Information Bits Research Articles

Performance Improvement of Polar Codes via UEP Product Coding

Aiming to improve the error correction performance of polar codes, researchers have proposed employing the product coding structure involving RS codes of different rates in the horizontal direction and the short polar codewords along the vertical direction. However, there is no efficient algorithm optimizing the rate allocation of RS codes. In order to address this problem, this paper provides an analytical formulation by maximizing the number of correctly decoded information bits. The proposed rate allocation formulation takes the channel statistics into consideration, and we further find that the number of different RS code rates could be limited to a small value. By doing so, the complexities of both the rate allocation optimization and the iterative product decoding could be reduced. Simulation results demonstrate the superiority of RS-polar product codes with the proposed rate allocation method over both additive white Gaussian noise channels and Gilbert–Elliott channels. When the inner polar codes of rate 1/2 are utilized, the optimized RS-polar product codes of low-to-medium rates significantly outperform the successive cancellation decoding of long polar codes, in the regime of a frame error rate ≥10−3.

Decoding Reed-Muller Codes With Successive Codeword Permutations

A novel recursive list decoding (RLD) algorithm for Reed-Muller (RM) codes based on successive permutations (SP) of the codeword is presented. A low-complexity SP scheme applied to a subset of the symmetry group of RM codes is first proposed to carefully select a good codeword permutation on the fly. Then, the proposed SP technique is integrated into an improved RLD algorithm that initializes different decoding paths with random codeword permutations, which are sampled from the full symmetry group of RM codes. Finally, efficient latency and complexity reduction schemes are introduced that virtually preserve the error-correction performance of the proposed decoder. Simulation results demonstrate that at the target frame error rate of 10−3 for the RM code of length 256 with 163 information bits, the proposed decoder reduces 6% of the computational complexity and 22% of the decoding latency of the state-of-the-art semi-parallel simplified successive-cancellation decoder with fast Hadamard transform (SSC-FHT) that uses 96 permutations from the full symmetry group of RM codes, while relatively maintaining the error-correction performance and memory consumption of the semi-parallel permuted SSC-FHT decoder.

Optimizing Training and Transmission Overheads for Secure URLLC Against Randomly Distributed Eavesdroppers

In this article, we focus on the pilot-assisted transmission design for secure ultra-reliable and low-latency communication (URLLC) systems, which has not yet been studied in the existing literatures. In each transmission period of this system, the multi-antenna controller sends confidential URLLC messages integrated with artificial noise (AN) to a single-antenna actuator for some mission-critical operations (e.g., remote control), and while an unknown number of passive eavesdroppers attempt to intercept this confidential message in a non-colluding manner. Since the conventional ergodic secrecy capacity is not accurate to describe the maximal achievable secrecy rate of URLLC with short blocklength coding, we establish the concept of achievable effective secrecy rate (AESR) to measure the secrecy performance of our URLLC system, which is defined as the average number of information bits can be transmitted per channel use under given reliability and information leakage constraints. Due to the exact expression of AESR has an intractable form, we derive a closed-form approximation on the AESR to simplify the calculation, via leveraging the Laplace approximation and Gaussian-Chebyshev quadrature method. Following by this approximation, we propose an efficient two-dimensional search algorithm to determine the optimal transmission parameters that maximize the AESR, i.e., the training pilot length and the power allocation ratio between confidential data signals and AN. Furthermore, the asymptotic performance of AESR in the high-SNR regime is also analyzed to gain more insights. Numerical results validate the accuracy of theoretical approximations presented in this paper, and illustrate how the particular system parameters impact the AESR of our considered URLLC system.

Linear-Equation Ordered-Statistics Decoding

In this paper, we propose a new linear-equation ordered-statistics decoding (LE-OSD). Unlike the OSD, LE-OSD uses high reliable parity bits rather than information bits to recover the codeword estimates, which is equivalent to solving a system of linear equations (SLE). Only test error patterns (TEPs) that create feasible SLEs, referred to as the valid TEPs, are used to obtain different codeword estimates. We introduce several constraints on the Hamming weight of TEPs to limit the overall decoding complexity. Furthermore, we analyze the block error rate (BLER) and the computational complexity of the proposed approach. It is shown that LE-OSD has a similar performance as OSD in terms of BLER, which can asymptotically approach Maximum-likelihood (ML) performance with proper parameter selections. Simulation results demonstrate that the LE-OSD has a significantly reduced complexity compared to OSD, especially for low-rate codes, that usually require high decoding order in OSD. Nevertheless, the complexity reduction can also be observed for high-rate codes. In addition, we further improve LE-OSD by applying the decoding stopping condition and the TEP discarding condition. As shown by simulations, the improved LE-OSD has a considerably reduced complexity while maintaining the BLER performance, compared to the latest OSD approach from literature.

