Low Implementation Complexity Research Articles

X-law detection scheme for monobit transmitted-reference ultra wideband receivers

<p>In ultra-wideband (UWB) communications, monobit receivers offer a low complexity implementation but at the same time exhibit a great performance loss. In this paper, a novel detection scheme, denoted as <em>x</em>-law detection (XLD), is proposed to diminish the performance loss caused by employing monobit analog-to-digital converters in transmitted-reference (TR) UWB receivers. Simulation results show that if the optimal value is employed for <em>x</em>, the XLD-based monobit weighted TR (MWTR) receiver can achieve 14.2~15.5 dB and 8~9.2 dB performance gain over the conventional MWTR receiver in LOS and NLOS scenarios, respectively. Moreover, the XLD-based MWTR receiver performance with the optimal value of <em>x</em> is only 1.6~3 dB away from the optimum MWTR receiver performance in intra-vehicle UWB channels. Additionally, the XLD-based MWTR receiver is not sensitive to the summation interval. This feature decreases the receiver complexity and guarantees a robust performance over different multipath channels. The significant performance improvement of the XLD scheme comes at a limited complexity increase. Thus, the XLD approach is a good candidate for TR-based and other training-based monobit receivers requiring low complexity, high performance, and low power consumption.</p>

Multi-Kernel Polar Codes versus Classical Designs with Different Rate-Matching Approaches

Polar codes, which have been proposed as a family of linear block codes, has garnered a lot of attention from the scientific community, owing to their low-complexity implementation and provably capacity-achieving capability. Thus, they have been proposed to be used for encoding information on the control channels in the upcoming 5G wireless networks. The basic approach introduced by Arikan in his landmark paper to polarize bit channels of equal capacities to those of unequal capacities can be used to design only codewords of length N=2n, which is a major limitation when codewords of different lengths are required for the underlying applications. In the predecessor paper, this aspect was partially addressed by using a 3×3 kernel circuit (used to generate codewords of length M=3m), along with downsizing techniques such as puncturing and shortening to asses the optimal design and resizing techniques based on the underlying system parameters. In this article, we extend this research to include the assessment of multi-kernel rate-matched polar codes for applicability over a much wider range of codeword lengths.

A probabilistic graph-based method to solve precision-diversity dilemma in recommender systems

Over the last few years, with significant growth of information on the web, users are swamped with a huge amount of information. Recommender system (RS) is an information retrieval technology that aims to provide relevant items to users by considering their preferences. Although several studies in the literature have proposed new RSs to improve the precision of recommendations, some studies have shown that increasing the diversity of recommendations is one way to increase the quality of the user’s experience and to solve the over-fitting problem. While some previous works have tried to make a trade-off between precision and diversity, they could not provide a linear and deterministic trade-off between precision and diversity. As such, these methods are either impractical or infeasible in a real RS. In this paper, we propose a new method to recommend items which are fit to users’ preferences. The method consists of following steps: i) finding users’ preferences using a limited user study, ii) proposing a probabilistic graph-based recommender system (PGBRS) to recommend items with a desirable level of precision and diversity by considering items that are likely to be preferred by the user in the future. PGBRS is a dataset-independent method which is significantly flexible to update with a low implementation complexity.

Review of PV array modelling, configuration and MPPT techniques

ABSTRACT This paper reviews the existing models, connection schemes and maximum power point tracking (MPPT) methods of PV arrays. The partial shading causes significant power losses. It is very difficult to maintain uniform irradiance over the entire PV array, especially for rooftop or building-integrated PV systems. The aspects such as connection scheme of PV array, shading pattern and maximum power point tracking (MPPT) techniques, etc., decide the power generated by the PV array. The conventional MPPT methods are only capable of reaching maximum power point (MPP) in identical insolation situations. Hence, conventional MPP tracking becomes inept due to the existence of several peaks in the P-V characteristics. There are different global maximum power point (GMPP) tracking techniques available in the literature that operate in partial shading scenarios. The reconfiguration of the PV array reduces the number of multiple peaks. This reduction in several peaks makes conventional MPP tracking techniques competent even under partial shading conditions with low implementation complexity and higher tracking speed. This paper can assist scientists in choosing a precise objective-based PV module model, connection schemes and MPP tracking methods out of numerous schemes available in the literature.

