We investigate cooperative impersonation jamming on angle-based physical layer authentication (PLA) within 6G systems using hybrid antenna arrays. PLA leverages angle-ofarrival (AoA) information to authenticate user equipment, but remains vulnerable to sophisticated jamming where multiple adversaries cooperate. We extend previous research by formulating a comprehensive model of PLA that integrates hybrid arrays and by developing optimized jamming strategies that consider energy and information constraints. Our results show that analog arrays are more vulnerable to cooperative jamming than hybrid arrays. Additionally, the combiner design in the hybrid array, along with the energy and information constraints on jamming strategies, significantly influences the success of jamming. By identifying vulnerabilities in PLA and studying effective countermeasures, this work contributes to advancing physical layer authentication in 6G systems.

In this paper, we devise preprocessing schemes to disentangle channel state information (CSI) into predictable and unpredictable components to simultaneously provide two cornerstone security operations. The predictable components are used for node authentication and the unpredictable components for secret key generation (SKG). For the case of SKG, to prevent Eve from exploiting potential spatial, frequency or time correlations with the legitimate users, which would reduce the effective key space through a decrease in the brute force attack size, in this work, we emphasise the need for reducing the spatial correlation (SC) at different transmitter locations. We also study the trade-off between SC and reconciliation in the uplink and the downlink. Furthermore, we discuss the importance of a more robust criterion - independence - over decorrelation between the legitimate users and eavesdroppers. Finally, we propose a metric for quantifying uniqueness in the predictable components for node authentication, using the total variation distance (TVD).

In this paper, we propose a scheme for the joint optimization of the user transmit power and the antenna selection at the access points (AP)s of a user-centric cell-free massive multiple-input-multiple-output (UC CF-mMIMO) system. We derive an approximate expression for the achievable uplink rate of the users in a UC CF-mMIMO system in the presence of a mixed analog-to-digital converter (ADC) resolution profile at the APs. Using the derived approximation, we propose to maximize the uplink sum-rate of UC CF-mMIMO systems subject to energy constraints at the APs. An alternating-optimization solution is proposed using binary particle swarm optimization (BPSO) and successive convex approximation (SCA). We also propose a complete meta-heuristic-based solution that can be used as an alternative solution for applications where latency is the critical metric. Along with this, we used a genetic algorithm (GA)-based approach to compare the performance of the proposed algorithm. We study the impact of various system parameters on the performance of the system.

This paper determines the optimum secondary user (SU) power allocation and ergodic multicast rate of point-to-multipoint communication in a cognitive radio network (CRN) in the presence of various quality of service (QoS) constraints for the primary users (PUs). Using tools from extreme value theory (EVT), it is first proved that the limiting distribution of the minimum of independent and identically distributed (i.i.d.) signal-to-interference ratio (SIR) random variables (RVs) is a Weibull distribution, when the user signal and the interferer signals undergo independent and non-identically distributed (i.n.i.d.) κ-μ shadowed fading. Also, the rate of convergence of the actual minimum distribution to the Weibull distribution is derived. This limiting distribution is then used for determining the optimum transmit power of a secondary network in an underlay CRN subject to three different QoS constraints at the primary network in a generalized fading scenario. Furthermore, the optimum transmit power and the asymptotic ergodic multicast rate of SUs is analyzed for varying channel fading parameters.

Using tools from extreme value theory (EVT), it is proved that when the user signal and the interferer signals undergo independent and non-identically distributed (i.n.i.d.) κ-μ shadowed fading, the limiting distribution of the maximum of L independent and identically distributed (i.i.d.) signal-to-interference ratio (SIR) random variables (RVs) is a Frechet distribution. It is observed that this limiting distribution is close to the true distribution of maximum for maximum SIR evaluated over moderate L. Furthermore, moments of the maximum RV is shown to converge to the moments of the Frechet RV. In addition, the rate of convergence of the actual distribution of the maximum to the Frechet distribution is derived and analyzed for different κ and μ parameters. Finally, results from the stochastic ordering are used to analyze the variation in the limiting distribution with respect to the variation in source fading parameters. These results are then used to derive upper bound for the rate in full array selection (FAS) schemes for the antenna selection and the asymptotic outage probability and the ergodic rate in maximum-sum-capacity (MSC) scheduling systems.