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We derive the capacity region of the two-user dirty-paper Gaussian multiaccess channel (MAC) with conferencing encoders. In this MAC, prior to each transmission block, the transmitters can hold a conference in which they can communicate with each other over error-free bit pipes of given capacities. The received signal suffers not only from additive Gaussian noise but also from additive interference, which is known noncausally to the transmitters but not to the receiver. The additive interference is modeled as Gaussian or uniform over a sphere. We show that the interference can be perfectly mitigated, i.e., that the capacity region without interference can also be achieved in its presence. This holds irrespective of whether the transmitters learn the interference before or after the conference. It follows as a corollary that also for the MAC with degraded message sets, the interference can be perfectly mitigated if it is known noncausally to the transmitters. To derive our results, we generalize Costa's single-user writing-on-dirty-paper achievability result to channels with dependent interference and not-necessarily Gaussian noise. [ABSTRACT FROM AUTHOR]

We propose a density evolution based dirty-paper code design framework that combines trellis coded quantization with multi-level low-density parity-check (LDPC) codes. Unlike existing design techniques based on Gaussian approximation and EXIT charts, the proposed framework tracks the empirically collected log-likelihood ratio (LLR) distributions at each iteration, and employs density evolution and differential evolution algorithms to design each LDPC component code. The performance of the dirty-paper codes designed using the proposed method comes within 0.37 dB of the theoretical limit at 1 bit per sample transmission rate, achieving an 0.21 dB gain over the best known result. [ABSTRACT FROM PUBLISHER]

Text-based emotion prediction is an important task in the field of affective computing. Most prior work has been restricted to predicting emotions corresponding to a few high-level emotion classes. This paper explores and experiments with various techniques for fine-grained (27 classes) emotion prediction $^\dagger$ † . In particular, 1) we present a method to incorporate multiple annotations from different raters, 2) we analyze the model's performance on fused emotion classes and with sub-sampled training data, 3) we present a method to leverage the correlations among the emotion categories, and 4) we propose a new framework for text-based fine-grained emotion prediction through emotion definition modeling. The emotion definition-based model outperforms the existing state-of-the-art for fine-grained emotion dataset GoEmotions. The approach involves a multi-task learning framework that models definitions of emotions as an auxiliary task while being trained on the primary task of emotion prediction. We model definitions using masked language modeling and class definition prediction tasks. We show that this trained model can be used for transfer learning on other benchmark datasets in emotion prediction with varying emotion label sets, domains, and sizes. The proposed models outperform the baselines on transfer learning experiments demonstrating the model's generalization capability. [ABSTRACT FROM AUTHOR]

We propose and analyze in this paper two new adaptive power controlled minimum selection generalized selection combining (MS-GSC) diversity schemes. The key idea behind these two schemes is to request the transmitter to vary its power level during very adverse channel conditions in order to communicate with the minimum required quality of service. For each scheme, four power control variants accounting for practical implementation constraints including discrete power levels and transmitter gain saturation are proposed and studied. Selected numerical examples, show that ideal continuous power control lowers the average bit error rate of MS-GSC and makes it always meet the specified target quality of service at the expense of an increase in the transmitter gain. Additional numerical examples, show that the power control variants that take into account practical implementation constraints conserve the main features of the ideal continuous power algorithm. [ABSTRACT FROM PUBLISHER]

In this letter, a combined encryption and error-control coding scheme based on turbo codes (TCs) is proposed to enhance the security of the transmission. It relies on convolutional encoders that operate over Galois fields ${\textrm {GF}}(4)$ and include variable encryption polynomials, whose coefficients are randomly selected every $L$ steps from a set of optimal polynomials. This type of encoder has been studied in previous papers, where a certain correspondence between the randomness of the encoded sequence and the performance of the TC was conjectured. In this work, a scheme with a varying length $L$ is proposed to increase the output randomness and, therefore, the security of the sequence to be transmitted. That is to say, the number of steps $L$ , over which one of the polynomials is iterated, is a random variable. The randomness of the output and the security of the TC are quantified using differential block entropy, showing that it is possible to improve the security of the transmitted data without compromising the corresponding bit error rate (BER). [ABSTRACT FROM AUTHOR]

This paper proposes Value-Aware solid-state drive (SSD) with fast access speed and low power consumption by eliminating error-correcting code (ECC). Value-Aware SSD utilizes the error tolerance of image recognition application using a deep neural network (DNN) to enhance reliability. In a previous paper, which proposes Value-Aware SSD, fast ECC decoder is implemented and SSD is evaluated with the 32-bit floating-point data format. On the other hand, in this paper, the proposed Value-Aware SSD is analyzed with 32-bit and 8-bit fixed-point data format and achieves the higher reliability even without ECC by newly proposed two techniques, Critical Bit Error Reduction (CBER) and Middle & Lower Page Error Reduction (M&L-PER). CBER and M&L-PER are proposed for 32-bit and 8-bit data format of application, respectively. These techniques modulate the threshold voltage ($V_{\mathrm {TH}}$) distribution of memory cells by recognizing the importance of each stored bit. By proposed CBER, as much as 15% bit error rate (BER) of NAND flash is allowed while the application provides high image recognition accuracy. Even if bit precision is truncated to 8 bit, 3.9% BER is accepted by M&L-PER. The fast read access and low power consumption are realized because ECC is not required. Finally, this paper analyzes the Value-Aware techniques with 3-D multi-level cell (MLC) NAND flash to compare the effects for 3D-MLC and triple-level cell (TLC) NAND flash. [ABSTRACT FROM AUTHOR]

This paper proposes an ordered sequence detection (OSD) for digital pulse interval modulation (DPIM) in optical wireless communications. Leveraging the sparsity of DPIM sequences, OSD shows a comparable performance to the optimal maximum likelihood sequence detection with much lower complexity. Compared with the widely adopted sample-by-sample optimal threshold detection (OTD), it considerably improves the bit-error-rate (BER) performance by mitigating error propagation. Moreover, this paper proposes a barrier signal-aided digital pulse interval modulation (BDPIM), where the last of every $K$ symbols is allocated with more power as an inserted barrier signal. BDPIM with OSD (BDPIM-OSD) can limit the error propagation between two adjacent barriers. To reduce the storing delay when using OSD to detect extremely large packets, we propose BDPIM with a combination of OTD and OSD (BDPIM-OTD-OSD), within which long sequences are cut into pieces and separately detected. Approximate upper bounds of the average BER performance of DPIM-OTD, DPIM-OSD, BDPIM-OSD, and BDPIM-OTD-OSD are analysed. Simulations are conducted to corroborate our analysis. Optimal parameter settings are also investigated in uncoded and coded systems by simulations. Simulation results show that the proposed OSD and BDPIM bring significant improvement in uncoded and coded systems over various channels. [ABSTRACT FROM AUTHOR]

