiority of our caching and transmission strategies.

In the fifth generation era, the pervasive applications of Internet of Things and massive machine-type communications have initiated increasing research interests on the backscatter wireless powered communication (B-WPC) technique due to its ultrahigh energy efficiency and low cost. The ubiquitous B-WPC network is characterized by nodes with dynamic spatial positions and sporadic short packets, of which the performance has not been fully investigated. In this paper, we give a comprehensive analysis of a multiantenna B-WPC network with sporadic short packets under a stochastic geometry framework. By exploiting a time-space Poisson point process model, the behavior of the network is well captured in a decentralized and asynchronous transmission way. We then analyze the energy and information outage performance in the energy harvest and backscatter modulation phases of the backscatter network, respectively. The optimal transmission slot length and division are obtained by maximizing the network-wide spatial throughput. Moreover, we find an interesting result that there exists the optimal tradeoff between the durations of the energy harvest and backscatter modulation phases for spatial throughput maximization. Numerical results are demonstrated to verify our analytical findings and show that this tradeoff region gets shrunk when the outage constraints become more stringent.

Transmitter-side channel state information of the legitimate destination plays a critical role in physical layer secure transmissions. However, channel training procedure is vulnerable to the pilot spoofing attack (PSA) or pilot jamming attack (PJA) by an active eavesdropper (Eve), which inevitably results in severe private information leakage. In this paper, we propose a random channel training (RCT)-based secure downlink transmission framework for a time division duplex multiple antennas base station. In the proposed RCT scheme, multiple orthogonal pilot sequences (PSs) are simultaneously allocated to the legitimate user (LU), and the LU randomly selects one PS from the assigned PS set to transmit. Under either the PSA or PJA, we provide the detailed steps for the BS to identify the PS transmitted by the LU, and to simultaneously estimate channels of the LU and Eve. The probability that the BS makes an incorrect decision on the PS of the LU is analytically investigated. Finally, closed-form secure beamforming vectors are designed and optimized to enhance the secrecy rates during the downlink transmissions. Numerical results show that the secrecy performance is greatly improved compared to the conventional channel training scheme wherein only one PS is assigned to the LU.

Millimeter wave (mmWave) signals are much more sensitive to blockage, which results in a significant increase of the outage probability, especially for the users at the edge of the cells. In this paper, we exploit the technique of base station (BS) cooperation to improve the performance of the cell-edge users in the downlink transmission of mmWave cellular networks. We design two cooperative schemes, which are referred to as fixed-number BS cooperation (FNC) scheme and fixed-region BS cooperation (FRC) scheme, respectively. In the FNC scheme, the cooperative BSs consist of the M nearest BSs around the served cell-edge users, and in the FRC scheme, the cooperative BSs include all the BSs located within a given region. We derive the expressions for the average rate and the outage probability of a typical cell-edge user located at the origin based on the stochastic geometry framework. To reduce the computational complexity of our analytical results for the outage probability, we further propose a Gamma approximation-based method to provide approximations with satisfying accuracy. Our analytical results incorporate the critical characteristics of mmWave channels, i.e., the blockage effects, the different path loss of LOS and NLOS links, and the highly directional antenna arrays. Simulation results show that the performance of the cell-edge users is greatly improved when mmWave networks are combined with the technique of BS cooperation.

Social awareness and social ties are becoming increasingly popular with emerging mobile and handheld devices. Social trust degree describing the strength of the social ties has drawn lots of research interests in many fields in wireless communications, such as resource sharing, cooperative communication, and so on. In this paper, we propose a social ties based hybrid cooperative beamforming and jamming scheme to secure wireless transmissions under a stochastic geometry framework, where the friendly nodes are categorized into relays and jammers according to their locations and social trust degrees with the source node. Connection outage probability (COP) and secrecy outage probability (SOP) of such a scheme in a random network have been analyzed. To facilitate a more convenient performance evaluation, we propose a double Gamma ratio approach through the Gamma approximation method. Based on this, the COP and SOP are tractably obtained in closed-forms. We further consider the SOP in the presence of Poisson point process distributed eavesdroppers and derive an upper bound. The simulation results verify our theoretical findings, and validate that the social trust degree has dramatic influences on the security performance in the networks.

In this paper, we consider the problem of joint secure routing and transmit power optimization for a multi-hop ad-hoc network under the existence of randomly distributed eavesdroppers following a Poisson point process. Secrecy messages are delivered from a source to a destination through a multi-hop route connected by multiple legitimate relays in the network. Our goal is to minimize the end-to-end connection outage probability under the constraint of a secrecy outage probability threshold, by optimizing the routing path and the transmit power of each hop jointly. We show that the globally optimal solution could be obtained by a two-step procedure where the optimal transmit power has a closed-form and the optimal routing path can be found by Dijkstra's algorithm. Then a friendly jammer with multiple antennas is applied to enhance the secrecy performance further, and the optimal transmit power of the jammer and each hop of the selected route is investigated. This problem can be solved optimally via an iterative outer polyblock approximation with 1-D search algorithm. Furthermore, suboptimal transmit powers can be derived using the successive convex approximation method with a lower complexity. Simulation results show the performance improvement of the proposed algorithms for both non-jamming and jamming scenarios, and also reveal a non-trivial tradeoff between the numbers of hops and the transmit power of each hop for secure routing.

This paper studies physical-layer security for a cache-enabled heterogeneous cellular network comprised of a macro base station and multiple small base stations (SBSs). We investigate a joint design on caching placement and file delivery for realizing secure and energy-efficient transmissions against randomly distributed eavesdroppers. We propose a novel hybrid “most popular content” and “largest content diversity” caching placement policy to distribute the files of different popularities. Depending on the availability and placement of the requested file, we employ three cooperative transmission schemes, namely, distributed beamforming, frequency-domain orthogonal transmission, and best SBS relaying. We derive analytical expressions for the connection outage probability and secrecy outage probability for each transmission scheme. Afterward, we design the optimal transmission rates and caching allocation successively to achieve a maximal overall secrecy throughput and secrecy energy efficiency, respectively. Numerical results verify the theoretical analyses and demonstrate the superiority of the proposed hybrid caching policy.

In this paper, we investigate the design of a pilot spoofing attack (PSA) carried out by multiple single-antenna eavesdroppers (Eves) in a downlink time-division duplex system, where a multiple antenna base station (BS) transmits confidential information to a single-antenna legitimate user. During the uplink channel training phase, multiple Eves collaboratively impair the channel acquisition of the legitimate link, aimed at maximizing the wiretapping signal-to-noise ratio (SNR) in the subsequent downlink data transmission phase. Two different scenarios are investigated: 1) the BS is unaware of the PSA and 2) the BS attempts to detect the presence of the PSA. For both scenarios, we formulate wiretapping SNR maximization problems. For the second scenario, we also investigate the probability of successful detection and constrain it to remain below a pre-designed threshold. The two resulting optimization problems can be unified into a more general non-convex optimization problem, and we propose an efficient algorithm based on the minorization-maximization (MM) method and the alternating direction method of multipliers (ADMM) to solve it. The proposed MM-ADMM algorithm is shown to converge to a stationary point of the general problem. In addition, we propose a semi-definite relaxation (SDR) method as a benchmark to evaluate the efficiency of the MM-ADMM algorithm. Numerical results show that the MM-ADMM algorithm achieves near-optimal performance and is computationally more efficient than the SDR-based method.

Mm-wave offers a sensible solution to the capacity crunch faced by 5G wireless communications. This paper comprehensively studies physical layer security in a multi-input single-output mm-wave system, where multiple single-antenna eavesdroppers are randomly located. Concerning the specific propagation characteristics of mm-wave, we investigate two secure transmission schemes, namely maximum ratio transmitting beamforming and artificial noise (AN) beamforming. Specifically, we first derive closed-form expressions of the connection probability for both schemes. We then analyze the secrecy outage probability in both non-colluding eavesdroppers and colluding eavesdroppers scenarios. Also, we maximize the secrecy throughput under a secrecy outage probability constraint, and obtain optimal transmission parameters, especially the power allocation between AN and the information signal for AN beamforming. Numerical results are provided to verify our theoretical analysis. We observe that the density of eavesdroppers, the spatially resolvable paths of the destination and eavesdroppers all contribute to the secrecy performance and the parameter design of mm-wave systems.

This paper investigates the link selection policy for secure communications over a buffer-aided two-hop communication link. It is assumed that a source wishes to send information to a destination with the aid of a trusted half-duplex relay node compromised by an eavesdropper, and that there is no direct link between the source and the destination. The buffer-aided relay forwards the information to the destination by employing the randomize-and-forward scheme. Both the source and the relay transmissions are assumed to be vulnerable to the eavesdropper. The perfect channel side information of the network is assumed to be available at the source and the relay. Initially, conventional relaying protocols where equal partition of the time for the reception and transmission of the relay is considered. Then, the optimal time fraction with the optimal power control policy that maximizes the secrecy throughput is identified. Moreover, the optimal joint link selection and power control policy that maximizes the secrecy throughput is derived. Subsequently, a low complexity and asymptotically optimal link selection with ON/OFF power control is proposed. Numerical results demonstrate that the proposed link selection policies with power control can significantly improve the achievable secrecy throughput of the buffer-aided two-hop communication system.

