Complexity Detection Scheme Research Articles

Permutation Matrix Modulation

We propose a novel scheme that allows MIMO system to modulate a set of permutation matrices to send more information bits, extending our initial work on the topic. This system is called Permutation Matrix Modulation (PMM). The basic idea is to employ a permutation matrix as a precoder and treat it as a modulated symbol. We continue the evolution of index modulation in MIMO by adopting all-antenna activation and obtaining a set of unique symbols from altering the positions of the antenna transmit power. We provide the analysis of the achievable rate of PMM under Gaussian Mixture Model (GMM) distribution \revv{and finite cardinality input (FCI). Numerical results are evaluated by comparing PMM with the other existing systems.} We also present a way to attain the optimal achievable rate of PMM by solving a maximization problem via interior-point method. A low complexity detection scheme based on zero-forcing (ZF) is proposed, and maximum likelihood (ML) detection is discussed. We demonstrate the trade-off between simulation of the symbol error rate (SER) and the computational complexity where ZF performs worse in the SER simulation but requires much less computational complexity than ML.

Evaluation of Non-Coherent Signal Detection Techniques for Mobile Molecular Communication.

In recent years, there have been more and more research on molecular communication (MC). Because the deployment of mobile nanomachines may be required in some applications of MC, research on mobile MC has become a trend. The signal detection schemes for static MC are no longer applicable due to the time varying channel impulse response (IR), which is caused by the mobile characteristics of nanomachines. In this paper, a low complexity and non-coherent detection scheme is proposed for mobile scenario, which is based on the energy difference between two adjacent symbols. Most of the existing signal detection methods do not consider inter-symbol interference (ISI). Compared with those methods, the proposed scheme can achieve signal detection utilizing ISI without knowing channel state information (CSI). The bit error rate (BER) performance of the proposed method is investigated under different conditions through simulations. Besides, the influence of mobility features of nanomachines on the signal detection accuracy is also investigated in detail. The simulation results demonstrate that the BER performance of the proposed scheme outperforms the latest signal detection scheme for short-distance mobile MC system with high velocity. Consequently, the detection scheme proposed in this paper can reduce the influence of nanomachines' mobility and has the potential to be used in mobile MC systems.

SCADA intrusion detection scheme exploiting the fusion of modified decision tree and Chi-square feature selection

The industrial internet of things (IIoT) and supervisory control and data acquisition (SCADA) have experienced ubiquitous growth recently. This growth comes with the challenge of an increased number of unusual attacks constituting threats. The existence and effect of intruders and their innovative attack techniques are rising. Although the existing intrusion detection systems (IDS) safeguard the networks, they have been computationally expensive. In real-time domains, available methods lag, necessitating additional research into effective feature extraction schemes with time exigency. An IDS with a fused feature selection (FS) approach for detecting and classifying attacks in a real-time SCADA network is imperative. It is to enable the resolution of computationally complex vulnerability detection schemes. The proposed technique is in three (3) phases: (a) data preparation which involves data cleansing and normalization, and (b) a fused feature selection approach built to obtain an optimal subset of features using Chi-square. (c) deployment of the modified decision tree (MDT) for anomaly detection and classification. Lastly, the reliability of the proposed model was validated, demonstrating suitability in precisely detecting abnormalities while minimizing computational time. This improvement enables adaptability for the IDS deployment scheme in a real-time situation, which could be in the control center. The validation results reveal that when the proposed chi-square-based (fused) feature extraction is employed, it performs optimally to other FS techniques and ML classifiers, compared across four (4) publicly available datasets. Cohen’s kappa coefficient (CKC) further validates the proposed model’s reliability. Further demonstrating the experimental results with recourse to false positive rates (FPR), the Mathews correlation coefficient (MCC) was employed. It also shows the resilience of the proposed model performance on an imbalanced dataset validating its suitability in real scenarios.