The read channel of a Flash memory cell degrades after repetitive program and erase (P/E) operations. This degradation is often modeled as a function of the number of P/E cycles. In contrast, this paper models the degradation as a function of the cumulative effect of the charge written and erased from the cell. Based on this modeling approach, this paper dynamically allocates voltage using lower voltage write thresholds at the beginning of the device lifetime and increasing the thresholds as needed to maintain the mutual information of the read channel in the face of degradation. This paper introduces the technique in an idealized setting and then removes ideal assumptions about channel knowledge and available voltage resolution to conclude with a practical scheme with performance close to that of the idealized setting. [ABSTRACT FROM PUBLISHER]

This paper investigates intelligent reflecting surface based backscatter communication (IRS-BackCom), in order to realize computational task offloading of energy-constrained mobile edge computing network in a self-sustainable manner. Specifically, the system operation is divided into two phases. In the first one, the ambient signal energy from a power beacon (PB) either provides the energy supply of local computing and energy harvesting circuits, or flows into the energy storage, when reaching the IRS. In the second one, the stored energy is used to enable IRS-BackCom for partial computational data offloading and energize local computing circuit. Based on this, the maximization problem of sum computational bits is formulated. By jointly optimizing the beamforming vector at the PB, the backscatter matrix at the IRS, the time scheduling of two-phase process, as well as the time of local computing, sum computational bits are maximized. In addition, this paper proposes element clustering to realize BackCom, so as to reduce the control and computation complexity of IRS. According to different operating mechanisms, two cluster operation modes are considered, namely independent cluster operation mode and joint cluster operation mode. Simulation results demonstrate the achievable sum computational bits by the proposed IRS-BackCom schemes. [ABSTRACT FROM AUTHOR]

This paper investigates the optimal signal detection problem with a particular interest in large-scale multiple-input multiple-output (MIMO) systems. The problem is NP-hard and can be solved optimally by searching the shortest path on the decision tree. Unfortunately, the existing optimal search algorithms often involve prohibitively high complexities, which indicates that they are infeasible in large-scale MIMO systems. To address this issue, we propose a general heuristic search algorithm, namely, hyper-accelerated tree search (HATS) algorithm. The proposed algorithm employs a deep neural network (DNN) to estimate the optimal heuristic, and then use the estimated heuristic to speed up the underlying memory-bounded search algorithm. This idea is inspired by the fact that the underlying heuristic search algorithm reaches the optimal efficiency with the optimal heuristic function. Simulation results show that the proposed algorithm reaches almost the optimal bit error rate (BER) performance in large-scale systems, while the memory size can be bounded. In the meanwhile, it visits nearly the fewest tree nodes. This indicates that the proposed algorithm reaches almost the optimal efficiency in practical scenarios, and thereby it is applicable for large-scale systems. Besides, the code for this paper is available at https://github.com/skypitcher/hats. [ABSTRACT FROM AUTHOR]

Non-orthogonal multiple access (NOMA) is a well-accepted technology for future Wi-Fi systems to improve spectral efficiency. NOMA allows an access point (AP) to simultaneously serve multiple devices by splitting the transmit power between them. Using the superposition coding the AP combines signals of different frames with predefined power weights. However, as it is already known, the phase noise caused by hardware imperfections limits the performance of NOMA transmissions. The paper proposes a practical, easy-to-implement, and backward-compatible method to rotate the constellation of the low power signal in order to make it more robust to the phase noise. A mathematical model is developed to find such a rotation angle that minimizes the bit error rate (BER) of the low power frame. A new NOMA Wi-Fi prototype testbed is developed with the new feature of constellation rotation ability, which is used to validate the performance of our proposed method. Many experimental results show the proposed constellation rotation approach significantly decreases the BER in high signal-to-noise scenarios. [ABSTRACT FROM AUTHOR]

The performance of the recently proposed orientational beamforming (OBF) system for ultra-wideband (UWB) signals degrades seriously in multiuser situation. Although various techniques have been proposed in the literature to suppress multiuser interference in the time-hopping UWB system, there has been no research on interference suppression in the OBF UWB system. In this paper, we propose a nonlinear OBF system via a modified radial basis function (RBF) neural network, named the RBF-OBF system, to reject orientational UWB interferences caused by multiuser transmission in the OBF system. The RBF neural network is selected mainly because of its simple structure, convenient training process, and fast convergence speed. However, the conventional Euclidean-distance-based RBF neural network is not suitable for the training process used in this work, as the training samples are noiseless orientational steering vectors in frequency domain. Therefore, a modified RBF neural network is proposed in this paper, which evaluates the similarity between an input vector and the center vector of a hidden layer neuron by their signed complex correlation coefficient. Numerous simulations demonstrate that compared to the conventional OBF system, the proposed RBF-OBF system can significantly reduce the bit error rates (BERs) under different noise and interference situations. The BER reduction rate of the proposed RBF-OBF system is higher than 92% in additive white Gaussian noise channel and higher than 89% in line-of-sight multipath channel. [ABSTRACT FROM AUTHOR]

Non-orthogonal multiple access (NOMA) is currently considered as a promising technology for the next-generation wireless networks. In this paper, the error rate performance of NOMA systems is investigated over Nakagami- $m$ fading channels, while considering imperfect successive interference cancelation. In particular, this paper focuses on the pairwise error probability (PEP) analysis, where exact PEP expressions are derived to characterize the performance of all users under different fading conditions. The obtained PEP expressions are then used to derive an exact union bound on the bit error rate (BER). Through the derived PEP expressions, the asymptotic PEP analysis is presented to investigate the maximum achievable diversity gain of NOMA users. Moreover, using the derived BER bound, the power allocation problem for all users in NOMA systems is considered under average power and users BER constraints, which allows realizing the full potential of NOMA. Monte Carlo simulation and numerical results are presented to corroborate the derived analytical expressions and give valuable insights into the error rate performance of each user and the achievable diversity gain. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the performance of the Viterbi decoding algorithm with/without Automatic Repeat reQuest (ARQ) over a Rician flat fading channel with unlimited interleaving. We show that the decay rate of the average bit error probability with respect to the bit energy to noise ratio is at least equal to $d_{f}$ at high-bit energy to noise ratio for both cases (with ARQ and without ARQ), where $d_{f}$ is the free distance of the convolutional code. The Yamamoto-Itoh flag helps to reduce the average bit error probability by a factor of $4^{d_{f}}$ with a negligible retransmission rate. We also prove an interesting result that the average bit error probability decays exponentially fast with respect to the Rician factor for any fixed bit energy per noise ratio. In addition, the average bit error exponent with respect to the Rician factor is shown to be $d_{f}$. [ABSTRACT FROM AUTHOR]

