13 research outputs found
Mitigating Smart Jammers in Multi-User MIMO
Wireless systems must be resilient to jamming attacks. Existing mitigation
methods based on multi-antenna processing require knowledge of the jammer's
transmit characteristics that may be difficult to acquire, especially for smart
jammers that evade mitigation by transmitting only at specific instants. We
propose a novel method to mitigate smart jamming attacks on the massive
multi-user multiple-input multiple-output (MU-MIMO) uplink which does not
require the jammer to be active at any specific instant. By formulating an
optimization problem that unifies jammer estimation and mitigation, channel
estimation, and data detection, we exploit that a jammer cannot change its
subspace within a coherence interval. Theoretical results for our problem
formulation show that its solution is guaranteed to recover the users' data
symbols under certain conditions. We develop two efficient iterative algorithms
for approximately solving the proposed problem formulation: MAED, a
parameter-free algorithm which uses forward-backward splitting with a box
symbol prior, and SO-MAED, which replaces the prior of MAED with soft-output
symbol estimates that exploit the discrete transmit constellation and which
uses deep unfolding to optimize algorithm parameters. We use simulations to
demonstrate that the proposed algorithms effectively mitigate a wide range of
smart jammers without a priori knowledge about the attack type.Comment: arXiv admin note: text overlap with arXiv:2201.0877
EM-Based Estimation and Compensation of Phase Noise in Massive-MIMO Uplink Communications
Phase noise (PN) is a major disturbance in MIMO systems, where the
contribution of different oscillators at the transmitter and the receiver side
may degrade the overall performance and offset the gains offered by MIMO
techniques. This is even more crucial in the case of massive MIMO, since the
number of PN sources may increase considerably. In this work, we propose an
iterative receiver based on the application of the expectation-maximization
algorithm. We consider a massive MIMO framework with a general association of
oscillators to antennas, and include other channel disturbances like imperfect
channel state information and Rician block fading. At each receiver iteration,
given the information on the transmitted symbols, steepest descent is used to
estimate the PN samples, with an optimized adaptive step size and a
threshold-based stopping rule. The results obtained for several test cases show
how the bit error rate and mean square error can benefit from the proposed
phase-detection algorithm, even to the point of reaching the same performance
as in the case where no PN is present{\color{black}, offering better results
than a state-of-the-art alternative}. Further analysis of the results allow to
draw some useful trade-offs respecting final performance and consumption of
resources.Comment: Submitted to IEEE Transactions on Communication
Analog-Domain Suppression of Strong Interference Using Hybrid Antenna Array.
The proliferation of wireless applications, the ever-increasing spectrum crowdedness, as well as cell densification makes the issue of interference increasingly severe in many emerging wireless applications. Most interference management/mitigation methods in the literature are problem-specific and require some cooperation/coordination between different radio frequency systems. Aiming to seek a more versatile solution to counteracting strong interference, we resort to the hybrid array of analog subarrays and suppress interference in the analog domain so as to greatly reduce the required quantization bits of the analog-to-digital converters and their power consumption. To this end, we design a real-time algorithm to steer nulls towards the interference directions and maintain flat in non-interference directions, solely using constant-modulus phase shifters. To ensure sufficient null depth for interference suppression, we also develop a two-stage method for accurately estimating interference directions. The proposed solution can be applicable to most (if not all) wireless systems as neither training/reference signal nor cooperation/coordination is required. Extensive simulations show that more than 65 dB of suppression can be achieved for 3 spatially resolvable interference signals yet with random directions
International Conference on Continuous Optimization (ICCOPT) 2019 Conference Book
The Sixth International Conference on Continuous Optimization took place on the campus of the Technical University of Berlin, August 3-8, 2019. The ICCOPT is a flagship conference of the Mathematical Optimization Society (MOS), organized every three years. ICCOPT 2019 was hosted by the Weierstrass Institute for Applied Analysis and Stochastics (WIAS) Berlin. It included a Summer School and a Conference with a series of plenary and semi-plenary talks, organized and contributed sessions, and poster sessions.
This book comprises the full conference program. It contains, in particular, the scientific program in survey style as well as with all details, and information on the social program, the venue, special meetings, and more
MS FT-2-2 7 Orthogonal polynomials and quadrature: Theory, computation, and applications
Quadrature rules find many applications in science and engineering. Their analysis is a classical area of applied mathematics and continues to attract considerable attention. This seminar brings together speakers with expertise in a large variety of quadrature rules. It is the aim of the seminar to provide an overview of recent developments in the analysis of quadrature rules. The computation of error estimates and novel applications also are described
Generalized averaged Gaussian quadrature and applications
A simple numerical method for constructing the optimal generalized averaged Gaussian quadrature formulas will be presented. These formulas exist in many cases in which real positive GaussKronrod formulas do not exist, and can be used as an adequate alternative in order to estimate the error of a Gaussian rule. We also investigate the conditions under which the optimal averaged Gaussian quadrature formulas and their truncated variants are internal