Uplink Training Phase Research Articles

Secure RIS-Aided MISO-NOMA System Design in the Presence of Active Eavesdropping

As for the time-division communications system, the pilot spoofing attack technique is maliciously utilized by active eavesdroppers during the uplink training phase, for contaminating the legitimate channel estimation and thus altering the beamforming design towards the eavesdroppers. Nonorthogonal multiple access (NOMA) has been recognized as the key technology for the envisioned Internet of Things (IoT) networks. In order to prevent the aforementioned information leakage in NOMA-IoT systems, we develop a novel two-way training scheme to detect pilot spoofing attack and a robust secure beamforming design for providing secure transmission, by utilizing the emerging technique of reconfigurable intelligent surface (RIS), which is turned off during the uplink training phase and turned on during the downlink training phase, respectively. Considering that the perfect channel state information related to the eavesdropping channel is typically difficult to obtain, a secrecy outage probability constrained robust secure beamforming design is proposed to maximize the achievable sum secrecy rate of the legitimate users, by alternatively optimizing the active beamforming and RIS passive beamforming, while satisfying the requirements of the NOMA transmission. Elaborate simulation results reveal that the proposed detection method attains a super pilot spoofing attack detection performance and the proposed robust secure beamforming design is capable of efficiently enhancing the achievable sum secrecy rate, compared with various benchmark schemes.

New LLRT-Based Methods for Active Eavesdropper Detection in Cell-Free Massive MIMO

In this paper, the problem of active eavesdropper detection is considered for a cell-free massive multiple-input multiple-output (m-MIMO) system which is attacked by an active eavesdropper within the uplink training phase, also called pilot spoofing attack. Two methods based on log-likelihoodratio tests (LLRT), one in a centralized and the other in a decentralized fashion, are proposed to detect the signal abnormality. The methods take advantage of a special protocol in which the legitimate users switch to an off-mode irregularly, without significantly affecting the spectral efficiency of the data transmission. The protocol is directly applicable to environments with low to moderate mobility, and can be extended to high mobility through a simple rearrangement of available pilot sequences among users if needed. More importantly, the proposed methods impose low fronthaul overhead which is imperative for a cellfree m-MIMO system with a large number of access points (APs). A closed-form expression for the joint probability density function (PDF) of the processed received signals conditioned on the alternative hypothesis, which is essential for the implementation of LLRT-based detection methods, is also derived. Through an asymptotic analysis, it is shown for the proposed methods that the detection and false-alarm probabilities approach to one and zero, respectively as the number of APs goes to infinity. Numerical results reveal that both methods significantly outperform a recent approach in terms of false-alarm rate with negligible degradation in the per user uplink spectral efficiency.

Is Massive MIMO Robust Against Distributed Jammers?

In this paper, we evaluate the uplink spectral efficiency (SE) of a single-cell massive multiple-input-multiple-output (MIMO) system with distributed jammers. We define four different attack scenarios and compare their impact on the massive MIMO system as well as on a conventional single-input-multiple-output (SIMO) system. More specifically, the jammers attack the base station (BS) during both the uplink training phase and data phase. The BS uses either least squares (LS) or linear minimum mean square error (LMMSE) estimators for channel estimation and utilizes either maximum-ratio-combining (MRC) or zero-forcing (ZF) decoding vectors. We show that ZF gives higher SE than MRC but, interestingly, the performance is unaffected by the choice of the estimators. The simulation results show that the performance loss percentage of massive MIMO is less than that of the SIMO system. Moreover, we consider two types of power control algorithms: jamming-aware and jamming-ignorant. In both cases, we consider the max-min and proportional fairness criteria to increase the uplink SE of massive MIMO systems. We notice numerically that max-min fairness is not a good option because if one user is strongly affected by the jamming, it will degrade the other users’ SE as well. On the other hand, proportional fairness improves the sum SE of the system compared with the full power transmission scenario.

