IEEE Signal Research Articles

Multiple-symbol noncoherent learning detection of coded QAM signals in IEEE 802.15.3 Wireless Multi-media Networks

We consider the noncoherent deep learning problem for coded signal detection under the phase noncoherent channels for remote home healthcare applications with high data rate. In particular, a multiple-symbol noncoherent learning detection (MNLD) scheme based on neural networks is proposed for low-density parity-check (LDPC) coded noncoherent quadrature amplitude modulation (QAM) signals in IEEE 802.15.3 Wireless Multi-media Networks. Our derivation shows that extensive operations for the first kind zero-order modified Bessel function is unavoidable for the implementation of the optimal bit log-likelihood ratio (LLR) for decoding in traditional multiple-symbol detection (MSD) scheme. The perfect estimation of the channel state information (CSI), i.e., a priori information about the variance of the additive white Gaussian noise (AWGN), is also required for the receiver. This is clearly not computationally practical for Wireless Multi-media Networks. Consequently, we developed an improved approach based on feed-forward neural networks to accurately calculate the bit LLR. Furthermore, to decrease the generation size of training set and thus increase the training speed of the proposed neural networks, we uniformly quantize the continuous carrier phase offset (CPO), which is random and unknown, into discrete status. Our simulation results verify the learning efficiency of this simplified training-set generation configuration. The decoding convergence is successfully accelerated and much performance gain is finally achieved when compared with traditional decoding using the perfect bit LLR. This is clearly critical for high reliable transmission of home healthcare information.

Simple Adaptive Single Differential Coherence Detection of BPSK Signals in IEEE 802.15.4 Wireless Sensor Networks.

In this paper, we propose an adaptive single differential coherent detection (SDCD) scheme for the binary phase shift keying (BPSK) signals in IEEE 802.15.4 Wireless Sensor Networks (WSNs). In particular, the residual carrier frequency offset effect (CFOE) for differential detection is adaptively estimated, with only linear operation, according to the changing channel conditions. It was found that the carrier frequency offset (CFO) and chip signal-to-noise ratio (SNR) conditions do not need a priori knowledge. This partly benefits from that the combination of the trigonometric approximation and a useful assumption, namely, the asymptotic or high chip SNR, is considered for simplification of the full estimation scheme. Simulation results demonstrate that the proposed algorithm can achieve an accurate estimation and the detection performance can completely meet the requirement of the IEEE 802.15.4 standard, although with a little loss of reliability and robustness as compared with the conventional optimal single-symbol detector.

Two years of signal and power integrity in Italy: a report on SPI2016 and SPI2017

The IEEE Signal and Power Integrity (SPI) Workshop started in 1997 following an intuition of a group of researchers from the University of Hannover, Germany. At that time, it was already clear that interconnects were going to be one of the major limiters of system performance in the years to come. The first edition of the conference was thus named IEEE Workshop on Signal Propagation on Interconnects and took place in Travemunde, Germany, with a strong technical focus on understanding, modeling and simulating the physics of interconnects.

Improving the Accuracy of Exposure Assessment to Stochastic-like Radiofrequency Signals

Assessment of human exposure to RF signals which are rapidly variable in time and wide-banded is not yet standardized. Signals in IEEE 802.11 standards are widespread among population use due to presence of wireless local area network in everyday life. Recently, with technological advancement of real-time vector signal analyzers, a more precise exposure evaluation became achievable. However, such instruments are prohibitive and not available for the majority of metrological laboratories. Therefore, it is of great value to improve accuracy obtained by using swept-spectrum analyzers through procedural adequacy. This paper contributes to the refinement of the measurement procedure of stochastic-like radio signals level by a solution of averaging which responds to the dual variability character of such signals: in time and in amplitude.

Bit error rate analysis in IEEE 802.15.3a UWB channels

In this paper, we present a computable bit error rate (BER) expression for the binary signals in the IEEE 802.15.3a ultra-wideband (UWB) channel. In the literature, the impacts of the RAKE receiver...

IEEE Journal of Selected Topics in Signal Processing Inaugural Issue: {editor-in-chief's message}

EMBERS of the signal processing community often complain that, for a technology that is so ubiquitous, few outside our world really understand and hence appreciate what it is we do. After all, signal processing engineers don’t pump oil out of the ground, they don’t build cars or iPods, nor do they work in hospitals attending to the sick or disabled. No, instead, we are faced with the task of explaining to friends and family the virtues of the discrete cosine transform, fast transversal filters and space-time coding. I am reminded of BASF’s well-known advertising slogan: “We don’t make the products you buy, we make the products you buy better.” While we cannot claim to be the architects of the products or services that form the foundation of our modern lives, it is fair to say that signal processing is at the heart of the technology that differentiates today’s generations from those of the past. From oil exploration to EEG signal monitoring, anti-lock brakestoMP3encoding,fighter-jetradarstodigitalcameras,GPS positioning devices to IC wafer inspection systems, signal processing is indeed everywhere. Not surprisingly then, the IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING (J-STSP) will be unique among IEEE publications in the broad array of technical subjects that it will address. While the Signal Processing Magazine covers similar topical territory, it does so at a higher level, focusing on introductory explanations and tutorial descriptions. J-STSP digs deeper into these subjects, at the same technical level as articles in other Transactions within the IEEE Signal

IEEE signal processing/Athos workshop on higher-order statistics

IEEE signal processing/Athos workshop on higher-order statistics