In this paper, we propose a pseudo-random beamforming (PRBF) technique for improving physical-layer security (PLS) in multiple input multiple output (MIMO) downlink cellular networks consisting of a legitimate base station (BS), multiple legitimate mobile stations (MSs) and potential eavesdroppers. The legitimate BS can obtain available potential eavesdroppers’ channel state information (CSI), which is registered in an adjacent cell. In the proposed PRBF technique, the legitimate BS pseudo-randomly generates multiple candidates of the transmit beamforming (BF) matrix, in which each transmit BF matrix consists of multiple orthonormal BF vectors and shares BF information with legitimate MSs before data transmission. Each legitimate MS generates receive BF vectors to maximize the receive signal-to-interference-plus-noise (SINR) for all pseudo-randomly generated transmit beams and calculates the corresponding SINR. Then, each legitimate MS sends a single beam index and the corresponding SINR value of the BF vector that maximizes the received SINR for each BF matrix since a single spatial stream is sent to each legitimate MS. Based on the feedback information from legitimate MSs and the CSI from the legitimate BS to eavesdroppers, the legitimate BS selects the optimal transmit BF matrix and the legitimate MSs that maximizes secrecy sum-rate. We also propose a codebook-based opportunistic feedback (CO-FB) strategy to reduce feedback overhead at legitimate MSs. Based on extensive computer simulations, the proposed PRBF with the proposed CO-FB significantly outperforms the conventional random beamforming (RBF) with the conventional opportunistic feedback (O-FB) strategies in terms of secrecy sum-rate and required feedback bits.
In this paper, we propose a pseudo-random beamforming (PRBF) technique for improving physical-layer security (PLS) in multiple input multiple output (MIMO) downlink cellular networks consisting of a legitimate base station (BS), multiple legitimate mobile stations (MSs) and potential eavesdroppers. The legitimate BS can obtain available potential eavesdroppers’ channel state information (CSI), which is registered in an adjacent cell. In the proposed PRBF technique, the legitimate BS pseudo-randomly generates multiple candidates of the transmit beamforming (BF) matrix, in which each transmit BF matrix consists of multiple orthonormal BF vectors and shares BF information with legitimate MSs before data transmission. Each legitimate MS generates receive BF vectors to maximize the receive signal-to-interference-plus-noise (SINR) for all pseudo-randomly generated transmit beams and calculates the corresponding SINR. Then, each legitimate MS sends a single beam index and the corresponding SINR value of the BF vector that maximizes the received SINR for each BF matrix since a single spatial stream is sent to each legitimate MS. Based on the feedback information from legitimate MSs and the CSI from the legitimate BS to eavesdroppers, the legitimate BS selects the optimal transmit BF matrix and the legitimate MSs that maximizes secrecy sum-rate. We also propose a codebook-based opportunistic feedback (CO-FB) strategy to reduce feedback overhead at legitimate MSs. Based on extensive computer simulations, the proposed PRBF with the proposed CO-FB significantly outperforms the conventional random beamforming (RBF) with the conventional opportunistic feedback (O-FB) strategies in terms of secrecy sum-rate and required feedback bits.
In this paper, we propose a novel pseudo-random beamforming technique with beam selection for improving physical-layer security (PLS) in a downlink cellular network where consists of a base station (BS) with Ntantennas, NMSlegitimate mobile stations (MSs), and NEeavesdroppers. In the proposed technique, the BS generates multiple candidates of beamforming matrix each of which consists of orthogonal beamforming vectors in a pseudo-random manner. Each legitimate MS opportunistically feeds back the received signal-to-interference-and-noise ratio (SINR) value for all beamforming vectors to the BS. The BS transmits data to the legitimate MSs with the optimal beamforming matrix among multiple beam forming matrices that maximizes the secrecy sum-rate. Simulation results show that the proposed technique outperforms the conventional random beamforming technique in terms of the achievable secrecy sum-rate.
