Proposed Mapping Scheme Research Articles

Co-design of SLC/MLC FeFET-based highly error-tolerant low-power CiM and strong lottery ticket hypothesis-based algorithm

This study co-designs single-level cell (SLC) mask and multilevel cell (MLC) weight twin FeFET devices and a strong lottery ticket hypothesis (SLTH)-based neural network (NN) algorithm to achieve highly error-tolerant low-power Computation-in-Memory (CiM). The SLC mask FeFET masks or transfers the NN weight stored in the MLC weight FeFET, and the masked NN weight reduces the CiM power consumption. The proposed SLC mask FeFETs, which are trained, and MLC weight FeFETs, in which V TH are uniformly randomized, achieve 87% inference accuracy against 10-year data retention and read disturb. The SLC mask FeFETs show 86% inference accuracy even at 2000 endurance cycles. In addition, shared-bottom-select-gate (BSG) SLTH CiM and common-mask SLTH CiM for the NN convolutional layer are proposed to reduce the CiM area by sharing BSG and mask FeFET. Moreover, NN weight mapping schemes for SLTH CiM are proposed. The proposed mapping schemes show a tradeoff between inference accuracy and CiM area. One of the schemes reduces the CiM area by 45% with a 9.1% accuracy loss.

Triaxial rotor in the O(6) limit of the interacting boson model

A mapping from the triaxial rotor Hamiltonian to that of the O(6) limit in the interacting boson model (IBM) is established, which is achieved by introducing the symmetry-conserving high-order interactional terms The validity of the proposed mapping scheme is further examined for the cases with γ = 0 and γ = π/6, respectively. It is shown that the rotor model results can be well reproduced in its O(6) image especially for the low-spin states. It thus provides an alternative way to understand the triaxiality in the finite-N systems and additional insight into the O(6) IBM theory.

SLM based Circular (6, 2) mapping scheme with improved SER performance for PAPR reduction in OCDM without side information

Abstract Like OFDM, OCDM signal also suffers from high PAPR. SLM is an attractive PAPR reduction method but it needs to transmit the information regarding phase sequence i.e. SI to the receiver, which results in reduction in SE and data rate. Various SLM based SI free and SI embedding schemes are available in the literature. In this paper, different possible quaternary to 8-QAM mapping schemes for SI free SLM based PAPR reduction in OCDM system are discussed. Moreover, a new mapping scheme to eliminate the SI requirement has also been presented in this manuscript for SLM based PAPR reduction in OCDM system. Proposed Circular (6, 2) mapping scheme doesn’t require SI at the receiving end which results in increase in SE and data rate as compared to standard SLM technique. Random sequence with phase factors {1, −1} is used to generate the phase sequences for the proposed mapping scheme. Also, the analytical expression for SER of Circular (6, 2) mapping scheme over AWGN channel is derived. We have also evaluated the mathematical expression for SER of other possible quaternary to 8-QAM mapping schemes. Computer simulation using MATLAB are also carried out to investigate the performance of all these mapping schemes in terms of PAPR reduction performance as well as SER performance over AWGN and multipath Rayleigh fading channel. Proposed scheme achieves the same PAPR reduction and improved SER performance w.r.t. other six schemes taken into consideration.

Index Modulation OFDM Systems with Direct Pattern of Subcarrier Activation

OFDM-IM is a spatial modulation technique applied to OFDM's block subcarriers, resulting in a modified version of OFDM. Compared to traditional OFDM, OFDM-IM boasts several benefits, such as enhanced bit-error rate (BER) performance and power efficiency. When working with OFDM-IM, the specification of subcarrier-activation-patterns (SAPs) is done by utilizing either look-up tables (LUTs) or a combinatorial approach to conform with data. However, the data-to-SAP mapping methods of both suffer from increased complexity as the number of subcarriers expands. The paper proposes a direct data-to-SAP mapping that eliminates the need for any type of look-up tables. Through the presented analysis and computer simulation results, it is demonstrated that the OFDM-IM system utilizing the proposed mapping scheme outperforms equivalent traditional OFDM-IM systems in both complexity and bit error rate (BER) performance.