As a comprehensive solution based on the data access frequency, this paper proposes word-line batch $V_{\mathrm {TH}}$ modulation (WBVM) to improve the reliability of 2-D and 3-D-triple-level-cell (TLC) nand flash memories. Proposed WBVM modulates the threshold voltage ($V_{\mathrm {TH}}$) distribution and decreases errors of frequently written/erased “write-hot data,” infrequently written or read “write- and read-cold data,” and frequently read “read-hot data.” For write-hot data, the proposed WBVM $V_{\mathrm {TH}}$ score modulation suppresses the degradation of the tunnel oxide, which is caused by programming higher $V_{\mathrm {TH}}$ state. On the other hand, for write- and read-cold and read-hot data, the proposed WBVM bit error rate (BER) score modulation reduces errors during data retention and read cycles. Moreover, for archive memory, the proposed BER score nLC-modulation achieves the higher reliability by expanding the read margin of the least reliable $V_{\mathrm {TH}}$ state. As a result, the proposed WBVM realizes the comprehensive reliability enhancement for write-hot, write- and read-cold, and read-hot data of 2-D and 3-D-TLC nand flash. WBVM extends the acceptable write/erase cycles, the acceptable data-retention time, and the acceptable read cycles by up to 1.8 $\times$ , 45 $\times$ , and 4.7 $\times$ , respectively. [ABSTRACT FROM AUTHOR]

Reconfigurable intelligent surface (RIS) has emerged as a promising technique for future wireless communication networks. How to reliably transmit information in a RIS-based communication system arouses much interest. This paper proposes a reflecting modulation (RM) scheme for RIS-based communications, where both the reflecting patterns and transmit signals can carry information. Depending on that the transmitter and RIS jointly or independently deliver information, RM is further classified into two categories: jointly mapped RM (JRM) and separately mapped RM (SRM). JRM and SRM are naturally superior to existing schemes, because the transmit signal vectors, reflecting patterns, and bit mapping methods of JRM and SRM are more flexibly designed. To enhance transmission reliability, this paper proposes a discrete optimization-based joint signal mapping, shaping, and reflecting (DJMSR) design for JRM and SRM to minimize the bit error rate (BER) with a given transmit signal candidate set and a given reflecting pattern candidate set. To further improve the performance, this paper optimizes multiple reflecting patterns and their associated transmit signal sets in continuous fields for JRM and SRM. Numerical results show that JRM and SRM with the proposed system optimization methods considerably outperform existing schemes in BER. [ABSTRACT FROM AUTHOR]

Signed quadrature spatial modulation (SQSM) was recently introduced to enhance the throughput of spatial modulation (SM) in multiple-input multiple-output (MIMO) systems. This strategy involves independently transmitting the real and imaginary components of a symbol and its inverse from four independent antennas. In this paper, an extended SQSM (ESQSM) system is proposed. It combines $K$ SQSM constellations and transmits them from the same transmit-antenna set with the aim of realizing a $K$ -fold improvement in the spectral efficiency (SE). The proposed ESQSM employs the average power of the $K$ SQSM constellations as an additional dimension for transmission. Performance of the proposed ESQSM surpasses that of other state-of-art SM systems such as the QSM, DSM, IQSM SQSM, and EQSM by 13 dB, 11 dB, 10.55 dB, 10 dB, and 6.8 dB, respectively. In this paper, we also propose an efficient ESQSM with a multi-user (ESQSM-MU) system inspired by the ESQSM ability in increasing the SE. The proposed ESQSM-MU system offers a significant bit error rate (BER) improvement and a higher capacity (i.e., $5K$ -users) compared to the current non orthogonal multiple access-SM (NOMA-SM) and SM-assisted multi-antenna NOMA (SM-AMA-NOMA) systems. Moreover, an efficient low-complexity detector is introduced for the ESQSM signal detection, promising a 91.2% reduction in the computational complexity of ESQSM and ESQSM-MU systems relative to the maximum likelihood (ML) with a trivial loss in performance. [ABSTRACT FROM AUTHOR]

This paper presents a multiple-input–multiple-output (MIMO) precoder with a compensated QR decomposition (CQRD) combination for coordinated multipoint (CoMP) downlink transmission. Unlike conventional QR decomposition (QRD) combination, CQRD combination adopts compensated channel matrix orderings. This paper first proposes CQRD combination for CoMP scenarios. The statistics for combined spatial subchannel gains with a CQRD combination of two coordinated base stations (BSs) are derived, and these statistics show that more balanced subchannel gains are generated with a CQRD combination than with a QRD combination. Furthermore, this paper proposes a generalized CQRD combination scheme with a joint sorting strategy that can be applied to scenarios with more than two coordinated BSs. Unlike the unsorted strategy, the joint sorting strategy determines an enhanced compensated combination to further increase spatial subchannel gains; therefore, the performance can be upgraded. Because conventional Tomlinson–Harashima precoding (THP) cannot be used in the CQRD combination, interference presubtraction and vector precoding (VP) is adopted. Theoretical analysis and simulation results are both provided to demonstrate the advantages of balanced spatial subchannel gains and enhanced bit-error-rate (BER) performance in the proposed CQRD-based schemes. Compared with existing QRD-based MIMO precoders in CoMP scenarios, the proposed CQRD-based schemes have substantial signal-to-noise ratio (SNR) improvements of 2–5 dB. [ABSTRACT FROM PUBLISHER]