This paper explores the physical-layer security in a small cell network with cooperative cache-enabled small base stations (SBSs) in the presence of randomly distributed eavesdroppers. We propose a joint design on the caching placement and the physical-layer transmission to improve the secure content delivery probability (SCDP). We first put forward a hybrid caching placement strategy in which a proportion of the cache unit in each SBS is assigned to store the most popular files (MPFs), while the remaining is used to cache the disjoint subfiles (DSFs) of the less popular files in different SBSs as a means to enhance transmission secrecy and content diversity. We then introduce two coordinated multi-point techniques, namely, joint transmission and orthogonal transmission, to deliver the MPFs and DSFs, respectively. We derive analytical expressions for the SCDP in each transmission scheme, considering both non-colluding and colluding eavesdropping scenarios. Based on the obtained analytical results, we jointly design the optimal transmission rates and the optimal caching assignment for maximizing the overall SCDP. Various insights into the optimal transmission and caching designs are further provided. Numerical results are also presented to verify our theoretical findings and to demonstrate the superiority of the proposed caching and transmission strategies.

This paper proposes a new nonadaptive (NADP) transmission scheme with adjustable power allocation based on the instantaneous channel state information (CSI) of the main channel for the multiple-input-single-output-single-eavesdropper (MISOSE) system. With the assistance of the adjustable power allocation ratio, we can improve the secure transmission performance under the constraints of secrecy outage probability (SOP) and upper bound rate (UBR). To verify the superiority of our new approach, we consider the multi-antenna communication systems with NADP scheme and give the optimal solution for achieving the maximum secrecy throughput based on a two-dimensional (2-D) searching method. In addition, a good suboptimal solution is also provided to reduce the time complexity of the optimal solution. Simulation results are provided and confirm that the proposed NADP scheme has significant advantages over the existing work especially when the transmit power is high.

This paper studies the artificial noise (AN) aided secure transmission design in a multiple-input- single-output multicast channel where a common message is transmitted to multiple receivers and only statistical channel state information of the eavesdropper is available. In this scenario, there may be no valid null space which allows the AN not to affect the legitimate receivers, and the traditional null-space AN scheme may not be applicable. To find the optimal design, we formulate a secrecy outage probability (SOP) constrained secrecy rate maximization problem which applies to an arbitrary number of the receivers. We adopt a novel approximation of the intractable SOP constraint and establish an efficient algorithm which solves the approximated problem to global optimality. The effectiveness of AN as well as the proposed solution is confirmed by simulation results. It is shown that the AN aided approach performs much better than pure beamforming even when there is no valid null space.

The artificial noise (AN) aided beamforming design in the MISOME (multiple-input, single-output, multiple-eavesdropper) wiretap channel is studied from the perspective of secrecy outage. Unlike many existing works which directly adopted the traditional null-space AN scheme, we start with a general assumption on the structure of the transmit signal, and seek to find the optimal structure by solving a secrecy outage probability (SOP) constrained secrecy rate maximization problem. By generalizing several existing conclusions regarding a single-antenna eavesdropper, we prove that the null-space AN scheme is indeed optimal for an arbitrary number of the eavesdropper's antennas from the perspective of secrecy outage. The power allocation problem is also studied and the closed-form optimal solution is obtained. It is found that the increase in the eavesdropper's antenna number is equivalent to requiring a smaller SOP.

In this paper, the outage performance of nonorthogonal multiple access (NOMA) is investigated in a downlink space division multiple access (SDMA) network with a multi-antenna base station and randomly deployed users. The NOMA technology is concurrently exploited with SDMA to further improve spectral efficiency. With limited channel state information (CSI) feedback taken into account, an analytical framework is proposed to evaluate outage performance for a given user. An expression for the outage probability is derived in closed form. Moreover, the diversity order and the effect of the number of feedback bits on the outage performance of NOMA are analyzed. Numerical results are demonstrated to verify our analytical findings and show that different from the perfect CSI case there always exists performance floor in the considered network due to limited feedback.

In this paper, we investigate physical-layer security in a wireless ad hoc network in which a large number of legitimate transmitter-receiver pairs coexist with randomly distributed eavesdroppers; each legitimate receiver works in either half-duplex (HD) or full-duplex (FD) mode. We aim to increase the number of secure links per unit area in the network of interest by determining the allocation between HD- and FD-mode links. We use tools from stochastic geometry theory and analyze the connection outage probability and the secrecy outage probability for an arbitrary legitimate link by deriving analytical expressions, based on which we then figure out the optimal fraction of FD-mode links that maximizes the area secure link number given a pair of wiretap code rates. We further develop insights into this optimal fraction and derive a closed-form expression for it assuming perfect self-interference cancellation. Numerical results are demonstrated to validate our theoretical findings.

Multi-region geocast, an efficient technique for routing protocols at the network layer, realizes the delivery of different information to different user groups that are differentiated from each other by their geographical locations. This paper studies multi-region geocast at the physical layer for the first time by exploiting non- orthogonal multiple access (NOMA) which is one of the promising technologies for future 5G systems. We investigate physical-layer multi-region geocast by studying its beamforming design in a multiple-input single-output (MISO) NOMA system. The objective is to minimize the total transmit power subject to a prescribed data rate for each user group. To this end, we propose an efficient algorithm based on the sequential convex approximation (SCA) method. Our simulation results show that multi-region geocast using NOMA achieves better performance than conventional multi-group multicast when the disparity level among the geographical locations of user groups is remarkable. Further, NOMA is more favorable for limited transmit antennas and massive connectivity in future 5G systems.

In this paper, the performance of non-orthogonal multiple access (NOMA) is investigated and optimized in a downlink space division multiple access network with a multi-antenna base station and randomly deployed users, under a general channel state information (CSI) limited feedback framework. We first propose a dynamic user scheduling and grouping strategy by leveraging limited feedback. Based on that, an analytical framework is proposed to obtain the outage probability of the network in closed form. The diversity order and the impacts of the number of feedback bits on the outage performance of NOMA are analyzed. Furthermore, the net throughput, which captures the network-wide throughput with the uplink feedback cost considered, is maximized by optimizing the number of feedback bits. Numerical results are demonstrated to verify our analytical findings and show that different from the perfect CSI case, there always exists a performance floor of outage probability in the considered network due to limited feedback. Moreover, the optimal number of feedback bits for net throughput maximization increases as the channel coherence time becomes longer.

This letter investigates the optimal power allocation for weighted sum rate maximization (WSRM) in nonorthogonal multiple access (NOMA) systems with power order and quality-of-service (QoS) constraints. We show that the NOMA WSRM problem is a convex problem under some condition of the user weights. The optimal solution to the WSRM problem without QoS constraints is analytically characterized in two cases. Then, we investigate the feasibility of the WSRM problem with QoS constraints. We further show that the power order constraint can be omitted without loss of any optimality under some mild condition of the QoS thresholds, which enables us to derive an analytical expression of the optimal power allocation.

Exploiting millimeter wave is an effective way to meet the data traffic demand in the 5G wireless communication system. In this paper, we study secure transmissions under slow fading channels with multipath propagation in millimeter wave systems. Concerning the new propagation characteristics of millimeter wave, we investigate three transmission schemes, namely, maximum ratio transmitting (MRT) beamforming, artificial noise (AN) beamforming, and partial MRT (PMRT) beamforming. We evaluate the secrecy performance by analyzing both the secrecy outage probability (SOP) and the secrecy throughput for each scheme. Particularly, for the AN scheme, we derive a closed-form expression for the optimal power allocation ratio of the information signal power to the total transmit power that minimizes the SOP, as well as obtain an explicit solution on the optimal transmission parameters that maximize the secrecy throughput. By comparing the secrecy performances achieved by different strategies, we demonstrate that the secrecy performance of the millimeter wave system is significantly influenced by the relationship between the legitimate user's and the eavesdropper's spatially resolvable paths, which is different from the wireless systems with statistically independent channel models. In the absence of the common path between the legitimate user and the eavesdropper, MRT beamforming is the best scheme. In the presence of common paths, AN beamforming and PMRT beamforming show their respective superiorities depending on the transmit power and the number of common paths. Numerical results are provided to verify our theoretical analysis.

In this paper, we propose a joint source-relay precoding scheme to secure an amplify-and-forward multiple-input multiple-output wireless relay network in the existence of a multi-antenna eavesdropper. Different from existing works that only consider some specific signal design to simplify the problem, we take both the direct links from the source to the destination and to the eavesdropper into account, and investigate the general joint signal covariance matrices optimization problem to maximize the secrecy rate, which leads to a difficult non-convex optimization problem. To handle it, we propose a group alternating optimization algorithm to find a solution, which alternately optimizes the signal covariance matrix and the linear precoding matrix at the source and the relay, respectively. For optimizing the linear precoding matrix at the relay, the problem is still non-convex, and we propose a minorization-maximization (MM) method to handle it. The MM method transforms the original non-convex problem into a series of convex problems and guarantees the convergence of a local optimum. For optimizing the signal covariance matrix at the source, we reveal the convex-concave property of the problem, and find its global optimum using a barrier method combined with the Newton iteration. We also provide an initialization method to trigger the algorithm and analyze the convergence and complexity. The numerical results show the computational efficiency and the prominent performance of the proposed algorithm.

In this paper, we study power-efficient resource allocation for multicarrier non-orthogonal multiple access systems. The resource allocation algorithm design is formulated as a non-convex optimization problem which jointly designs the power allocation, rate allocation, user scheduling, and successive interference cancellation (SIC) decoding policy for minimizing the total transmit power. The proposed framework takes into account the imperfection of channel state information at transmitter and quality of service requirements of users. To facilitate the design of optimal SIC decoding policy on each subcarrier, we define a channel-to-noise ratio outage threshold. Subsequently, the considered non-convex optimization problem is recast as a generalized linear multiplicative programming problem, for which a globally optimal solution is obtained via employing the branch-and-bound approach. The optimal resource allocation policy serves as a system performance benchmark due to its high computational complexity. To strike a balance between system performance and computational complexity, we propose a suboptimal iterative resource allocation algorithm based on difference of convex programming. Simulation results demonstrate that the suboptimal scheme achieves a close-to-optimal performance. Also, both proposed schemes provide significant transmit power savings than that of conventional orthogonal multiple access schemes.

