In this paper, we propose a framework for protecting the uplink transmission of a massive multipleinput multiple-output (mMIMO) system from a jamming attack. Our framework includes a novel minimum mean-squared error based jamming suppression (MMSE-JS) estimator for channel training and a linear zero-forcing jamming suppression (ZFJS) detector for uplink combining. The MMSE-JS exploits some intentionally unused pilots to reduce the pilot contamination caused by the jammer. The ZFJS suppresses the jamming interference during the detection of the legitimate users' data symbols.The implementation of the proposed framework is practical, since the complexities of computing the MMSE-JS and the ZFJS are linear (not exponential) with respect to the number of antennas at the base station and linear detectors with the same complexities as the ZFJS have been already fabricated using 28 nm FD-SOI (Fully Depleted Silicon On Insulator) technology in [12] and Xilinx for the mMIMO systems. Our analysis shows that the jammer cannot dramatically affect the performance of a mMIMO system equipped with the combination of MMSE-JS and ZFJS. Numerical results confirm our analysis. Index TermsMassive MIMO, jamming suppression.

Abstract-This paper considers the physical layer security of a pilot-based massive multiple-input multiple-output (MaMIMO) system in presence of a multi-antenna jammer. To improve security of the network, we propose a new jamming detection method that makes use of a generalized likelihood ratio test over some coherence blocks. Our proposed method utilizes intentionally unused pilots in the network. The performance of the proposed detector improves by increasing the number of antennas at the base station, the number of unused pilots and also by the number of the coherence blocks that are utilized. Simulation results confirm our analyses and show that in the MaMIMO regime, perfect detection (i.e., correct detection probability is one) is achievable even with a small number of unused pilots.Index Terms-Massive MIMO, physical layer security, jamming detection, unused pilots. I. INTRODUCTIONMassive multiple-input multiple-output (MaMIMO) technology provides improvements of the physical layer security against passive eavesdropping [1]. To cause more harm, the eavesdropper can decide to actively attack the legitimate system. The asymptotic secrecy rate for downlink MaMIMO systems is derived in [2] in the presence of an active multi-antenna eavesdropper. Furthermore, for detection of an active eavesdropper in a single-input multiple-output system, the authors in [3] propose a detection method based on random training. Detection methods based on cooperation between the base station (BS) and the legitimate user are also suggested in [4]. A jammer can be viewed as an active eavesdropper, which transmits jamming signals in both the pilot and data phases. In MaMIMO systems, by jamming the pilot phase, pilot contamination is caused which significantly decreases the spectral efficiency of the legitimate users. In [5], the authors propose a jamming detection and countermeasure scheme for MaMIMO systems based on random matrix theory. The authors in [6] propose a linear combining scheme that exploits unused pilots to improve the spectral efficiency of the MaMIMO systems in presence of a singleantenna jammer. In [7], a jamming power allocation scheme is investigated for MaMIMO systems, where a smart jammer aims to maximize its deterioration effect on the spectral efficiency of the legitimate system. In order to apply the known methods for combating jamming, we first need to detect the presence of the jammer. In this letter, we propose a new jamming detection method by exploiting a generalized likelihood ratio test (GLRT) in the MaMIMO systems. Our proposed detector utilizes the key properties of MaMIMO systems, i.e., many antennas at the BS and the use of uplink pilot transmission, in order to detect the jamming with high accuracy. To this end, the proposed method estimates the power of the multi-antenna jammer in some intentionally unused pilot sequences (i.e., the pilots that are not assigned to any active users, except during peak hours) over multiple coherence blocks. To evaluate performance of the proposed method, we derive c...

In this paper, we consider how the uplink transmission of a spatially correlated massive multiple-input multipleoutput (MIMO) system can be protected from a jamming attack. To suppress the jamming, we propose a novel framework including a new optimal linear estimator in the training phase and a bilinear equalizer in the data phase.The proposed estimator is optimal in the sense of maximizing the spectral efficiency of the legitimate system attacked by a jammer, and its implementation needs the statistical knowledge about the jammer's channel. We derive an efficient algorithm to estimate the jamming information needed for implementation of the proposed framework. Furthermore, we demonstrate that optimized power allocation at the legitimate users can improve the performance of the proposed framework regardless of the jamming power optimization. Our proposed framework can be exploited to combat jamming in scenarios with either ideal or non-ideal hardware at the legitimate users and the jammer. Numerical results reveal that using the proposed framework, the jammer cannot dramatically affect the performance of the legitimate system.

In this paper, we address the problem of three dimensional beamforming (3DBF) in millimeter wave (mmWave) wireless networks. In particular, we study the impact of base station (BS) antenna tilt angle optimization on the energy efficiency (EE) of mmWave networks under two different scenarios: a homogeneous network consisting of multiple macro base stations (MBSs), and a heterogeneous network where several femto base stations are added within the coverage areas of the MBSs. First, by adopting a stochastic geometry approach, we analyze the coverage probability of both scenarios that incorporate the 3DBF. Then, we derive the EE of the networks as a function of the MBS antenna tilt angle. Next, optimization problems are formulated to maximize the EE of the networks by optimizing the tilt angle. Since the computational complexity of the optimal solution is very high, near-optimal low-complexity methods are proposed for solving the optimization problems. Simulation results show that in the mmWave networks, the 3DBF technique with optimized tilt angle can considerably improve the EE of the network. Also, the proposed low complexity approach presents a performance close to the optimal solution but with a significant reduced complexity. Index TermsmmWave network, 3D beamforming, coverage probability, energy efficiency, tilt angle optimization, blockage effect, stochastic geometry, HetNet.

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