Sphere detector with low complexity Euclidean distance computation based on affine transform modulation

The foreseen scale of connected autonomous and low power consumption devices in the near future is a challenging aspect for the next generation of mobile communication networks. As the number of available connection resources is limited, frequency-time multiplexing may not be sufficient to meet the expected demand for capacity, where scheduling solutions might incur in undesired latency levels and also increase the power expenditure to meet a more stringent synchronisation. In this scenario, spatial multiplexing based on multi-user multiple-input multiple-output can extend the uplink capacity at the cost of inter-antenna interference at the base station, requiring more complex detection schemes. The sphere detector can mitigate the inter-antenna interference, achieving close-to-optimum bit error rate performance with average polynomial complexity that still challenges the field programmable gate array implementation in terms of resources and area. To further reduce the sphere detector complexity, the authors introduce the concept of affine transform modulation, which allows us to describe the received signal in terms of the sequence of transmitted bits per symbol. The authors demonstrate that this approach allows to evaluate the Euclidean distance in the sphere detector algorithm in terms of the transmitted bits, replacing the complex inner product by a complex accumulator in its extensively accessed core function. The approach proposed in this paper leads to a considerable complexity reduction in terms of FLOPs for low-order modulations while attaining the conventional sphere detector performance.

On the Error Analysis of Hexagonal-QAM Constellations

Future communication systems are envisioned to support applications that require very high data rates in an energy efficient manner. To this direction, the use of hexagonal quadrature amplitude modulation (HQAM) provides high data rates and power efficiency, due to its compact allocation of symbols on the 2D plane. However, because of its hexagonal lattice, it is difficult, if not impossible, to evaluate exactly the error probability. In this letter, we propose a tight upper bound as well as a closed-form approximation for the symbol error probability of HQAM, which are validated from numerical and simulation results. Finally, exploiting the analytical results a novel low complexity detection scheme is presented.

Gibbs Sampling Detection for Large MIMO and MTC Uplinks with Adaptive Modulation.

Wireless networks beyond 5G will mostly be serving myriads of sensors and other machine-type communications (MTC), with each device having different requirements in respect to latency, error rate, energy consumption, spectral efficiency or other specifications. Multiple-input multiple-output (MIMO) systems remain a central technology towards 6G, and in cases where massive antenna arrays or cell-free networks are not possible to deploy and only moderately large antenna arrays are allowed, the detection problem at the base-station cannot rely on zero-forcing or matched filters and more complex detection schemes have to be used. The main challenge is to find low complexity, hardware feasible methods that are able to attain near optimal performance. Randomized algorithms based on Gibbs sampling (GS) were proven to perform very close to the optimal detection, even for moderately large antenna arrays, while yielding an acceptable number of operations. However, their performance is highly dependent on the chosen “temperature” parameter (TP). In this paper, we propose and study an optimized variant of the GS method, denoted by triple mixed GS, and where three distinct values for the TP are considered. The method exhibits faster convergence rates than the existing ones in the literature, hence requiring fewer iterations to achieve a target bit error rate. The proposed detector is suitable for symmetric large MIMO systems, however the proposed fixed complexity detector is highly suitable to spectrally efficient adaptively modulated MIMO (AM-MIMO) systems where different types of devices upload information at different bit rates or have different requirements regarding spectral efficiency. The proposed receiver is shown to attain quasi-optimal performance in both scenarios.

Rotated Golden Codewords Based Space-Time Line Code Systems

The space-time line code (STLC) has been recently proposed in the literature. In STLC systems, the channel state information is assumed to be known at the transmitter, but not at the receiver. In the conventional STLC systems, the inputs of the STLC encoder are either M-ary phase shift keying symbols or M-ary quadrature amplitude modulation symbols and can achieve diversity order with very low detection complexity. In order to further improve the error performance of the STLC systems, in this paper, rotated Golden codewords based STLC (RGC-STLC) systems are proposed.We extend the 1×2 and 2 × 2 transmit-receive antenna structure in the conventional STLC into 1 × 4 and 2 × 4 transmit-receive antenna structures in the proposed RGC-STLC system. The inputs of the proposed RGC-STLC encoder are the rotated Golden codewords. Compared to the conventional 1 × 2 and 2 × 2 STLC systems, the 1 × 4 and 2 × 4 RGC-STLC systems achieve a higher diversity order. Based on the feature of the rotated Golden codewords, low complexity detection schemes for the 1 × 4 and 2 × 4 RGC-STLC systems are further proposed. Finally, the union bounds on the average symbol error probability for the 1 × 4 and 2 × 4 RGC-STLC systems are derived and shown to match the simulation results very well at high signal-to-noise ratios.

