Non-Binary Low-Density Parity-Check (LDPC) codes have gained significant attention due to their remarkable error correction capabilities in various communication systems. Decoding algorithms play a pivotal role in realizing the potential of non-binary LDPC codes. This paper provides a comprehensive review and analysis of non-binary LDPC decoding algorithms, focusing on their efficiency, complexity, and performance. Furthermore, recent advancements and innovations in non-binary LDPC decoding algorithms are discussed, such as improved message passing strategies, layered decoding techniques, and adaptive algorithms. The review also highlights challenges and open research directions in non-binary LDPC decoding, such as mitigating error floors, reducing decoding complexity, and integrating with emerging communication technologies. Finally, the paper draws conclusions on the current state of non-binary LDPC decoding algorithms, underscoring their promising applications in wireless communication, visible light communication (VLC), and power line communication (PLC). Simulation results demonstrate a marked improvement in bit error rate performance for both VLC and PLC systems, highlighting the practical potential of these advanced decoding techniques.

This paper investigates the performance of coded massive multiple-input multiple-output (MIMO) systems utilizing Orthogonal Time Frequency and Space modulation (OTFS). Our innovative approach harnesses the power of OTFS modulation, a cutting-edge modulation technique renowned for its capacity to mitigate the detrimental effects of time-varying channels. Additionally, we introduce a comprehensive system model that incorporates the pivotal elements of channel coding and decoding The system model incorporates channel coding and decoding to improve the bit error rate and enhance the overall performance. The numerical results show that the proposed scheme outperforms existing techniques in terms of BER and spectral efficiency, especially in high-mobility scenarios. Additionally, the proposed system is shown to be robust against channel estimation errors and Doppler spread. Overall, the results suggest that coded massive MIMO using OTFS modulation is a promising solution for future wireless communication systems.

A compact fork‐shaped MIMO antenna system with a 2 × 2 arrangement with four elements is presented. The MIMO elements are arranged orthogonally to achieve a small overall size of 36 × 28 mm2 and a wide bandwidth for 5G mm‐wave applications. MIMO elements are positioned 4 mm from each corner of the substrate to achieve compact size and minimize coupling. To improve the isolation of the proposed MIMO system, a metamaterial slab is inserted in the middle of the substrate and between radiating elements of the MIMO antenna system, which improves isolation by 10 dB within the whole operating band and achieves maximum isolation of 65 dB at 34.5 GHz. The proposed MIMO system operates in the Ka‐band frequency range of 22–50 GHz with isolation greater than 30 dB and efficiency above 80% across the entire frequency spectrum for 5G communication. Additionally, the performance parameters of MIMO are examined, including diversity gain (DG) and envelope correlation coefficient (ECC), and it is found that they meet the required standards of DG approximately equal to 10 and ECC < 0.05. The proposed MIMO system has been fabricated and tested. The measured results are consistent with the design of the simulated structure using the CST Microwave Studio (CSTMWS) simulator.

The paper introduces two decoding techniques based on grouping for symbol flipping non-binary LDPC codes. Firstly, a new technique of adaptive grouping of variable nodes in each iteration using bit reliability and majority voting of each received symbol is presented. Grouping of variable nodes and the subsequent decoding are based on individual symbol reliability and majority voting. To form groups adaptively, the cumulative density of variable nodes is used where a high priority group is considered to contain the most unreliable variable nodes and is decoded while the second priority group contains variable nodes having a second level of reliability and so on. Secondly, a fixed grouping technique is applied to symbol flipping decoding of non-binary LDPC codes. In the fixed grouping decoding, each group contains an equal number of variable nodes, and selected symbols in each group are flipped according to pre-defined flipping criteria. Numerical results and analysis show that the proposed group-based hard decision symbol flipping decoding algorithms have the advantage of reduced computational complexity and show better performance. Therefore, the proposed algorithms can be considered for applications like data storage and mobile communication.

This article presents a compact ultra-wideband (UWB) circular monopole antenna with a frequency-selective surface (FSS) for gain enhancement. The proposed antenna has a circular patch with circular cuts at the edges and is excited by a microstrip feed. The bottom plane is truncated and further modified by two triangular cuts at the sides and one rectangular cut in the middle to improve the radiation characteristics of the UWB antenna. The antenna is designed on an FR-4 substrate with a thickness of 1.6 mm, a relative permittivity of 4.3, and planner dimensions of 30 mm × 30 mm. To improve the proposed antenna’s gain, an FSS is designed that consists of periodic unit cells of metal printed on the upper layer of an FR-4 substrate with dimensions of 0.11λ × 0.11λ at the lowest operating frequency of 3.3 GHz. The FSS shows a very low transmission coefficient and linearly reducing reflection phase with increasing frequency over a frequency range of 3.3–10.8 GHz. The gain of the proposed antenna is increased from 3 dB to 8.1 dB at 9 GHz by placing the antenna on the FSS. Moreover, the prototype of the proposed antenna is fabricated, and the experimental results are measured, which show close agreements with simulated results. The FSS-based antenna has directional radiation patterns, making it a potential candidate for ground-penetrating radar and UWB applications.

