25 accepted papers
Spatial frequency estimation from a mixture of noisy sinusoids finds applications in various fields. The widely used subspace-based methods provide super-resolution parameter estimation at a low computational cost. However, they require an accurate array calibration, which is difficult for large ant…
Localization in terrestrial and non-terrestrial networks plays an important role in various applications, such as autonomous driving, robotics, and unmanned aerial vehicles. Although the relative distances between neighboring devices can be directly detected by embedded sensors, the relative distanc…
The Partial Relaxation framework has recently been introduced to address the Direction-of-Arrival (DOA) estimation problem [1]–[3]. DOA estimators under the Partial Relaxation (PR) framework are computationally efficient while preserving excellent DOA estimation accuracy. This is achieved by keeping…
We propose a new formulation for the joint phase retrieval and dictionary learning problem with a reduced number of regularization parameters to be tuned. A parallel algorithm based on the block successive convex approximation framework is developed for the proposed formulation. The performance of t…
In practical applications, non-Gaussianity of the signal at the sensor array is detrimental to the performance of conventional Direction-of-Arrival (DOA) estimators developed under the Gaussian model. In this paper, we propose a novel robust DOA estimator from the data collected at the sensor array…
In this paper, the outlier production mechanism of the G-MUSIC Direction-of-Arrival estimation technique is investigated using tools from Random Matrix Theory. The G-MUSIC Direction-of-Arrival estimation technique is an improved version of the conventional MUSIC method that provides superior perform…
A family of computationally efficient DOA estimators under the partial relaxation framework has recently been proposed. In this framework, the manifold structure of the "interfering" signals is relaxed, and only the manifold structure of one desired signal is retained. This particular type of relaxa…
The Partial Relaxation approach has recently been proposed to solve the Direction-of-Arrival estimation problem [1], [2]. In this paper, we investigate the outlier production mechanism of the Partially Relaxed Deterministic Maximum Likelihood (PR-DML) Direction-of-Arrival estimator using tools from…
In this paper, the Cramér-Rao Bound for the Direction-ofArrival parameter under the partial relaxation framework is derived. We introduce a non-redundant parameterization of the signal model corresponding to the partial relaxation framework, in which the array structure in part of the steering matri…
This paper deals with semi-blind channel estimation in Single-Input Single-Output (SISO) Orthogonal Frequency Division Multiplexing (OFDM) communications system. The proposed algorithm proceeds in two main stages. The first one addresses the pilot-based Time-Of-Arrival (TOA) estimation using subspac…
In this paper, we study the sparse phase retrieval problem, that is, to estimate a sparse signal from a small number of noisy magnitude-only measurements. We propose an iterative soft-thresholding with exact line search algorithm (STELA). It is a parallel coordinate descent algorithm, which has seve…
In this paper, we propose a convergent parallel best-response algorithm with the exact line search for the nondifferentiable nonconvex sparsity-regularized rank minimization problem. On the one hand, it exhibits a faster convergence than subgradient algorithms and block coordinate descent algorithms…
In the partial relaxation approach, at each desired direction, the manifold structure of the remaining interfering signals impinging on the sensor array is relaxed, which results in closed form estimates for the interference parameters. By adopting this approach, in this paper, a new estimator based…
Future generations of mobile communication networks are envisioned to utilize dense deployments of heterogeneous cell types to fulfill increasing performance requirements. An efficient and optimized utilization of the network resources, including user allocation management and load balancing between…
In this paper, we consider the energy efficiency optimization problem in MIMO multi-cell systems, where all users suffer from intercell interference. To solve this multi-objective optimization problem, we consider both socially optimal solutions and max-min fairness solutions. We propose two novel i…
We present an equivalent, compact reformulation of the ℓ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2,1</sub> mixed-norm minimization problem for joint sparse signal reconstruction from multiple measurement vectors (MMVs). The reformulation builds…
In this paper, we study a constructive interference based cognitive radio beamforming optimization problem under perfect channel state information at the transmitter and the knowledge of data information. The beamformers are designed to minimize the worst secondary user's symbol error probability un…
Parameter estimation has applications in many fields of signal processing, such as spectral analysis or direction-of-arrival estimation. Subspace-based methods like root-MUSIC and ESPRIT provide high parameter resolution at low computational complexity by exploiting specific sampling structure, name…
We consider the problem of designing hybrid analog-digital beamformers in a downlink multi-user large-scale MIMO system. The objective is to minimize the total transmit power, while fulfilling SINR targets of all users. A dual virtual uplink problem is formulated for the original downlink problem ba…
This paper investigates parametric direction-of-arrival (DOA) estimation in a particular context: i) each sensor is characterized by an unknown complex gain and ii) the array consists of a collection of subarrays which are substantially separated from each other leading ] to a structured noise covar…
This paper addresses multiuser downlink beamforming with shaping constraints under the assumption that the transmitter has long-term covariance based channel state information (CSI). Beamformers are designed to maximize the minimum average signal-to-interference-plus-noise ratio (SINR) of users subj…
The maximum likelihood (ML) and maximum a posteriori (MAP) estimation techniques are widely used to address the direction-of-arrival (DOA) estimation problems, an important topic in sensor array processing. Conventionally the ML estimators in the DOA estimation context assume the sensor noise to fol…
In this paper, we investigate user association and resource block (RB) allocation in downlink heterogeneous cellular networks. Our goal is to jointly optimize user association and RB allocation to maximize network throughput while taking into account fairness among users. To effectively control inte…
In this work we present a novel scheme for load management in microgrids based on stochastic scheduling of loads under risk-limiting constraints. When trying to enforce adequate power supply in a microgrid, the volatility of renewable resources such as wind energy has to be considered. In the risk o…
In this work, we propose a differential beamforming (DBF) scheme for bi-directional communication between two single-antenna terminals via a multi-antenna relay station (RS). The proposed scheme utilizes differential phase-shift keying modulation to enable beamforming at the RS without knowledge of…