An Alternative Encoding of the Golden Code and its Low Complexity Detection

The Golden code is a full-rate full-diversity (FRFD) space-time block code. The encoder of the Golden code takes four complex symbols and generates two pairs of Golden codewords. The encoding of each Golden codeword can be regarded as superposition coding with “complex” power allocation. In this paper, we propose an alternative encoding of the Golden code which can be regarded as superposition coding with “real” power allocation. The Golden code with “complex” power allocation or “real” power allocation is hereinafter referred to as the C-Golden code or R-Golden code, respectively. The R-Golden code also preserves the FRFD property. The R-Golden code can be easily implemented in passband modulation using in-phase and quadrature components compared to the C-Golden code. An equivalent received signal model of the R-Golden code system is constructed, then used to derive a closed-form on the lower bound of the average bit error probability. We further propose a low complexity detection scheme, the fast essentially maximum-likelihood detection with adaptive signal detection subset (FE-ML-ASDS) for the R-Golden code. Both simulation and theoretical results show that both the C-Golden code and the R-Golden code achieve the same error performance. Compared to the fast essentially ML detection with signal detection subset (FE-ML-SDS), at high signal-to-noise ratios, the proposed FE-ML-ASDS further reduces detection complexity by at least 68% for the 16QAM or 64QAM R-Golden code with three receive antennas.

A Novel Index Modulation Dimension Based on Filter Domain: Filter Shapes Index Modulation

A novel domain for Index Modulation (IM) named “Filter Domain” is proposed. This new domain generalizes many existing modulations and IM domains. In addition, a novel scheme “Filter Shape Index Modulation” (FSIM) is proposed. This FSIM scheme allows a higher Spectral Efficiency (SE) gain than the time and frequency IM dimensions in Single-Input Single-Output (SISO) systems. In the FSIM system, the bit-stream is mapped using an Amplitude Phase Modulation (APM) as QAM or PSK, and an index of a filter-shape changing at the symbol rate. This filter shape, being changed at each symbol, enables a SE gain in SISO system without sacrificing any time or frequency resources. Compared to an equivalent 8QAM and 16QAM schemes and at the same SE, the FSIM with QPSK using 2 and 4 non-optimal filter shapes achieves a gain of 3.8 dB and 1.7 dB respectively at BER= 10−4, and this superiority is maintained in frequency selective fading channel compared to equivalent SISO-IM schemes. A low complexity detection scheme, approaching the maximum likelihood detector performance, is proposed along with a full performance characterization in terms of theoretical probability of filter index error and BER lower bound. Finally, FSIM can achieve better spectral and energy efficiencies when a filter bank and an ISI cancellation technique are optimally designed.

A multiple pattern complex event detection scheme based on decomposition and merge sharing for massive event streams

Quickly detecting related primitive events for multiple complex events from massive event stream usually faces with a great challenge due to their single pattern characteristic of the existing complex event detection methods. Aiming to solve the problem, a multiple pattern complex event detection scheme based on decomposition and merge sharing is proposed in this article. The achievement of this article lies that we successfully use decomposition and merge sharing technology to realize the high-efficient detection for multiple complex events from massive event streams. Specially, in our scheme, we first use decomposition sharing technology to decompose pattern expressions into multiple subexpressions, which can provide many sharing opportunities for subexpressions. We then use merge sharing technology to construct a multiple pattern complex events by merging sharing all the same prefix, suffix, or subpattern into one based on the above decomposition results. As a result, our proposed detection method in this article can effectively solve the above problem. The experimental results show that the proposed detection method in this article outperforms some general detection methods in detection model and detection algorithm in multiple pattern complex event detection as a whole.

Objective identification of potentially damaging tropical cyclones over the Western North Pacific

An impact-oriented objective windstorm identification algorithm (WiTRACK), originally developed and well established for studies on extra-tropical storms, is further developed to identify damage and loss related Tropical Cyclones (TC) over the Western North Pacific. Results based on JRA-55 reanalysis data reveal that WiTRACK is able to detect the majority of strong events with hitrates of about 77%/90%/98% for TCs of the three most severe categories. Using economic loss data for China, it is found that especially events with large losses are associated with a windstorm event identified by WiTRACK. Past loss events successfully tracked by WiTRACK are associated with substantially higher losses than those events, not identified by WiTRACK. Thus, even though less skilful than traditional detection schemes if evaluated for the totality of TC events, WiTRACK is a powerful tool to identify severe, damage and loss-related TC events which additionally benefits from its simplicity and minimal input data demands. The latter may allow to apply WiTRACK to datasets not meeting the data requirements of more complex TC detection schemes.

