Low Complexity Detection Algorithms Based on ADMIN for Massive MIMO

This paper proposes the alternating direction method of multipliers-based infinity-norm(ADMIN) with threshold(ADMIN-T) and with percentage(ADMIN-P) detection algorithms,which make full use of the distribution of the signal to interference plus noise ratio(SINR) for an uplink massive MIMO system.The ADMIN-T and ADMIN-P detection algorithms are improved visions of the ADMIN detection algorithm,in which an appropriate SINR threshold in the ADMIN-T detection algorithm and a certain percentage in the ADMIN-P detection algorithm are designed to reduce the overall computational complexity.The detected symbols are divided into two parts by the SINR threshold which is based on the cumulative probability density function(CDF) of SINR and a percentage,respectively.The symbols in higher SINR part are detected by MMSE.The interference of these symbols is then cancelled by successive interference cancellation(SIC).Afterwards the remaining symbols with low SINR are iteratively detected by ADMIN.The simulation results show that the ADMIIN-T and the ADMIN-P detection algorithms provide a significant performance gain compared with some recently proposed detection algorithms.In addition,the computational complexity of ADMIN-T and ADMIN-P are significantly reduced.Furthermore,in the case of same number of transceiver antennas,the proposed algorithms have a higher performance compared with the case of asymmetric transceiver antennas.

Low complexity method for spreading sequence estimation of DSSS signal in non-cooperative communication systems

It is a necessary step to estimate the spreading sequence of direct sequence spread spectrum （DSSS） signal for blind despreading and demodulation in non-cooperative communications. Two innovative and effective detection statistics are proposed to implement the synchronization and spreading sequence estimation procedure. The proposed algorithm also has a low computational complexity with only linear additions and modifications. Theoretical analysis and simulation results show that the algorithm performs quite well in low SNR environment, and is much better than all the existing typical algorithms with a comprehensive consideration both in performance and computational complexity.

Low complexity DOA estimation for massive UCA with single snapshot

In this paper, a low complexity direction of arrival(DOA) estimation method for massive uniform circular array(UCA) with single snapshot is proposed.Firstly, the coarse DOAs are estimated by finding the peaks from the circular convolution between a fixed coefficient vector and the received data vector.Thereafter, in order to refine coarse DOA estimates, we reconstruct the direction matrix based on the coarse DOA estimations and take the first order Taylor expansion with DOA estimation offsets into account.Finally, the refined estimations are obtained by compensating the offsets, which are obtained via least squares(LS) without any complex searches.In addition, the refinement can be iteratively implemented to enhance the estimation results.Compared to the offset search method, the proposed method achieves a better estimation performance while requiring lower complexity.Numerical simulations are presented to demonstrate the effectiveness of the proposed method.

Low complexity SEU mitigation technique for SRAM-based FPGAs

An internal single event upset（SEU）mitigation technique is proposed,which reads back the configuration frames from the static random access memory（SRAM）-based field programmable gate array（FPGA）through an internal port and compares them with those stored in the radiationhardened memory to detect and correct SEUs.Triple modular redundancy（TMR）,which triplicates the circuit of the technique and uses majority voters to isolate any single upset within it,is used to enhance the reliability.Performance analysis shows that the proposed technique can satisfy the requirement of ordinary aerospace missions with less power dissipation,size and weight.The fault injection experiment validates that the proposed technique is capable of correcting most errors to protect spaceborne facilities from SEUs.