3D Compressed Spectrum Mapping With Sampling Locations Optimization in Spectrum-Heterogeneous Environment

Spectrum mapping has emerged as an important problem in wireless communications, which generates a spectrum map for the spectrum resource analysis and management. Given the constrained transceiver volume and the limited energy consumption, how to effectively reconstruct the spectrum situation by the limited sampling data is a pressing challenge for spectrum mapping. In this paper, by exploiting the sparse nature of spectrum situation, we firstly attempt to solve the three-dimensional (3D) compressed spectrum mapping problem in the way of compressed sensing. Then, we develop a quadrature and right-triangular (QR) pivoting based measurement matrix optimization algorithm. By iteratively selecting new dominant sampling locations, it promotes the recovery accuracy compared to random measurement. After that, we propose a 3D spatial subspace based orthogonal matching pursuit (OMP) algorithm to recover spectrum situation for 3D compressed spectrum mapping. Finally, simulations are presented to show the comparisons in terms of localization, source signal strength recovery, recovery success rate and situation recovery. Results show our proposed 3D spectrum mapping scheme not only effectively reduces the sampling number, but also achieves a high level of spectrum mapping accuracy.

UAV-Assisted Three-Dimensional Spectrum Mapping Driven by Spectrum Data and Channel Model

As the number of civil aerial vehicles increase explosively, spectrum scarcity and security become an increasingly challenge in both the airspace and terrestrial space. To address this difficulty, this paper presents an unmanned aerial vehicle-assisted (UAV-assisted) spectrum mapping system and a spectrum data reconstruction algorithm driven by spectrum data and channel model are proposed. The reconstruction algorithm, which includes a model-driven spectrum data inference method and a spectrum data completion method with uniformity decision mechanism, can reconstruct limited and incomplete spectrum data to a three-dimensional (3D) spectrum map. As a result, spectrum scarcity and security can be achieved. Spectrum mapping is a symmetry-based digital twin technology. By employing an uniformity decision mechanism, the proposed completion method can effectively interpolate spatial data even when the collected data are unevenly distributed. The effectiveness of the proposed mapping scheme is evaluated by comparing its results with the ray-tracing simulated data of the campus scenario. Simulation results show that the proposed reconstruction algorithm outperforms the classical inverse distance weighted (IDW) interpolation method and the tensor completion method by about 12.5% and 92.3%, respectively, in terms of reconstruction accuracy when the collected spectrum data are regularly missing, unevenly distributed and limited.

An Effective Mapping Scheme for Visible Light Communication With Smartphone Camera

In this paper, an effective mapping scheme is proposed and experimentally demonstrated for visible light communication (VLC) based on light emitting diode (LED) and smartphone camera. At the transmitter, parking information is mapped to a number of bits using the proposed mapping scheme. Based on the parking information, the parking position can be achieved quickly, and the extra processing time is not required for data reception. In addition, the BER performance of the proposed mapping scheme under different distances and speeds are investigated. Experimental results show that optimum receiving distance range is from 0.5 to 1.0 m when exposure time is 1/12800s and international standard organization (ISO) is 160. Moreover, the bit error rate (BER) performance is not affected by low velocity range of 0.5-0.9 m/s under same conditions. And the transmission time of data takes only 1/15s using the proposed scheme, which is much less than that of traditional picture. As the picture resolution is 360×180, its transmission of data is 225 times more than that of using the proposed scheme.

Development and evaluation of a new merged sea surface height product from multi-satellite altimeters

