A Proficient Fair Resource Allocation in the Channel of Multiuser Orthogonal Frequency Division Multiplexing using a Novel Hybrid Bat-Krill Herd Optimization

Hindumathi, V.; Reddy, K. Rama Linga

doi:10.1007/s11277-021-08519-8

Cited by 4 publications

(2 citation statements)

References 32 publications

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“…Future wireless networks will not only provide much higher spectral efficiency/data rates and lower latency but will also provide new services and technologies that can be applied in various vertical industries [1]. The presence of ubiquitous connections and the growing number of devices that are connected to the internet are expected to cause a challenge for efficient and reliable resource management systems [2][3][4]. Moreover, the rapid growth of the massive number of new devices that are connected to the internet and the Internet of Things (IoT) is expected to cause a serious risk to network security if not manipulated properly [5].…”

Section: Introductionmentioning

confidence: 99%

A Review of Fundamental Optimization Approaches and the Role of AI Enabling Technologies in Physical Layer Security

Tefera

Jin

Zhang

2022

Sensors

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With the proliferation of 5G mobile networks within next-generation wireless communication, the design and optimization of 5G networks are progressing in the direction of improving the physical layer security (PLS) paradigm. This phenomenon is due to the fact that traditional methods for the network optimization of PLS fail to adapt new features, technologies, and resource management to diversified demand applications. To improve these methods, future 5G and beyond 5G (B5G) networks will need to rely on new enabling technologies. Therefore, approaches for PLS design and optimization that are based on artificial intelligence (AI) and machine learning (ML) have been corroborated to outperform traditional security technologies. This will allow future 5G networks to be more intelligent and robust in order to significantly improve the performance of system design over traditional security methods. With the objective of advancing future PLS research, this review paper presents an elaborate discussion on the design and optimization approaches of wireless PLS techniques. In particular, we focus on both signal processing and information-theoretic security approaches to investigate the optimization techniques and system designs of PLS strategies. The review begins with the fundamental concepts that are associated with PLS, including a discussion on conventional cryptographic techniques and wiretap channel models. We then move on to discuss the performance metrics and basic optimization schemes that are typically adopted in PLS design strategies. The research directions for secure system designs and optimization problems are then reviewed in terms of signal processing, resource allocation and node/antenna selection. Thereafter, the applications of AI and ML technologies in the optimization and design of PLS systems are discussed. In this context, the ML- and AI-based solutions that pertain to end-to-end physical layer joint optimization, secure resource allocation and signal processing methods are presented. We finally conclude with discussions on future trends and technical challenges that are related to the topics of PLS system design and the benefits of AI technologies.

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Section: Introductionmentioning

confidence: 99%

A Review of Fundamental Optimization Approaches and the Role of AI Enabling Technologies in Physical Layer Security

Tefera

Jin

Zhang

2022

Sensors

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“…The optimization of packet sizes is a popular subject in WSN research. Several research have been conducted in order to improve energy economy in terms of power and data rates, however an experiment using CR and dynamic spectrum access revealed that fixed-size packets get better throughput than variable-size packets [19][20]. In WSNs, the phrase "energy dissipation" is often used.…”

Section: Introductionmentioning

confidence: 99%

Design of an adaptive CRSN using OFDM

Kandasamy¹,

Ravi²

2022

Wireless Netw

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Cognitive Radio (CR) is a novel concept that enables wireless devices to detect and adapt to their surroundings in order to enhance communication quality. The cognitive radio sensor network (CRSN) has proved to be a cost-effective solution to the spectrum constraints that wireless sensor networks (WSN). Optimizing the optimum packet size is regarded to be an essential energy constrained issue to address the practical implementation of CRSN out of all the difficulties. Small packets generate data traffic in device-to-device communication, a flexible way for transferring data in wireless networks, while big packets may cause data bit corruption, requiring retransmission at a greater frequency. This will not allow access from the secondary network to the main network, since it may cause further disturbance. To maximise the WSN's energy efficiency, the optimum packet size for CRSN should be utilised while keeping the same degree of interference as the primary licenced users (PU). The purpose of this article is to examine formulations for small, medium, and large packet sizes in order to determine the optimum packet size for adaptive CRSN. To do so, CR requires a flexible physical layer capable of carrying out the necessary tasks. This article examines the performance of CR systems that use the Orthogonal Frequency Division Multiplexing (OFDM) technique, which is a possible transmission technology for CR. Interference delays are minimised, and the channels are ultimately utilised effectively. This article shows that medium-sized packets are the optimum choice for achieving the greatest performance on the Cognitive Radio Sensor Network (CRSN). The Jellyfish Search Optimization algorithm (JSO) and the hybrid Momentum Search Algorithm (MSA) are hybridised, and results are achieved. This makes it possible to calculate precise packet sizes. The suggested approach decision outperforms existing methods like the Group Sparse Optimization algorithm and the Throughput Maximization Algorithm. The MATLAB / SIMULINK Platform were used to get the results.

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Multi-source Frequency Modulation Optimization Strategy Based on Multi-objective Two-Layer Game

Yang,

Chen,

Zhao

et al. 2024

J. Electr. Eng. Technol.

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A Proficient Fair Resource Allocation in the Channel of Multiuser Orthogonal Frequency Division Multiplexing using a Novel Hybrid Bat-Krill Herd Optimization

Cited by 4 publications

References 32 publications

A Review of Fundamental Optimization Approaches and the Role of AI Enabling Technologies in Physical Layer Security

A Review of Fundamental Optimization Approaches and the Role of AI Enabling Technologies in Physical Layer Security

Design of an adaptive CRSN using OFDM

Multi-source Frequency Modulation Optimization Strategy Based on Multi-objective Two-Layer Game

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