Light-fidelity (LiFi) is a fully-networked bidirectional optical wireless communication (OWC) technology that is considered as a promising solution for high-speed indoor connectivity. In this paper, the joint estimation of user 3D position and user equipment (UE) orientation in indoor LiFi systems with unknown emission power is investigated. Existing solutions for this problem assume either ideal LiFi system settings or perfect knowledge of the UE states, rendering them unsuitable for realistic LiFi systems. In addition, these solutions consider the non-line-of-sight (NLOS) links of the LiFi channel gain as a source of deterioration for the estimation performance instead of harnessing these components in improving the position and the orientation estimation performance. This is mainly due to the lack of appropriate estimation techniques that can extract the position and orientation information hidden in these components. In this paper, and against the above limitations, the UE is assumed to be connected with at least one access point (AP), i.e., at least one active LiFi link. Fingerprinting is employed as an estimation technique and the received signal-to-noise ratio (SNR) is used as an estimation metric, where both the line-of-sight (LOS) and NLOS components of the LiFi channel are considered. Motivated by the success of deep learning techniques in solving several complex estimation and prediction problems, we employ two deep artificial neural network (ANN) models, one based on the multilayer perceptron (MLP) and the second on the convolutional neural network (CNN), that can map efficiently the instantaneous received SNR with the user 3D position and the UE orientation. Through numerous examples, we investigate the performance of the proposed schemes in terms of the average estimation error, precision, computational time, and the bit error rate. We also compare this performance to that of the k-nearest neighbours (KNN) scheme, which is widely used in solving wireless localization problems. It is demonstrated that the proposed schemes achieve significant gains and are superior to the KNN scheme. [ABSTRACT FROM AUTHOR]

The visible light communication (VLC) can provide data transmission via the illumination light emitting diodes (LED). This paper introduces a new model to analyze the bit error rate (BER) of binary phase modulation in VLC for an arbitrary modulation depth and data duty cycle while taking into account both the Gaussian and signal-dependent shot noise. The impact of the driver design on the BER and its impact on ripple have not been considered in detail before. We compare two different LED driver schemes, namely directly adapting the driver control loop and binary shunting. We address data rate, BER, and power efficiency, for which we propose to use the extra energy per symbol above unmodulated light. We further introduce an analysis of the effect that (truncated) ripple interference has in the (matched or other) filter of the receiver. Ripple causes a harmful interference in VLC, and thus a BER expression is derived to include its effect. Two approximations are proposed to model the ripple interference, and their accuracies are compared by simulations. A low-pass filtering is proposed to alleviate the impact of ripple interference in VLC system. [ABSTRACT FROM PUBLISHER]

Heat-assisted magnetic recording (HAMR) is the leading candidate for the next generation of magnetic recording. In HAMR, the thermal profile (with circular contours produced by the near-field transducer) combined with the current writer structures results in recording transitions with noticeable curvature, which causes edge erasure at high linear density and increased transition noise. This transition curvature affects the bit error rate (BER) and is thus important to the model. As the micromagnetic simulations are computationally demanding, in this paper we investigate a fast and simplified write model to capture the transition curvature of HAMR. As the transition curvature causes signal degradation in normally oriented read head array (NHA) having straight gaps, we propose a V-shaped read head array (VHA) by rotating the side readers at appropriate angles to follow the curvature shapes and improve the readback signal. Simulations indicate that, with 2-D signal processing, VHA can provide improved BER performance compared to the NHA in the presence of readback transition curvature on HAMR media. Also this paper indicates that the Curie temperature variance affects BER performance more severely than the anisotropy field variance. [ABSTRACT FROM AUTHOR]

Within the scenario of the proliferation of smart vehicles, a novel tendency is to exploit the cooperation between vehicles to create vehicular ad hoc networks (VANETs) using the IEEE 802.11p standard. IEEE 802.11p includes dedicated short-range communications (DSRC) between high-speed vehicles and between the vehicles and the roadside infrastructure in the licensed intelligent transportation system (ITS) band at 5.9 GHz. At such frequencies, fading problems caused by the Doppler effect and/or multipath adversely affect propagation, particularly in dense urban environments. To reduce such propagation impairments, the use of lower frequencies has been proposed in literature, namely the TV white spaces (TVWS) in the ultrahigh-frequency (UHF) band. TVWS is the part of the spectrum licensed to broadcasters that is not occupied at a given time in a given geographical area on a noninterfering/nonprotected basis with regard to primary services. This paper analyses coexistence issues between digital video broadcasting—terrestrial (DVB-T)2 and IEEE 802.11p transmission in the TVWS. The aim of this paper is twofold: to evaluate the protection of DVB-T2 broadcasting services interfered by IEEE 802.11p communications and the impact of adjacent DVB-T2 services on IEEE 802.11p communications in the TVWS. The main outcomes of this paper are the maximum transmission power level and bandwidth configuration of an 802.11p signal in the adjacent channel (i.e., TVWS) of an active DVB-T2 system while protecting the broadcast service, as well as the error rate curves for each allowed mode of IEEE 802.11p in the TVWS to evaluate the performance of VANETs communications coexisting with DVB-T2 regular services in the licensed TV band. [ABSTRACT FROM AUTHOR]

In shingled magnetic recording, the multihead multitrack (MHMT) detector can better combat the effect of intertrack interference than the single-head single-track detector. Such a detector, however, has prohibitive implementation complexity. In this paper, we propose to use the reduced-state sequence estimation algorithm to significantly reduce the complexity, and render MHMT practical. A commonly used symmetric two-head two-track channel model is considered in this paper. Well-structured reduced-state trellises are constructed by evaluating the effective symbol pair distances and designing proper set partitioning principles. Different trellis configurations are obtained based on the desired performance/complexity tradeoff. Simulation results show that the MHMT detector can achieve near maximum-likelihood performance with a small fraction of the original number of trellis states. [ABSTRACT FROM AUTHOR]

A primary source of increased read time on nand flash comes from the fact that, in the presence of noise, the flash medium must be read several times using different read threshold voltages for the decoder to succeed. This paper proposes an algorithm that uses a limited number of rereads to characterize the noise distribution and recover the stored information. Both hard and soft decoding are considered. For hard decoding, this paper attempts to find a read threshold minimizing bit error rate (BER) and derives an expression for the resulting codeword error rate. For soft decoding, it shows that minimizing BER and minimizing codeword error rate are competing objectives in the presence of a limited number of allowed rereads, and proposes a tradeoff between the two. The proposed method does not require any prior knowledge about the noise distribution but can take advantage of such information when it is available. Each read threshold is chosen based on the results of previous reads, following an optimal policy derived through a dynamic programming backward recursion. The method and results are studied from the perspective of an SLC Flash memory with Gaussian noise, but this paper explains how the method could be extended to other scenarios. [ABSTRACT FROM PUBLISHER]