Large-scale multi-input multi-output (MIMO) technique has drawn considerable research interest recently. However, multiuser transmissions in large-scale MIMO systems would face challenging estimation and compensation for multiple carrier frequency offsets (CFOs) that co-exist at the receiver. In this paper, we design a new frequency synchronization scheme in multiuser orthogonal frequency division multiplexing uplink with the aid of scattered pilot symbols. We specifically consider a base station with a large number of antennas and propose to assign a number of scattered pilot subcarriers to each user. With sufficient spatial dimensions offered by the large number of antennas, the designed scheme could estimate CFO for each user individually and eliminate the necessity of the multidimensional search. Moreover, after the CFO estimation, the receive beamforming matrix is further designed for inter-user interference cancelation, which yields an equivalent single user transmission model. The conventional single user channel estimation and data detection can then be performed. Finally, the numerical results are provided to verify the proposed studies.

With the recent emergence of 5G era, heterogeneous cellular networks (HCNs) have invoked a popular research interest. In this paper, we provide a comprehensive analysis for multi-antenna transmissions in a multi-tier downlink HCN. We first propose a reliability-oriented threshold-based mobile association policy, where each user connects to the strongest base station from which this user can obtain the largest truncated long-term received power. Under our mobile association policy, we derive analytical expressions for the exact outage probability of an arbitrary randomly located user, along with computationally convenient lower and upper bounds. Asymptotic analysis on the outage probability shows that introducing a large access threshold into mobile association significantly decreases the outage probability. We further investigate the spectrum efficiency and the energy efficiency of the HCN. Our theoretic analysis and numerical validations show that both the spectrum and energy efficiencies can be improved by properly choosing the access threshold.

This paper studies physical layer security in a wireless ad hoc network with numerous legitimate transmitter-receiver pairs and eavesdroppers. A hybrid full-duplex (FD)/half-duplex receiver deployment strategy is proposed to secure legitimate transmissions, by letting a fraction of legitimate receivers work in the FD mode sending jamming signals to confuse eavesdroppers upon their information receptions, and letting the other receivers work in the half-duplex mode just receiving their desired signals. The objective of this paper is to choose properly the fraction of FD receivers for achieving the optimal network security performance. Both accurate expressions and tractable approximations for the connection outage probability and the secrecy outage probability of an arbitrary legitimate link are derived, based on which the area secure link number, network-wide secrecy throughput, and network-wide secrecy energy efficiency are optimized, respectively. Various insights into the optimal fraction are further developed, and its closed-form expressions are also derived under perfect self-interference cancellation or in a dense network. It is concluded that the fraction of FD receivers triggers a non-trivial tradeoff between reliability and secrecy, and the proposed strategy can significantly enhance the network security performance.

In this paper, we study the benefits of full-duplex (FD) receiver jamming in enhancing the physical-layer security of a two-tier decentralized wireless network with each tier deployed with a large number of pairs of a single-antenna transmitter and a multi-antenna receiver. In the underlying tier, the transmitter sends unclassified information and the receiver works in the half-duplex (HD) mode receiving the desired signal. In the overlaid tier, the transmitter delivers confidential information in the presence of randomly located eavesdroppers, and the receiver works in the FD mode radiating jamming signals to confuse eavesdroppers and receiving the desired signal simultaneously. We provide a comprehensive performance analysis and network design under a stochastic geometry framework. Specifically, we consider the scenarios where each FD receiver uses single- and multi-antenna jamming, and analyze the connection probability and the secrecy outage probability of a typical FD receiver by deriving accurate expressions and more tractable approximations for the two probabilities. We also determine the optimal deployment density of the FD-mode tier to maximize the network-wide secrecy throughput subject to constraints including the given dual probabilities and the network-wide throughput of the HD-mode tier. Numerical results are demonstrated to verify our theoretical findings, and show that the network-wide secrecy throughput is significantly improved by properly deploying the FD-mode tier.

In this paper, we investigate the physical-layer security of slow fading wiretap channel with channel estimation errors. We aim to maximize the reliable secrecy rate under constraints of secrecy outage probability and reliability outage probability. To this end, we propose an adaptive (ADP) transmission scheme in which the communication rate and secrecy rate are adaptively adjusted based on the estimated imperfect channel state information (CSI) of the legitimate channel. The optimal solution is obtained by solving a single-variable maximization problem, where the objective function is log-concave. Numerical results are provided to verify our approach as well as to show the impact of imperfect CSI on the secrecy throughput.

In this paper, we propose a new frequency synchronization scheme for multiuser orthogonal frequency division multiplexing (OFDM) uplink with a large-scale uniform linear array (ULA) at base station (BS). Considering that the incident signal at BS from each user can be restricted within a narrow angular spread, the proposed scheme performs carrier frequency offset (CFO) estimation for each user individually through a joint spatial-frequency alignment procedure. The basic idea behind is that with sufficient spatial dimension, the multiuser interference (MUI) effect can be effectively mitigated via beamforming with the steering vectors corresponding to any direction of arrival (DOA) of each user. A multi-branch receive beamforming is further designed for each user which results in an equivalent single user transmission model and the conventional single-user channel estimation and data detection can be carried out. We show that the proposed CFO estimation can be applied efficiently with the aided of fast Fourier transform (FFT). The theoretical CFO estimation performance analysis is also conducted. Various numerical results are provided to verify the proposed studies.

This paper studies the dirty-paper coding (DPC) based secure transmission in a multiuser broadcast channel. Since the encoding order of DPC determines which information-bearing signals must be treated as noise by potential eavesdroppers, adopting DPC enables the accurate characterization of the intrinsic secrecy as well as secrecy outage of multiuser broadcasting. Furthermore, the information-bearing signals can be designed to provide secrecy in addition to supporting normal (unclassified) transmission. To show this, we consider the scenario where one user requests secure transmission and the other users request normal transmission, and propose a hybrid secure transmission scheme which combines zero-forcing DPC and artificial noise (AN). By solving the secrecy rate maximization problem under constraints on the secrecy outage probability and the normal communication rates, we find that in addition to supporting the normal transmission, the proposed scheme has the potential to achieve a secrecy rate close to that of the traditional AN-based beamforming.

Backscatter wireless communication is an emerging technique widely used in passive radio frequency identification (RFID) systems. Recently, the requirement of a high data rate, data reliability, and secure transmission is becoming the main driving force for the development of RFID systems, which motivates the introduction of multiple-input multiple-output (MIMO) schemes and physical layer security techniques into backscatter systems. In this paper, the combination of multiple antennas and physical layer security techniques is exploited to improve the security level of backscatter systems. We propose a noise-injection precoding strategy and subsequently study the transmit optimization, wherein we aim at maximizing the achievable secrecy rate (SRM) under a total transmit power constraint. To this end, the sequential parametric convex approximation (SPCA) method is exploited to tackle the non-convex SRM problem and subsequently an algorithm based on projected gradient (PG) is proposed for fast implementation, which is especially beneficial to the resource-constrained RFID device. Our simulation results show the superior secrecy rate performance achieved by the proposed noise-injection precoding scheme and high computational efficiency of the proposed fast PG algorithm.

In this paper, we provide a comprehensive analysis of the multi-antenna transmission in a K-tier downlink heterogeneous cellular network (HCN). We first propose a reliability-oriented mobile access policy with an access threshold, in which each user connects to the strongest base station in terms of the truncated long-term received power. Under this policy, we derive for a random user explicit analytical expressions of the exact out-age probability along with its computational convenient lower and upper bounds. Asymptotic analysis on the outage probabilities shows that introducing the access threshold efficiently improves outage performance. We further investigate the area network throughput from the perspective of outage. Our theoretic analysis and numerical validations show that throughput performance can be enhanced by properly designing the access threshold.

In this paper, we study the secrecy throughput in millimeter wave systems under slow fading channels considering multipath propagation. For the specific propagation characteristics of millimeter wave, we provide transmission scheme designs and a comprehensive secrecy performance analysis. Specifically, we maximize the secrecy throughput under a secrecy outage probability (SOP) constraint through a dynamic parameter transmission scheme, and provide the optimal solution to transmission parameters, including the codeword rate and the power allocation ratio of the information signal power to the total transmit power. We find that the secrecy performance of the millimeter wave system under investigation is significantly influenced by the relationship between spatially resolvable paths of the legitimate user and those of the eavesdropper, which differs from those wireless systems with statistically independent channel. Numerical results are provided to verify our theoretical analysis.

In this paper, we propose a new blind frequency synchronization scheme for an OFDM system with I/Q imbalance. A blind estimation of joint CFO and I/Q imbalance parameters is first developed by exploiting the multi-antenna redundancy at the receiver. The estimation computational complexity is reduced by expressing the cost function as a superposition of very few harmonically related cosine waves. The compensation for CFO and I/Q imbalance can be further carried out, which would result in an equivalent received signal model without CFO and I/Q imbalance distortion. Then the conventional channel estimation and data detection can be performed. The Cramer-Rao bound (CRB) of the CFO estimation is derived. We also provide numerical simulations to demonstrate the superiority of the proposed method over the existing competitors.

Non-orthogonal multiple access (NOMA) has been recognized as a potential technique to achieve higher spectral efficiency (SE) for future 5G systems. However, the anticipated thousand-fold increase in wireless data traffic urgently calls for new designs of power-efficient communication systems. In this paper, we investigate NOMA from the perspective of energy efficiency (EE) in a multiuser downlink system. Firstly, we generalize an existing cognitive radio (CR) inspired NOMA scheme by introducing multiple antenna techniques and extending the number of primary users to an arbitrary number. Then, we aim at optimizing the EE of this generalized CR inspired NOMA scheme subject to an individual quality of service (QoS) constraint for each primary user, which leads to a non-convex fractional programming problem. For this challenging problem, we propose an efficient algorithm based on the sequential convex approximation (SCA) method. Our numerical results show that NOMA has superior EE performance in comparison with conventional orthogonal multiple access (OMA).