This paper introduces an adaptive technique for grouping variable nodes in decoding non-binary LDPC codes that involve symbol flipping. The technique considers both the individual symbol reliability and majority-based voting when grouping variable nodes in each iteration. Groups are formed based on the cumulative density of the variable nodes, with the least reliable variable nodes given the highest priority. The decoding algorithm then proceeds to decode subsequent groups in order of decreasing priority. The results of numerical analysis demonstrate that this approach strikes a balance between computational complexity and bit error rate performance, making it suitable for various applications, such as data storage and mobile networks.

This paper proposes the distributed Reed–Solomon (RS)-coded spatial modulation (DRSC-SM) scheme over quasi-static Rayleigh fading channel. Two different RS codes are used, one having a smaller minimum distance at the source and the other having a larger minimum distance at the relay. In order to obtain an optimized code at the destination, a proper encoding strategy must be adapted at the relay. Thus, an efficient design approach is proposed that suitably selects the symbols at the relay. Using this optimized approach as a benchmark, another design is proposed to achieve reduced complexity. To jointly decode the source and relay RS codes, three different decoding algorithms known as the naive, smart and improved smart algorithms are presented. Monte Carlo simulated results reveal that the proposed DRSC-SM scheme utilizing the improved smart decoding algorithm outperforms its counterpart DRSC-SM scheme employing the naive and smart decoding algorithms under identical conditions. The simulation results also validate the superiority of the proposed DRSC-SM scheme over its corresponding coded noncooperative scheme under the same decoding algorithm.

The fundamental characteristics of chaos, including sensitivity to beginning conditions and unpredictability, render it a prime candidate for cryptographic applications. This research introduces an encryption methodology for effective and safe image encryption. The encryption system has two ciphering phases and a substitution phase. This study proposes a method for key creation. The design of a pseudo-random number generator utilized for key generation is founded on chaotic algorithms. The chaotic map will be employed in encryption systems owing to its superior security. NIST tests are employed to assess the randomness of the proposed PRNG sequences. The subsequent part presents a security study of the suggested picture encryption approach to evaluate its efficacy. The statistical analysis now confirms that the technique is secure and efficient for encrypting both basic and complicated images, whether in monochrome or color. Through a comparison with previous chaotic investigations, it is evident that our method is competitive with earlier efforts.

In Wireless Sensor Networks (WSNs), the sensor nodes are expected to remain autonomous for a long time and the communication must be successful. So, energy efficiency and communication reliability are the main challenges for WSN. Routing protocols and, in particular, clustering is the key to energy constraints in WSNs. In a loss milieu, data shared between nodes is susceptible to corruption by errors caused by signal fading, random noise, and some other forces. For this reason, channel coding is necessary to assure efficient and reliable transmission. Therefore, energy efficiency and reliability of communications are the most crucial factors in the design of an efficient cluster-based routing protocol. In this context, to raise the reliability of the communication link and minimize the necessary transmission energy, a new adaptive coding routing protocol is proposed, which implements RS and LDPC codes to a routing protocol. Simulation results show that our proposed protocol improves energy consumption, network lifetime, stability, and throughput compared to LEACH and BRE-LEACH. In addition, it reaches a good BER performance and coding gain by using the LDPC code.

In this article, two algorithms for improving the bit error rate performance of the non-binary LDPC codes over higher order modulation are proposed. The first algorithm is the predictive syndrome based symbol flipping decoding algorithm. The flipping function of this algorithm utilizes the channel reliability to identify the least reliable symbol position. In Algorithm 1, if the predicted symbol value satisfies the check sum, then the candidate symbol value is declared as correct otherwise that value is adjusted and sent back to the QAM detector. Algorithm 2 in this paper is an improvement to iterative joint detection-decoding algorithm by using the method of iterative hard decision based majority logic to select the new candidate symbol value. The feedback value to the QAM detector is adjusted by using Euclidean distance between the current symbol and the newly selected symbol value. Numerical results and complexity analysis show that the proposed schemes have better bit error rate versus complexity trade-off in comparison to some of the existing algorithms.

