Electronics

Outage-Constrained Coordinated Beamforming With Opportunistic Interference Cancellation
In this paper, interference management is considered for the K-user multiple-input single-output (MISO) block-faded interference channel. It is assumed that perfect channel state information (CSI) can be obtained at the receivers, whereas only channel distribution information (CDI) is available to the transmitters. Furthermore, the receivers are assumed to be capable of implementing opportunist...


Kernel Additive Models for Source Separation
Source separation consists of separating a signal into additive components. It is a topic of considerable interest with many applications that has gathered much attention recently. Here, we introduce a new framework for source separation called Kernel Additive Modelling, which is based on local regression and permits efficient separation of multidimensional and/or nonnegative and/or non-regular...
An Online Algorithm for Separating Sparse and Low-Dimensional Signal Sequences From Their Sum
This paper designs and extensively evaluates an online algorithm, called practical recursive projected compressive sensing (Prac-ReProCS), for recovering a time sequence of sparse vectors $S_{t}$ and a time sequence of dense vectors $L_{t}$ from their sum, $M_{t}:=S_{t}+L_{t}$, when the $L_{t}$ 's lie in a slowly changing low-dimensional subspace of the full space. A key application where this...


An MGF-Based Unified Framework to Determine the Joint Statistics of Partial Sums of Ordered i.n.d. Random Variables
The joint statistics of partial sums of ordered random variables (RVs) are often needed for the accurate performance characterization of a wide variety of wireless communication systems. A unified analytical framework to determine the joint statistics of partial sums of ordered independent and identically distributed (i.i.d.) random variables was recently presented. However, the identical distr...
Blind Source Separation by Entropy Rate Minimization
By assuming latent sources are statistically independent, independent component analysis separates underlying sources from a given linear mixture. Since in many applications, latent sources are both non-Gaussian and have sample dependence, it is desirable to exploit both properties jointly. In this paper, we use mutual information rate to construct a general framework for analysis and derivatio...


Likelihood Estimators for Dependent Samples and Their Application to Order Detection
Estimation of the dimension of the signal subspace, or order detection, is one of the key issues in many signal processing problems. Information theoretic criteria are widely used to estimate the order under the independently and identically distributed (i.i.d.) sampling assumption. However, in many applications, the i.i.d. sampling assumption does not hold. Previous approaches address the depe...
Bayesian Estimation of Clean Speech Spectral Coefficients Given a Priori Knowledge of the Phase
While most short-time discrete Fourier transform-based single-channel speech enhancement algorithms only modify the noisy spectral amplitude, in recent years the interest in phase processing has increased in the field. The goal of this paper is twofold. First, we derive Bayesian probability density functions and estimators for the clean speech phase when different amounts of prior knowledge abo...

Sum-Rate Maximization for Active Channels With Unequal Subchannel Noise Powers
In this paper, an active channel, between a source and a destination, refers to a parallel channel where the source transmits power over different subchannels as well as the powers of the subchannels can be adjusted. We herein study the sum-rate maximization for an active channel subject to two constraints, one on the source total transmit power and one on the total channel power. Although this...
Efficient Hardware Architecture for Sparse Coding
Sparse coding encodes natural stimuli using a small number of basis functions known as receptive fields. In this work, we design custom hardware architectures for efficient and high-performance implementations of a sparse coding algorithm called the sparse and independent local network (SAILnet). A study of the neuron spiking dynamics uncovers important design considerations involving the neura...

Ramanujan Sums in the Context of Signal Processing—Part II: FIR Representations and Applications
The mathematician Ramanujan introduced a summation in 1918, now known as the Ramanujan sum $c_q(n)$ . In a companion paper (Part I), properties of Ramanujan sums were reviewed, and Ramanujan subspaces ${cal S}_q$ introduced, of which the Ramanujan sum is a member. In this paper, the problem of representing finite duration (FIR) signals based on Ramanujan sums and spaces is considered. First, it...
Ramanujan Sums in the Context of Signal Processing—Part I: Fundamentals
The famous mathematician S. Ramanujan introduced a summation in 1918, now known as the Ramanujan sum $c_q(n)$ . For any fixed integer $q$ , this is a sequence in $n$ with periodicity $q$ . Ramanujan showed that many standard arithmetic functions in the theory of numbers, such as Euler’s totient function $phi(n)$ and the Möbius function $mu (n)$, can be expressed as linear combin...

Multitask Diffusion Adaptation Over Networks
Adaptive networks are suitable for decentralized inference tasks. Recent works have intensively studied distributed optimization problems in the case where the nodes have to estimate a single optimum parameter vector collaboratively. However, there are many important applications that are multitask-oriented in the sense that there are multiple optimum parameter vectors to be inferred simultaneo...
Tomlinson–Harashima Precoding for Multiuser MIMO Systems With Quantized CSI Feedback and User Scheduling
This paper studies the sum rate performance of a low complexity quantized CSI-based Tomlinson–Harashima (TH) precoding scheme for downlink multiuser MIMO transmission, employing greedy user selection. The asymptotic distribution of the output-signal-to-interference-plus-noise ratio of each selected user and the asymptotic sum rate as the number of users $K$ grows large are derived by us...
Estimation of Amplitude, Phase and Unbalance Parameters in Three-phase Systems: Analytical Solutions, Efficient Implementation and Performance Analysis
This paper focuses on the estimation of the instantaneous amplitude, phase, and unbalance parameters in three-phase power systems. Due to the particular structure of three-phase systems, we demonstrate that the maximum-likelihood estimates (MLEs) of the unknown parameters have simple closed-form expressions and can be easily implemented without matrix algebra libraries. We also derive and analy...
A Survey on Peer to Peer Video Streaming Systems
Due to the development of internet technology peer to peer video streaming have become more widespread in latest years. These systems exploit the upload bandwidth of every peer to provide services to other peers. In this paper we conducted a survey on the P2P video streaming systems. Moreover we examined the advantages and limitations of the existing systems.