Coded Parity Packet Transmission Method for Two Group Resource Allocation

Gap value control is investigated when the number of source and parity packets is adjusted in a concatenated coding scheme whilst keeping the overall coding rate fixed. Packet-based outer codes which are generated from bit-wise XOR combinations of the source packets are used to adjust the number of both source packets. Having the source packets, the number of parity packets, which are the bit-wise XOR combinations of the source packets can be adjusted such that the gap value, which measures the gap between the theoretical and the required signal-to-noise ratio (SNR), is controlled without changing the actual coding rate. Consequently, the required SNR reduces, yielding a lower required energy to realize the transmission data rate. Integrating this coding technique with a two-group resource allocation scheme renders efficient utilization of the total energy to further improve the data rates. With a relatively small-sized set of discrete data rates, the system throughput achieved by the proposed two-group loading scheme is observed to be approximately equal to that of the existing loading scheme, which is operated with a much larger set of discrete data rates. The gain obtained by the proposed scheme over the existing equal rate and equal energy loading scheme is approximately 5 dB. Furthermore, a successive interference cancellation scheme is also integrated with this coding technique, which can be used to decode and provide consecutive symbols for inter-symbol interference (ISI) and multiple access interference (MAI) mitigation. With this integrated scheme, the computational complexity is signi cantly reduced by eliminating matrix inversions. In the same manner, the proposed coding scheme is also incorporated into a novel fixed energy loading, which distributes packets over parallel channels, to control the gap value of the data rates although the SNR of each code channel varies from each other

Adaptive interference mitigation with user grouping for fast transmission in cellular networks

Designing uplink systems which group users with adaptive interference mitigation techniques is the objective of this research. Reduction in error rates and improvement in the energy efficiency is expected with this approach in addition to spectral efficiency. This paper reports a study on interference mitigation and transmission designs for groups of users in the uplinks. New formulations for the interference mitigation are produced based on the minimum mean square error and successive interference cancellation approach. By reducing the interference, the energy efficiency can be maintained and improved although the number of users per group increases. The measured error rates of this approach with user grouping achieve gains between 1 to 3 dB against that of the existing approach. With reduced complexity, the proposed scheme should be viable for practical deployment

Experimental analysis on the transduction coefficient of a non-linear electromagnetic energy harvesting device with softening stiffness

Non-linear energy harvesting devices in the form of stiffness non-linearity have emerged as among the effective solutions to overcome the performance limit of linear energy harvesting devices. However, up to now, researches on the non-linear devices are only focusing on the ability to widen the bandwidth while the limit of employing linear transduction coefficient in a non-linear system has yet to be heavily discussed. This paper investigates on the transduction coefficient for both linear and non-linear systems of an electromagnetic energy harvesting device as a function of the excitation frequency. It is proven that the transduction coefficient of the nonlinear device is larger than its equivalent linear device, especially in the multi-stable solutions region. In common practice, the non-linearity in the non-linear system is considered weak, and its transduction coefficient is assumed to converge to the one produced by the linear system. The limits to which the transduction coefficient of a linear system can be employed on the non-linear system were drawn based on the experimental analysis conducted on the proposed device. The device was designed to perform as a linear or non-linear system, where the degree of non-linearity was changed by varying the gap between the magnets. The limit of the transduction coefficient was determined from the analysis of the harmonic ratio. The results show that the linear transduction coefficient is valid to be employed to the non-linear system when the harmonic ratio is less than five per cent at the multi-stable solutions regio

Physical layer security and energy efficiency over different error correcting codes in wireless sensor networks

Despite the rapid growth in the market demanding for wireless sensor networks (WSNs), they are far from being secured or efficient. WSNs are vulnerable to malicious attacks and utilize too much power. At the same time, there is a significant increment of the security threats due to the growth of the several applications that employ wireless sensor networks. Therefore, introducing physical layer security is considered to be a promising solution to mitigate the threats. This paper evaluates popular coding techniques like Reed solomon (RS) techniques and scrambled error correcting codes specifically in terms of security gap. The difference between the signal to nose ratio (SNR) of the eavesdropper and the legitimate receiver nodes is defined as the security gap. We investigate the security gap, energy efficiency, and bit error rate between RS and scrambled t-error correcting codes for wireless sensor networks. Lastly, energy efficiency in RS and Bose-Chaudhuri-Hocquenghem (BCH) is also studied. The results of the simulation emphasize that RS technique achieves similar security gap as scrambled error correcting codes. However, the analysis concludes that the computational complexities of the RS is less compared to the scrambled error correcting codes. We also found that BCH code is more energy-efficient than RS

