The increasing exploitation of natural resources under water, particularly in the sea, has ignited development many technological advances domains environmental monitoring, oil and gas exploration, warfare, among others. In all these domains, underwater wireless communications play an important role, where technologies available rely on radio-frequency, optical, acoustic transmissions. This paper surveys key features inherent to communication technologies, putting into perspective their...

This letter presents a new data selective adaptive filtering algorithm, the set-membership affine projection (SM-AP) algorithm. The algorithm generalizes idea of NLMS (SM-NLMS) to include constraint sets constructed from past input and desired signal pairs. resulting can be seen as version affine-projection (AP) with an optimized step size. Also, SM-AP does not trade convergence speed misadjustment computational complexity most algorithms. Simulations show good performance especially for...

In this paper, we discuss the compression of waveforms obtained from measurements power system quantities and analyze reasons why its importance is growing with advent smart grid systems. While generation transmission networks already use a considerable number automation measurement devices, large monitors meters are to be deployed in distribution network allow broad observability real-time monitoring. This situation creates new requirements concerning communication interface, computational...

The increasing scarcity in the available spectrum for wireless communication is one of current bottlenecks impairing further deployment services and coverage. proper exploitation white spaces radio requires fast, robust, accurate methods their detection. This paper proposes a new strategy to detect adaptively spectrum. Such works cognitive (CR) networks whose nodes perform sensing based on energy detection cooperative way or not. main novelty proposal use cost-function that depends upon...

This paper presents and analyzes novel data selective normalized adaptive filtering algorithms with two reuses. The [the set-membership binormalized LMS (SM-BN-DRLMS) algorithms] are derived using the concept of (SMF). These can be regarded as generalizations previously proposed NLMS (SM-NLMS) algorithm. They include constraint sets in order to construct a space feasible solutions for coefficient updates. data-dependent step sizes that provide fast convergence low-excess mean-squared error...

This paper presents set-membership (SM) adaptive algorithms based on time-varying error bounds for code-division multiple-access (CDMA) interference suppression. We introduce a modified family of SM parameter estimation with bounds. The considered include versions the normalized least mean square (SM-NLMS), affine projection (SM-AP), and bounding ellipsoidal constrained (BEACON) recursive least-square technique. important issue error-bound specification is addressed in new framework that...

We propose two adaptive filtering algorithms that combine sparsity-promoting schemes with data-selection mechanisms. Sparsity is promoted via some well-known nonconvex approximations to the l <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sup> norm in order increase convergence speed of when dealing sparse/compressible signals. These circumvent difficulties working norm, thus allowing development online data-selective algorithms. Data...

Recent standards for cellular transmission systems offer a lot of flexibility, such as the choice modes, modulation alphabets, coding rates, and precoding matrices. Despite this trend, pilot-symbol patterns in today's remain fixed, although an approach is suboptimal. In paper, we show how to design optimal by maximizing upper bound constrained capacity that takes channel estimation errors Inter Carrier Interference into account. Furthermore, propose adaptive follow changing statistics. As...

In recent years, deep learning has been widely used in remote sensing, especially the field of synthetic aperture radar (SAR) image target detection. However, all these models continue increasing network's depth and width without maintaining a good balance between accuracy speed. Therefore, this article, we propose hybrid representation learning-enhanced SAR detection algorithm based on unique features images from lightweight perspective called HRLE-SARDet. First, design scattering feature...

In this paper, we present mean-squared convergence analysis for the partial-update normalized least-mean square (PU-NLMS) algorithm with closed-form expressions case of white input signals. The formulae presented here are more accurate than ones found in literature PU-NLMS algorithm. Thereafter, ideas NLMS-type algorithms incorporated framework set-membership filtering, from which data-selective derived. new algorithms, referred to herein as (SM-PU-NLMS) combine updating filtering reduced...

We propose two versions of affine projection (AP) algorithms tailored for sparse system identification (SSI). Contrary to most adaptive filtering devised SSI, which are based on the l <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> norm, proposed rely homotopic xmlns:xlink="http://www.w3.org/1999/xlink">0</sup> norm minimization, has proven yield better results in some practical contexts. The first proposal is obtained by direct...

Normalized least mean squares algorithms for FIR adaptive filtering with or without the reuse of past information are known to converge often faster than conventional (LMS) algorithm. This correspondence analyzes an LMS-like algorithm: binormalized data-reusing (BNDR-LMS) algorithm, which corresponds affine projection algorithm case two projections, compares favorably other normalized when input signal is correlated. Convergence analyses in and mean-squared presented, a closed-form formula...

Some properties of an adaptive filtering structure that employs analysis filterbank to decompose the input signal and sparse filters in subbands are investigated this paper. The necessary conditions on parameters for exact modeling arbitrary linear system with finite impulse response (FIR) derived. Then, based results obtained subfilter structure, a new family structures critical sampling subband signals, which can also yield modeling, is obtained. Two adaptation algorithms normalized LMS...

The current trend of acquiring data pervasively calls for some data-selection strategy, particularly in the case a subset does not bring enough innovation. In this paper, we present extensions existing adaptive filtering algorithms enabling selection, which also address censorship outliers measured through unexpected high estimation errors. resulting allow prescription how often acquired are expected to be incorporated learning process based on priori assumptions regarding environment data....

As wireless services proliferate, the demand for available spectrum also grows. a result, spectral efficiency is still an issue being addressed by many researchers aiming at improving quality of service to growing number users. Massive multiple-input multiple-output (MIMO) has been presented as attractive technology next systems since it can alleviate expected shortage. Nevertheless, such technique requires dedicated chain radio frequency (RF) components each antenna element which result in...

This paper proposes low-complexity constrained affine-projection (CAP) algorithms. The algorithms are suitable for linearly filtering problems often encountered in communications systems. CAP derived this trade convergence speed and computational complexity the same way as conventional (AP) algorithm. In addition, data-selective versions of algorithm based on concept set-membership filtering. (SM-CAP) include several constraint sets order to construct a space feasible solutions coefficient...