A harmonics detection method based on triangle orthogonal principle for shunt active power filter

Harmonic current detection is a key algorithms for shunt active power filter controller, which generates reference currents to compensate the harmonics of grid current. This paper presents a new harmonics detection method based on the triangle orthogonal principle algorithm. Compared to the conventional harmonic current detection methods, the presented method has the advantages of simple structure, low calculation, and fast execution time. Using the phase signal detected by the phase-locked loop synchronized with the power grid signal, the method based on the triangle orthogonal principle can provide a simple method to detect the reference current. At the same time, because the method proposed in this paper has lower implementation complexity and less microcontroller resource consumption, low-cost microcontrollers can be used to implement the proposed method, which has practical engineering value. Finally, this paper analysis the proposed method in detailly and verifies its great performance through experimental results.

Low complexity multiobjective finite impulse response filter design using Salp swarm algorithm and its improved version

AbstractRecent trend indicates that the assessment of low complexity is crucial for an effectual design of digital filter. Earlier the existing algorithms solely focused on reducing the pass band ripples and the stop band ripples in spite of the requirement of low implementation complexity in finite impulse response (FIR) filter design. In this regard, the optimization‐based FIR filter using multiobjective improved Salp swarm optimization algorithm have been designed. The proposed method not only minimizes the ripples of pass band and stop band but also minimizes the transition band, number of sparsity, which is used to implement a FIR filter that abides the specified frequency. The nondominated solution of filter design has a set of an optimum solution as pareto front that maintains the trade‐off between the various specifications. The designed FIR filter has been compared with other reported method to validate the applicability of the proposed method. The evaluation and analysis have been performed regrading minimum pass band ripples, minimum stop band ripple, minimum transition band, and implementation complexity. To prove the practical applicability of the proposed method, the designed FIR filters have been implemented in Xilinx ISE14.7 (Virtex‐VII) environment. The comparison result shows that the proposed method performs better than all other reported method in achieving minimum ripples and implementation complexity.

Coded Caching Schemes With Linear Subpacketizations

In coded caching system we prefer to design a coded caching scheme with low subpacketization and small transmission rate (i.e., the low implementation complexity and the efficient transmission during the peak traffic times). Placement delivery arrays (PDA) can be used to design code caching schemes. In this article we propose a framework of constructing PDAs via Hamming distance. As an application, two classes of coded caching schemes with linear subpacketizations and small transmission rates are obtained.

Uncovering biomarkers during therapeutic neuromodulation with PARRM: Period-based Artifact Reconstruction and Removal Method

SummaryAdvances in therapeutic neuromodulation devices have enabled concurrent stimulation and electrophysiology in the central nervous system. However, stimulation artifacts often obscure the sensed underlying neural activity. Here, we develop a method, termed Period-based Artifact Reconstruction and Removal Method (PARRM), to remove stimulation artifacts from neural recordings by leveraging the exact period of stimulation to construct and subtract a high-fidelity template of the artifact. Benchtop saline experiments, computational simulations, five unique in vivo paradigms across animal and human studies, and an obscured movement biomarker are used for validation. Performance is found to exceed that of state-of-the-art filters in recovering complex signals without introducing contamination. PARRM has several advantages: (1) it is superior in signal recovery; (2) it is easily adaptable to several neurostimulation paradigms; and (3) it has low complexity for future on-device implementation. Real-time artifact removal via PARRM will enable unbiased exploration and detection of neural biomarkers to enhance efficacy of closed-loop therapies.

Performance of a parallel Hamming coding in short-frame OFDM sensor's network

In this paper, we focus on the most relevant Error Correcting Codes (ECCs): the Hamming code and the Reed-Solomon code in order to meet the trade-off between the low implementation complexity and the high error correction capacity in a short-frame OFDM communication system. Moreover, we discuss and validate via simulations this trade-off between complexity (Hamming is the easiest to code) and error correction capability (Reed-Solomon being the most effective). Therefore, we have to either improve the correction capacity of the Hamming code, or decrease the complexity cost for the Reed-Solomon code. Based on this analysis, we propose a new design of parallel Hamming coding. On the one hand, we validate this new model of parallel Hamming coding with numerical results using MATLAB-Simulink tools and BERTool Application which makes easier the Bit Error Rate (BER) performance simulations. On the other hand, we implement the design of this new model on an FPGA mock-up and we show that this solution of a parallel Hamming encoder/decoder uses a few resources (LUTs) and has a higher capability of correcting when compared to the simple Hamming code.