Considering the highly dynamic nature of the vehicular environment and the delay-sensitive wireless medium, enabling secure and reliable vehicle-to-vehicle communication becomes a very challenging task. In this paper, we propose a novel system design that uses blockchain technology to establish a high-level trust-management successful trustworthy cooperative vehicular wireless communication. The proposed system is a cross-layer approach that optimizes the best-relay selection process allowing only trustworthy relays to participate in data transmission. In this work, blockchain stores real-time information about relaying, transmitting, and receiving vehicles. The information includes channel characteristics and participation quality. The information is vetted and verified by mining vehicles. The result guides the relay selection process to block untrustworthy vehicles from participation. The entire system is comprehensively modeled and mathematically analyzed. Simulations using throughput and Bit Error Rate (BER) as evaluation metrics demonstrated the effectiveness and efficacy of the presented approach in enabling reliable wireless communication in presence of maliciously behaving vehicles. On average, the overall system throughput rate increased by $3bps$ , the BER was reduced by almost by $2dB$ , and the percentage of false messages decreased by 90% considering high Signal to Noise Ratio (SNR). [ABSTRACT FROM AUTHOR]

This paper presents techniques that are expected to improve the bit error rate (BER) performance of Unmanned Aerial Vehicles (UAVs) communication systems. The decode-and-forward (DF)-based cooperative multi-hop Rician network using space shift keying (SSK) modulation is employed for this purpose. The SSK modulation and cooperative communication are merged and used together. This enhances the BER performance for multiple-input multiple-output (MIMO) channels, thus accentuating its significance as an important technique for consistently reliable communication methodology while, at the same time, eliminating wastage of energy. The new technique is named as high performance (HP) due to not only BER performance improvement but also increase of the diversity of the communication system. This new model is further used for multi-hop networks and the resulting BER characteristics are assessed for possible enhanced performance in Rician channels. The paper also showcases the generalized-n-hop BER equation for various multi-hop DF-based cooperative communication systems in diverse UAV models. The Monte Carlo simulations further confirm the theoretical results that already exist for transmit-receive antennas. This work also underlines the fact that the number of hops in a communication system has no bearing whatsoever on the BER performance diversity value. [ABSTRACT FROM AUTHOR]

Text encoding is one of the most important steps in Natural Language Processing (NLP). It has been done well by the self-attention mechanism in the current state-of-the-art Transformer encoder, which has brought about significant improvements in the performance of many NLP tasks. Though the Transformer encoder may effectively capture general information in its resulting representations, the backbone information, meaning the gist of the input text, is not specifically focused on. In this paper, we propose explicit and implicit text compression approaches to enhance the Transformer encoding and evaluate models using this approach on several typical downstream tasks that rely on the encoding heavily. Our explicit text compression approaches use dedicated models to compress text, while our implicit text compression approach simply adds an additional module to the main model to handle text compression. We propose three ways of integration, namely backbone source-side fusion, target-side fusion, and both-side fusion, to integrate the backbone information into Transformer-based models for various downstream tasks. Our evaluation on benchmark datasets shows that the proposed explicit and implicit text compression approaches improve results in comparison to strong baselines. We therefore conclude, when comparing the encodings to the baseline models, text compression helps the encoders to learn better language representations. [ABSTRACT FROM AUTHOR]

Existing linguistic steganalysis methods share a similar conceptual learning paradigm: namely, learning specific features derived from a word and its surrounding words, then passing them to the classifier. However, these features are unable to deal with the impact of the association between words and the corpus, which gives rise to significant limitations. In this paper, we discover the missing link between the words and the corpus, and accordingly propose a framework of linguistic steganalysis named LS-BGAT. Specifically, we fine-tune a large-scale pre-training BERT as the local feature extraction model and employ Graph Attention Network (GAT) as the global feature extraction model. Through ensuring collaboration between the local BERT-based features and the global GAT-based features in the joint prediction layer, we combine rich semantic and syntactic information at the sentence level with underlying global information at the corpus level. Furthermore, we extend the binary classification of steganalysis to multi-category classification, thereby enhancing practicality. We empirically substantiate the effectiveness and universality of LS-BGAT on three tasks. [ABSTRACT FROM AUTHOR]

Neuro-spike communication (NSC) is a communication method that includes electrical communication process and molecular communication process, which has been investigated extensively in recent years. The vesicle release process has a great influence on the accuracy of NSC systems. So the modeling of the vesicle release process has become a hot spot. There exist different vesicle release mechanisms, including univesicular release (UVR) case, multivesicular release (MVR) case and hybrid vesicle release (HVR) case. When a spike arrives, the UVR case refers to that at most one vesicle can be released. The MVR case refers to that more than one vesicle can be released. The HVR case is a mixed case of the UVR and MVR cases. This paper proposes the modeling of these three vesicle release cases. The theoretical analysis is conducted to compare them in terms of efficiency. Simulations are performed to evaluate the impacts of main vesicle releasing parameters on signal transmission accuracy. The simulation results show that the HVR model can effectively improve the transmission accuracy compared with UVR and MVR models under some conditions. [ABSTRACT FROM AUTHOR]

In this paper, we consider a mobile molecular communication (MC) system consisting of two mobile nanomachines, a transmitter and a receiver, propelled by a positive drift velocity and Brownian motion in a realistic blood-vessel-type flow regime. Considering the nonlinear movement of the nanomachines, an extended Kalman filter is employed to estimate the distance from the transmitter. Furthermore, based on the predicted distance, to keep the number of received molecules for bit 1 at a stable level, we employ power control on the number of transmitted molecules based on the distance between the transmitter and the receiver and the residual molecules in the channel from the previous transmission. Finally, the optimal detection threshold is obtained by minimizing the error probability. It is verified that a fixed optimal detection threshold can be effective for the power control scheme in the mobile MC. The bit error rate (BER) performance of our scheme is verified via simulation results. [ABSTRACT FROM AUTHOR]