IRS-Based TDD Reciprocity Breaking for Pilot Decontamination in Massive MIMO

In this letter, we propose a novel way to mitigate the notorious pilot contamination in massive multiple-input multiple-output (MIMO) systems by exploiting the intelligent reflecting surfaces (IRSs). Particularly, we intentionally break the uplink (UL) and downlink (DL) channel reciprocity in time-division duplexing (TDD) systems by configuring the phases of the IRSs differently during the UL training phase and the DL data transmission phase. In this way, we show that the pilot contamination is mitigated and can be eliminated in some cases. Meanwhile, we analyze the signal-to-interference-plus-noise ratio (SINR) performance due to the non-reciprocal UL and DL channels. We further show the asymptotic optimality of our proposed decontamination scheme. The analytical results are also corroborated by numerical simulations.

Secure Simultaneous Information and Power Transfer for Downlink Multi-User Massive MIMO

In this article, downlink secure transmission in simultaneous information and power transfer (SWIPT) system enabled with massive multiple-input multiple-output (MIMO) is studied. A base station (BS) with a large number of antennas transmits energy and information signals to its intended users, but these signals are also received by an active eavesdropper. The users and eavesdropper employ a power splitting technique to simultaneously decode information and harvest energy. Massive MIMO helps the BS to focus energy to the users and prevent information leakage to the eavesdropper. The harvested energy by each user is employed for decoding information and transmitting uplink pilot signals for channel estimation. It is assumed that the active eavesdropper also harvests energy in the downlink and then contributes during the uplink training phase. Achievable secrecy rate is considered as the performance criterion and a closed-form lower bound for it is derived. To provide secure transmission, the achievable secrecy rate is then maximized through an optimization problem with constraints on the minimum harvested energy by the user and the maximum harvested energy by the eavesdropper. Numerical results show the effectiveness of using massive MIMO in providing physical layer security in SWIPT systems and also show that our closed-form expressions for the secrecy rate are accurate.

Detection and Localization of the Eavesdropper in MIMO Systems

The pilot spoofing attack (PSA) is one kind of active eavesdropping that happens in the channel training phase, in which an intelligent eavesdropper transmits identical pilot sequences synchronously with the legitimate user to spoof the transmitter. This attack leads to the estimated channel being a mix of a legitimate channel (the channel from the transmitter to the legitimate user) and an eavesdropper channel (the channel from the transmitter to the eavesdropper). And as a result, confidential information is leaked to the eavesdropper during the data transmission phase. Especially when the eavesdropper utilizes sufficiently large power, the channel rate at the legitimate user end decreases observably and increases dramatically at the eavesdropper. To against the active PSA, we propose a new effective scheme called the spatial spectrum method (SSM) which can be applied in situations in which the eavesdropper attacks not only the transmitter but also the legitimate user in multiple-input multiple-output (MIMO) communication systems. Specifically, this method utilizes the spatial spectrums that are attained by the uplink training phase to detect the eavesdropper. Besides it also can locate the legitimate user and the eavesdropper by identifying the direction-of-arrival (DOA) of the legitimate user and the eavesdropper based on the symmetry of the uplink and downlink channels in a time-division-duplex (TDD) system and estimating the geographical distance between the legitimate user and the eavesdropper. Consequently, the secure transmission of secret information can be guaranteed by utilizing spatial information, such as by adopting beamforming technology. Numerical results show that our method can effectively detect and locate the eavesdropper.