A practical uncoordinated cooperative jamming (UCJ) scheme with multiple single-antenna helpers is proposed in this paper to enhance the physical layer security of single-input-multiple-output (SIMO) wiretap channel. In the scheme, both the intended receiver and the eavesdropper are equipped with multiple antennas and apply the minimum mean-square error (MMSE) combiner. The multiple uncoordinated single-antenna helpers transmit jamming signals independently to confound the eavesdropper, and we focus on power allocation for the helpers to solve the secrecy rate maximization (SRM) problem. Assuming that the statistical channel state information (CSI) concerning the eavesdropper is available, a convex conservative secrecy outage probability (SOP) constraint is derived and then used to solve the SRM problem with DC (difference of convex function) programming method. Furthermore, a bisection-like refinement method is provided to find a quality solution of the SRM problem with the original SOP constraint. Numerical results show that the proposed scheme has good secrecy performance especially when the number of helpers is large.

The use of millimeter wave is an effective way to meet the data traffic demand of the 5G wireless communication system. For the new propagation characteristics of millimeter wave, in this paper, we study the secure transmission with artificial noise under slow fading channels considering multipath propagation in millimeter wave systems. Firstly, when partial eavesdropper's channel state information is known at the transmitter, an artificial noise transmission strategy which depends on directions of the destination's and the eavesdropper's propagation paths is proposed. Then we analyze the secrecy outage probability (SOP) through an on-off transmission scheme. Furthermore, we minimize the SOP subject to a secrecy rate constraint and derive a closed-form optimal power allocation between the information bearing signal and artificial noise. Numerical results are provided to show the superiority of the proposed scheme.

In this paper, we investigate secure communications uplink transmissions, where there are a base station (BS) with M receive antennas, K mobile users each with a single antenna, and an eavesdropper with N receive antennas. The closed-form expressions of the achievable ergodic secrecy sum rates (ESSRs) for a random k users selection scheme in the high and low signal-to-noise ratio regimes are presented. It is shown that the scaling behavior of ESSR with respect to the number served users k can be quite different under different system configurations, determined by the numbers of the BS antennas and that of the eavesdropper antennas. In order to achieve multiuser gain, two low-complexity user selection schemes are proposed under different assumptions on the eavesdropper's channel state information. The closed-form expressions of the achievable ESSRs and the multiuser secrecy gains of the two schemes are also presented in both low and high SNR regimes. observe that, as k increases, the multiuser secrecy gain increases, while the ESSR may decrease. Therefore, when N much larger than M, serving one user with the strongest channel (Time Division Multiple Address-like) is a favorable secrecy scheme, where the ESSR scales with √2 log K.

The heterogeneous cellular network (HCN) is a promising approach to the deployment of 5G cellular networks. This paper comprehensively studies physical layer security in a multitier HCN where base stations (BSs), authorized users, and eavesdroppers are all randomly located. We first propose an access threshold-based secrecy mobile association policy that associates each user with the BS providing the maximum truncated average received signal power beyond a threshold. Under the proposed policy, we investigate the connection probability and secrecy probability of a randomly located user and provide tractable expressions for the two metrics. Asymptotic analysis reveals that setting a larger access threshold increases the connection probability while decreases the secrecy probability. We further evaluate the network-wide secrecy throughput and the minimum secrecy throughput per user with both connection and secrecy probability constraints. We show that introducing a properly chosen access threshold significantly enhances the secrecy throughput performance of a HCN.

Recent studies show that millimeter wave (mmWave) communications can offer orders of magnitude, which increases in the cellular capacity. However, the secrecy performance of an mmWave cellular network has not been investigated so far. Leveraging the new path-loss and blockage models for mmWave channels, which are significantly different from the conventional microwave channel, this paper comprehensively studies the network-wide physical layer security performance of the downlink transmission in an mmWave cellular network under a stochastic geometry framework. We first study the secure connectivity probability and the average number of perfect communication links per unit area in a noise-limited mmWave network for both non-colluding and colluding eavesdroppers scenarios, respectively. Then, we evaluate the effect of the artificial noise (AN) on the secrecy performance, and derive the analysis result of average number of perfect communication links per unit area in an interference-limited mmWave network. Numerical results demonstrate the network-wide secrecy performance, and provide interesting insights into how the secrecy performance is influenced by various network parameters: antenna array pattern, base station intensity, and AN power allocation.

This paper studies the impact of artificial noise (AN) on the secrecy performance of a target cell in multi-cell cellular networks. Although AN turns out to be an efficient approach for securing a point-to-point/single-cell confidential transmission, it would increase the inter-cell interference in a multi-cell cellular network, which may degrade the network reliability and secrecy performance. For analyzing the average secrecy performance of the target cell which is of significant interest, we employ a hybrid cellular deployment model, where the target cell is a circle of fixed size, and the base stations outside the target cell are modeled as a homogeneous Poisson point process. We investigate the impact of AN on the reliability and security of users in the target cell in the presence of pilot contamination using a stochastic geometry approach. The analytical results of the average connection outage and the secrecy outage of its cellular user (CU) in the target cell are given, which facilitates the evaluation of the average secrecy throughput of a randomly chosen CU in the target cell. It shows that with an optimized power allocation between the desired signals and AN, the AN scheme is an efficient solution for securing the communications in a multi-cell cellular network.

Backscatter wireless communication is an emerging technique widely used in low-cost and low-power wireless systems, especially in passive radio frequency identification (RFID) systems. Recently, the requirement of high data rates, data reliability, and security drives the development of RFID systems, which motivates our investigation on the physical layer security of a multiple-input multiple-output (MIMO) RFID system. In this paper, we propose a noise-injection precoding strategy to safeguard the system security with the resource-constrained nature of the backscatter system taken into consideration. We first consider a multi-antenna RFID tag case and investigate the secrecy rate maximization (SRM) problem by jointly optimizing the energy supply power and the precoding matrix of the injected artificial noise at the RFID reader. We exploit the alternating optimization method and the sequential parametric convex approximation method, respectively, to tackle the non-convex SRM problem and show an interesting fact that the two methods are actually equivalent for our SRM problem with the convergence of a Karush-Kuhn-Tucker point. To facilitate the practical implementation for resource-constrained RFID devices, we propose a fast algorithm based on projected gradient. We also consider a single-antenna RFID tag case and develop a low-complexity algorithm, which yields the global optimal solution. Simulation results show the superiority of our proposed algorithms in terms of the secrecy rate and computational complexity.

In this paper, we investigate the secrecy performance of matched-filter (MF) and zero-forcing (ZF) precoding in a multiuser massive multiple-input multiple-output (MIMO) system with a multi-antenna passive eavesdropper. For the two precoding schemes, we find that the equivalent wiretap channels are similar and thus the eavesdropper achieves the approximate same sum-rate. Closed-form expressions of ergodic secrecy sum-rate (ESSR) are derived for the both schemes in the low and high signal-to-noise ratio (SNR) regimes. We show that a positive ESSR of MF scheme may be not achieved when the BS simultaneously serves more than two users with high transmit power, while the ESSR of ZF scheme always grows with the number of the served users. On the contrast, MF scheme is better than ZF scheme in the low SNR regime. Simulation results corroborate the analytic results.

In this paper, we propose a new efficient blind carrier frequency offset (CFO) estimator for multi-input multi-output orthogonal frequency division multiplexing (MIMO-OFDM) systems. A cost function is carefully designed which can be exactly expressed as a superposition of very few harmonically related cosine waves even with the effect of noise. By using this property, the minimization of the designed cost function can be solved in a quite computationally efficient manner without any exhausted grid searching procedure. We provide numerical results to corroborate the proposed studies. It is seen that the proposed estimator can achieve comparable estimation performance with existing competitors with substantially reduced computational burden.

In this paper, we focus on the physical-layer security of a multiuser cellular downlink system. A multi-antenna base station (BS) communicates with several legitimate users, where a target user is overheard by an eavesdropper in the downlink transmission. We aim at designing linear precoders for the BS to maximize the secrecy rate of target user under the condition that a certain Quality-of- Service (QoS) is guaranteed for the other legitimate users. To solve the non-convex optimization problem, we propose an iterative algorithm to transform the original problem into a sequence of approximate convex problems, which can be solved using interior point method. Simulation results reveal that compared with two other methods dealing with the similar optimization problem in previous works, our proposed method can achieve a higher secrecy rate.

In this letter, we propose a distributed jamming strategy to maximize the achievable ergodic secrecy rate (ESR) of a single-input multi-output (SIMO) transmission with a multiple-antenna eavesdropper based on only the statistical channel state information (CSI). In the scheme, exploring the heterogeneous large-scale fading effects, multiple geographically distributed single-antenna jammers transmit independent and uncoordinated jamming signals to confound the eavesdropper. We derive a large-scale asymptotic approximation of the achievable ESR, and optimize the transmit power of each jammer for maximizing the asymptotic ESR by geometric programming (GP). The proposed scheme does not require signal coordination among jammers and greatly reduces the training/synchronization overhead, which is applicable when the receiver has a large number of antennas, i.e., massive MIMO system.