Efficient Method for Three Loop MMSE-SIC based Iterative MIMO Systems

Iterative decoding is one of the promising methods to improve the performance of MIMO systems. In iterative processing channel decoder and MIMO detector share the information in order to enhance the overall system performance. However, iterative processing requires a lot of computations therefore it is considered as a computationally complex approach due to complex detection schemes involving iterative processing. There are several promising detection methods that require further improvements and they can be candidates in order to practically implement iterative processing. In this paper, the propose method to improve the efficiency of three loop-based minimum mean squared errors with soft interference cancellation (MMSE-SIC) method by reducing its complexity with a single inverse operation. Simulation results are given in order to provide detail analysis of the proposed MMSE-SIC based approach for iterative detection and decoding (IDD).

Multiple Complex Symbol Golden Code

The Golden code is a full-rate full-diversity (FRFD) space-time block code (STBC). The conventional Golden code takes four complex symbols and generates two pairs of Golden codewords. Each pair of Golden codewords contains two complex symbols. In this paper, a new type of Golden code is proposed, where we extend the two complex symbols in each pair of Golden codewords into multiple complex symbols. The scheme hereinafter referred to as the multiple complex symbol Golden code (MCS-Golden code) preserves the FRFD property but achieves a diversity order of 2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</sup> N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">r</sub> compared to the conventional Golden code, where N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">r</sub> is the number of receive antennas, n, n ≥ 1, is an integer, and 2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</sup> is the number of multiple complex symbols in the MCS-Golden code system. An equivalent model of the MCS-Golden code is constructed, then used to derive a closed-form bound on the average bit error probability (ABEP) for the MCS-Golden code system. We further propose a low complexity detection scheme, sphere decoding with sorted detection subset (SD-SDS) for the MCS-Golden code. Finally, we discuss the detection complexity for the proposed SD-SDS. Both simulation and theoretical results show that the MCS-Golden code significantly improves error performance compared to the conventional Golden code. For example, at an average bit error rate of 3 × 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-6</sup> , a four complex symbol Golden code system with three receive antennas achieves approximately 2.5 dB signal-to-noise ratio (SNR) gain compared to the conventional Golden code.

Pulsed Millimeter Wave Radar for Hand Gesture Sensing and Classification

A pulsed millimeter wave radar operating at a frame rate of 144 Hz is utilized to record 2160 scattering signatures of 12 generic hand gestures. Gesture recognition is achieved by machine learning, utilizing transfer learning on a pretrained convolutional neural network. This yields excellent classification results with a validation accuracy of 99.5%, based on a 60% training versus 40% validation split. The corresponding confusion matrix is also presented, showing a high level of classification orthogonality between the tested gestures. This is the first demonstration where data from a pulsed millimeter wave radar is used for gesture recognition by machine learning. It proves that the range-time envelope representation of high frame-rate data from a pulsed radar is suitable for hand gesture recognition. Further improvements are expected for more complex detection schemes and tailored neural networks.

Golden codeword–based modulation schemes for single‐input multiple‐output systems

SummaryThe Golden code has full rate and full diversity. The Golden codeword matrix contains two pairs of super symbols. Based on one pair of super symbols, two modulation schemes, Golden codeword–based M‐ary quadrature amplitude modulation (GC‐MQAM) and component‐interleaved GC‐MQAM (CI‐GC‐MQAM), are proposed for single‐input multiple‐output (SIMO) systems. Since the complexities of the maximum likelihood detection for the proposed GC‐MQAM and CI‐GC‐MQAM are proportional to O(M2) and O(M4), respectively, low complexity detection schemes for the proposed GC‐MQAM and CI‐GC‐MQAM are further proposed. In addition, the theoretical average bit error probabilities (ABEPs) for the proposed GC‐MQAM and CI‐GC‐MQAM are derived. The derived ABEPs are validated through Monte Carlo simulations. Simulation and theoretical results show that the proposed GC‐MQAM can achieve the error performance of signal space diversity. Simulation and theoretical results further show that the proposed CI‐GC‐16QAM, ‐64QAM, and ‐256QAM with three receive antennas can achieve approximately 2.2, 2.0, and 2.1 dB gain at a bit error rate of 4 × 10−6 compared with GC‐16QAM, ‐64QAM, and ‐256QAM, respectively.