Adversarial attacks on deep learning networks in image classification based on Smell Bees Optimization Algorithm

Adversarial machine learning is an active trend in artificial intelligence that attempts to fool deep learning models by causing malfunctions during the prediction of decisions. In this work, we are interested in image classification, and propose a black box for adversarial examples generation which is driven by an optimization algorithm. The main ideas of the used approach are firstly inspired from the steganography principles in which hiding information in image pixels with minimal payload capacity to reduce the distortion between the real image and the adversarial image constitutes a constraint to be respected. In fact, this distance must be sufficient to lead to deceive an already trained classifier. Secondly, the selection of relevant pixels for embedding information bits is mainly done by the optimization algorithm Smell Bees Optimization (SBO). Some investigations are done on Convolutional neural network, Softmax classifier and Residual network, providing good results on both MINST and CIFAR datasets.

Reversible Transformation between Isolated Skyrmions and Bimerons.

Skyrmions and bimerons are versatile topological spin textures that can be used as information bits for both classical and quantum computing. The transformation between isolated skyrmions and bimerons is an essential operation for computing architecture based on multiple different topological bits. Here we report the creation of isolated skyrmions and their subsequent transformation to bimerons by harnessing the electric current-induced Oersted field and temperature-induced perpendicular magnetic anisotropy variation. The transformation between skyrmions and bimerons is reversible, which is controlled by the current amplitude and scanning direction. Both skyrmions and bimerons can be created in the same system through the skyrmion-bimeron transformation and magnetization switching. Deformed skyrmion bubbles and chiral labyrinth domains are found as nontrivial intermediate transition states. Our results may provide a unique way for building advanced information-processing devices using different types of topological spin textures in the same system.

Design of Noncoherent and Coherent Receivers for Chirp Spread Spectrum Systems

LoRaWAN is a prominent communication standard to enable reliable low-power, long-range communications for the Internet of Things (IoT). The modulation technique used in LoRaWAN, commonly known as LoRa modulation, is based on the principle of chirp spread spectrum (CSS). The main objective of this article is to design a practical, low-complexity coherent receiver for a recently proposed CSS-based modulation scheme, called phase-shift keying CSS (PSK-CSS), that embeds extra information bits in the starting phases of conventional CSS symbols. To this end, a novel method is proposed to perform coarse timing and frequency synchronization that makes use of a preamble consisting of both up and down chirps and the shape of the pulse shaping and/or receive (matched) filters. Furthermore, to enable fine synchronization, timing, and phase loop filters are designed as simple first-order and second-order phase-locked loop (PLL) circuits with dynamic gain control. A natural outcome of our design is a practical noncoherent receiver that can be used for the conventional LoRa/CSS system and has better performance and/or lower computational complexity as compared to other existing designs. Extensive simulation results are presented to demonstrate the excellent performance and merits of the proposed design. In particular, the bit-error-rate (BER) performance of the higher-rate PSK-CSS system obtained with the proposed coherent receiver is only 0.25 dB worse than that obtained with the ideal co-coherent receiver, whereas it enjoys about 0.75-dB power gain over the noncoherent detection performance of the conventional CSS system. Thanks to the extra information bits carried by the phases of CSS symbols, the PSK-CSS system implemented with quadrature phase-shift keying (QPSK) delivers additional 23.44% and 18.75% data rate as compared to the conventional CSS system for the spreading factors (SFs) of 8 and 10, respectively.