In this paper, we provide a comprehensive study of secrecy transmission in decode-and-forward (DF) relay networks subjected to slow fading. With only channel distribution information (CDI) of the wiretap channels, we aim at maximizing secrecy throughput of the two-hop transmission under a secrecy outage constraint through optimizing transmission region, rate parameters of the wiretap codes and power allocation between the source and relay. We propose fixed transmission parameter scheme (FTPS) and variable transmission parameter scheme (VTPS), which are based on the CDI and instantaneous channel state information of the main channels, respectively. In both schemes, source and relay use the same codeword, and the eavesdropper can use maximum ratio combining (MRC) reception. To improve the secrecy throughput, we further propose VTPS-D1 and VTPS-D2 schemes, where the source and relay either use independent codewords with identical code rates, or different codebooks with different code rates so that the eavesdropper can only decode the two-hop signals individually rather than using MRC. We provide explicit results on the design for all proposed schemes. Numerical results and comparisons on the secrecy throughput of these schemes are presented to reveal their respective superiorities and give some insights into the choice of design scheme.

In this paper, we study the secure multi-antenna transmission with artificial noise (AN) under slow fading channels coexisting with randomly located eavesdroppers. We provide a comprehensive secrecy performance analysis and system design/optimization under a stochastic geometry framework. Specifically, we first evaluate the secrecy outage performance, and derive a closed-form expression for the optimal power allocation ratio of the information signal power to the total transmit power that minimizes the secrecy outage probability (SOP). Subject to a SOP constraint, we then propose a dynamic parameter transmission scheme (DPTS) and a static parameter transmission scheme (SPTS) to maximize secrecy throughput, and provide explicit solutions on the optimal transmission parameters, including the wiretap code rates, the on-off transmission threshold and the power allocation ratio. Our results give new insight into secure transmission designs. For example, secrecy rate is a concave function of the power allocation ratio in DPTS, and AN plays a significant role under SOP constraints and in dense eavesdropper scenarios. In SPTS, transmission probability is a concave function of the power allocation ratio, and secrecy throughput is a quasi-concave function of the secrecy rate. Numerical results are demonstrated to validate our theoretical analysis.

In this paper, we consider the problem of secure communications for a four-node system consisting of one source, one destination, one eavesdropper, and one helper. We investigate the question of which role should the helper act to improve the secrecy, to jam, or to relay. Two transmission schemes are investigated: (1) direct transmission scheme (DTS) with jamming and (2) relay transmission scheme (RTS). We consider both the path-loss and fading-in channel models and define a notion of distance normalized signal-to-noise-ratio (DN-SNR) to account for propagation. The ergodic secrecy rate (ESR) is adopted as the performance metric and semi-closed-form expressions of ESR for the two schemes are derived. Additionally, optimal power allocations in both low and high DN-SNR regimes are characterized analytically. We give the performance comparison of the two schemes from the perspective of energy efficiency in the low DN-SNR regime, and characterize the secrecy degree of freedom in the high DN-SNR regime. In the high DN-SNR regime, DTS provides higher secrecy rate compared with RTS, while in the low DN-SNR regime, RTS outperforms DTS. Furthermore, we show that eavesdropper's position impacts greatly on security.

This paper investigates the physical-layer security of a multiuser peer-to-peer (MUP2P) relay network for amplify-and-forward (AF) protocol, where a secure user and other unclassified users coexist with a multi-antenna eavesdropper and the eavesdropper can wiretap the confidential information in both two cooperative phases. Our goal is to optimize the transmit power of the source and the beamforming weights of the relays jointly for secrecy rate maximization subject to the minimum signal-to-interference-noise-ratio (SINR) constraint at each user, and the individual and total power constraints. Mathematically, the optimization problem is non-linear and non-convex, which does not facilitate an efficient resource allocation algorithm design. As an alternative, a null space beamforming scheme is adopted at the relays for simplifying the joint optimization and eliminating the confidential information leakage in the second cooperative phase, where the relay beamforming vector lies in the null space of the equivalent channel of the relay to eavesdropper links. Although the null space beamforming scheme simplifies the design of resource allocation algorithm, the considered problem is still non-convex and obtaining the global optimum is very difficult, if not impossible. Employing a sequential parametric convex approximation (SPCA) method, we propose an iterative algorithm to obtain an efficient solution of the non-convex problem. Besides, the proposed joint design algorithm requires a feasible starting point, we also propose a low complexity feasible initial points searching algorithm. Simulations demonstrate the validity of the proposed strategy.

This paper studies the cooperative transmission for securing a decode-and-forward (DF) two-hop network where multiple cooperative nodes coexist with a potential eavesdropper. Under the more practical assumption that only the channel distribution information (CDI) of the eavesdropper is known, we propose an opportunistic relaying with artificial jamming secrecy scheme, where a “best” cooperative node is chosen among a collection of N possible candidates to forward the confidential signal and the others send jamming signals to confuse the eavesdroppers. We first investigate the ergodic secrecy rate (ESR) maximization problem by optimizing the power allocation between the confidential signal and jamming signals. In particular, we exploit the limiting distribution technique of extreme order statistics to build an asymptotic closed-form expression of the achievable ESR and the power allocation is optimized to maximize the ESR lower bound. Although the optimization problems are non-convex, we propose a sequential parametric convex approximation (SPCA) algorithm to locate the Karush-Kuhn-Tucker (KKT) solutions. Furthermore, taking the time variance of the legitimate links' CSIs into consideration, we address the impacts of the outdated CSIs to the proposed secrecy scheme, and derive an asymptotic ESR. Finally, we generalize the analysis to the scenario with multiple eavesdroppers, and give the asymptotic analytical results of the achievable ESR. Simulation results confirm our analytical results.

This paper studies a single-input multi-output multi-eavesdropper (SIMOME) wiretap channel with multiple friendly single-antenna jammers. We consider random networks where the jammers and the eavesdroppers are distributed according to independent two-dimensional homogeneous Poisson point processes (PPP). We propose an opportunistic jammer selection scheme for the physical layer security enhancement, where the jammers whose channels are nearly orthogonal to the channel direction information (CDI) of the legitimate channel are selected to transmit independent and identically distributed (i.i.d.) Gaussian jamming signals to confound the eavesdroppers. The proposed scheme does not require a centralized design and signal coordinations among multiple jammers are not needed anymore. Furthermore, we analyze both the achievable secrecy throughput and the ergodic secrecy rate of the proposed jammer selection scheme. Based on the analysis results, we optimize the selection threshold for the secrecy throughput maximization and ergodic secrecy rate maximization. Simulation results show that the proposed jammer selection scheme can achieve a substantial performance gain.

The artificial noise (AN) scheme is an efficient strategy for enhancing the secrecy rate of a multiple-input-single-output channel in the presence of a passive eavesdropper, whose channel state information is unavailable. Recently, a randomized beamforming scheme has been proposed for deteriorating the eavesdropper's bit-error-rate performance via corrupting its receiving signal by time-varying multiplicative noise. However, the secrecy rate of such a scheme has not been well addressed yet. In this paper, we name it the artificial fast fading (AFF) scheme and provide a comprehensive secrecy rate analysis for it. We show that with this scheme, the eavesdropper will face a noncoherent Ricean fading single-input-multiple-output channel. Although the closed-form secrecy rate is difficult to obtain, we derive an exact expression for the single-antenna-eavesdropper case and a lower bound for the multiantenna-eavesdropper case, both of which can be numerically calculated conveniently. Furthermore, we compare the AFF scheme with the AN scheme and show that their respective superiorities to each other depend on the number of antennas that the transmitter and the eavesdropper possessed, i.e., when the eavesdropper has more antennas than the transmitter does, the AFF scheme achieves a larger secrecy rate; otherwise, the AN scheme outperforms. Motivated by this observation, we propose a hybrid AN-AFF scheme and investigate the power allocation problem, which achieves better secrecy performance further.

The secrecy outage of a two-user slow fading broadcast channel is studied in this paper. We consider the scenario where independent and confidential messages are transmitted to each user using superposition coding in the presence of an external eavesdropper. We assume the instantaneous channel state information (CSI) of the eavesdropper's channel is not available and the secrecy outage can be claimed for each user. The secrecy outage probability of each user conditioned on the instantaneous CSI of the legitimate channel is studied and used to derive the achievable secrecy rate region under the conditional secrecy outage probability constraints. The average achievable secrecy rate, i.e. the secrecy throughput, is studied as the measure of performance under the slow fading. The optimal secrecy rate allocation strategy that achieves the boundary of the achievable secrecy throughput region is characterized for the general case and for the maximum sum secrecy throughput. Numerical results of the secrecy throughput regions are shown, and the parameters that influence the secrecy throughput are discussed.

In this paper, we investigate the security issue of a two-hop amplify-and-forward MIMO wireless relay networks in the existence of a multi-antenna eavesdropper. The optimal scheme to achieve the secrecy capacity involves a non-convex optimization and is still an open problem. Aiming to find an efficient way to enhance the secrecy rate, we propose a suboptimal joint source and relay linear precoding scheme. In the scheme, the source node adopt a generalized singular value decomposition (GSVD) based precoding to transmit the signal in the first phase, and the relay node forwards the received signal based on SVD in the null-space of the wiretap channel in the second phase. Power allocations in both phases are optimized to maximize the secrecy rate. An alternating iterative optimization algorithm is proposed to solve the problem. The algorithm is computationally efficient and guarantees to converge to a local optimum. Numerical evaluation results are provided to show the effectiveness of the iterative algorithm and the proposed secrecy scheme.

We investigate the physical layer security of a multiple-input single-output (MISO) channel in the presence of a multi-antenna passive eavesdropper. Traditionally, artificial noise (AN) scheme is an efficient security strategy without the channel state information (CSI) of the eavesdropper. In this paper, we propose and analyze an efficient security scheme called the artificial fast fading (AFF) scheme. The basic idea is to randomly weight the information symbols at different transmit antennas in a special manner so that the channel of the intended receiver is an AWGN channel while that of the eavesdropper is a fast fading channel. This prevents the eavesdropper obtaining the CSI using the blind channel estimation techniques so that it can only detect the information symbols in a non-coherent way, which greatly reduces the amount of information intercepted. More importantly, we derive the achievable secrecy rate of the sheme and provide a low bound of it, which can be numerically calculated. Compared with the exact secrecy rate of the AN scheme, even the low bound of the AFF scheme is larger, when the eavesdropper has more antennas than the transmitter.