In this paper, we propose a precoded faster-than-Nyquist (FTN) signaling technique for time-domain single-carrier index-modulated symbol transmission. More precisely, eigenvalue decomposition (EVD) precoding is adopted for the FTN transmission of data bits modulated by single-carrier time-domain index modulation (IM). While the FTN scheme increases the spectral efficiency and data rate by increasing the density of transmit symbols, the time-domain IM works towards the same objective while maintaining symbol sparsity. We analytically derive the constrained capacity of the proposed system. Our simulation results show that the proposed scheme has better bit error ratio (BER) performance than the conventional FTN-IM scheme, particularly for the scenario of a higher packing ratio. With the proposed scheme, a 2.5 dB performance gain is observed at the BER of 10−4, where the packing ratio is 0.7 and the roll-off factor is 0.5 in the channel-uncoded scenario. We further analyze our scheme’s performance by characterizing its minimum Euclidean distance and inter-symbol interference. Furthermore, we present a three-stage serially concatenated iterative detection architecture for the proposed EVD-FTN-IM signaling scheme. It is demonstrated in our simulations that a near-capacity BER performance is achievable in the proposed turbo-coded FTN-IM scheme. [ABSTRACT FROM AUTHOR]

Orthogonal Time Frequency Space (OTFS) modulation is a recently proposed scheme for time-varying narrowband channels in terrestrial radio-frequency communications. Underwater acoustic (UWA) and ultra-wideband (UWB) communication systems, on the other hand, confront wideband time-varying channels. Unlike narrowband channels, for which time contractions or dilations due to Doppler effect can be approximated by frequency-shifts, the Doppler effect in wideband channels results in frequency-dependent non-uniform shift of signal frequencies across the band. In this paper, we develop an OTFS-like modulation scheme – Orthogonal Delay Scale Space (ODSS) modulation – for handling wideband time-varying channels. We derive the ODSS transmission and reception schemes from first principles. In the process, we introduce the notion of $\omega$ -convolution in the delay-scale space that parallels the twisted convolution used in the time-frequency space. The preprocessing 2D transformation from the Fourier-Mellin domain to the delay-scale space in ODSS, which plays the role of inverse symplectic Fourier transform (ISFFT) in OTFS, improves the bit error rate performance compared to OTFS and Orthogonal Frequency Division Multiplexing (OFDM) in wideband time-varying channels. Furthermore, since the channel matrix is rendered near-diagonal, ODSS retains the advantage of OFDM in terms of its low-complexity receiver structure. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the precoder design for multiple-input multiple-output (MIMO) dual-functional radar-communication (DFRC) system with one-bit digital-to-analog converters (DACs). In order to form the dual-functional beam-pattern, we formulate the precoding problem as a weighted optimization problem with the constant modulus constraint, which aims at minimizing the average error power and guaranteeing radar waveform similarity. The problem is divided into three sub-problems corresponding to the multiple variables, i.e., the precoding factor, transmit signal matrix, and radar waveform matrix. Due to the discrete and non-convex properties of the optimization problem, we propose a multi-variable alternating minimization (MVAM) framework to achieve the near-optimal solutions. The precoding factor and radar waveform can be solved in closed-forms. For the transmit signal matrix, we devise a binary particle swarm optimization-simulated annealing (BPSO-SA) algorithm to obtain it under the MVAM framework. Extensive simulations validate the effectiveness of the proposed approach under various scenarios, including the case without perfect channel state information. The simulation results show that, compared with existing non-linear precoders, the proposed approach achieves 7dB SNR gain at the bit error rate of 10−4 in the 8-antenna system, and the gain of SNR is 0.2dB in the massive MIMO system with 128 antennas. [ABSTRACT FROM AUTHOR]

The joint transmission scheme of polar codes and sparse code multiple access (SCMA) has been regarded as a promising technology for future wireless communication systems. However, most of the existing polar-coded SCMA (PC-SCMA) systems suffer from high latency caused by the feedback iteration and list decoding. In addition, the error performance of PC-SCMA systems is unsatisfactory for ultra-reliable transmission. Inspired by the compelling benefits of non-binary polar codes, in this paper, we design a non-binary polar-coded SCMA (NB-PC-SCMA) system with a free order matching strategy to address the issues of delay and reliability. Specifically, we first formulate a joint factor graph for NB-PC-SCMA and propose a non-binary successive cancellation list (NB-SCL) and damping based joint iterative detection and decoding (NSD-JIDD) multiuser receiver to improve the BER and latency performance. Then, a lazy-search based NB-SCL (L-NB-SCL) decoding is proposed to reduce the computational complexity by simplifying the path search pattern of the list decoder. After that, we modify the update of user nodes for SCMA detection to improve the convergence error and finally propose the improved NSD-JIDD (ISD-JIDD) algorithm, which can avoid redundant operations by exploiting L-NB-SCL decoding. Simulation results show that the proposed NB-PC-SCMA system achieves better bit error rate (BER) performance and considerable latency gain when compared to its counterparts. In particular, the proposed ISD-JIDD can achieve similar BER performance of NSD-JIDD with less complexity. [ABSTRACT FROM AUTHOR]

This paper proposes multilevel Reed–Solomon (MRS) codes and their iterative multistage soft decoding (IMSD) for visible light communication (VLC), realizing both high decoding performance and transmission spectrum efficiency. The proposed IMSD algorithm decodes the MRS codes level-by-level through iterating either hard decisions or extrinsic information of RS coded bits. Each level RS decoding is realized by cascading the adaptive belief propagation (ABP) algorithm that produces the extrinsic information and the Berlekamp–Massey (BM) algorithm that estimates the codeword. The earlier level decoding provides better a priori information for the later ones. A complexity reducing IMSD (CR-IMSD) algorithm is also proposed to facilitate the decoding. This paper further investigates a joint design of color-shift keying (CSK) constellation and the MRS code, optimizing the decoding performance. The CSK constellation is designed by considering both the set partitioning (SP) criterion and the harmonic mean of constellation’s minimum squared Euclidean distance (MSED). The MRS codes are further designed using the capacity and the equal error probability rules. Our simulation results show that the IMSD algorithm achieves significant iterative decoding gains. The performance of the designed MRS code is 0.3 dB away from the capacity limit at the bit error rate (BER) of 10−9. [ABSTRACT FROM AUTHOR]