Reactive jammer detection in OFDM with index modulation

Detection of jamming attacks is an important tool to improve the resource efficiency of jammer resilient communication networks. Detecting reactive jammers is especially difficult since the attacker is cognitive and focuses only on the used channels. Orthogonal frequency division multiplexing with index modulation (OFDM-IM) consists of active and passive subcarriers. Only active subcarriers carry modulated signals while passive subcarriers are left unused. In OFDM-IM systems, information bits are also dynamically embedded in the indices of these active subcarriers. As a result, remaining passive subcarriers cause instantaneously changing and unused holes in the spectrum that a reactive jammer cannot escape from attacking. In this paper, we propose an OFDM-IM-based detection scheme to improve the detection performance against reactive jammers. The proposed method exploits the dynamically changing empty OFDM-IM subcarriers to improve detection performance. A detection mechanism that is based on the variance of received signals is considered to identify the jammed subcarriers reliably and with low complexity. We assumed a destructive and elusive reactive jammer model that applies a zero-mean Gaussian jamming signal to the occupied channels. The performance of the variance detector is investigated analytically for OFDM-IM and OFDM-based systems under the given jammer model. The results showed that passive subcarriers of OFDM-IM inherently provide a better detection performance compared to the classical OFDM. Lastly, the analytical results are verified via simulations against both full-band and partial-band reactive jammers. Also, the effect of noise and the jamming power on the detection performance is investigated via extensive simulations.

Joint Design of Channel Training and Data Transmission for MISO-URLLC Systems

For the ultra-reliable low-latency communication (URLLC), the existing joint design algorithms of channel training and data transmission are not applicable due to the stringent reliability requirement and limited blocklength. To address this issue, we develop a low-complexity joint design framework for MISO communication based on the finite blocklength code (FBC). Specifically, an approximate bound of the packet error probability (PEP) is first derived and validated by practical modulation and coding schemes. It reveals the inherent tension between reliability, latency, and information bit number. Then, we formulate the joint design into a nonconvex optimization problem with the objective to maximize the information bit number. By exploiting the monotonicity of the PEP approximate bound, we provide closed-form solutions of power and blocklength allocation. Thereby, we develop a low-complexity algorithm to support the URLLC services aiming at the information bit number maximization. Furthermore, we investigate the joint designs to optimize the reliability, latency, and total energy, respectively, to fully meet the diverse demands of URLLC services. Finally, numerical results are provided to validate the proposed joint designs. The results show the outage capacity-based design severely underestimates the required wireless resources.

АЛГОРИТМ ОПТИМАЛЬНОГО ПОСИМВОЛЬНОГО ПРИЕМА ЧАСТОТНО-ЭФФЕКТИВНЫХ СИГНАЛОВ С КОРРЕКТИРУЮЩИМИ КОДАМИ В НЕДВОИЧНЫХ ПОЛЯХ ГАЛУА

The description of the developed algorithm for optimal symbol-by-symbol reception of signal structures based on frequency-efficient signals with two-dimensional «constellations» intensively used in applications and block correction codes in non-binary Galois fields is given. It is shown that symbol-by-symbol reception minimizes the error probability for code symbol or for information bit in contrast to the well-known maximum likelihood rule which minimizes the error-probability for code word. It is proved that the basis of this decoding algorithm is the spectral transform in the Walsh-Hadamard basis and the resulting complexity of the algorithm is determined by the dimension of the dual code which makes it promising for block correction codes with a high code rate (with low redundancy). The study of the error-performance characteristics (probability of erroneous reception for information bit) of the considered symbol-by-symbol reception algorithm was carried out by simulating it for signal structures based on signals with multilevel phase shift keying (PSK-16 signals) and on signals with quadrature amplitude manipulation (QAM-16 signals) and on simple correcting code with a general parity check in non-binary Galois field of size 16. It is shown that the use of the symbol-by-symbol reception algorithm provides an energy gain for the bit error probability from 0.00001 to 1.25…1.5 in relation to the considered signals without coding. As the bit error probability decreases the energy gains increase.

Multi-User Successive-Coded Spatial Modulation Scheme Based on Beamforming

By combining an existing successive-coded spatial shift keying (SC-SSK) modulation scheme with a modulation scheme that uses the traditional constellation, we propose a new successive coded spatial modulation (SC-SM) scheme. This scheme uses spatial domain and constellation domain to jointly transmit information bits, which increases the achievable rate of the system. In order to extend the SC-SM scheme to multi-user scenario, a multi-user SC-SM (MU-SC-SM) scheme based on beamforming is proposed. The proposed MU-SC-SM scheme not only eliminates the inter-user interference (IUI) and enhances the received signal-to-noise ratio (SNR) of the served user, but also resolves the conflict between beamforming and spatial modulation. The achievable rate, the bit-error-rate (BER) performance and computational complexity of the proposed MU-SC-SM scheme are analyzed in detail. The impacts of the imperfect channel state information on the BER performance are also analyzed. Simulations are carried out to verify that the proposed MU-SC-SM scheme is superior to existing multi-user spatial modulation schemes in BER performance.