In this paper, we investigate the security issue of a two-hop amplify-and-forward multiple-input multiple-output wireless relay network in the existence of a multiantenna eavesdropper. The optimal scheme to achieve the secrecy capacity involves a nonconvex optimization and is still an open problem. Aiming to find an efficient way to enhance the secrecy rate with a tractable complexity, we propose a suboptimal joint source and relay linear precoding and power allocation scheme. In the scheme, the source node adopts a generalized singular value decomposition (SVD)-based precoding to transmit the signal in the first phase, and the relay node forwards the received signal based on the SVD precoding in the null-space of the wiretap channel in the second phase. Power allocations in both phases are optimized to maximize the secrecy rate by an alternating iterative optimization algorithm. Each iteration involves two subproblems. One has a water-filling solution and the other has a closed-form solution or a water-filling-like solution as well, both of which are computationally very efficient. The iteration converges fast and we prove that it guarantees to find a stationary optimum. Furthermore, we show that when the eavesdropper has equal or more antennas than the source does, the secrecy rate is a quasi-concave function of the source power so that allocating all the source power is generally not optimal. Numerical evaluation results are provided to show the effectiveness of the iterative algorithm and the proposed secrecy scheme.

This paper studies the secure multiple-antenna transmission in slow fading channels for the cognitive radio network, where a multiple-input, single-output, multieavesdropper (MISOME) primary network coexisting with a multiple-input single-output secondary user (SU) pair. The SU can get the transmission opportunity to achieve its own data traffic by providing the secrecy guarantee for the PU with artificial noise. Different from the existing works, which adopt the instantaneous secrecy rate as the performance metric, with only the statistical channel state information (CSI) of the eavesdroppers, we maximize the secrecy throughput of the PU by designing and optimizing the beamforming, rate parameters of the wiretap code adopted by the PU, and power allocation between the information signal and the artificial noise of the SU, subjected to the secrecy outage constraint at the PU and a throughput constraint at the SU. We propose two design strategies: 1) nonadaptive secure transmission strategy (NASTS) and 2) adaptive secure transmission strategy, which are based on the statistical and instantaneous CSIs of the primary and secondary links, respectively. For both strategies, the exact rate parameters can be optimized through numerical methods. Moreover, we derive an explicit approximation for the optimal rate parameters of the NASTS at high SNR regime. Numerical results are illustrated to show the efficiency of the proposed schemes.

Cooperative beamforming and jamming are two efficient schemes to improve the physical-layer security of a wireless transmission in the presence of a passive eavesdropper. However, in most works they are discussed separately. In this paper, we propose a joint cooperative beamforming and jamming scheme to enhance the security of a cooperative relay network, where some intermediate nodes adopt distributed beamforming while the others jam the eavesdropper, simultaneously. Subjected to the more practical individual power constraint of each node, we propose a null-space beamforming based secrecy strategy. The beamformer design can be optimized by a bisection method and second-order convex cone programming (SOCP). Simulations show the joint scheme greatly improves the security.

In this paper, we propose an Alamouti coded orthogonal frequency-division multiplexing (OFDM) scheme for amplify-and-forward (AF) relay networks that contain multiple distributed relay nodes. The frequency asynchronous nature of the distributed system is considered in our design. By implementing simple operations, e.g., time reversal, conjugation and amplification, the proposed scheme eliminates the needs of knowledge of both channel states and the frequency offsets at the relay nodes. We prove that when the frequency offsets among the relay nodes are smaller than a certain threshold, full spatial diversity can be achieved at the destination node even with the linear receivers, e.g., zero-forcing (ZF) receiver. Numerical results are provided to corroborate the proposed studies.

Exploiting the idea of cooperative communications is an efficient way to improve the physical-layer security of a wireless transmission in the presence of passive eavesdroppers. In this paper, we propose a hybrid cooperative relaying and jamming scheme to enhance the security of a two-way relay network, where some intermediate nodes help to relay the signal to the legitimate terminals via distributed beamforming and the others jam the eavesdropper simultaneously. In such a way, both two cooperative phases of the data transmission are protected. Subjected to the more practical per-node power constraint of each node and without the channel state information (CSI) of the eavesdropper, we propose a scheme to enhance the secrecy of the two terminals. It is shown that the problem can be transformed into a semidefinite programming (SDP) problem with an additional rank-1 constraint. We then develop a penalty function method and an iterative algorithm to solve such a problem efficiently, instead of the popular semi-definite relaxation (SDR) and randomization techniques proposed in the previous literatures. Simulations show that the proposed hybrid scheme greatly improves the security of the two-way relay networks.

Cooperative beamforming and jamming are two efficient schemes to improve the physical-layer security of a wireless relay system in the presence of passive eavesdroppers. However, in most works these two techniques are adopted separately. In this letter, we propose a joint cooperative beamforming and jamming scheme to enhance the security of a cooperative relay network, where a part of intermediate nodes adopt distributed beamforming while others jam the eavesdropper, simultaneously. Since the instantaneous channel state information (CSI) of the eavesdropper may not be known, we propose a cooperative artificial noise transmission based secrecy strategy, subjected to the individual power constraint of each node. The beamformer weights and power allocation can be obtained by solving a second-order convex cone programming (SOCP) together with a linear programming problem. Simulations show the joint scheme greatly improves the security.

In this paper, we propose a hybrid cooperative beamforming and jamming scheme to enhance the physical-layer security of a single-antenna-equipped two-way relay network in the presence of an eavesdropper. The basic idea is that in both cooperative transmission phases, some intermediate nodes help to relay signals to the legitimate destination adopting distributed beamforming, while the remaining nodes jam the eavesdropper, simultaneously, which takes the data transmissions in both phases under protection. Two different schemes are proposed, with and without the instantaneous channel state information of the eavesdropper, respectively, and both are subjected to the more practical individual power constraint of each cooperative node. Under the general channel model, it is shown that both problems can be transformed into a semi-definite programming (SDP) problem with an additional rank-1 constraint. A current state of the art technique for handling such a problem is the semi-definite relaxation (SDR) and randomization techniques. In this paper, however, we propose a penalty function method incorporating the rank-1 constraint into the objective function. Although the so-obtained problem is not convex, we develop an efficient iterative algorithm to solve it. Each iteration is a convex SDP problem, thus it can be efficiently solved using the interior point method. When the channels are reciprocal such as in TDD mode, we show that the problems become second-order convex cone programming ones. Numerical evaluation results are provided and analyzed to show the properties and efficiency of the proposed hybrid security scheme, and also demonstrate that our optimization algorithms outperform the SDR technique.

In this paper, we address the physical-layer security of a two-way wireless transmission with the help of multiple inter-mediate nodes in the presence of an eavesdropper. We propose a hybrid cooperative relaying and jamming mechanism to enhance the security of the data exchange, where some intermediate nodes adopt distributed beamforming to improve the channel quality to legitimate terminals and others jam the eavesdropper, simultaneously. Two different schemes are proposed with and without the instantaneous channel state information (CSI) of the eavesdropper, respectively. The solutions of both schemes can be obtained by convex optimization techniques. Comparisons show that the proposed hybrid schemes greatly improve the security of the two-way relay networks.

In this paper, we propose an energy-efficient cooperative geographic routing (ECGR) to reach energy-efficient routing in wireless sensor networks(WSN). ECGR fully takes advantage of cooperative diversity and geographic routing. At physical layer, the sensor nodes cooperatively transmit the same packet to achieve farther transmission distance of each hop. While at the network layer, ECGR adaptively selects the appropriate cooperative nodes to form forwarding clusters to forward the packet when we consider energy consumption and geographic information of the sensor nodes. In order to fully assess the energy consumption, we take circuit energy consumption of the sensor nodes into consideration. According to the description above, we increase the transmitting distance of each hop but decrease the hop number. Meanwhile, the overall network energy consumption is reduced and balanced among nodes to extend the life of the network.

In this paper, we develop a new carrier frequency offset (CFO) estimation scheme for interleaved orthogonal frequency division multiple access (OFDMA) transmission. We employ multi-antenna at the receiver and exploit the rank reduction approach to blindly estimate the CFOs of multiple users. The proposed scheme supports full load transmission that allows all sub-carriers being allocated to users, which is a significant advantage over the existing schemes. Both performance analysis and numerical results are provided to corroborate the proposed studies.

A novel bind algorithm is proposed for ranges and direction-of-arrivals (DOAs) estimation of the hybrid narrow-band sources, which contain both the near field sources and the far field ones. To separate them, a two-step algorithm is exploited. In the first step, the far-field sources are identified by exploiting the MUSIC method. After eliminating the far field source components in the auto correlation matrix and adding the conjugate formulation, the dimensions of covariance matrix for near field sources are increased. Therefore, compared with the conventional methods, more independent near filed sources, near 4p/3 ones can be identified with a uniformly linear array (ULA) of 2p + 1 elements. Furthermore, in the near-field source estimation of our method, the peak search and pairing operations, needed in most algorithms for near field sources, can be omitted completely. Simulation results show that our ESPRIT-based near-field method provides the improved performance over conventional ones because of the dimensions increment of the covariance matrix.