Low Complexity Encoder with Multilabel Classification and Image Captioning Model

Due to the advanced development in the multimedia-on-demandtraffic in different forms of audio, video, and images, has extremely movedon the vision of the Internet of Things (IoT) from scalar to Internet ofMultimedia Things (IoMT). Since Unmanned Aerial Vehicles (UAVs) generates a massive quantity of the multimedia data, it becomes a part of IoMT,which are commonly employed in diverse application areas, especially forcapturing remote sensing (RS) images. At the same time, the interpretationof the captured RS image also plays a crucial issue, which can be addressedby the multi-label classification and Computational Linguistics based imagecaptioning techniques. To achieve this, this paper presents an efficient lowcomplexity encoding technique with multi-label classification and image captioning for UAV based RS images. The presented model primarily involves thelow complexity encoder using the Neighborhood Correlation Sequence (NCS)with a burrows wheeler transform (BWT) technique called LCE-BWT forencoding the RS images captured by the UAV. The application of NCS greatlyreduces the computation complexity and requires fewer resources for imagetransmission. Secondly, deep learning (DL) based shallow convolutional neural network for RS image classification (SCNN-RSIC) technique is presentedto determine the multiple class labels of the RS image, shows the novelty ofthe work. Finally, the Computational Linguistics based Bidirectional EncoderRepresentations from Transformers (BERT) technique is applied for imagecaptioning, to provide a proficient textual description of the RS image. Theperformance of the presented technique is tested using the UCM dataset. Thesimulation outcome implied that the presented model has obtained effectivecompression performance, reconstructed image quality, classification results,and image captioning outcome.

Low complexity domains, condensates, and stem cell pluripotency

Biological reactions require self-assembly of factors in the complex cellular milieu.Recent evidence indicates that intrinsically disordered,low-complexity sequence domains(LCDs)found in regulatory factors mediate diverse cellular processes from gene expression to DNA repair to signal transduction,by enriching specific biomolecules in membraneless compartments or hubs that may undergo liquidliquid phase separation(LLPS).In this review,we discuss how embryonic stem cells take advantage of LCD-driven interactions to promote cell-specific transcription,DNA damage response,and DNA repair.We propose that LCDmediated interactions play key roles in stem cell maintenance and safeguarding genome integrity.

IDMA based MAI mitigation scheme with low complexity and low latency

High complexity and high latency are key problems for multiuser detection （MUD） to be applied to a mobile station in cellular networks. To tackle these problems, an interleave division multiple access （IDMA） based multiple access scheme, grouped spread IDMA （GSIDMA）, is proposed. In a GSIDMA system, lower complexity and latency for mobile stations can be achieved by appropriately dividing active users into different groups. The system model of GSIDMA is constructed and followed by analysing on its system capacity, complexity and latency, and bit error rate （BER） performance. The extrinsic information transfer （EXIT） chart is used to analyze the convergence behavior of the iteration process. The grouping method and interleavers-reuse issue for GSIDMA are also discussed preliminarily. The analyses and simulation results indicate that the complexity and latency of the proposed scheme are much lower than those of IDMA, whereas its BER performance is close to the latter. The properties of low complexity and low latency make it more feasible for the practical implementation.

A Low Complexity VCS Method for PAPR Reduction in Multicarrier Code Division Multiple Access

This paper investigates a peak to average power ratio （PAPR） reduction method in multicarrier code division multiple access （MC-CDMA） system. Variable code sets （VCS）, a spreading codes selection scheme, can improve the PAPR property of the MC-CDMA signals, but this technique requires an exhaustive search over the combinations of spreading code sets. It is observed that when the number of active users increases, the search complexity will increase exponentially. Based on this fact, we propose a low complexity VCS （LC-VCS） method to reduce the computational complexity. The basic idea of LC-VCS is to derive new signals using the relationship between candidature signals. Simulation results show that the proposed approach can reduce PAPR with lower comtational pucomplexity. In addition, it can be blindly received without any side information.

Low complexity asymptotically unitary algorithm for hybrid beamforming in mmWave communication systems

In millimeter wave （mmWave） massive multiple-input multiple-output （MIMO） systems, because of the high hardware cost and high power consumption, the traditional fully digital beamforming （DBF） cannot be implemented easily. Meanwhile, analog beamforming which is implemented with phase shifters has high availability but suffers poor performance. Considering the advantages of above two, a potential solution is to design an appropriate hybrid analog and digital beamforming structure, where the available iterative optimization algorithm can get performance close to fully digital processing, but solving this sparse optimization problem faces with a high computational complexity. The key challenge of seeking out hybrid beamforming （HBF） matrices lies in leveraging the trade-off between the spectral efficiency performance and the computational complexity. In this paper, we propose an asymptotically unitary hybrid precoding （AUHP） algorithm based on antenna array response （AAR） properties to solve the HBF optimization problem. Firstly, we get the optimal orthogonal analog and digital beamforming matrices relying on the channel＇s path gain in absolute value by taking into account that the AAR matrices are asymptotically unitary. Then, an improved simultaneously orthogonal matching pursuit （SOMP） algorithm based on recursion is adopted to refine the hybrid combining. Numerical results demonstrate that our proposed AUHP algorithm enables a lower computational complexity with negligible spectral efficiency performance degradation.