Low complexity and high performance symbol detection scheme for uplink wide‐banded cyclic prefixed filter bank multiple access system without analysis filtering

This Letter proposes a new symbol detection scheme for an uplink wide-banded cyclic prefixed filter bank multiple access system. The feature of the proposed scheme is that it eliminates the analysis filter bank processing that is commonly employed in the existing schemes. By leveraging a particular interleaving structure, the large matrix inversion operation is decomposed into parallel matrices inversions with small sizes. The benefits of the proposed scheme include lower complexity and higher spectral efficiency. In addition, the detection performance is also improved, which is verified by simulations.

Accurate tunable-Q wavelet transform based method for QRS complex detection

The patient monitoring and diagnosis using electrocardiogram (ECG) signal involve accurate QRS complex detection. However, the reliability of QRS detection is limited by the presence of variety of noises and morphologies. A high performance QRS complex detection scheme based on the tunable-Q wavelet transform (TQWT) is presented in this paper. The tunable parameters of TQWT can improve the localization of QRS when selected suitably. These parameters help to choose appropriate mother wavelet and proper sub-band of interest with fine separation from the undesired sub-bands. The method starts with TQWT based decomposition and reconstruction of the ECG signal with optimally selected input parameters and sub-bands. The correntropy envelope is computed from the resultant QRS enhanced signal which in turn assists the QRS localization. Our proposed method has yielded an average detection accuracy of 99.88%, sensitivity of 99.89% and positive productivity of 99.83% on the MIT-BIH arrhythmia database.

Reduced Complexity Detection Schemes for Golden Code Systems

The Golden code has full-rate and full-diversity. However, its applications are limited because of the very high detection complexity. The complexity of sphere decoding depends on the size of signal set, $M^{2}$ , and the depth of search. Meanwhile, the complexity of fast essentially maximum likelihood (ML) detection is still $\mathcal {O}(M^{2})$ for $M$ -ary quadrature amplitude modulation ( $M$ QAM). In this paper, we propose two reduced complexity detection schemes, fast essentially ML with detection subset and sphere decoding with detection subset. Two theoretical bounds on the average bit error probability for the Golden code with $M$ QAM are also formulated in this paper. Simulation results demonstrate that both the fast essentially ML with detection subset and sphere decoding with detection subset agree well with the formulated theoretical bounds and can achieve the error performance of the conventional fast essentially ML detector and sphere decoding.

SSD‐enhanced uncoded space‐time labeling diversity

SummarySpace‐time labeling diversity (STLD) has been shown to be an efficient technique for improving the bit error rate (BER) performance of an uncoded space‐time coded modulation system. In this paper, signal space diversity (SSD) is incorporated into the uncoded STLD system to further enhance the system BER performance. A tight closed‐form union bound on the BER of the proposed system is derived and is used to optimize the rotation angle of the SSD scheme. Simulation results are used to confirm the theoretical bound derived for the system. The results also show performance gains of approximately 2.0 dB at a BER of 10−6 and 1.6 dB at a BER 10−4 from incorporating SSD into the uncoded STLD system using 16QAM and 64QAM, respectively. Furthermore, a low complexity detection scheme based on orthogonal projection is formulated for the proposed scheme and, in comparison with the optimal maximum‐likelihood detector, is shown to result in a 56% and 95% reduction in computation complexity for the 16QAM and 64QAM versions of the proposed system, respectively.

Coherent multi-dimensional spectroscopy at optical frequencies in a single beam with optical readout.

Ultrafast coherent multi-dimensional spectroscopies form a powerful set of techniques to unravel complex processes, ranging from light-harvesting, chemical exchange in biological systems to many-body interactions in quantum-confined materials. Yet these spectroscopies remain complex to implement at the high frequencies of vibrational and electronic transitions, thereby limiting their widespread use. Here we demonstrate the feasibility of two-dimensional spectroscopy at optical frequencies in a single beam. Femtosecond optical pulses are spectrally broadened to a relevant bandwidth and subsequently shaped into phase coherent pulse trains. By suitably modulating the phases of the pulses within the beam, we show that it is possible to directly read out the relevant optical signals. This work shows that one needs neither complex beam geometries nor complex detection schemes in order to measure two-dimensional spectra at optical frequencies. Our setup provides not only a simplified experimental design over standard two-dimensional spectrometers but its optical readout also enables novel applications in microscopy.