To distributed sources, the usage of conventional point-source model will cause inaccuracy in the direction-of-arrival (DOA) estimation. Conventional methods for distributed sources usually estimate the DOAs and the distribution parameters with multi-dimensional peak search operations, which will lead to much higher computational complexity than that in the point source model. In this paper, a blind parameter estimation method is proposed for distributed sources, where the DOAs are estimated in a closed form. As a result, the computational burden is decreased a lot. Furthermore, the proposed method can work in the scenario with mixture sources of many kinds of distributions. The selection method and its spatial-time domain version are also discussed in this paper. Simulation results show the effectiveness of our method.

Single carrier cyclic prefix system with frequency domain equalization (SC-CP-FDE) is an attractive technology for broadband wireless communications. In this paper, we investigate the diversity order of a SC-CP-FDE system without channel coding in frequency-selective channels. Existing analytic proofs in [6], [7] indicate that the achievable diversity order is only 1, which contradicts the conclusion in [11] and simulation results in [1]-[3]. We explain why the proofs in [6], [7] can not support the claim that SC-CP system is unable to provide any frequency diversity gain. We then re-investigate the diversity order of a SC-CP system with frequency domain decision feedback equalizer (FD-DFE) based on MMSE criteria at the receiver end. Adopting outage analysis instead of pairwise error probability (PEP) analysis, we show that with MMSE-FD-DFE, the asymptotic achievable diversity order is Lc+1 when the block length N is sufficiently large, where Lc+1 is the number of independent channel paths, i.e., full multipath diversity is asymptotically achieved.

In this paper, we address the physical-layer security of two-way (bi-directional) transmissions of two terminals with the help of multiple relay nodes in the presence of an eavesdropper, where each node in the network is only equipped with single antenna. The secrecy sum rate is used as the metric of security, which is the rate difference between the legitimate information exchange between the terminals and the information leakage to the eavesdropper. We propose two-phase analog network coding (ANC) and power allocation scheme for the relay nodes and terminals to enhance the security of the data exchange. Three different schemes are proposed. The first scheme is the optimal ANC to achieve the maximum secrecy sum rate, i.e. secrecy capacity, which is found to be mathematically difficult to solve. Two suboptimal schemes are proposed with and without the instantaneous channel state information (CSI) of the eavesdropper, respectively. The solutions of both schemes are shown to be unique and globally optimum, which are solved by convex optimization techniques. Numerical evaluation results of the obtained secrecy sum rate and transmit power are provided and analyzed to show the properties and efficiency of the proposed ANCs.

Time asynchronism is a practical issue needs to be addressed for a general distributed two-way relay network, where two terminal nodes exchange information through multiple spatial-separated relay nodes. In this paper, we propose an analog network coding (ANC) scheme for a time asynchronous two-way relay network. In the proposed scheme, each relay node linearly transforms the received mixed asynchronous signals in the first time-slot by a Toeplitz matrix, and then broadcasts them back to the terminals in the second time-slot. A sufficient condition is derived for the proposed ANC to achieve full cooperative diversity using only linear receivers at the terminal nodes, such as zero-forcing (ZF), or minimum mean square error (MMSE) receivers, with any delay profiles of the timing errors. The design of the coefficients in the Toeplitz matrix to satisfy the sufficient condition is also proposed, which is shown coincides with the design we proposed in the previous work. Simulation results verify our analysis of the diversity order.

Cooperative relay networks are inherently time- and frequency- asynchronous due to their distributed nature. The existence of multiple time and frequency offsets results in a time-varying and frequency-selective equivalent channel between relay nodes and destination node. In this paper, we propose a transceiver scheme to combat both time and frequency offsets for cooperative relay networks. At the relay nodes, the distributed linear convolutive space-time coding is adopted to achieve the time-asynchronous full cooperative diversity. This transmission scheme leads to an equivalent channel with special structure at the destination node. By taking full advantage of this special structure, fast Kalman equalizations based on linear minimum mean square error (LMMSE) and MMSE decision feedback equalizers (MMSE-DFE) are proposed for the receiver, where the estimation of the state vector (information symbols) can be operated recursively and computational efficiently. The proposed scheme can achieve considerable diversity gain with both time and frequency offsets, and also applies to frequency-selective fading channels.

In this paper, we propose a family of distributed space-frequency codes (SFCs) for frequency asynchronous cooperative relay networks with multiple carrier frequency offsets (CFOs) and flat fading channels. The codes have the special structures that the columns of each code matrix can be divided into several orthogonal groups and each group is stacked by several sub-blocks with Toeplitz structure. These codes possess two interesting properties: a) Even under the frequency-asynchronous scenario, the codes can , namely, if R relay nodes participate the cooperation adopting the proposed SFCs, then at the destination node, the achievable diversity order is R; b) Only , such as zero-forcing (ZF) and minimum mean square error (MMSE) receivers, are required to collect the full cooperative diversity, instead of the maximum likelihood (ML) detector as utilized in most existing STC (SFC) schemes. The codes in this family have different symbol rates, orthogonality and performances for different numbers of relay nodes, which can be adjusted by choosing different design parameters. It is shown that frequency-reversal SFC (FR-SFC), and frequency-shift SFC (FS-SFC) proposed in previous papers are only two special members of the code family, and new SFCs outperforming both of them are proposed.

Opportunistic relay selection is considered as an efficient approach to implement cooperative communication in multi-relay cooperative networks owing to its low implementation complexity. However, due to channel fluctuations, the channel state information (CSI) employed in relay selection process may differ from the exact CSI in data forwarding, in other words, the CSI is outdated. Addressing this issue, this paper focuses on the design of relay selection strategies in decode-and-forward (DF) cooperative networks with outdated CSIs being available in relay judgement, as well as their performance analysis. We resort to two main cases, 1) only outdated CSIs are available in relay selection process; 2) both outdated CSIs and statistical channel information are available in selection procedure, and propose three different relay selection schemes. The expressions of outage probability are derived, and asymptotic analysis in high SNR region is also carried out. Simulation results are finally provided, which not only validate our theoretical analysis, but also shed light on the way of designing relay selection strategies in various scenarios.

In cooperative communication systems, due to their distributed nature, multiple carrier frequency offsets (CFOs) may occur and make the channel time-varying, thus most existing space-time codes (STC) to collect diversity gain for the co-located multi-input multi-output (MIMO) systems may not be applied directly. In this paper, we propose a family of distributed space-frequency codes (SFCs) for cooperative transmissions with multiple CFOs and flat fading channels. These codes can achieve full cooperative (spatial) diversity with only linear receivers, such as zero-forcing (ZF) and minimum mean square error (MMSE) receivers, instead of the computationally exhausted maximum likelihood (ML) detector. The codes in this family have different symbol rates, orthogonality and performances for different number of relay nodes, which can be adjusted by choosing different design parameters. Actually, frequency-reversal SFC (FR-SFC), and frequency-shift SFC (FS-SFC) proposed in our previous paper are special cases of the new codes. Furthermore, new SFCs outperform both FD-SFC and FS-SFC can be obtained, from the systematic design.

Time asynchronism is a practical issue need to be addressed for a general distributed two-way relay network, where two terminal nodes exchange information through multiple spatial-separated relay nodes. In this letter, we propose an analog network coding (ANC) scheme for a time asynchronous two-way relay network. In the proposed scheme, each relay node linearly transforms the received mixed asynchronous signals in the first time-slot by a Toeplitz matrix, and then broadcasts them back to the terminals in the second time-slot. A sufficient condition is derived for the proposed ANC to achieve full cooperative diversity using only linear receivers at the terminal nodes, such as zero-forcing (ZF), or minimum mean square error (MMSE) receivers, with any delay profiles of the timing errors. The decoding of the proposed ANC scheme is computationally efficient and the symbol rate can approach 1, when the coding block length is sufficiently large compared to the number of relay nodes R and the timing errors.

In this paper, we propose a family of space-time block codes (STBC) that achieve full diversity when linear receivers, such as zero-forcing (ZF) or minimum mean square error (MMSE) receivers, are used. Our proposed STBC family is a combination/overlay between orthogonal STBC and Toeplitz codes, which can be viewed as a generalization of overlapped Alamouti codes (OAC) and Toeplitz codes recently proposed in the literature. Simulation results show that the newly proposed STBC may outperform the existing codes when linear receivers are used.

Two novel algorithms are proposed for ranges, frequencies and direction-of-arrivals (DOAs) estimation of the narrow-band near field sources. By exploiting the time-domain and space-domain correlations of impinging signals jointly, we can identify 2p independent sources and estimate 3 groups of parameters with a uniformly linear array (ULA) of 2p + 1 elements, being double of the conventional methods. In addition, the peak search and pairing operations, needed in most algorithms for near field sources, can be omitted completely in our methods. Simulation results show that our two ESPRIT-based methods provide the improved performance over conventional ones based on the second-order statistics.

Multiple frequency offsets (CFO) in cooperative communications are difficult, if not impossible, to compensate completely at the destination node. The multiple CFO make the channel time-varying, and thus the conventional space-time codes to collect diversity gain for co-located multi-input multi-output (MIMO) systems may not be applied directly. In a previous paper, we proposed a distributed space-frequency code (SFC), called frequency-reversal SFC (FR-SFC), for cooperative transmissions with multiple CFOs and flat fading channels. We have shown that this code can achieve the full cooperative diversity with only linear receivers, such as zero-forcing (ZF) and minimum mean square error (MMSE) receivers. However, the code is not bandwidth efficient when the relay nodes are more than 3. To have a higher bandwidth efficiency, in this paper we propose a new distributed SFC called frequency-domain linear convolutive SFC (FLC-SFC). The symbol rates of the new codes approach 1 when code block length is sufficiently larger than the number of relay nodes. Furthermore. It achieves the full cooperative diversity with linear receivers.