Efficient polar coding scheme and implementation with shared information bits

Efficient polar coding scheme and implementation with shared information bits

MIMO spread spectrum GFDM communication systems with index modulation

SummaryIn the fourth‐generation communication system (4G), orthogonal frequency division multiplexing (OFDM) is widely used. However, due to the cyclic prefix (CP) being added, the low spectrum efficiency and high out‐of‐band radiation (OOB) cause OFDM not to be suitable for the beyond fifth‐generation (B5G) communication system. Therefore, to meet the rigorous demands in B5G for the Internet of Things (IoT) and massive machine‐type communications (MMTC), generalized frequency division multiplexing (GFDM) technology has received significant attention. On the other hand, index modulation (IM) can provide flexible settings of different parameters to achieve the ideal system goals. Therefore, this paper considers the combination of spread spectrum (SS) and IM under the framework of GFDM, called SS‐IM‐GFDM. In this scheme, the information bits are jointly conveyed by the indices of spreading codes and the conventional M‐ary modulated symbols, which increase the spectrum efficiency and improve the bit error rate performance. Furthermore, a low‐complexity maximum likelihood (ML) detector is proposed to recover the transmitted signal effectively at the receiver. Finally, the space‐time block code (STBC) is employed to construct the multi‐input multi‐output SS‐GFDM‐IM (MIMO SS‐GFDM‐IM) system to improve the system's reliability. The simulation results show that the proposed scheme is superior to the existing systems.

Short packet communication in underlay cognitive network assisted by an intelligent reflecting surface

AbstractWe propose short packet communication in an underlay cognitive radio network assisted by an intelligent reflecting surface (IRS) composed of multiple reconfigurable reflectors. This scheme, called the IRS protocol, operates in only one time slot (TS) using the IRS. The IRS adjusts its phases to give zero received cumulative phase at the secondary destination, thereby enhancing the end‐to‐end signal‐to‐noise ratio. The transmitting power of the secondary source is optimized to simultaneously satisfy the multi‐interference constraints, hardware limitations, and performance improvement. Simulation and analysis results of the average block error rates (BLERs) show that the performance can be enhanced by installing more reconfigurable reflectors, increasing the blocklength, lowering the number of required primary receivers, or sending fewer information bits. Moreover, the proposed IRS protocol always outperforms underlay relaying protocols using two TSs for data transmission, and achieves the best average BLER at identical transmission distances between the secondary source and secondary destination. The theoretical analyses are confirmed by Monte Carlo simulations.

An electro-optic reconfigurable OR to Ex-OR gate based on microring resonator loaded on Mach–Zehnder interferometric structure

In this paper, we proposed a novel electro-optic reconfigurable OR to Ex-OR gate and vice-versa. The proposed design consists of two microring resonators (MRR), employed in parallel, in a Mach–Zehnder interferometric (MZI) structure’s upper and lower arms with a tunable phase shifter attached in its lower arm, and can be controlled externally. The design will work as an OR gate when the phase of the tunable phase shifter is 0, and it will work as an Ex-OR gate when the phase is ‘π’. The micro-ring resonator employs an electro-optic modulation technique based on carrier injection, with electrical voltage sets 2 V and -1.85 V respectively for logic 1 and logic 0. We have also studied the performance of the Ex-OR gate when the phase shift deviates from the ideal required value. The extinction ratio obtained for Ex-OR operation is 17 dB and for OR operation it is 7.58 dB respectively. To demonstrate the circuit’s working operation at a data rate of 10 Gbps, @1550 nm time domain simulations were carried out with two electrical information bit streams fed into it.

Spatial time index non‐orthogonal multiple access for beyond 5G wireless networks

AbstractMultiple input multiple output (MIMO) based non‐orthogonal multiple access (NOMA) has been an evolving technique for 5G and beyond 5G wireless networks in the last decade. The goal of the proposed technique is to achieve improved spectral efficiency, with reduced complexity in the transceiver design. A novel time‐based spatial modulation‐MIMO based NOMA (SM‐MIMO‐NOMA) known as space time index‐based NOMA (STIN) has been proposed, which brings down the number of RF chains used at the transmitter end and improves the spectral efficiency in terms of bits per channel use. In the STIN algorithm, Joint GPS enabled channel estimation and threshold rate‐based power allocation are performed for user clustering and enhancing capacity. The transmit information bits are conveyed by the active antenna index as well as amplitude phase modulation by incorporating the block user‐symbol ratio at the base station. On the receiver side, user‐timeslot‐based successive interference cancellation with a maximum likelihood detector is implemented in the user equipment. STIN improves the bits per channel use with increasing modulation order and number of users by 33%. This novel algorithm has shown better performance in comparison with the existing NOMA‐based spatial modulation techniques in terms of average bit error rate, spectral efficiency, and complexity.

