Resource allocation algorithm for downlink MIMO‐OFDMA based cognitive radio networks in spectrum underlay scenario

Mohammadi, Mahla; Andargoli, Seyed Mehdi Hosseini

doi:10.1049/iet-com.2019.0512

Cited by 5 publications

(4 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…where t BSR is the time to transfer the BSR frame, t TF is the time for the TF frame transmission, and t MBA is the transmission time for the MBA frame, and both are fixed values. Substituting Equations ( 20), (21), and ( 24) into (22), the following expression is obtained:…”

Section: Throughput Of Pumentioning

confidence: 99%

“…Recently, there has been some work to evaluate the performance of CR-OFDMA systems. In [20,21], the author proposed a resource allocation method in OFDMA-based CR networks to improve the throughput of CRN. A downlink resource allocation strategy for CR-OFDMA systems is proposed in [22], which maximizes the total throughput for the CR network under the total power constraint of the cognitive base station and the interference power constraint of the PU.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Performance Analysis of QoS-Oriented OFDMA Protocol Based on IEEE 802.11ax for Cognitive Radio Network

Yang

Gao

et al. 2023

Applied Sciences

View full text Add to dashboard Cite

To improve the quality of service (QoS) on the internet of medical things, a cognitive radio (CR) protocol based on orthogonal frequency division multiple access (OFDMA) is proposed, named CR-OFDMA. In this protocol, we divide a complete channel into multiple orthogonal subchannels and enhance the subchannel assignment scheme, which achieves QoS improvement under consideration of priority and fairness. Furthermore, we improve spectrum resource utilization by fully utilizing the remaining subchannels, feedback slots, and backoff slots. Then, a two-dimensional Markov model is established to describe the dynamic characteristics of the protocol operation, where the backoff stage and the backoff counter value constitute the system state. By establishing the traffic conservation equations for the system operation, the transmission probability and collision probability are calculated, and expressions of system throughput, channel utilization, and fairness index are derived. Finally, numerical results validate the advantages of CR-OFDMA.

show abstract

Section: Throughput Of Pumentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Performance Analysis of QoS-Oriented OFDMA Protocol Based on IEEE 802.11ax for Cognitive Radio Network

Yang

Gao

et al. 2023

Applied Sciences

View full text Add to dashboard Cite

show abstract

“…Therefore, wireless networks are facing serious problems of relative "shortage" and "waste" of spectrum resources. The root cause of these problems lies in the contradiction that the centralized static network is difficult to adapt to the dynamic changes of the environment and avoiding or eliminating the interference to the primary user (PU), while ensuring the normal communication of the secondary user (SU) [7][8][9][10][11]. An effective method is to use the beamforming technology for interference control, which well solves the coexistence problem of the PU and the cognitive user (CU) [2][3][4].…”

Section: Introductionmentioning

confidence: 99%

“…An effective method is to use the beamforming technology for interference control, which well solves the coexistence problem of the PU and the cognitive user (CU) [2][3][4]. This is because the beamforming technology is a spatial interference suppression technology [8][9][10][11][12][13][14][15], which can adaptively adjust the antenna array pattern according to the changes in the environment, and align the main beam at the desired signal with zero trapping or the low sidelobe is aligned with the interference signal, which has the characteristics of suppressing interference, improving the signal transmission quality and increasing the spectrum utilization. By selecting the optimal beamforming weight vector at the transmitting and receiving end, the communication quality of the SU can be optimized while suppressing the interference to the primary user, and the normal communication between the CU and the PU can be ensured in the same frequency band [16].…”

Section: Introductionmentioning

confidence: 99%

An Optimized Algorithm for CR-MIMO Wireless Networks

Elmitwally¹,

Kanwal²,

Abbas³

et al. 2022

Computers, Materials &Amp; Continua

View full text Add to dashboard Cite

With the rapid development of wireless communication technology, the spectrum resources are increasingly strained which needs optimal solutions. Cognitive radio (CR) is one of the key technologies to solve this problem. Spectrum sensing not only includes the precise detection of the communication signal of the primary user (PU), but also the precise identification of its modulation type, which can then determine the a priori information such as the PU' service category, so as to use this information to make the cognitive user (CU) aware to discover and use the idle spectrum more effectively, and improve the spectrum utilization. Spectrum sensing is the primary feature and core part of CR. Classical sensing algorithms includes energy detection, cyclostationary feature detection, matched filter detection, and so on. The energy detection algorithm has a simple structure and does not require prior knowledge of the PU transmitter signal, but it is easily affected by noise and the threshold is not easy to determine. The combination of multiple-input multiple-output (MIMO) with CR improves the spectral efficiency and multipath fading utilization. To best utilize the PU spectrum while minimizing the overall transmit power, an iterative technique based on semidefinite programming (SDP) and minimum mean squared error (MMSE) is proposed. Also, this article proposed a new method for max-min fairness beamforming. When compared to existing algorithms, the simulation results show that the proposed algorithms perform better in terms of total transmitted power and signal-tointerference plus noise ratio (SINR). Furthermore, the proposed algorithm effectively improved the system performance in terms of number of iterations,

show abstract

Throughput maximization for downlink DF MIMO relay based SWIPT cognitive radio networks

Mohammadi

Andargoli

2023

Computer Communications

View full text Add to dashboard Cite

Resource allocation algorithm for downlink MIMO‐OFDMA based cognitive radio networks in spectrum underlay scenario

Cited by 5 publications

References 35 publications

Performance Analysis of QoS-Oriented OFDMA Protocol Based on IEEE 802.11ax for Cognitive Radio Network

Performance Analysis of QoS-Oriented OFDMA Protocol Based on IEEE 802.11ax for Cognitive Radio Network

An Optimized Algorithm for CR-MIMO Wireless Networks

Throughput maximization for downlink DF MIMO relay based SWIPT cognitive radio networks

Contact Info

Product

Resources

About