This paper develops novel deep learning-based architectures and design methodologies for an orthogonal frequency division multiplexing (OFDM) receiver under the constraint of one-bit complex quantization. Single bit quantization reduces greatly the complexity and power consumption but makes accurate channel estimation and data detection difficult. This is particularly true for multicarrier waveforms that have high peak-to-average power ratio in the time domain and fragile subcarrier orthogonality in the frequency domain. The severe distortion for one-bit quantization typically results in an error floor even at moderately low signal-to-noise-ratio (SNR) such as 5 dB. For channel estimation (using pilots), we design a novel generative supervised deep neural network that can be trained with a reasonable number of pilots. After channel estimation, a neural network-based receiver—specifically, an autoencoder—jointly learns a precoder and decoder for data symbol detection. Since quantization prevents end-to-end training, we propose a two-step sequential training policy for this model. With synthetic data, our deep learning-based channel estimation can outperform least squares channel estimation for unquantized (full-resolution) OFDM at average SNRs up to 14 dB. For data detection, our proposed design achieves lower bit error rate (BER) in fading than unquantized OFDM at average SNRs up to 10 dB. [ABSTRACT FROM AUTHOR]

This paper considers a low-complexity iterative linear minimum mean square error (LMMSE) multiuser detector for the multiple-input and multiple-output system with nonorthogonal multiple access (MIMO-NOMA), where multiple single-antenna users simultaneously communicate with a multiple-antenna base station (BS). While LMMSE being a linear detector has a low complexity, it has suboptimal performance in multiuser detection scenario due to the mismatch between LMMSE detection and multiuser decoding. Therefore, in this paper, we provide the matching conditions between the detector and decoders for MIMO-NOMA, which are then used to derive the achievable rate of the iterative detection. We prove that a matched iterative LMMSE detector can achieve the optimal capacity of symmetric MIMO-NOMA with any number of users, the optimal sum capacity of asymmetric MIMO-NOMA with any number of users, all the maximal extreme points in the capacity region of asymmetric MIMO-NOMA with any number of users, and all points in the capacity region of two-user and three-user asymmetric MIMO-NOMA systems. In addition, a kind of practical low-complexity error-correcting multiuser code, called irregular repeat-accumulate code, is designed to match the LMMSE detector. Numerical results shows that the bit error rate performance of the proposed iterative LMMSE detection outperforms the state-of-art methods and is within 0.8 dB from the associated capacity limit. [ABSTRACT FROM AUTHOR]

This paper presents a four-level pulse amplitude modulation (PAM4) quarter-rate receiver that efficiently compensates for moderate channel loss in a robust manner through background adaptation of the receiver thresholds and equalization taps. The front-end utilizes an input single-stage continuous-time linear equalizer (CTLE) to boost the main cursor and relax the pre-cursor cancellation requirement, requiring only a 2-tap pre-cursor feed-forward equalizer (FFE) on the transmitter side. A 2-tap decision feedback equalizer (DFE) follows that includes one finite impulse response (FIR) tap and one infinite impulse response (IIR) tap to cancel first post-cursor and long-tail inter-symbol interference (ISI), respectively. In addition to the per-slice main three data samplers, a single error sampler is utilized for background threshold control and an edge-based sampler performs both phase-locked loop (PLL)-based clock and data recovery (CDR) phase detection and generates information for background DFE tap adaptation. Fabricated in general purpose (GP) 65-nm CMOS, the 56-Gb/s receiver achieves 4.63 mW/Gb/s and compensates for up to 20.8-dB loss at a bit error rate (BER) < 10−12 when operated with a 2-tap FFE transmitter. [ABSTRACT FROM AUTHOR]

Visible light communications (VLC) has been studied thoroughly in recent years as an alternative or complementary technology to radio frequency communications. The reliability of VLC channels highly depends on the availability and alignment of line of sight links. In this paper, we study the effect of random receiver orientation for mobile users over VLC downlink channels, which affects the existence and quality of line of sight links. Based on the statistics of the receiver location and relative orientation with respect to the transmitter LED, we develop an analytical framework to characterize the statistical distribution of VLC downlink channels, which is then utilized to obtain the outage probability and the bit error rate. Our analysis is generalized for arbitrary distributions of relative orientation and location for a single transmitter, and extended to multiple transmitter case for some certain scenarios. Extensive Monte Carlo simulations show a perfect match between the analytical and the simulation data in terms of both the statistical channel distribution and the resulting bit error rate. Our results also characterize the channel attenuation due to random receiver orientation and location for various scenarios of interest. [ABSTRACT FROM AUTHOR]

In recent years, optical interconnection networks have been proposed in order to achieve the ultrahigh bandwidth and low latency requirements for inter/intra-chip communication. In these optical interconection networks, series of basic optical elements are employed. Via these series of optical elements, the intrinsic crosstalk noise is generated. With a large scale of these optical elements, the signal-to-noise ratio (SNR) of an optical interconnect can be reduced by this crosstalk noise. In this paper, we utilize the adaptive power control (APC) to enhance the SNR under the crosstalk noise constraints. APC has been known to save energy and reduce power consumption. We apply this technique in one of the inter/intra-chip optical interconnect called I2CON. A new cluster design, namely the Beam cluster, is also introduced. Results have demonstrated that the APC can help to reduce crosstalk noise, hence, the overall SNR is improved. Comparison results have also indicated the further improvement of SNR in I2CON using Beam cluster when APC is applied. [ABSTRACT FROM AUTHOR]

In this paper, we consider diffusion-based molecular communication with and without drift between two static nano-machines. We employ type-based information encoding, releasing a single molecule per information bit. At the receiver, we consider an asynchronous detection algorithm which exploits the arrival order of the molecules. In such systems, transposition errors fundamentally undermine reliability and capacity. Thus, in this paper, we study the impact of transpositions on the system performance. Toward this, we present an analytical expression for the exact bit error probability (BEP) caused by transpositions and derive computationally tractable approximations of the BEP for diffusion-based channels with and without drift. Based on these results, we analyze the BEP when background is not negligible and derive the optimal bit interval that minimizes the BEP. Simulation results confirm the theoretical results and show the error and goodput performance for different parameters such as block size or noise generation rate. [ABSTRACT FROM AUTHOR]