5G NOMA user grouping using discrete particle swarm optimization approach

Non-orthogonal multiple access (NOMA) technology meets the increasing demand for high-seed cellular networks such as 5G by offering more users to be accommodated at once in accessing the cellular and wireless network. Moreover, the current demand of cellular networks for enhanced user fairness, greater spectrum efficiency and improved sum capacity further increase the need for NOMA improvement. However, the incurred interference in implementing NOMA user grouping constitutes one of the major barriers in achieving high throughput in NOMA systems. Therefore, this paper presents a computationally lower user grouping approach based on discrete particle swarm intelligence in finding the best user-pairing for 5G NOMA networks and beyond. A discrete particle swarm optimization (DPSO) algorithm is designed and proposed as a promising scheme in performing the user-grouping mechanism. The performance of this proposed approach is measured and demonstrated to have comparable result against the existing state-of-the art approach

Ant-colony and nature-inspired heuristic models for NOMA systems: a review

The increasing computational complexity in scheduling the large number of users for non-orthogonal multiple access (NOMA) system and future cellular networks lead to the need for scheduling models with relatively lower computational complexity such as heuristic models. The main objective of this paper is to conduct a concise study on ant-colony optimization (ACO) methods and potential nature-inspired heuristic models for NOMA implementation in future high-speed networks. The issues, challenges and future work of ACO and other related heuristic models in NOMA are concisely reviewed. The throughput result of the proposed ACO method is observed to be close to the maximum theoretical value and stands 44% higher than that of the existing method. This result demonstrates the effectiveness of ACO implementation for NOMA user scheduling and grouping

Energy-limited ant colony optimization with cooperative transmission

Cooperative transmission utilizes the presence of multiple radio transmission equipment including base stations, antennas and mobile stations to create transmission such that capacity and performance of the transmission are improved. This paper proposes a new transmission model embedded with a modified ant colony algorithm to improve transmission performance whilst reducing computational complexity

Defining factors in hospital admissions during COVID-19 using LSTM-FCA explainable model

Outbreaks of the COVID-19 pandemic caused by the SARS-CoV-2 infection that started in Wuhan, China, have quickly spread worldwide. The current situation has contributed to a dynamic rate of hospital admissions. Global efforts by Artificial Intelligence (AI) and Machine Learning (ML) communities to develop solutions to assist COVID-19-related research have escalated ever since. However, despite overwhelming efforts from the AI and ML community, many machine learning-based AI systems have been designed as black boxes. This paper proposes a model that utilizes Formal Concept Analysis (FCA) to explain a machine learning technique called Long-short Term Memory (LSTM) on a dataset of hospital admissions due to COVID-19 in the United Kingdom. This paper intends to increase the transparency of decision-making in the era of ML by using the proposed LSTM-FCA explainable model. Both LSTM and FCA are able to evaluate the data and explain the model to make the results more understandable and interpretable. The results and discussions are helpful and may lead to new research to optimize the use of ML in various real-world applications and to contain the disease

Road Marker Classification Mechanism Using Slope Contour Analysis In Rainy Days

The first step of the approach is to select an ROI, turn it into a warped perspective or birds-eye view, divide equally ithorizontally, and then divide each of them vertically into group 1 and group 2. Second, we eliminate and ignore non-roadmarkercontour by applying minimum and maximum RGB value and contour size filters. Last we identify a unique combination of the contour present in group 1 and group 2

Road Marker Classification Mechanism Using Slope Contour Analysis In Rainy Days

A binary map is generated from the recorded video frames to calculate points for contours in the region of interest (ROI) using an approximation function. Any 4-points with a parallel slope across the side are recognized as road marker contours. For the first and last road marker contours, a slope value from both centroids is the determination of its class. A confusion matrix table is created to measure the classification accuracy