Recently, wireless security has been highlighted as one of the most important techniques for 6G mobile communication systems. Many researchers have tried to improve the Physical-Layer Security (PLS) performance such as Secrecy Outage Probability (SOP) and Secrecy Energy-Efficiency (SEE). The SOP indicates the outage probability that the data transmission between legitimate devices does not guarantee a certain reliability level, and the SEE is defined as the ratio between the achievable secrecy-rate and the consumed transmit power. In this paper, we consider a Multi-User Multi-Input Single-Output (MU-MISO) downlink cellular network where a legitimate Base Station (BS) equipped with multiple transmit antennas sends secure information to multiple legitimate Mobile Stations (MSs), and multiple potential eavesdroppers (EVEs) equipped with a single receive antenna try to eavesdrop on this information. Each potential EVE tries to intercept the secure information, i.e., the private message, from the legitimate BS to legitimate MSs with a certain eavesdropping probability. To securely receive the private information, each legitimate MS feeds back its effective channel gain to the legitimate BS only when the effective channel gain is higher than a certain threshold, i.e., the legitimate MSs adopt an Opportunistic Feedback (OF) strategy. In such eavesdropping channels, both SOP and SEE are analyzed as performance measures of PLS and their closed-form expressions are derived mathematically. Based on the analytical results, it is shown that the SOP of the OF strategy approaches that of a Full Feedback (FF) strategy as the number of legitimate MSs or the number of antennas at the BS increases. Furthermore, the trade-off between SOP and SEE as a function of the channel feedback threshold in the OF strategy is investigated. The analytical results and related observations are verified by numerical simulations.
In this paper we investigate the physical layer security for downlink MU-MIMO systems where the transmitter and the eavesdropper are equipped with multiple antennas, while the legitimate users have single antenna. This is a more challenging topic because the eavesdropper appears to be more powerful than the legitimate users. We propose a transmission scheme able to enhance secure transmission for legitimate users, by intentionally applying different beamforming matrices to pilot signals and data signals. The beamforming matrix for data signals is constructed in a way that legitimate users can derive the channel matrix experienced by data signals based on pilot signals, whereas the eavesdropper fails to obtain the channel matrix experienced by data signals even with the aid of pilot signals. Therefore coherent detection at the eavesdropper is impossible and the signal-plus-interference-to-noise (SINR) of the eavesdropper is significantly degraded. In addition, the proposed beamforming design is formulated as an optimization problem to maximize the minimum SINR. We theoretically prove that with this formulation, the resultant optimal SINR is not affected by the proposed format of beamforming matrix for data signals. Numerical results show that, the proposed beamforming design outperforms the conventional beamforming design in terms of ergodic secrecy sum rate. Furthermore, with suitable beamforming designs, the ergodic secrecy sum rate achieved will not be noticeably affected by the number of antennas at the eavesdropper, although it is significantly degraded with conventional beamforming design.
In this paper, we consider secure transmission in the downlink of a multicell multiple-input multiple-output (MIMO) system with M cells; each cell consists of an N -antenna base station (BS) and K single-antenna users. Coordinated beamforming (CBf) is employed for secrecy enhancement. For CBf, the BSs can jointly design their respective beamformers to control intercell interference and information leakage. Based on regularized channel inversion (RCI) precoding structures, we derive the concise formulas for the signal-to-interference-plus-noise ratio (SINR) for the legitimate users and the colluding malicious users and the achievable secrecy sum rate for the CBf. Furthermore, we obtain a novel closed-form expression of the secrecy sum in the large-system regime where N and K tend to infinity with a fixed ratio β=K/N . Based on the large-system regime result, the regularization parameter is optimized to maximize the secrecy sum rate. It shows that the optimal regularization parameter decreases with the signal-to-noise ratio (SNR) and stays constant at high SNR if β>1/M . Compared with single-cell processing (SCP) without BS cooperation, simulation results show that the secrecy performance can be significantly enhanced by exploiting CBf. The analytical results are validated with the finite-size system by simulation.