Low complexity detection algorithm based on optimized Neumann series for massive MIMO system

An optimized Neumann series（NS） approximation is described based on Frobenius matrix decomposition, this method aims to reduce the high complexity, which caused by the large matrix inversion of detection algorithm in the massive multiple input multiple output（MIMO） system. The large matrix in the inversion is decomposed into the sum of the hollow matrix and a Frobenius matrix, and the Frobenius matrix has the diagonal elements and the first column of the large matrix. In order to ensure the detection performance approach to minimum mean square error（MMSE） algorithm, the first three terms of the series approximation are needed, which results in high complexity as O（K;）, where K is the number of users. This paper further optimize the third term of the series approximation to reduce the computational complexity from O（K;） to O（K;）. The computational complexity analysis and simulation results show that the performance of proposed algorithm can approach to MMSE algorithm with low complexity O（K;）.

A novel low-complexity power allocation algorithm based on the NOMA system in a low-speed environment

For future wireless communication systems,Power Domain Non-Orthogonal Multiple Access(PD-NOMA)using an advanced receiver has been considered as a promising radio access technology candidate.Power allocation plays an important role in the PD-NOMA system because it considerably affects the total throughput and Geometric Mean User Throughput(GMUT)performance.However,most existing studies have not completely accounted for the computational complexity of the power allocation process when the User Terminals(UTs)move in a slow fading channel environment.To resolve such problems,a power allocation method is proposed to considerably reduce the search space of a Full Search Power(FSP)allocation algorithm.The initial power reallocation coefficients will be set to start with former optimal values by the proposed Lemma before searching for optimal power reallocation coefficients based on total throughput performance.Step size and correction granularity will be adjusted within a much narrower power search range while invalid power combinations may be reasonably discarded during the search process.The simulation results show that the proposed power reallocation scheme can greatly reduce computational complexity while the total throughput and GMUT performance loss are not greater than 1.5%compared with the FSP algorithm.

Low-complexity model predictive control of a four-level active neutral point clamped inverter without weighting factors

The four-level active neutral point clamped(ANPC)inverter has become increasingly widely used in the renewable energy indus-try since it offers one more voltage level without increasing the total number of active switches compared to the three-level ANPC inverter.The model predictive current control(MPCC)is a promising control method for multi-level inverters.However,the conven-tional MPCC suffers from high computational complexity and tedious weighting factor tuning in multi-level inverter applications.A low-complexity MPCC without weighting factors for a four-level ANPC inverter is proposed in this paper.The computational burden and voltage vector candidate set are reduced according to the relationship between voltage vector and neutral point voltage balance.The proposed MPCC shows excellent steady-state and dynamics performances while ensuring the neutral point voltage balancing.The efficacy of the proposed MPCC is verified by simulation and experimental results.

SPECTRAL VARIATION AND CHARACTERISTICS OF LOW VALENCY RARE EARTH IONS IN COMPLEX OXIDESⅢ.EFFECT OF THE CRYSTAL ENVIRONMENT AND CHEMICAL FACTORS ON LUMINESCENCE PROPERTIES OF EUROPIUM (Ⅱ) ION