Satellite altimetry data has been a backbone of global oceanography research since the early 1990s. Because a satellite altimeter measures sea surface height (SSH) at the nadir point, it produces a one-dimensional profile of SSH. Along the track, an altimeter provides SSH sampling at an interval of about 7 km. However, the distance between adjacent tracks is larger than 100 km, and satellites have repeat times of 10–30 d. These characteristics limit the usefulness of altimetry data from a single satellite for scientific analysis of the space-time structure of ocean circulation. During the past two decades, there have usually been three to four altimeters in orbit at any one time. Mapping along-track measurements from multiple altimeters onto a uniform grid has been a major research theme. A popular merged data product, known as AVISO, has been developed and extensively applied to a wide variety of ocean research. One of key properties of a merged data product is its effective resolution. The effective resolution represents the minimum spatial size of an eddy or other mesoscale circulation that the data product can resolve. The AVISO data product has an effective resolution of 300 km in equatorial regions to 100 km in high latitudes. Nowadays, there are more than five satellite altimeters in orbit, including the Chinese HY-2A that was launched in 2011, and thus the density of the tracks has been much improved. However, the effective resolution of the AVISO data product has not increased accordingly. Effective resolution of mapped data is closely related to the background error correlation coefficient scale in the mapping scheme. The effective resolution is no more than twice the correlation coefficient scale even when the amount of satellite altimeter is more than 5. As the background fields contains the correct large scale information, the meso-scale or small-scale information in the background error will play a dominant role and the background error correlation coefficient scale becomes even smaller. Therefore, The option of background determines the effective resolution of mapped data. The above theory is the basement of our new proposed mapping scheme, which effectively improved the effective resolution. Another key technique is how to deal with the observation errors: to reduce time-smoothing by introducing evolution errors in observation errors and effectively mapping multi-mission satellite altimeters from different times. In this study, a new mapping system has been developed, aiming to maximize the effective resolution of the mapped data product. The formulation is based on a variational method and optimal estimation theory. The system has been applied to the South China Sea region. The product uses a regular grid with spacing of 0.08°, in comparison to 0.25° for AVISO. The product merged data from five satellites, Sentinel-3A, Jason-3, Cryosat-2, Saral/AltiKa and HY-2A. Systematic evaluations show that this new product has an effective resolution of 125 km, whereas the AVISO data product an effective resolution of 240 km for the same region. The accuracy is also significantly improved. The new proposed mapping scheme is important in the application of satellite altimeters on the study of meso-scale ocean eddies. In addition, the option of background fields and the processing method of observation error are strictly general and can be used in other schemes of high-resolution data mapping.

A Lifetime Reliability-Constrained Runtime Mapping for Throughput Optimization in Many-Core Systems

Due to technology scaling, lifetime reliability is becoming one of the major design constraints in the performance optimization of future many-core systems. Given a lifetime reliability constraint, the existing lifetime-constrained runtime mapping schemes often lead to low throughput because of the requirement to map all applications to compact regions. In this paper, we propose a runtime application mapping scheme that exploits a borrowing strategy to improve the throughput of many-core systems given a lifetime constraint. First, we propose using different strategies for mapping communication-intensive applications and computation-intensive applications. The lifetime reliability constraint can be relaxed in the local time scale when the communication requirement is high. The throughput is improved because the communication distance of communication-intensive applications is optimized while the waiting time of computation-intensive application is reduced. Then, we propose a method to effectively classify applications depending on the communication-to-computation ratio. A dynamic threshold is determined according to the current locations of available cores. Finally, we propose an improved neighborhood allocation scheme to reduce the communication cost in the task mapping. The experimental results show that compared to the state-of-the-art lifetime-constrained mapping, the proposed mapping scheme improves the throughput of many-core systems by 26% on average for synthetic task graphs and by 20% on average for realistic task graphs while the lifetime reliability is maintained within a constraint.

A Joint Bit-to-Symbol Mapping Scheme in Cooperative Spatial Modulation System

In this paper, a joint bit-to-symbol mapping scheme in a cooperative spatial modulation (SM) system with amplify-and-forward (AF) and decode-and-forward (DF) protocols is proposed to improve the system performance, such as the transmission bit rate and the average bit error rate (BER). The system model and the corresponding signal processing with maximum likelihood (ML) detection for the cooperative SM system without a direct link are presented first. With the consideration of both the cosine similarity among the relay nodes and the channel state information (CSI) of each transmit antenna, the bit-to-symbol mapping scheme that jointly selects the cooperative relay node, the transmit antenna, and the signal constellation is proposed. Then, its average BER performance is derived based on the moment generation function (MGF). For the proposed mapping scheme, a detailed realization process has been given as an example. Furthermore, the simulation results verify that the proposed mapping scheme effectively increases the system transmission bit rate and also improves the system average BER performance compared with the traditional natural mapping scheme.

Octagonal Mapping Scheme for Panoramic Video Encoding

As modern video coding standards are not designed to code panoramic videos, the pixels on the sphere need to be sampled onto a rectangle, and this process is called mapping. The mapping schemes generally include two steps: sampling points on sphere and arranging points into one compression-friendly rectangular frame. Traditional mapping schemes including equirectangular and cubic mapping have high sampling density on some sampling areas, which result in wasted pixels. In this letter, we propose a novel octagonal mapping scheme, which can decrease the oversampling areas and arrange points into an octagon. The octagon can be reshaped and rearranged into a rectangle before encoding. Experimental results demonstrate that the proposed mapping scheme saves more bitrates, compared to the existing mapping schemes.