The protection of turbine generator systems is an important factor that must be considered in power plant for efficient production of electricity. This project deals with temperature level monitoring of the power generator and it will be compared with the predetermined standard value through an LM35 sensor. Once it exceeds the predetermined value then the cooling fan will automatically turn on which will be useful to prevent the generator from internal winding thermal failure. The protection system consists of 16x2 LCD display, LM35 temperature sensor, a coolant fan and a microcontroller [ATMEGA328P]. The internal winding temperature of generator is increased as the turbine is rotated at its axis which may lead to major damages in the axial position and shafts of the power generator. To overcome this, an LM35 sensor is connected and linked with the microcontroller which monitors the temperature and once it exceeds the standard temperature the coolant fan automatically is turned on by the microcontroller and the heat of the steam will be countered by the cooling air produced by the coolant fan. The fan runs continuously until the temperature is sensed to have dropped below the standard temperature. At the same instances, the LCD display outputs readable current temperature parameters for the operator. The protection of power generator system is a vital component in power plant for efficient production of electricity.

This paper proposes a distributed RS coding scheme to construct a subcode at the destination. Practically in any distributed coding scheme, an appropriate encoding strategy at the relay plays a vital role in achieving an optimized code. Therefore, the authors have proposed an efficient approach for proper selection of information at the relay based on subspace approach. Using this approach as the proper benchmark, another more practical selection approach with low complexity is also proposed. Monte Carlo simulations demonstrate that the distributed RS coding scheme under the two approaches can achieve nearly the same bit error rate performance. Furthermore, to jointly decode the source and relay codes at the destination, two different decoding algorithms named as naive and smart algorithms are proposed. The simulation results reveal that the advantage of smart algorithm as compared to naive one. The proposed distributed RS coding scheme with smart algorithm outperforms its non-cooperative scheme by a gain of 2.4–3.2 dB under identical conditions. Moreover, the proposed distributed RS coding scheme outperforms multiple existing distributed coding schemes, making it an excellent candidate for the future distributed coding wireless communications.

The demand for Telehealth is rapidly increasing worldwide. Digital solutions in the current epidemic are revealing the powers and flaws of current Telehealth infrastructures. Telehealth brings remote access to medical facilities and covering the extent of physicians and health services. The outbreak of COVID-19 emphasizes the necessity for timely tracking of persons who are infected, and preferably, their connections. Telehealth facilities are speedily becoming a frontline force in the struggle to lessen healthcare-linked COVID-19 spreads, and eventually shielding healthcare professional. Whereas telehealth can substitute competence and accessibility, its dependence on real-time communication of medical records over the cloud also generates danger. At each phase of the practice, hostile measures may happen, together with diagnostic blunders, technical problems, and patient confidentiality and safety defilements. This paper developed a highly secure and robust decoder for the Telehealth model to monitor the patients' vital signs and psychological signals. The proposed Telehealth system reduced the transmission power and congestion on the database and ensured secured reliable data at the receiving end.

This paper addresses the problem of decoding non-binary low density parity check codes(LDPC) over finite field GF(q) using symbol flipping approach.To achieve low complexity reliable communication, three new algorithms for improving the bit error rate performance of the non-binary LDPC decoder are presented.The first type is the symbol flipping decoding algorithm using a flipping function based on the channel reliability to identify the least reliable symbol position.In this algorithm, if the predicted symbol value satisfies the check sum, then the value is declared as correct otherwise the value is adjusted and sent back to the QAM detector.Algorithms 2 in this paper is an improvement to iterative joint detection-decoding algorithm by using the method of iterative hard decision based majority logic to select the new candidate symbol value.The feedback value to the QAM detector is adjusted by using Euclidean distance between the current symbol and the newly selected symbol value.Algorithm 3 is a low complexity version of Algorithm 2 which is derived by applying a majority voting scheme.In the majority voting scheme, symbols are short listed first by voting and all the computation are carried out only for the short listed least reliable symbols which significantly lowers the processing complexity.Numerical results and complexity analysis show that the proposed methods have good bit error rate versus complexity trade-off for various applications when compared with some existing algorithms.

This paper proposes a distributed RS coding scheme which is comprised of two different ReedSolomon (RS) codes over fast Rayleigh fading channel. Practically in any distributed coding scheme, an appropriate encoding strategy at the relay plays a vital role in achieving an optimized code at the destination. Therefore, the authors have proposed an efficient approach for proper selection of information at the relay based on subspace approach. Using this approach as the proper benchmark, another more practical selection approach with low complexity is also proposed. Monte Carlo simulations demonstrate that the distributed RS coding scheme under the two approaches can achieve nearly the same bit error rate (BER) performance. Furthermore, to jointly decode the source and relay codes at the destination, two different decoding algorithms named as naive and smart algorithms are proposed. The simulation results reveal that the advantage of smart algorithm as compared to naive one. The proposed distributed RS coding scheme with smart algorithm outperforms its non-cooperative scheme by a gain of 2.4-3.2 dB under identical conditions. Moreover, the proposed distributed RS coding scheme outperforms multiple existing distributed coding schemes, making it an excellent candidate for the future distributed coding wireless communications.