In this paper,the influence of crystal-field on the Luminescence properties of Eu^(2+) in complex oxides are studied theoretically by using purely electrostatic model,the dependence of the 4f^65d levels on Eu-O bond distance is given.Quantum chemistry calculation shows that the splitting extent of 4f^65d energy band in cubic or in octahedral fields will be inversely proportional to R^5,where R is the distance of Eu^(2+) to oxygen ligand.The value of R affects slightly the location of the centre of 4f^65d energy band.According to the exper- imental spectrum data,we have discussed the influence of the host chemical composition,the replaced sites of Eu^(2+) and degree of covalency of Eu-O bond on luminescence properties of Eu^(2+).Some regularity of fluorescence spectrum was observed. In alkali-alkaline earth-phosphates,the splitting extent of 4f^65d band (△E) becomes smaller as the Eu-O bond distance (R) increases.In Na_(3-x)(PO_4)_(1-x)(SO_4)_x and Na_(2-x)CaSi_(1-x)P_xO_4 hosts,d-d emission peak of Eu^(2+) will shift to shorter wavelength with the increase of x's value. The crystal structure data show that Eu^(2+) in K_2Mg_2(SO_4)_3 is affected more strongly by crystal-field and covalancy than in KMgF_3,so K_2Mg_2(SO_4)_3:Eu^(2+) emits blue light (E_(em)~m=400nm) and KMgF_3:Eu^(2+) produces ultraviolet fluorescence.

Low-cost,large-coverage,and high-flexibility coherent PON for next-generation access networks:advances,challenges,and prospects[Invited]

Increasing bandwidth requirements have posed significant challenges for traditional access networks.It is difficult for intensity modulation/direct detection to meet the power budget and flexibility requirements of the next-generation passive optical network(PON)at 100G and beyond considering the new requirements.This is driving researchers to develop novel optical access technologies.Low-cost,wide-coverage,and high-flexibility coherent PON is emerging as a strong contender in the competition.In this article,we will review technologies that reduce the complexity of coherent PON(CPON),enabling it to meet the commercial requirements.Also,advanced algorithms and architectures that can enhance system coverage and flexibility are also discussed.

Tracking multiple targets in MIMO radar via adaptive asymmetric joint diagonalization with deflation

In view of the low performance of adaptive asymmetric joint diagonalization（AAJD）, especially its failure in tracking high maneuvering targets, an adaptive asymmetric joint diagonalization with deflation（AAJDd） algorithm is proposed. The AAJDd algorithm improves performance by estimating the direction of departure（DOD） and direction of arrival（DOA） directly, avoiding the reuse of the previous moment information in the AAJD algorithm.On this basis, the idea of sequential estimation of the principal component is introduced to turn the matrix operation into a constant operation, reducing the amount of computation and speeding up the convergence. Meanwhile, the eigenvalue is obtained, which can be used to estimate the number of targets. Then, the estimation of signal parameters via rotational invariance technique（ESPRIT） algorithm is improved to realize the automatic matching and association of DOD and DOA. The simulation results show that the AAJDd algorithm has higher tracking performance than the AAJD algorithm, especially when the high maneuvering target is tracked. The efficiency of the proposed method is verified.

Efficient multiuser detector based on box-constrained deregularization and its FPGA design

Multiuser detection can be described as a quadratic optimization problem with binary constraint. Many techniques are available to find approximate solution to this problem. These tech- niques can be characterized in terms of complexity and detection performance. The ＂efficient frontier＂ of known techniques include the decision-feedback, branch-and-bound and probabilistic data association detectors. The presented iterative multiuser detection technique is based on joint deregularized and box-constrained so- lution to quadratic optimization with iterations similar to that used in the nonstationary Tikhonov iterated algorithm. The deregulari- zation maximizes the energy of the solution, this is opposite to the Tikhonov regularization where the energy is minimized. However, combined with box-constraints, the deregularization forces the solution to be close to the binary set. We further exploit the box- constrained dichotomous coordinate descent （DCD） algorithm and adapt it to the nonstationary iterative Tikhonov regularization to present an efficient detector. As a result, the worst-case and aver- age complexity are reduced down to K28 and K2~ floating point operation per second, respectively. The development improves the ＂efficient frontier＂ in multiuser detection, which is illustrated by simulation results. Finally, a field programmable gate array （FPGA） design of the detector is presented. The detection performance obtained from the fixed-point FPGA implementation shows a good match to the floating-point implementation.