Deriving Humanlike Arm Hand System Poses

Robots are rapidly becoming part of our lives, coexisting, interacting, and collaborating with humans in dynamic and unstructured environments. Mapping of human to robot motion has become increasingly important, as human demonstrations are employed in order to “teach” robots how to execute tasks both efficiently and anthropomorphically. Previous mapping approaches utilized complex analytical or numerical methods for the computation of the robot inverse kinematics (IK), without considering the humanlikeness of robot motion. The scope of this work is to synthesize humanlike robot trajectories for robot arm-hand systems with arbitrary kinematics, formulating a constrained optimization scheme with minimal design complexity and specifications (only the robot forward kinematics (FK) are used). In so doing, we capture the actual human arm-hand kinematics, and we employ specific metrics of anthropomorphism, deriving humanlike poses and trajectories for various arm-hand systems (e.g., even for redundant or hyper-redundant robot arms and multifingered robot hands). The proposed mapping scheme exhibits the following characteristics: (1) it achieves an efficient execution of specific human-imposed goals in task-space, and (2) it optimizes anthropomorphism of robot poses, minimizing the structural dissimilarity/distance between the human and the robot arm-hand systems.

Link-Adaptive Mapper Designs for Space-Shift-Keying-Modulated MIMO Systems

This work focuses on the design and analysis of link-adaptive bits-to-antenna-indexes mapping for closed-loop space-shift keying (SSK)-modulated multiple-input multiple-output (MIMO) systems. With the aim of achieving a lower bit error rate (BER), optimal mappers are designed under different transmission conditions. Assuming that perfect channel state information (CSI) is available at the transceivers, an original binary switch algorithm (OBSA) is proposed. For the case in which there is no CSI at the transmitter and the feedback channel is bandwidth limited, a restricted binary switch algorithm (RBSA)-based mapping design is proposed. Both of the proposed algorithms can bring considerable performance gains but are of high computational complexity if there are a large number of transmit antennas. To overcome this, algorithms with reduced computational complexity are proposed and investigated, which are named partial OBSA and partial RBSA. The performance improvement brought by all of the proposed mapping schemes in terms of BER performance enhancement and signal-to-noise ratio (SNR) gain in a high-SNR regime is theoretically given. Simulations are done to validate the theoretical analysis, and results show that the proposed schemes can improve BER performance considerably in a wide range of SNR regimes. In addition, all of the proposed mapping schemes can cowork with those existing transmit processing techniques and bring additional performance gain without incurring any extra cost on physical components (e.g., additional phase shifters or power amplifiers). All these make the proposed mapping schemes promising choices for the link-adaptive design of closed-loop SSK MIMO systems.

An Efficient Bit-Level Lossless Grayscale Image Compression Based on Adaptive Source Mapping

Image compression is an essential technique for saving time and storage space for the gigantic amount of data generated by images. This paper introduces an adaptive source-mapping scheme that greatly improves bit-level lossless grayscale image compression. In the proposed mapping scheme, the frequency of occurrence of each symbol in the original image is computed. According to their corresponding frequencies, these symbols are sorted in descending order. Based on this order, each symbol is replaced by an 8-bit weighted fixed-length code. This replacement will generate an equivalent binary source with an increased length of successive identical symbols (0s or 1s). Different experiments using Lempel-Ziv lossless image compression algorithms have been conducted on the generated binary source. Results show that the newly proposed mapping scheme achieves some dramatic improvements in regards to compression ratios.

Precorrected-FFT Method on Graphics Processing Units

A detailed scheme of mapping Precorrected-FFT (P-FFT) method to graphics processing units (GPUs) is presented through the solution of electric field integral equation (EFIE) for modeling the scattering from 3-D perfectly electric conducting (PEC) object. The procedure of the P-FFT method is analyzed to identify its computationally intensive spots, which are to be implemented on GPU. Based on this, a mapping scheme is proposed. Moreover, the optimization of the GPU code is discussed to demonstrate its importance in achieving better performance. The optimization scheme is broken down into several stages to show the gradual performance improvement in each stage. Accurate numerical results obtained using the GPU code validate the proposed mapping and optimization scheme. The performance of GPU code is benchmarked and the acceleration ratio achieved is more than 50.