The main challenge for hardware implementation of non-binary LDPC decoding is the high computational complexity and large memory requirement. To address this challenge, five new low complexity LDPC decoding algorithms are proposed in this paper. The proposed algorithms are developed specifically towards the low complexity, yet effective, decoding of the NB LDPC codes. The proposed decoding algorithms update, iteratively, the hard decision received vector to search for the valid codeword in the vector space of Galois field (GF). The selection criterion for least reliable symbol positions is based on the information from the failed checks and the reliability information from the Galois field structure as well as from the received channel soft information. To choose the correct value for the candidate symbol, two methods are used. The first method is based on the prediction of the error symbol from the set of Galois field symbols which maximize an objective function. In the second method, individual bits are flipped based on the reliability information obtained from the channel. Algorithms 1 and 2 flip a single symbol per iteration whilst the other three algorithms 3, 4 and 5 flip multiple symbols in each iteration. The proposed voting based Algorithms 1, 2 and 5 first short list the unreliable positions using a majority voting scheme and then choose the candidate symbol value from the set of the symbols in GF(q) while not violating the field order q. These methods simplify the decoding complexity in terms of computation and memory. Results and analysis of these algorithms show an appealing tradeoff between computational complexity and bit error rate performance for NB LDPC codes.

In this paper, we present two low complexity algorithms to decode non-binary LDPC codes. The proposed decoding algorithms update iteratively the hard decision received vector to search for a valid codeword in the vector space of Galois field (GF). The selection criterion for the position of unreliable symbols is based on failed checks and the information from the Galois field structure. In the first proposed algorithm, the flipping function is calculated for all symbols of the received sequence and multiple symbols are flipped in each iteration while in the second proposed algorithm, a single symbol is flipped per iteration. In the second method, unreliable positions are short-listed by using a majority voting scheme, and then the flipping function is computed to predict candidate symbols from the set of symbols in GF(q) while not violating the field order q. The proposed methods reduce the decoding complexity and memory use. The results of the algorithms show appealing tradeoffs between complexity and bit error rate performance for non-binary LDPC codes.

Secure and reliable information flow is one of the main challenges in social IoT and mobile networks. Information flow and data integrity is still an open research problem. In this paper, we develop new methods of constructing systematic and regular Low-Density Parity-Check Matrices (LDPCM), inspired by the structure of the Sarrus method and geometric designs. Furthermore, these codes have cyclic structure and therefore, are less complex in computation and also require less memory in hardware implementation. Besides, an optimal method of post-processing for deleting girths four is presented. Numerical results show that the codes constructed by these methods perform well over the additive white Gaussian noise (AWGN) channel when decoded with the sum-product LDPC iterative algorithms. The proposed methods can be very efficient in terms of reducing memory consumption and improving the convergence speed of the decoder particularly in IoT and mobile networks.

The present study has analyzed the impact of COVID-19 on the stock market. The study was intended in the context of Pakistan Stock Exchange. The paper attempted on the basis of two major objective i.e. analyzed direct impact of COVID-19 on the stock market and the COVID-19 impact on foreign markets spillover effects on Pakistan Stock Exchange. The paper has adopted conventional t-test and Mann Whitney test on the average return on the basis of stock market indexes. The results have been estimated on two basis i.e. domestic & foreign timeline. Three event windows were selected for the estimation of average return i.e. pre-event window (starting time of COVID-19), short-event window (increasing time of COVID-19 cases) and long-event window (Peak time of COVID-19). The time period has been taken from January 1st to 30th December 2020. The stock markets of Pakistan, India, Canada, Japan, UK, & United States were included in the study. The findings show (1) COVID-19 has negative but limited impact on the stock market; (2) there is an evidence of spillover effect of COVID-19 on Europe and US markets on Pakistan Stock Exchange. The findings contribute towards the economic and financial impact of COVID-19 in the context of stock market. The proof has been received that the Europe and US markets have impact on the Asian Stock Markets.

LDPC codes are gaining attention due to their excellent performance but still there are a lot of challenges in the hardware implementation. Due to high complexity, LDPC codes generally offer high processing delays which makes them impractical for many applications. Efforts have been made to keep a good tradeoff between the complexity and performance. Quasi cyclic LDPC codes have the advantage of both encoding and decoding over the conventional LDPC (non-structured) as they reduce the hardware complexity greatly. It has simplified the check and variable node interconnections. QC LDPC has limited decoding performance compared to unstructured random LDPC codes. Different architectures have been proposed to improve the throughput as well as reduce the complexity.