DoA Estimation Using Low-Resolution Multi-BitSparse Array Measurements

in IEEE Signal Processing Letters (2021)

This letter studies the problem of Direction of Arrival (DoA) estimation from low-resolution few-bit quantized data collected by Sparse Linear Array (SLA). In such cases, contrary to the one-bit ... [more ▼]

This letter studies the problem of Direction of Arrival (DoA) estimation from low-resolution few-bit quantized data collected by Sparse Linear Array (SLA). In such cases, contrary to the one-bit quantization case, the well known arcsine law cannot be employed to estimate the covaraince matrix of unquantized array data. Instead, we develop a novel optimization-based framework for retrieving the covaraince matrix of unquantized array data from low-resolution few-bit measurements. The MUSIC algorithm is then applied to an augmented version of the recovered covariance matrix to find the source DoAs. The simulation results show that increasing the sampling resolution to $2$ or $4$ bits per samples could significantly increase the DoA estimation performance compared to the one-bit sampling regime while the power consumption and implementation costs is still much lower in comparison to the high-resolution sampling implementations. [less ▲]

Optimal fractional linear prediction with restricted memory

in IEEE Signal Processing Letters (2019), 26(5), 760-764

Linear prediction is extensively used in modeling, compression, coding, and generation of speech signal. Various formulations of linear prediction are available, both in time and frequency domain, which ... [more ▼]

Linear prediction is extensively used in modeling, compression, coding, and generation of speech signal. Various formulations of linear prediction are available, both in time and frequency domain, which start from different assumptions but result in the same solution. In this letter, we propose a novel, generalized formulation of the optimal low-order linear prediction using the fractional (non-integer) derivatives. The proposed fractional derivative formulation allows for the definition of predictor with versatile behavior based on the order of fractional derivative. We derive the closed-form expressions of the optimal fractional linear predictor with restricted memory, and prove that the optimal first-order and the optimal second-order linear predictors are only its special cases. Furthermore, we empirically prove that the optimal order of fractional derivative can be approximated by the inverse of the predictor memory, and thus, it is a priori known. Therefore, the complexity is reduced by optimizing and transferring only one predictor coefficient, i.e., one parameter less in comparison to the second-order linear predictor, at the same level of performance. [less ▲]

Constructive Interference for Generic Constellations

in IEEE Signal Processing Letters (2018), 25(4), 586-590

In this letter, we investigate optimal and relaxed constructive interference regions (CIR) for the symbol-level precoding (SLP) problem in the downlink of a multiuser multiple-input single-output (MISO ... [more ▼]

In this letter, we investigate optimal and relaxed constructive interference regions (CIR) for the symbol-level precoding (SLP) problem in the downlink of a multiuser multiple-input single-output (MISO) channel.We define two types of CIRs, namely, distance preserving CIR (DPCIR) and union bound CIR (UBCIR) for any given constellation shape and size. We then provide a systematic way to describe these regions as convex sets. Using the definitions of DPCIR and UBCIR, we show that the SLP power minimization problem, minimizing either sum or peak (per-antenna) transmit power, can always be formulated as a convex optimization problem. Our results indicate that these regions allow further reduction of the transmit power compared to the current state of the art without increasing the computational complexity at the transmitter or receiver. [less ▲]

An efficient algorithm for unit-modulus quadratic programs with application in beamforming for wireless sensor networks

in IEEE Signal Processing Letters (2018)

Performance Analysis of Network Coded Cooperation with Channel Coding and Adaptive DF-Based Relaying in Rayleigh Fading Channels

in IEEE Signal Processing Letters (2015), 22(9), 1354-1358

Diversity fairness in tomlinson-harashima precoded multiuser MIMO through retransmission

in IEEE Signal Processing Letters (2013), 20(4), 375-378

In this letter, we study the diversity unfairness associated with the conventional Tomlinson-Harashima precoding (THP) in multiuser multiple-input multiple-output downlink transmission. A single ... [more ▼]

In this letter, we study the diversity unfairness associated with the conventional Tomlinson-Harashima precoding (THP) in multiuser multiple-input multiple-output downlink transmission. A single-retransmission scheme that combines two THP signals at each user with a complementary multi-user suppression order is investigated. For a system with $M$ antennas at the transmitter and a single antenna at each user, the proposed scheme provides a diversity order $M+1$ for all users and ensures diversity fairness. We study two retransmission policies, where the users either consider only the current received codeword or combine both codewords for decoding. An asymptotic analysis of the outage probability for both THP retransmission schemes is provided. In addition, a power allocation policy that minimizes the outage probability and accommodates the same coding gain at each user is discussed by formulating a geometric optimization problem. © 1994-2012 IEEE. [less ▲]

Collaborative-Relay Beamforming with Perfect CSI: Optimum and Distributed Implementation

in IEEE Signal Processing Letters (2009), 16(4), 257260

This letter studies the collaborative use of amplify-and-forward (AF) relays to form a virtual multiple-input single-output (MISO) beamforming system with the aid of perfect channel state information (CSI ... [more ▼]

This letter studies the collaborative use of amplify-and-forward (AF) relays to form a virtual multiple-input single-output (MISO) beamforming system with the aid of perfect channel state information (CSI) in a flat-fading channel. In particular, we optimize the relay weights jointly to maximize the received signal-to-noise ratio (SNR) at the destination terminal with both individual and total power constraints at the relays. We show that the optimal collaborative-relay beamforming (CRB) solution achieves the full diversity of a MISO antenna system. Another main contribution of this letter is a distributed algorithm that allows each individual relay to learn its own weight, based on the Karush-Kuhn-Tucker (KKT) analysis. [less ▲]

Robust Blind Second-Order Deconvolution

in IEEE Signal Processing Letters (1999), 6