Traditional approaches for providing confidentiality of wirelessly transmitted signals are often based on cryptographic techniques. While these techniques ensure that messages are encrypted and secured against eavesdropping, they are not sufficient to protect important transmission attributes at the physical (PHY) layer. Specifically, several elds in the headers of PHY and medium access control (MAC) frames are typically sent unencrypted to maintain proper protocol functionality (e.g., sender/receiver identification). As a result, they leak side-channel information (SCI), including payload size, frequency and phase oset, modulation and coding scheme, identities of communication nodes, frame type, transmission rate, etc. These SCI can be exploited by an adversary to launch various passive (eavesdropping) and active (jamming) attacks. To complement cryptographic techniques used at upper layers and prevent the leakage of SCI at the PHY/MAC layers, PHY-layer security techniques have been introduced. These techniques exploit the characteristics of the wireless channel along with multiple-input multiple-output (MIMO) technologies, in which multiple transmitting and receiving antennas are utilized to prevent information leakage to eavesdroppers and/or avoid jamming attacks. In particular, if the signal-to-interference-plus-noise ratio (SINR) at an adversary is lower than the one at a legitimate receiver, secure communication can be achieved through the so-called wiretap coding. MIMO systems enable the transmitter and/or the receiver to generate artificial noise, called friendly jamming (FJ), so as to reduce the SINR at the adversary without impacting the SINR at the legitimate receiver. In this dissertation, we focus on exploring the security threats to next-generation wireless systems. We develop MIMO-based PHY-layer security methods to achieve reliable and secret communications in these systems. First, we consider a broadcast channel, in which a multi-antenna transmitter (Alice) sends K confidential information signals to K legitimate receivers (Bobs) in the presence of L eavesdropping devices (Eves). Alice uses MIMO precoding to generate the information signals along with her own Tx-based friendly jamming (TxFJ). Interference at each Bob is removed via a technique called MIMO zero-forcing. This TxFJ, however, leaves an eavesdropping \vulnerability region" in the proximity of each Bob, which can be exploited by a nearby Eve. Specically, because of the high correlation in the channel state information (CSI) at a Bob and nearby Eves, the TxFJ becomes less effective in preventing eavesdropping at these Eves. We address this problem by augmenting TxFJ with receiver-based friendly jamming (RxFJ), generated by each Bob. Specifically, we allow each Bob to use self-interference suppression (SIS) techniques to transmit a friendly jamming signal while simultaneously receiving an information signal over the same channel. These SIS techniques exploit circulators to attenuate the self-interference power of RxFJ at Bobs and utilize analog/digital cancellation methods to clean out any remaining residual self-interference. Considering the resulting broadcast channel, we rst study a two-user scenario and develop a secrecy encoding scheme for constructing the signals intended to two Bobs. We characterize the corresponding achievable secrecy sum-rate and formulate an optimization problem to maximize this metric. We then extend our approach to K-user scenarios and study a power minimization problem. Particularly, in our analysis we minimize the powers allocated to information and friendly jamming signals (both TxFJ and RxFJ) while guaranteeing individual secrecy rates for various Bobs. The problem is solved for the cases when the eavesdropper's CSI (ECSI) is known or unknown (but with a known distribution). Simulations show the effectiveness of the proposed solutions. Furthermore, we discuss how to schedule transmissions when the rate requirements need to be satised on average rather than instantaneously. In low and high power regime, a scheduling algorithm that serves only the strongest receivers is shown to outperform the one that schedules all receivers. Next, we consider a single-cell massive MIMO system in which a base station (BS) with a large number of antennas transmits simultaneously to several single antenna users. The BS acquires the CSI for various receivers using uplink pilot transmissions. We demonstrate the vulnerability of the CSI estimation process to a pilot-contamination (PC) attack that aims at minimizing the sum-rate of downlink transmissions by contaminating uplink pilots. We rst study PC attacks for two downlink power allocation strategies under the assumption that the attacker knows the locations of the BS and its users. Later on, we relax this assumption and consider the case when such knowledge is probabilistic. The formulated problems are solved using stochastic optimization, Lagrangian minimization, and game-theoretic methods. A closed-form solution for a special case of the problem is obtained. Furthermore, we analyze the \achievable individual secrecy rates" under PC attacks, and provide an upper-bound on these rates. We also study this scenario without a priori knowledge of user locations at the attacker by introducing chance constraints. Another attack model is considered, where the attacker generates jamming signals in both the CSI estimation and data transmission phases by exploiting inband full-duplex techniques. Our results indicate that such attacks can degrade the throughput of a massive MIMO system by more than 50%, and reduce fairness among users significantly.
The most of existing physical layer security research focus on the situation where decentralized nodes transmit signals to the Base Station(BS).But considering a scenario where nonorthogonal transmission is allowed, when the BS transmits signals to decentralized nodes, the multi-downlinks will interfere each other, decreasing the signal-to-interference-plus-noise ratios (SINRs) at receivers.Focusing on the above problem, this paper optimizes the downlink beamforming and power allocation jointly to meet the SINRs requirement.On this basis, when confronted with synergistic eavesdroping where a malicious jammer helps the eavesdropper to eavesdrop, the BS transmits the artificial noise(AN) to improve the secrecy rate.Then zero-sum game model is proposed to obtain the strategies and corresponding expectation value of the secrecy rate when system reaches the mixed strategy equilibrium.By simulation, this method will obtain a good secrecy rate.