A novel version of the TODIM method based on the exponential model of prospect theory: The ExpTODIM method

The adherence of the TODIM method and its variations, including two new versions of TODIM with the use of the exponential and logarithmic functions, to prospect theory was compared based on performance indicators with a very frequently used MCDM method, namely TOPSIS and its variation, Behavioral TOPSIS. It was hypothesized that the use of methods with mathematical models more adherent to prospect theory would provide more accurate predictions of individual decision making. A hundred students from the University of São Paulo in Ribeirão Preto were invited to participate in a field study where three different cases should be solved without the support of any method. Then, performance indicators were used to evaluate the prediction capacity of the methods with the ones provided by the volunteers, having the TODIM method with the new mathematical function presented in this paper, hereafter named Exponential TODIM (ExpTODIM), reached the best scores in all three performance indicators. The main contribution of the present paper is the proposal of a novel version of TODIM method that fits among the low implementation complexity multicriteria methods with high predictive power, since it is based on a value function that is more adherent to prospect theory.

Wireless Energy Transfer in Extra-Large Massive MIMO Rician Channels

In application scenarios such as Internet of Things, a large number of energy receivers (ERs) exist and line-of-sight (LOS) propagation could be common. Considering this, we investigate wireless energy transfer (WET) in extra-large massive MIMO Rician channels. We derive analytical expressions of the received net energy for different schemes, including 1) training-based WET, where the ER sends beacon signal for channel training and the energy transmitter (ET) uses the channel estimate for energy beamforming, 2) LOS beamforming, where the ET transmits to the LOS direction of the ER, and 3) energy harvesting, which allows an ER to harvest the training energy from the other ERs. We derive a path loss threshold for switching between training and LOS beamforming-based WET. We further show that the WET scheme selection of one ER is not affected by the other ERs, and the energy harvested from training is minimal in practice. With these insights, we propose an algorithm for the multi-ER scenario, which minimizes the power consumption by iteratively updating the WET scheme selection and power allocation for all ERs. Simulations show that the proposed algorithm achieves near-optimal performance as compared to exhaustive searching, while with much lower implementation complexity.

Lifting method for quasi-cyclic low-density parity-check codes based on approximated cycle extrinsic message degree in optical communication systems

Quasi-cyclic low-density parity-check (QC-LDPC) codes with low-complexity hardware implementation and excellent performance have become a hot research topic in many optical communication systems. To meet the different requirements of code lengths in optical communication systems, lifting methods which remove all the short cycles equally are usually used to construct long QC-LDPC codes of larger lengths by lifting short QC-LDPC codes. A lifting method is proposed, which considers both length and connectivity of short cycles. The proposed lifting method reduces the complexity of calculating the approximated cycle extrinsic message degree -related metrics and improves connectivity of the Tanner graph. The numerical results prove that, by employing our proposed lifting method, the lifted long QC-LDPC codes have better bit error rate performance compared with the lifted codes employing the traditional lifting method.

Low‐power fast Fourier transform hardware architecture combining a split‐radix butterfly and efficient adder compressors

Fast Fourier transform (FFT) is the most common low-complexity implementation of the discrete Fourier transform, intensively employed to process real-world signals in smart sensors for the internet of things. Butterflies play a central role as the FFT computing core data path since it calculates complex terms employing several multipliers. A low-power FFT hardware architecture combining split-radix decimation-in-time butterfly and 5-2 adder compressors (ACs) is proposed and implemented. The circuits are described in Verilog hardware description language and synthesized using the Cadence Genus synthesis tool. The circuits are mapped onto a 65-nm CMOS ST standard cell library. Results reveal that the proposed FFT hardware architecture using the split-radix butterfly is 13.28% more power efficient than the radix-4 one. The results further show that, by combining 5-2 AC within the split-radix butterfly, our proposal saves up to 43.1% of the total power dissipation considering the whole FFT hardware architecture, compared with the state-of-the-art radix-4 butterfly employing the adder automatically selected by the logic synthesis tool.