Mine Intelligent Receiver: MIMO-OFDM Intelligent Receiver for Mine Information Recovery

With the advancement of an intellectual and numerical society, the coal mining industry has also begun to change to intelligence. As an important aspect of intelligent coal mine construction, coal mine communication has put forward more stringent standards for communication quality. For the complex communication environment in mines, the transmission of communication signals is always damaged by various noises and interferences, resulting in serious distortion of the communication signals received at the receiving end. Therefore, the use of traditional receivers for information recovery has the problem of high bit error rate (BER), which cannot meet the standard of intelligent coal mine construction. Based on this, the aim of this research is to combine convolutional neural networks (CNN) and multi-input multi-output orthogonal frequency division multiplexing (MIMO-OFDM) communication systems to design an intelligent receiver model for complex mine communication systems. At the receiver side, CNNs are used to take the place of all the information processing processes. First, features are extracted from the received IQ signal by the convolutional neural network, and then the original information bit is recovered using a multi-label classifier to finally realize end-to-end information restoration. The experimental results show that the intelligent receiver model designed in this research has more accurate information recovery capability in the complex mine channel environment compared with the traditional receiver. In addition, they also verify that the intelligent receiver can still recover information effectively when the traditional receiver cannot recover information properly in the case of partial loss of received data.

Distributed CRC scheme for low-complexity successive cancellation flip decoding of polar codes

In this paper, we propose a novel successive cancellation flip (SCF) decoding to reduce the computational complexity compared to the conventional SCF decoding by using distributed CRC bits. The proposed decoding reduces the number of estimations for information bits by early termination of decodings for failed frames of the first SC decoding, while trying to minimize the additional sorting operations. Simulation results show that the proposed SCF decoding reduces the computational complexity of repeated SC decoding at least 27% compared to the conventional SCF decoding.

Simple Clock Drift Estimation and Compensation for Packet-Level Index Modulation and Its Implementation in LoRaWAN

Low-power wide-area network (LPWAN), which includes the long-range wide-area network (LoRaWAN) protocol, is an enabling technology that satisfy low power consumption and long-range communication. In many applications of LPWAN, an end node (EN) transmits data at regular intervals. Based on this, we had previously proposed the concept of packet-level index modulation (PLIM) to increase the number of information bits transmitted by one data packet. In PLIM, the generation interval between two consecutive packets is split into multiple time slots. Each EN transmits its packet in a specific combination of time slot and frequency channel, which represents the index, to convey additional information bits. To retrieve additional information, the gateway (GW) detects the time slot in which the data packet is being transmitted. Therefore, accurate synchronization between EN and GW is essential. However, clock drift occurs due to the inexpensive real-time clock oscillator on each EN, which results in timing misalignment between each node and the GW. This article proposes a simple clock drift estimation and compensation method for the PLIM. An experimental measurement is performed to model the clock drift. The numerical results obtained using the clock drift model show that it can accurately detect the time slot index under the influence of clock drift. Furthermore, PLIM is implemented on a commercial LoRaWAN node and GW to demonstrate its practicability.

Simulated Annealing Algorithm-Aided SC Decoder for Polar Codes

A new decoding scheme aided by simulated annealing algorithm is proposed to further improve the decoding performance of successive cancellation (SC) for polar codes at the short block. We use simulated annealing to revise the decoding result of SC which cannot pass the CRC check. To generate the new neighbors, the decoder flips one bit from the set of the least unreliable information bits each time in the estimated source vector of SC decoding. Euclidean distance is used to measure the gap between the new neighbor solution and the received word so that the decoder can obtain a global optimal solution. Simulation shows that the proposed decoder has a performance gain about 0.5 dB in terms of frame error rate (FER) under short blocks in the additive white Gaussian noise (AWGN) channel compared to other basic decoders, while keeping a low time cost through a parameter tuning process.