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1. DDPG Learning for Aerial RIS-Assisted MU-MISO Communications

   Aly Sabri Abdalla; Vuk Marojevic (September 2022, IEEE PIMRC 2022)

   This paper defines the problem of optimizing the downlink multi-user multiple input, single output (MU-MISO) sum-rate for ground users served by an aerial reconfigurable intelligent surface (ARIS) that acts as a relay to the terrestrial base station. The deep deterministic policy gradient (DDPG) is proposed to calculate the optimal active beamforming matrix at the base station and the phase shifts of the reflecting elements at the ARIS to maximize the data rate. Simulation results show the superiority of the proposed scheme when compared to deep Q-learning (DQL) and baseline approaches. 

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2. Applications of Absorptive Reconfigurable Intelligent Surfaces in Interference Mitigation and Physical Layer Security

   https://doi.org/10.1109/TWC.2023.3312693  

   Wang, Fangzhou; Swindlehurst, A Lee (May 2024, IEEE Transactions on Wireless Communications)

   This paper explores the use of reconfigurable intelligent surfaces (RIS) in mitigating cross-system interference in spectrum sharing and secure wireless applications. Unlike conventional RIS that can only adjust the phase of the incoming signal and essentially reflect all impinging energy, or active RIS, which also amplify the reflected signal at the cost of significantly higher complexity, noise, and power consumption, an absorptive RIS (ARIS) is considered. An ARIS can in principle modify both the phase and modulus of the impinging signal by absorbing a portion of the signal energy, providing a compromise between its conventional and active counterparts in terms of complexity, power consumption, and degrees of freedom (DoFs). We first use a toy example to illustrate the benefit of ARIS, and then we consider three applications: 1) spectral coexistence of radar and communication systems, where a convex optimization problem is formulated to minimize the Frobenius norm of the channel matrix from the communication base station to the radar receiver; 2) spectrum sharing in device-to-device (D2D) communications, where a max-min scheme that maximizes the worst-case signal-to-interference-plus-noise ratio (SINR) among the D2D links is developed and then solved via fractional programming; 3) physical layer security of a downlink communication system, where the secrecy rate is maximized and the resulting nonconvex problem is solved by a fractional programming algorithm together with a sequential convex relaxation procedure. Numerical results are then presented to show the significant benefit of ARIS in these applications. 

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3. Aerial Base Station Positioning and Power Control for Securing Communications: A Deep Q-Network Approach

   https://doi.org/10.1109/WCNC51071.2022.9771893  

   Abdalla, Aly Sabri; Behfarnia, Ali; Marojevic, Vuk (April 2022, 2022 IEEE Wireless Communications and Networking Conference (WCNC))

   The unmanned aerial vehicle (UAV) is one of the technological breakthroughs that supports a variety of services, including communications. UAVs can also enhance the security of wireless networks. This paper defines the problem of eavesdropping on the link between the ground user and the UAV, which serves as an aerial base station (ABS). The reinforcement learning algorithms Q-learning and deep Q-network (DQN) are proposed for optimizing the position of the ABS and the transmission power to enhance the data rate of the ground user. This increases the secrecy capacity without the system knowing the location of the eavesdropper. Simulation results show fast convergence and the highest secrecy capacity of the proposed DQN compared to Q-learning and two baseline approaches. 

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4. Multi-user Downlink Beamforming using Uplink Downlink Duality with 1-bit Converters for Flat Fading Channels

   https://doi.org/10.1109/TVT.2022.3196603  

   Mazher, Khurram Usman; Mezghani, Amine; Heath, Robert W. (October 2022, IEEE Transactions on Vehicular Technology)

   The increased power consumption of high-resolution data converters at higher carrier frequencies and larger bandwidths is becoming a bottleneck for communication systems. In this paper, we consider a fully digital base station equipped with 1-bit analog-to-digital (in uplink) and digital-to-analog (in downlink) converters on each radio frequency chain. The base station communicates with multiple single antenna users with individual SINR constraints. We first establish the uplink downlink duality principle under 1-bit hardware constraints under an uncorrelated quantization noise assumption. We then present a linear solution to the multi-user downlink beamforming problem based on the uplink downlink duality principle. The proposed solution takes into account the hardware constraints and jointly optimizes the downlink beamformers and the power allocated to each user. Optimized dithering obtained by adding dummy users to the true system users ensures that the uncorrelated quantization noise assumption is true under realistic settings. Detailed simulations carried out using 3GPP channel models generated from Quadriga show that our proposed solution outperforms state of the art solutions in terms of the ergodic sum and minimum rate especially when the number of users is large. We also demonstrate that the proposed solution significantly reduces the performance gap from non-linear solutions in terms of the uncoded bit error rate at a fraction of the computational complexity. 

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5. Look Before You Leap: Secure Connection Bootstrapping for 5G Networks to Defend Against Fake Base-Stations

   https://doi.org/10.1145/3433210.3453082  

   Singla, Ankush; Behnia, Rouzbeh; Hussain, Syed Rafiul; Yavuz, Attila; Bertino, Elisa (May 2021, Proceedings of the 2021 ACM Asia Conference on Computer and Communications Security)

   The lack of authentication protection for bootstrapping messages broadcast by base-stations makes impossible for devices to differentiate between a legitimate and a fake base-station. This vulnerability has been widely acknowledged, but not yet fixed and thus enables law-enforcement agencies, motivated adversaries, and nation-states to carry out attacks against targeted users. Although 5G cellular protocols have been enhanced to prevent some of these attacks, the root vulnerability for fake base-stations still exists. In this paper, we propose an efficient broadcast authentication protocol based on a hierarchical identity-based signature scheme, Schnorr-HIBS, which addresses the root cause of the fake base-station problem with minimal computation and communication overhead. We implement and evaluate our proposed protocol using off-the-shelf software-defined radios and open-source libraries. We also provide a comprehensive quantitative and qualitative comparison between our scheme and other candidate solutions for 5G base-station authentication proposed by 3GPP. Our proposed protocol achieves at least a 6x speedup in terms of end-to-end cryptographic delay and a communication cost reduction of 31% over other 3GPP proposals. 

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