Angle-domain secure transmission in air–terrestrial mMIMO system with single antenna ground eavesdropper

In this paper, we consider a hybrid air–terrestrial network secure transmission scenario, where a low-altitude air platform (AP) equipped with a two-dimensional (2D) rectangular antenna array serves a set of legitimate users (LUs). The entire transmission can be divided into two phases: uplink training and transmission phase, and downlink transmission phase. A single-antenna vehicle eavesdropper (ED) is within the coverage of the AP, and the eavesdropper sends jamming signals in the uplink training and transmission phase and eavesdrops on LUs signals in the downlink transmission phase. During the training phase, a beam extraction based beam-domain (BD) channel estimation and transmission scheme is proposed. The active beam sets (ABS) of the interference channel and the LU channels can be separately extracted by comparing the beam gain vectors from different LUs. The pilot contamination can be eliminated and the channel state information (CSI) of LUs can be purified. By using spatial basis expansion model (BEM), full-dimension CSI of LUs and ED can be obtained, based on which the digital domain beam alignment method is designed to locate the ED. By utilizing the purified full-dimension CSI of LUs and location information of ED, the system achievable rate is analyzed and a geometric programming (GP) based power allocation scheme is proposed to further improve the secrecy capacity performance. The superiority of the proposed scheme is evaluated by simulations.

Securing Downlink Massive MIMO-NOMA Networks With Artificial Noise

In this paper, we focus on securing the confidential information of massive multiple-input multiple-output (MIMO) non-orthogonal multiple access (NOMA) networks by exploiting artificial noise (AN). An uplink training scheme is first proposed with minimum mean squared error estimation at the base station. Based on the estimated channel state information, the base station precodes the confidential information and injects the AN. Following this, the ergodic secrecy rate is derived for downlink transmission. An asymptotic secrecy performance analysis is also carried out for a large number of transmit antennas and high transmit power at the base station, respectively, to highlight the effects of key parameters on the secrecy performance of the considered system. Based on the derived ergodic secrecy rate, we propose the joint power allocation of the uplink training phase and downlink transmission phase to maximize the sum secrecy rates of the system. Besides, from the perspective of security, another optimization algorithm is proposed to maximize the energy efficiency. The results show that the combination of massive MIMO technique and AN greatly benefits NOMA networks in term of the secrecy performance. In addition, the effects of the uplink training phase and clustering process on the secrecy performance are revealed. Besides, the proposed optimization algorithms are compared with other baseline algorithms through simulations, and their superiority is validated. Finally, it is shown that the proposed system outperforms the conventional massive MIMO orthogonal multiple access in terms of the secrecy performance.

Outage of Periodic Downlink Wireless Networks With Hard Deadlines

We consider a downlink periodic wireless communications system, where multiple access points cooperatively transmit packets to a number of devices, e.g., actuators in an industrial control system. Each period consists of two phases: an uplink training phase and a downlink data transmission phase. Each actuator must successfully receive its unique packet within a single transmission phase; else, an outage is declared. Such an outage can be caused by two events: a transmission error due to transmission at a rate that the channel cannot actually support or time overflow, where the downlink data phase is too short, given the channel conditions to successfully communicate all the packets. We determine the closed-form expressions for the time overflow probability when there are just two field devices, as well as the transmission error probability for an arbitrary number of devices. In addition, we provide upper and lower bounds on the time overflow probability for an arbitrary number of devices. We propose a novel variable-rate transmission method that eliminates time overflow. Detailed system-level simulations are used to identify system design guidelines, such as the optimal amount of training time, as well as for benchmarking the proposed system design versus non-cooperative cellular, cooperative fixed-rate, and cooperative relaying.

Pilot Power Control for Cell-Free Massive MIMO

In this correspondence paper, we consider a cell-free massive Multiple-Input Multiple-Output (MIMO) system where access points (APs) serve a much smaller number of users under the time-division duplex operation. The APs first estimate the channels via the uplink training phase. Then, these channel estimates are used to detect desired symbols in the uplink and precode the transmit symbols in the downlink. Nonorthogonality of pilot sequences and AP selection (e.g., received-power-based selection or largest-large-scale-fading based selection schemes) are taken into account. To reduce the effect of pilot contamination, we propose a pilot power control design, which chooses the pilot power control coefficients to minimize the mean-squared error of the channel estimation. This is achieved via the sequential convex approximation method. By using pilot power control in training phase, the system performance is considerably improved. In addition, we derive closed-form expressions for the uplink and downlink achievable rates with arbitrary power data/pilot control coefficients and any AP selection schemes.