Recent physical-layer designs capable of decoding multi-packet collisions demonstrate great potential for improving the network performance. Current network protocols, however, tailor the traditional physical layer to avoid collisions and thus cannot fully exploit the benefits of concurrent transmission techniques. In this paper, we propose an innovative generic concurrent transmission aware routing design called mShare. The mShare design exploits the benefits of these techniques by scheduling concurrent senders to utilize co-owned receiver(s) in parallel. This design significantly increases the available number of routing choices and thus improves the network performance. To illustrate the versatility of our design, we test mShare in three settings: unicast, opportunistic routing, and data collection (convergecast). The performance of mShare is evaluated with physical testbed experiments running on USRP and simulations. The experimental results show that compared to conventional designs, mShare: 1) improves 277% of the throughput in unicast; 2) saves 78% of transmissions in opportunistic routing; and 3) reduces 70% of the delivery delay in data collection. [ABSTRACT FROM AUTHOR]

In magnetic recording systems, consecutive sections experience different signal-to-noise ratios (SNRs). To perform error correction over these systems, one approach is to use an individual block code for each section. However, the performance over a section affected by a lower SNR is weaker compared to the performance over a section affected by a higher SNR. Spatially-coupled (SC) codes are a family of graph-based codes with capacity approaching performance and low latency decoding. An SC code is constructed by partitioning an underlying block code to several component matrices, and coupling copies of the component matrices together. The contribution of this paper is threefold. First, we present a new partitioning technique to efficiently construct SC codes with column weights 4 and 6. Second, we present an SC code construction for channels with SNR variation. Our SC code construction provides local error correction for each section by means of the underlying codes that cover one section each, and simultaneously, an added level of error correction by means of coupling among the underlying codes. Third, we introduce a low-complexity interleaving scheme specific to SC codes that further improves their performance over channels with SNR variation. Our simulation results show that our SC codes outperform individual block codes by more than one and two orders of magnitudes in the error floor region compared to the block codes with and without regular interleaving, respectively. This improvement is more pronounced by increasing the memory and column weight. [ABSTRACT FROM AUTHOR]

Spatially coupled low-density parity-check (SC-LDPC) codes have emerged to possess capacity-approaching performance. The SC-LDPC codes can be decoded by a sliding window, therefore, the decoding latency and complexity of SC-LDPC codes are lower than those of underlying LDPC codes when the codeword length is very large. In this paper, the SC-LDPC decoder with the sliding window is employed in turbo equalization of magnetic recording systems. We examine the bit error rates (BERs) of the output of the sliding window during the iterative decoding, and then observe that the consecutive code blocks have approximately the same BERs. Herein, to reduce decoding complexity of SC-LDPC codes, the consecutive code blocks can be considered as the output of SC-LDPC codes. In addition, the non-uniform schedule update is adopted in the window decoding to avoid unnecessary updates within a window. The simulation results show that the proposed decoding algorithms applied in bit-patterned media magnetic recording systems can achieve a significant reduction in complexity compared to the traditional decoding without any loss in BER performance. [ABSTRACT FROM AUTHOR]

Inter-block-interference (IBI) caused in the pursuit of spectral efficiency can deteriorate channel estimation performance. For this problem, previously-proposed chained turbo estimation performs IBI cancelation by using the soft replica of the transmitted signal. The IBI cancelation technique can, however, suffer from a mean squared error (MSE) floor problem, since the soft replica is unavailable at the first turbo iteration. The IBI problem can be avoided by using channel impulse response length constraint. Nevertheless, as shown in this paper, the IBI avoidance approach is difficult to perform independently since it requires unbiased second-order statistics. This paper proposes, therefore, a new conditional $\ell 1$ regularized minimum mean square error channel estimation algorithm by jointly utilizing the IBI avoidance/cancelation and subspace techniques. Simulation results verify that the proposed algorithm solves the MSE floor problem, and, hence, improves the bit error rate convergence performance in realistic IBI channels including the effect of pulse shaping filters. [ABSTRACT FROM AUTHOR]

High peak-to-average power ratio (PAPR) is a long-standing problem of orthogonal frequency division multiplexing (OFDM) system. Although there have been a plethora of proposals presented to date, most of the proposals sacrifice spectral efficiency to attain low PAPR. In this paper, a concept of subcarrier group modulation (SGM) is proposed to transform those spectrum inefficient schemes into spectrum efficient ones. The SGM scheme groups available subcarriers, and assigns one extra bit to each group depending on one of two different sets of constellation, thereby freeing some subcarriers for PAPR reduction. At the receiver, the constellation set used in a particular group is determined by the maximum-likelihood detection. The SGM scheme can be integrated to different PAPR reduction schemes. In this paper, it is integrated with the dummy sequence insertion (DSI) scheme. The DSI with SGM can attain the same spectral efficiency as the conventional OFDM does. Through simulations, it is found that it can achieve PAPR almost similar to that the conventional DSI scheme does without degrading BER performance significantly over both additive white Gaussian noise and Rayleigh fading channels. In addition to the PAPR reduction application, the proposed scheme can be used to improve throughput of any conventional OFDM systems. [ABSTRACT FROM AUTHOR]

In this paper, a delay diversity orthogonal frequency-division multiplexing (DD OFDM) transmission scheme in amplify-and-forward (AF) full-duplex relay systems is investigated. One direct source-to-destination link, one relay forwarding link, and residual self-interference are considered in the system. The necessary cyclic prefix length is investigated and a suitable AF relay protocol in the full-duplex relay OFDM system is proposed. This paper demonstrates that the AF relay link and the direct source-to-destination link can be combined to provide spatial diversity. The key is that the DD OFDM scheme is used to transform the spatial diversity into increased channel frequency diversity that is further exploited by using the bit-interleaved coding. The bit error rate performance of the proposed system is verified by simulation results. [ABSTRACT FROM PUBLISHER]

A functional test sequence for a design may not be effective as a manufacturing test for a logic block in the design because it achieves a low gate-level fault coverage. This paper describes a procedure for selecting a clock sequence that increases the gate-level fault coverage of a functional test sequence when it is used for testing a subset of logic blocks. The procedure deactivates the clocks to the logic blocks in the subset when a primary input vector has a negative effect on their fault coverage. The procedure is different from earlier test generation and test compaction procedures in that it increases the fault coverage without modifying the functional test sequence. It thus preserves some of the functional characteristics and the test application process for the sequence. Experimental results for benchmark circuits are presented to demonstrate the effectiveness of the procedure. [ABSTRACT FROM AUTHOR]