Cross-Layer Minimum-Delay Scheduling and Maximum-Throughput Resource Allocation for Multiuser Cognitive Networks

2013 ◽  
Vol 12 (4) ◽  
pp. 761-773 ◽  
Author(s):  
Ghada Saleh ◽  
Amr El-Keyi ◽  
Mohammed Nafie
Keyword(s):  
Resource Allocation ◽  
Cognitive Networks ◽  
Cross Layer ◽  
Maximum Throughput ◽  
Minimum Delay

scholarly journals Social-sine cosine algorithm-based cross layer resource allocation in wireless network

2021 ◽  
Vol 11 (1) ◽  
pp. 458
Author(s):  
Praveena T. ◽  
Nagaraja G. S.
Keyword(s):  
Resource Allocation ◽  
Wireless Network ◽  
Proportional Fairness ◽  
Cross Layer ◽  
Random Errors ◽  
Maximum Throughput ◽  
Medium Access ◽  
Fixed Rate ◽  
Sine Cosine Algorithm ◽  
The Cross

Cross layer resource allocation in the wireless networks is approached traditionally either by communications networks or information theory. The major issue in networking is the allocation of limited resources from the users of network. In traditional layered network, the resource are allocated at medium access control (MAC) and the network layers uses the communication links in bit pipes for delivering the data at fixed rate with the occasional random errors. Hence, this paper presents the cross-layer resource allocation in wireless network based on the proposed social-sine cosine algorithm (SSCA). The proposed SSCA is designed by integrating social ski driver (SSD) and sine cosine algorithm (SCA). Also, for further refining the resource allocation scheme, the proposed SSCA uses the fitness based on energy and fairness in which max-min, hard-fairness, proportional fairness, mixed-bias and the maximum throughput is considered. Based on energy and fairness, the cross-layer optimization entity makes the decision on resource allocation to mitigate the sum rate of network. The performance of resource allocation based on proposed model is evaluated based on energy, throughput, and the fairness. The developed model achieves the maximal energy of 258213, maximal throughput of 3.703, and the maximal fairness of 0.868, respectively.

Prediction-Based Cross-Layer Resource Allocation for Wireless Multi-Hop Networks with Outdated CSI

2014 ◽  
Vol E97.B (4) ◽  
pp. 746-754 ◽  
Author(s):  
Wei FENG ◽  
Suili FENG ◽  
Yuehua DING ◽  
Yongzhong ZHANG
Keyword(s):  
Resource Allocation ◽  
Cross Layer ◽  
Outdated Csi

scholarly journals Improvement of Spectral Efficiency in Home Area Network using Cognitive Radio Algorithm

2019 ◽  
Vol 8 (12) ◽  
pp. 1129-1131
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sharing ◽  
Queuing Theory ◽  
Primary User ◽  
Cognitive Networks ◽  
Area Network ◽  
Maximum Throughput ◽  
Multiple Channel ◽  
Faster Development ◽  
Home Region

The faster development of wireless communications has made the spectrum ending up with increasingly with more shortage. The idea of CR was proposed to meet the problem of spectrum effectiveness. In the cognitive networks, the SUs are permitted to detect, distinguish and access the frequency bands that are not at present used by the PU’s. the SU’s must outfit with the spectrum access information to use the primary user’s licence in the home region network. We propose a maximum throughput and power based cognitive radio for home region systems (HAN). At the point when there are different SU’s and numerous channels, spectrum sharing must be taken into account. In this paper we additionally propose a system of multiple channel sensing. We consider the interference to PU brought about by the dynamic access and the erroneous spectrum sensing technique. We investigate the obstruction brought about by the secondary user’s through a reestablishment hypothesis. Under the limitation of interference to primary user, the queuing theory is used to overcome this issue and to obtain the higher data rate of SU’s. finally, it is demonstrated that the cyclostationary detection method can be improved when extra channels are accessible.

scholarly journals Optimal and Robust Distributed Resource Allocation for SWIPT-Enabled Cognitive Networks

2020 ◽  
Author(s):  
Yongjun Xu ◽  
Haijian Sun ◽  
Jie Yang ◽  
Guan Gui ◽  
Song Guo
Keyword(s):  
Resource Allocation ◽  
Closed Form ◽  
Power Allocation ◽  
Energy Region ◽  
High Energy ◽  
Cognitive Networks ◽  
Feasible Region ◽  
Power Splitting ◽  
Joint Power ◽  
The Impact

Simultaneous wireless information and power transfer (SWIPT)-enabled cognitive networks (CRNs) is recognized as one of the most promising techniques to improve spectrum efficiency and prolong operation lifetime in 5G and beyond. However, existing methods focus on the centralized algorithm and the power allocation under perfect channel state information (CSI). The analytical solution and the impact of power splitting (PS) on the optimal power allocation strategy are not addressed. In addition, the influence of the PS factor on the feasible region of transit power is rarely analyzed. In this paper, we propose a joint power allocation and PS algorithm under perfect CSI and imperfect CSI, respectively, for multiuser SWIPT-enabled CRNs scenarios. The power minimization of resource allocation problem is formulated as a multivariate nonconvex optimization which is hard to obtain the closed-form solution. Hence, we propose a suboptimal algorithm to alternatively optimize the power allocation and PS coefficient under the cases of the low-harvested energy region and the high-harvested energy region, respectively. Moreover, a closed-form distributed power allocation and PS expressions are derived by the Lagrangian approach. Simulation results confirm the proposed method with good robustness and high energy efficiency.

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