Introductory Chapter: Primary and Secondary Users in Cognitive Radio-Based Wireless Communication Systems

Moghaddam, Shahriar Shirvani

doi:10.5772/intechopen.82033

Cited by 5 publications

(3 citation statements)

References 35 publications

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“…For one OFDM transmission, DSRC required 64 FFT subcarriers, while mobile networks required 256 FFT subcarriers. With DSRC OFDM, these FFT subcarriers are matched with padding zeros, making them comparable to the mobile network subcarrier [32][33][34]. Each OFDM symbol associated with I/Q signaling in this mathematical model will be:…”

Section: Mathematical Model For Physical Layer Ofdmmentioning

confidence: 99%

DAHP–TOPSIS-Based Channel Decision Model for Co-Operative CR-Enabled Internet on Vehicle (CR-IoV)

et al. 2021

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The Internet of Vehicles (IoV) is an important idea in developing intelligent transportation systems and self-driving cars. Vehicles with various wireless networking options can communicate both inside and outside the vehicles. IoVs with cognitive radio (CR) enable communication between vehicles in a variety of communication scenarios, increasing the rate of data transfer and bandwidth. The use of CR can meet the future need for quicker data transport between vehicles and infrastructure (V2I). Vehicles with CR capabilities on VANET have a different appearance than regular VANET vehicles. This paper aims to develop effective spectrum management for CR-equipped automobiles. An improved channel decision model has been proposed with proven outcomes to boost the pace of transmission, eliminate end-to-end delays, and minimize the number of handoffs. Many high-bandwidth channels will be used in the near future to communicate large-sized multimedia content between vehicles and roadside units (RSU) for both entertainment and safety purposes. Co-operative sensing promotes energy-constrained CR vehicles for sensing a wide spectrum, resulting in high-quality communication channels for requesting vehicles. Our research on the CR-VANET focuses on channel decision instead of spectrum sensing and it differs from previous studies. We used the DAHP–TOPSIS model under multi-criteria decision analysis (MCDA), a sub-domain of operations research, to boost profits, i.e., transmission rate with less computing time. We constructed a test-bed in MATLAB and carried out several analyses to demonstrate that the suggested model performs better than other parallel MCDA models because there has been a limited amount of research work conducted with CR-VANET

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Section: Mathematical Model For Physical Layer Ofdmmentioning

confidence: 99%

DAHP–TOPSIS-Based Channel Decision Model for Co-Operative CR-Enabled Internet on Vehicle (CR-IoV)

et al. 2021

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“…Furthermore, aspects of secure communication are also added and the power efficiency of the network is maximized under practical secrecy rate and energy harvesting constraints. In order to improve the secrecy rate of secondary users [96], techniques of multiple antennas, cooperative relaying, jamming and artificial noise aided techniques are used. The transmission beamforming and artificial noise aided covariance were jointly optimized to satisfy secrecy rates of both primary and secondary users [96] and energy harvesting of receivers.…”

Section: Practical Aspects Of Deploying Green Nomamentioning

confidence: 99%

“…In order to improve the secrecy rate of secondary users [96], techniques of multiple antennas, cooperative relaying, jamming and artificial noise aided techniques are used. The transmission beamforming and artificial noise aided covariance were jointly optimized to satisfy secrecy rates of both primary and secondary users [96] and energy harvesting of receivers. Power optimization was carried under both perfect CSI and bounded CSI error model.…”

Section: Practical Aspects Of Deploying Green Nomamentioning

confidence: 99%

A New Green Prospective of Non-orthogonal Multiple Access (NOMA) for 5G

et al. 2020

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Energy efficiency is a major concern in the emerging mobile cellular wireless networks since massive connectivity is to be expected with high energy requirements from the network operators. Non-orthogonal multiple access (NOMA) being the frontier multiple access scheme for 5G, there exists numerous research attempts on enhancing the energy efficiency of NOMA enabled wireless networks while maintaining its outstanding performance metrics such as high throughput, data rates and capacity maximized optimally.The concept of green NOMA is introduced in a generalized manner to identify the energy efficient NOMA schemes. These schemes will result in an optimal scenario in which the energy generated for communication is managed sustainably. Hence, the effect on the environment, economy, living beings, etc is minimized. The recent research developments are classified for a better understanding of areas which are lacking attention and needs further improvement. Also, the performance comparison of energy efficient, NOMA schemes against conventional NOMA is presented. Finally, challenges and emerging research trends, for energy efficient NOMA are discussed.

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On the Performance of Mean-Based Sort for Large Data Sets

Moghaddam

2021

IEEE Access

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Computer and communication systems and networks deal with many cases that require rearrangement of data either in descending or ascending order. This operation is called sorting, and the purpose of an efficient sorting algorithm is to reduce the computational complexity and time taken to perform the comparison, swapping, and assignment operations. In this paper, we propose an efficient mean-based sorting algorithm that sorts integer/non-integer data by making approximately the same length independent quasi-sorted subarrays. It gradually finds sorted data and checks if the elements are partially sorted or have similar values. The elapsed time, the number of divisions and swaps, and the difference between the locations of the sorted and unsorted data in different samples demonstrate the superiority of the proposed algorithm to the Merge, Quick, Heap, and conventional mean-based sorts for both integer and non-integer large data sets which are random or partially/entirely sorted. Numerical analyses indicate that the mean-based pivot is appropriate for making subarrays with approximately similar lengths. Also, the complexity study shows that the proposed mean-based sorting algorithm offers a memory complexity same as the Quick-sort and a time complexity better than the Merge, Heap, and Quick sorts in the best-case. It is similar to the Merge and Heap sorts in view of the time complexity of the worst-case much better than the Quick-sort while these algorithms experience identical complexity in the average-case. In addition to finding part by part incremental (or decremental) sorted data before reaching the end, it can be implemented by parallel processing the sections running at the same time faster than the other conventional algorithms due to having independent subarrays with similar lengths.

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Introductory Chapter: Primary and Secondary Users in Cognitive Radio-Based Wireless Communication Systems

Cited by 5 publications

References 35 publications

DAHP–TOPSIS-Based Channel Decision Model for Co-Operative CR-Enabled Internet on Vehicle (CR-IoV)

DAHP–TOPSIS-Based Channel Decision Model for Co-Operative CR-Enabled Internet on Vehicle (CR-IoV)

A New Green Prospective of Non-orthogonal Multiple Access (NOMA) for 5G

On the Performance of Mean-Based Sort for Large Data Sets

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