New Multi-Dimensional Mapping for MIMO-BICM-ID Systems

In this paper, Bit Interleaved Coded Modulation systems with Iterative Decoding (BICM-ID) for Multiple Input Multiple Output (MIMO) channel are considered. Based on minimizing pair-wise error probability, a design criterion is proposed to find the optimal multi-dimensional constellation mapping for a MIMO-BICM-ID system. Using the design criterion and employing the Binary Switching Algorithm, some optimal constellation mappings are found for 2-dimensional and 3-dimensional cases. Mutual information is utilized to evaluate the proposed constellation mappings. It is illustrated that the proposed mapping schemes outperform conventional ones significantly at high Signal to Noise Ratio (SNR) over fading channels.

Genetic-based minimum classification error mapping for accurate identifying Peer-to-Peer applications in the internet traffic

In this paper, we propose a hybrid approach using genetic algorithm and neural networks to classify Peer-to-Peer (P2P) traffic in IP networks. We first compute the minimum classification error (MCE) matrix using genetic algorithm. The MCE matrix is then used during the pre-processing step to map the original dataset into a new space. The mapped data set is then fed to three different classifiers: distance-based, K-Nearest Neighbors, and neural networks classifiers. We measure three different indexes, namely mutual information, Dunn, and SD to evaluate the extent of separation of the data points before and after mapping is performed. The experimental results demonstrate that with the proposed mapping scheme we achieve, on average, 8% higher accuracy in classification of the P2P traffic compare to the previous solutions. Moreover, the genetic-based MCE matrix increases the classification accuracy more than what the basic MCE does.

An efficient uplink mapping scheme for VoIP services in the IEEE 802.16e OFDMA system

Informing subscriber stations about new resource assignments creates a signaling overhead that influences the system throughput. In particular, the performance of voice over Internet protocol (VoIP) services is seriously affected by the signaling overhead because the VoIP packet size is small. In this paper, we address the problem of allocation representation of VoIP packets and propose an efficient uplink mapping scheme that decreases the size of the allocation map in the IEEE 802.16e OFDMA system. We also develop analytical and simulation models to evaluate the performance of the VoIP services. The results show that the signaling overhead is greatly decreased when the proposed mapping scheme is used.

Mapping Speech Spectra from Throat Microphone to Close-Speaking Microphone: A Neural Network Approach

Speech recorded from a throat microphone is robust to the surrounding noise, but sounds unnatural unlike the speech recorded from a close-speaking microphone. This paper addresses the issue of improving the perceptual quality of the throat microphone speech by mapping the speech spectra from the throat microphone to the close-speaking microphone. A neural network model is used to capture the speaker-dependent functional relationship between the feature vectors (cepstral coefficients) of the two speech signals. A method is proposed to ensure the stability of the all-pole synthesis filter. Objective evaluations indicate the effectiveness of the proposed mapping scheme. The advantage of this method is that the model gives a smooth estimate of the spectra of the close-speaking microphone speech. No distortions are perceived in the reconstructed speech. This mapping technique is also used for bandwidth extension of telephone speech.

Construction of sliding constraint surfaces and initial guess shapes for intermediate steps in multi-step finite element inverse analysis

Multi-step inverse analysis has been developed for more accurate results while one-step analysis can affirm qualitative deformation behavior. An inverse finite element approach has more capability to design the optimum blank shape from the desired final shape with small amount of computation time and effort. In forming simulation with the inverse method, multi-step inverse analysis is difficult to apply because sliding constraint surfaces and initial guesses of intermediate steps described by complex die and punch set are hard to generate with present mapping schemes. In this paper, intermediate sliding constraint surfaces for multi-step finite element inverse analysis are automatically constructed from the die–punch set at each step with the given stroke. The initial guess of intermediate steps is constructed by a direct mesh mapping scheme that is suggested to generate an initial guess on the constructed sliding constraint surface. Construction of sliding constraint surfaces and initial guesses for intermediate steps is applied to a multi-step rectangular cup drawing process and an S-rail forming process. The numerical example of the multi-step rectangular cup drawing process demonstrates that the proposed mapping scheme is applicable to construct sliding constraint surfaces and initial guesses for analysis of a multi-step drawing process with large aspect ratio. The analysis result of the S-rail forming process is compared with that of a direct finite element analysis to evaluate the effectiveness of the mapping scheme proposed.