Joint Channel Estimation and Equalization Using New AFB Output Signal Models for FBMC/OQAM Systems

Filter bank multicarrier with offset quadrature amplitude modulation (FBMC/OQAM) has been studied as an alternative waveform for post-orthogonal frequency division multiplexing (OFDM) wireless communications. However, due to the intrinsic imaginary inter-carrier/inter-symbol interference of FBMC/OQAM signals, accurate channel estimation and equalization remain open issues for FBMC/OQAM systems in dispersive channels. In this article, two new signal models of the analysis filter bank (AFB) output are first derived in the absence of any channel assumption and in the presence of a relaxed channel assumption, respectively. Based on the new-built models, initial channel estimation with least squares (LS) (IniCE-LS) is presented and its output is used as the initial condition of recursive weighted LS (RWLS) estimation; moreover, non-iterative and iterative channel equalization combined with RWLS channel estimation (i.e., N-ICE-RWLS and ICE-RWLS) are proposed by using the real-time reconstructed FBMC/OQAM data symbols as pilots. The proposed N-ICE-RWLS and ICE-RWLS schemes not only allow to improve channel estimation and equalization performance, but also achieve high transmission efficiency. Considering the requirements of practical application, we further develop the low-complexity implementation methods of N-ICE-RWLS and ICE-RWLS. All these schemes are validated by analyzing the channel estimation accuracy and bit error rate (BER) over various frequency selective channels.

A Lightweight Key Generation Scheme for the Internet of Things

Devices in the Internet of Things (IoT) are usually limited in computing resources and energy capacity, which means that encryption schemes with higher complexity are not suitable for them to ensure secure communication. As a promising solution to this problem, physical layer key generation suggests that shared secret keys can be generated from noisy wireless channel measurements to enhance the security of wireless communications. In this article, we propose a key generation scheme with extremely low implementation complexity, which allows physical layer key generation to be implemented on IoT nodes. First, we preprocess the channel measurements with simple moving average filtering before quantization to improve channel reciprocity. Next, a bidirectional difference quantization scheme is proposed to realize reliable quantization of channel measurements, which is ingenious in that the quantization process does not depend on quantization thresholds, and thus, the mismatched key bits caused by measurements close to quantization thresholds can be effectively avoided. Then, we propose an improved Cascade protocol to achieve lightweight and efficient information reconciliation. The simulation results show that our scheme can well balance the reliability and efficiency of key generation, and has excellent performance in terms of implementation complexity and key randomness.

Novel filter bank-based cooperative spectrum sensing under practical challenges for beyond 5G cognitive radios

Cognitive radio (CR) technology with dynamic spectrum management capabilities is widely advocated for utilizing effectively the unused spectrum resources. The main idea behind CR technology is to trigger secondary communications to utilize the unused spectral resources. However, CR technology heavily relies on spectrum sensing techniques which are applied to estimate the presence of primary user (PU) signals. This paper firstly focuses on novel analysis filter bank (AFB) and FFT-based cooperative spectrum sensing (CSS) techniques as conceptually and computationally simplified CSS methods based on subband energies to detect the spectral holes in the interesting part of the radio spectrum. To counteract the practical wireless channel effects, collaborative subband-based approaches of PU signal sensing are studied. CSS has the capability to relax the problems of both hidden nodes and fading multipath channels. FFT- and AFB-based receiver side sensing methods are applied for OFDM waveform and filter bank-based multicarrier (FBMC) waveform, respectively, the latter one as a candidate beyond-OFDM/beyond-5G scheme. Subband energies are then applied for enhanced energy detection (ED)-based CSS methods that are proposed in the context of wideband, multimode sensing. Our first case study focuses on sensing potential spectral gaps close to relatively strong primary users, considering also the effects of spectral regrowth due to power amplifier nonlinearities. The study shows that AFB-based CSS with FBMC waveform is able to improve the performance significantly. Our second case study considers a novel maximum–minimum energy detector (Max–Min ED)-based CSS. The proposed method is expected to effectively overcome the issue of noise uncertainty (NU) with remarkably lower implementation complexity compared to the existing methods. The developed algorithm with reduced complexity, enhanced detection performance, and improved reliability is presented as an attractive solution to counteract the practical wireless channel effects under low SNR. Closed-form analytic expressions are derived for the threshold and false alarm and detection probabilities considering frequency selective scenarios under NU. The validity of the novel expressions is justified through comparisons with respective results from computer simulations.