Grouping pilot allocation scheme based on matching algorithm in massive MIMO system

Pilot allocation is one of the effective means to reduce pilot pollution in massive multiple-input multiple-output(MIMO)systems.The goal of this paper is to improve the uplink achievable sum rates of strong users,and ensure the quality of service(QoS)requirements of weak users at the same time,so that the sum rates of system can be improved.Combining with the technical advantage of pilot grouping,a low complexity pilot allocation scheme based on matching algorithm is proposed,which divides the users in the target cell into weak user group and strong user group,and adopts the minimum-maximum matching method to allocate pilots in weak user group.Through the introduction of Hungarian algorithm,a pilot allocation method is designed to ensure the fairness of the strong users.The simulation results show that,compared with the smart pilot allocation scheme,the pilot allocation scheme based on Hungarian algorithm,the pilot allocation scheme based on user grouping and the random pilot allocation scheme,the system performance of the proposed scheme has been effectively improved.

A Secure Visual Secret Sharing Scheme with Authentication Based on QR Code

With the rise of the Internet of Things(IoT),various devices in life and industry are closely linked.Because of its high payload,stable error correction capability,and convenience in reading and writing,Quick Response(QR)code has been widely researched in IoT.However,the security of privacy data in IoT is also a very important issue.At the same time,because IoT is developing towards low-power devices in order to be applied to more fields,the technology protecting the security of private needs to have the characteristics of low computational complexity.Visual Secret Sharing(VSS),with its features of safety and low computational cost,can fully meet the requirements of communication security in IoT.Therefore,a VSS scheme with QR code(VSS-QR)was proposed and has been applied to some extent.In VSS-QR,the secret is shared into a series of shares.These shares are usually common QR codes,which cannot cause the attention of the attacker.However,if there is dishonesty among participants,the secret cannot be recovered,which will lead to VSS-QR cannot be widely used due to its inadequate security.In this paper,we propose a visual secret sharing scheme with authentication based on QR code(VSSA-QR).Both the reconstructed secret QR code and shares can be verified whether they are forged by attackers.The above-mentioned operations conveniently are performed on low-power QR scanning devices.Not only does the proposed scheme prevent some dishonest participants or attackers from cheating,but also prevent all participants from conspiring.In addition,the payload is the QR code itself,which is higher than other schemes.Theoretical analysis and experiments prove that the proposed scheme is effective.

New Near Shannon Limit Codes: Zigzag Codes and Concatenated Zigzag Codes

This paper introduces a family of error correcting codes called zigzag codes. A zigzag code is described by a highly structured zigzag graph. Due to the structural properties of the graph, very low complexity soft in, soft out decoding rules can be implemented. We present a decoding rule, based on the Max Log APP(MLA) formulation, which requires a total of only 20 addition equivalent operations per information bit per iteration. Simulation of a rate 1/2 concatenated zigzag code with four constituent encoders with interleaver length 65536 yields a bit error rate (BER) and of 10 5 at 0.9 dB and 1.4 dB away from the Shannon limit by optimal (APP) and low cost sub optimal (MLA) decoders, respectively.

A low power 2.4 GHz transceiver for ZigBee applications

This paper presents a low power 2.4 GHz transceiver for ZigBee applications.This transceiver adopts low power system architecture with a low-IF receiver and a direct-conversion transmitter.The receiver consists of a new low noise amplifier（LNA） with a noise cancellation function,a new inverter-based variable gain complex filter （VGCF） for image rejection,a passive quadrature mixer,and a decibel linear programmable gain amplifier（PGA）. The transmitter adopts a quadrature mixer and a class-B mode variable gain power amplifier（PA） to reduce power consumption.This transceiver is implemented in 0.18μm CMOS technology.The receiver achieves—95 dBm of sensitivity,28 dBc of image rejection,and -8 dBm of third-order input intercept point（IIP3）.The transmitter can deliver a maximum of＋3 dBm output power with PA efficiency of 30%.The whole chip area is less than 4.32 mm^2. It only consumes 12.63 mW in receiving mode and 14.22 mW in transmitting mode,respectively.