Two novel algorithms which exploit the fourth-order statistics are proposed for DOA and range estimation of the near-field narrow-band sources. Compared with most proposed methods which can identify only p sources with a (2p + 1)-element ULA (uniformly linear array), the proposed methods can identify 2p or 2p − 1 sources with the same one. Moreover, our methods calculate much fewer fourth-order statistics than conventional ones. Simulation results show that our two ESPRIT-based methods also provide improved performance over conventional ones because of more efficient use of received signals.

In this paper, we propose a design scheme for a family of space-time block codes (STBCs) that achieve full diversity when linear receivers, such as zero-forcing (ZF) or minimum mean square error (MMSE) receivers, are used. New STBCs obtained based on this design scheme are characterized by their special structure that combines/overlays orthogonal STBCs (OSTBCs) and Toeplitz codes together, which are called Group Orthogonal-Toeplitz Codes (GOTCs). By choosing different parameters, codes with different symbol rates and orthogonality can be obtained. It is indicated that the existing STBCs achieving full diversity with linear receivers, such as the Toeplitz codes and overlapped Alamouti codes (OACs) recently proposed in the literature and the OSTBCs are three members of the GOTCs with different parameters. It is also shown that the time-reversal space-time block codes (TR-STBCs) and delay diversity codes (DDCs) for frequency selective channels are equivalent to OACs and Toeplitz codes, respectively, and thus they both can achieve full space-frequency diversity with only linear receivers. Furthermore, simulations show that with linear receivers, GOTCs outperforming the above mentioned three codes can be obtained from the proposed design scheme.

In cooperative communications, time and frequency synchronization is an important issue needed to be addressed in practice. Due to the nature of cooperative communications, multiple frequency offsets may occur and the traditional frequency offset compensations may not apply. For this problem, equalization for the time-varying channel has been used in the literature, where the equalization matrix inverse needs to be retaken every symbol. In this paper, we propose computationally efficient minimum mean square error (MMSE) and MMSE decision feedback equalizers (MMSE-DFE) when multiple frequency offsets are present, where the equalization matrix inverses do not need to be retaken every symbol. Our proposed equalization methods apply to linear convolutively coded cooperative systems, where linear convolutive space-time coding is used to achieve the full cooperative diversity when there are timing errors from the cooperative users or relay nodes, i.e., asynchronous cooperative communication systems.

In cooperative communications, due to the distributed nature, multiple different carrier frequency offsets (CFOs) may occur and make the channel time-varying. It is hard for the receiver to compensate multiple CFOs from multiple relay nodes simultaneously. Thus, the conventional space-time codes to collect cooperative diversity for co-located multi-input multi-output (MIMO) systems may not be applied directly. In this paper, we consider the cooperative transmission with multiple CFOs when the channels from relay nodes to destination node are flat (frequency-non-selective) fading. We approximate a flat fading channel with CFO as a block time-invariant intersymbol-interference (ISI) channel in the frequency domain. We then propose two distributed space-frequency codes (SFC) for such ISI channels in the frequency domain to achieve the cooperative full spatial diversity, where the space-frequency coding concept is different from the one in the literature and also has a different role. One is called frequency-reversal SFC and the other is called frequency-domain linear convolutive SFC. Furthermore, we show that, with only linear receivers, such as zero-forcing (ZF) and minimum mean square error (MMSE) receivers, our codes achieve the full cooperative diversity.

The frequency synchronization issue of multiuser in the uplink of an orthogonal frequency-division multiple-access (OFDMA) system is investigated in this letter. We develop a subspace based blind carrier frequency offsets (CFOs) estimation algorithm for the base station (BS) equipped with uniform linear array (ULA). Due to the adoption of ULA at the BS and the narrowband signal assumption, CFOs of different users can be separated by their spatial information. Thus, unlike existing blind alternatives, which are subject to some specific carrier assignment schemes (CAS) or rely on null subcarriers, our proposed method can support generalized carrier assignment scheme (GCAS) and fully loaded systems, i.e., all subcarriers are available to users. Consequently, the dynamic channel assignment is available and the bandwidth efficiency is higher. Moreover, the closed-form directions of arrival (DOAs) of all active users are also obtained, which can be used in downlink beamforming in frequency division duplex (FDD) systems. Performance of the proposed scheme is evaluated by computer Monte Carlo simulations.

In cooperative communications, due to the distributed nature, multiple different carrier frequency offsets (CFOs) may be present and make the channel time-varying. It is hard for the receiver to compensate multiple CFOs from multiple relay nodes simultaneously. Thus, the conventional space-time codes to collect cooperative diversity for co-located multi-input multi-output (MIMO) systems may not be applied directly. In this paper, we consider the cooperative transmission with multiple CFOs when the channels from relay nodes to destination node are flat fading. We approximate a flat fading channel with CFO as a block time-invariant intersymbol-interference (ISI) channel in the frequency domain. We then propose a distributed space- frequency code (SFC), called frequency-reversal SFC, for such ISI channels in the frequency domain to achieve the cooperative spatial diversity, where the space-frequency coding concept is different from the one in the literature and also has a different role. Furthermore, we show that, with only linear receivers, such as zero-forcing (ZF) and minimum mean square error (MMSE) receivers, our code achieves the full cooperative diversity.

In this paper, we develop a blind carrier frequency offsets (CFOs) estimation algorithm for multiusers in the uplink of an orthogonal frequency-division multiple-access (OFDMA) system, where the base station equipped with uniform linear array (ULA). Due to the ULA at base station, different users could be separated by their spatial information. So unlike existing blind alternatives, which are subject to some specific carrier assignment schemes or rely on null carriers, our proposed method can support generalized carrier assignment scheme (GCAS) and full loaded systems. Thus, our method is more flexible and bandwidth efficient. Besides, the closed-form directions of arrival (DOAs) of all active users are also obtained, which can be used in downlink beamforming in frequency division duplex (FDD) systems. Performance of the proposed scheme is evaluated by computer Monte Carlo simulations.

We present a smart antenna assisted gradient broadcasting (SA-GRAB) data delivery protocol for large-scale WSN, where only the sink is equipped with a low-cost smart antenna offering a relative small coverage. SA-GRAB partitions the smart antenna's coverage into N inner sectors directly and the rest part of WSN into N outer sectors during the cost field building by means of a "dyeing" procedure. Once an event occurs, data are forwarded jointly by sector aware gradient broadcasting and direct communication with smart antenna. Simulations show that SA-GRAB achieves better energy-efficiency and scalability for large-scale WSN applications than prior work.

The optimal maximum-likelihood (ML) detector for a single-carrier (SC) multiple-input multiple-output (MIMO) system is often prohibitive due to its enormous computational complexity. In this paper, we propose a low complexity layered space-frequency equalization with time domain noise prediction (LSFE-NP) structure, where at each stage of the detector, a given data stream is detected by a multiple-input single-output (MISO) frequency domain equalization with time domain noise prediction (FDE-NP). It is shown that the proposed structure is optimal in the minimum mean square error (MMSE) sense, and the coefficients of the feedback filter are independent of the feedforward equalizer. Therefore, an alterable feedback taps LSFE-NP scheme is outlined for the coded SC MIMO system, which can feed as many reliable decisions as possible back to the equalizer to achieve better performance. Simulation results show that our proposed scheme can outperform the conventional LSFE and the MIMO FDE-NP significantly.

A novel closed-form subspace-based blind CFO estimation approach for MIMO-OFDM systems is proposed. Our key observation is that the CFO information is redundant in spectrum structure. By allocating null carriers equispaced at the transmitter and downsampling and collecting the received blocks from all antennas at the receiver, the dimension of parameter space is greatly reduced compared with previous proposed subspace- based methods. Consequently, a lower computational complexity approach is obtained. Furthermore, estimation performance is also improved significantly. Analysis and simulation results demonstrate the effectiveness of our proposed method.

In cooperative communications, due to distributed nature, cooperative transmission may not be either time or frequency synchronized. In this paper, we propose computationally efficient minimum mean square error (MMSE) and MMSE decision feedback equalizer (MMSE-DFE) equalizers for cooperative communication systems when multiple time offsets and frequency offsets present, where the equalization matrix inverses do not need to be retaken every symbol. Our proposed equalization methods apply to linear convolutively coded cooperative systems, where the linear convolutive space-time coding is used to achieve the full cooperative diversity when there are timing errors from the cooperative users or relay nodes, i.e., asynchronous cooperative communication systems.

A novel subspace-based blind carrier frequency offset (CFO) estimation approach for orthogonal frequency-division multiplexing (OFDM) systems is proposed. The key observation is that the CFO information is redundant in spectrum structure. By locating null carriers equispaced and remodeling the received blocks through downsampling, we compact parameter space and obtain a low complexity estimator with the performance of high-resolution. Analysis and simulations show the estimator is robust in both AWGN channel and frequency-selective channel.

Synchronization is an important issue in orthogonal frequency-division multiplexing (OFDM) systems including symbol timing and carrier frequency offset (CFO) estimation. In this paper, we derive a new subspace based CFO estimation method exploiting the cyclic prefix (CP) samples which are not disturbed by the preceding OFDM symbol. As a special and more practicable case, we provide an adaptive joint symbol timing and CFO estimation scheme. It is robust in both AWGN channel and frequency selective channel.

Two novel algorithms are proposed for ranges and direction-of-arrivals (DOAs) estimation of the narrow-band near field sources. By exploiting the time-domain and space-domain correlations of impinging signals jointly, we can estimate 2p independent sources with a uniformly linear array (ULA) of 2p + 1 elements, being double of the conventional methods. In our methods, the peak search and pairing operations, needed in most algorithms for near field sources, can be omitted completely. Simulation results show that our two ESPRIT-based methods provide the improved performance over conventional ones based on the second-order statistics.