An iterative receiver for time-domain oversampled OFDM system over time-varying underwater acoustic channels

This paper investigates an iterative receiver for time-domain oversampled orthogonal frequency division multiplexing (OFDM) over time-varying underwater acoustic channels for both single-input, single-output (SISO), single-input, multiple-output (SIMO) and multiple-input, multiple-output (MIMO) scenarios. We extend two widely used parametric models for time-varying channels: (i) Doppler rate model (DRM) and (ii) basis expansion model (BEM) to work with oversampled OFDM systems. To exploit the inherent sparsity of underwater acoustic channel, iterative orthogonal matching pursuit (OMP) algorithm is adopted for channel estimation. To further reduce computational complexity, fast Fourier transform (FFT) based low-complexity implementations for iterative OMP algorithm are proposed for both BEM and DRM. The proposed receiver is evaluated by sea trial conducted in the Trondheim Fjord, Norway. Both 8-phase shift keying modulation scheme and 16-quadrature modulation (16-QAM) scheme are carried out during the sea trial. The experimental results show that the proposed iterative time-domain oversampled OFDM receiver achieves lower bit error rates (BERs) than conventional iterative symbol rate sampled OFDM receiver.

Huffman-Coded Sphere Shaping for Extended-Reach Single-Span Links

Huffman-coded sphere shaping (HCSS) is an algorithm for finite-length probabilistic constellation shaping, which provides nearly optimal energy efficiency at low implementation complexity. In this paper, we experimentally study the nonlinear performance of HCSS employing dual-polarization 64-ary quadrature amplitude modulation (DP-64QAM) in an extended-reach single-span link comprising 200 km of standard single-mode fiber (SSMF). We investigate the effects of shaping sequence length, dimensionality of symbol mapping, and shaping rate. We determine that the naive approach of Maxwell–Boltzmann distribution matching — which is optimal in the additive white Gaussian noise channel — provides a maximum achievable information rate (AIR) gain of 0.18 bits/4D-symbol with respect to uniform signaling at optimum launch power in the infinite length regime. Conversely, HCSS can achieve a gain of 0.37 bits/4D-symbol over uniform signaling using amplitude sequence length of 32, which may be implemented without multiplications, using integer comparison and addition operations only. Coded system performance, with a net data rate of approximately 425 Gb/s for both shaped and uniform inputs, is also analyzed.

Machine learning aided carrier recovery in continuous-variable quantum key distribution

The secret key rate of a continuous-variable quantum key distribution (CV-QKD) system is limited by excess noise. A key issue typical to all modern CV-QKD systems implemented with a reference or pilot signal and an independent local oscillator is controlling the excess noise generated from the frequency and phase noise accrued by the transmitter and receiver. Therefore accurate phase estimation and compensation, so-called carrier recovery, is a critical subsystem of CV-QKD. Here, we explore the implementation of a machine learning framework based on Bayesian inference, namely an unscented Kalman filter (UKF), for estimation of phase noise and compare it to a standard reference method and a previously demonstrated machine learning method. Experimental results obtained over a 20-km fibre-optic link indicate that the UKF can ensure very low excess noise even at low pilot powers. The measurements exhibited low variance and high stability in excess noise over a wide range of pilot signal to noise ratios. This may enable CV-QKD systems with low hardware implementation complexity which can seamlessly work on diverse transmission lines.

A real-time estimator for model parameters and state of charge of lead acid batteries in photovoltaic applications

The intermittent nature of photovoltaic energy source has revealed concerns about the stability of the power electric system. For that, a massive use of storage elements becomes needed. Batteries are considered as one of the most important technologies for energy storage. In order to achieve the needs of safety, durability and reliability for the battery management system (BMS), data monitoring and diagnosis system has been discussed in this work. In fact, several methods have been presented with the intention of estimating the internal parameters of an AGM lead acid battery model such as the Recursive least square algorithm (RLS) with variable forgetting factor, a novel Adaptive Joint Extended Kalman Filter (AJEKF), and the Unscented Kalman Filter (UKF). The state of charge (SOC) of electrochemical storage device has been considered as one of the most important state which needs to be monitored in order to optimize the performance and to extend the lifetime of the system. SOC estimation is a challenging task hindered by considerable changes of the battery characteristic throughout its lifetime due to its nonlinear behavior and aging factor. In this work, online state of the charge estimation has been evaluated through the Extended Kalman Filter, Unscented Kalman Filter (UKF), and Cubature Kalman Filter (CKF). An Open circuit voltage experimental test (OCV) has been established in order to validate the operation of the proposed battery model under real work conditions.This paper proposes an exhaustive review for the online identification of battery parameters and its state of charge, where the tendency of estimation techniques has been oriented toward a mixture of different techniques that clearly raised the challenge of establishing a relationship between the accuracy and the robustness of these methods, without forgetting their low complexity of implementation.