Covariance Matrix Estimation in Massive MIMO

Interference during the uplink training phase significantly deteriorates the performance of a massive MIMO system. The impact of the interference can be reduced by exploiting second order statistics of the channel vectors, e.g., to obtain minimum mean squared error estimates of the channel. In practice, the channel covariance matrices have to be estimated. The estimation of the covariance matrices is also impeded by the interference during the training phase. However, the coherence interval of the covariance matrices is larger than that of the channel vectors. This allows us to derive methods for accurate covariance matrix estimation by appropriate assignment of pilot sequences to users in consecutive channel coherence intervals.

Partially Loaded Superimposed Training Scheme for Large MIMO Uplink Systems

This paper proposes a new superimposed training (ST) scheme for uplink multi-user multi-cell system, where each base station, equipped with a large number of antennas (M), communicates to single antenna users. In uplink training phase, large number of users within limited coherence time introduces the pilot contamination, which causes two types of interferences in data estimation. The first type, which is referred as self interference, arises due to the dependence between channel estimate and estimation error of the same user, while the second type, known as cross interference, occurs because of the correlation between ST vectors of different users. In this paper, an ST scheme with variable data length is proposed for Rician fading channels. For simplicity of analysis, a single cell model is considered first to derive mean squared error and signal to interference plus noise ratio. The analysis is further extended to multi-cell system. Various limiting cases are investigated, and the design parameters viz., power allocation factor and length of data vector, are optimized. Simulation results verify that the proposed ST scheme reduces self interference, and yields sum rate improvement over conventional ST scheme.

On the Performance of Multiuser MIMO Systems Relying on Full-Duplex CSI Acquisition

In this paper, we propose a combined full duplex (FD)- and half duplex (HD)-based transmission and channel acquisition model for an open-loop multiuser multiple-input multiple-output (MIMO) systems. Assuming residual self-interference at the base station (BS), the idea is to utilize the FD mode during the uplink (UL) training phase in order to achieve simultaneous downlink (DL) data transmission and UL CSI acquisition. More specifically, the BS begins serving a user when its CSI becomes available, while at the same time, it also receives UL pilots from the next scheduled user. We investigate both zero-forcing (ZF) and maximum ratio transmission MIMO beamforming techniques for the DL data transmission in the FD mode. The BS switches to the HD mode once it receives the CSI of all users and it employs ZF beamforming for the DL data transmission until the end of the transmission frame. Furthermore, we derive closed-form approximations for the lower bounded ergodic achievable rate relying on the proposed model. Our numerical results show that the proposed FD–HD transmission and channel acquisition approach outperforms its conventional HD counterpart and achieves higher data rates.

Joint Interference Alignment and Power Allocation for Multi-User MIMO Interference Channels Under Perfect and Imperfect CSI

We present centralized-based iterative algorithms that jointly determine the optimal transceiver filters as well as the optimum power allocation for a $K$ -user multiple-input multiple-output (MIMO) interference channel (IC). The optimality criterion is developed on the basis of the average per user multiplexing gain and the achievable sum-rate in the MIMO IC. By allowing channel state information (CSI) exchanged between base stations (BSs) and a central unit (CU), we design a feedback topology where CU collects local CSIs from all BSs, computes all transceiver filters and sends them to corresponding user-BS pairs. Note that the local CSIs at BSs are obtained from the estimation of the channel states during the so-called uplink-training phase. At the CU, using the alternating optimization strategy, various iterative algorithms are proposed to design the filters. In other related studies, the equal transmit power policy for all user-BS pairs is chosen ignoring the essential need to search for the optimal power allocation policy; they do not take the full advantage of the system’s total power. Thus, another key aspect of this paper is to make optimal power allocation decisions for all the user-BS pairs based on the sum-rate maximization strategy and under a sum power constraint.