scholarly journals A multi-link communication connectivity game under hostile interference

2021 ◽  
Vol 2 (1) ◽  
pp. 101-112
Author(s):  
H.Vincent Poor ◽  
Narayan B. Mandayam ◽  
Wade Trappe ◽  
Andrey Garnaev
Keyword(s):  
Resource Allocation ◽  
Fixed Point ◽  
Rayleigh Fading ◽  
Primary User ◽  
Ground Control ◽  
Secondary Users ◽  
Power Resource ◽  
Zero Sum ◽  
Connectivity Problem ◽  
Allocation Strategies

In this paper, we consider a communication connectivity problem involving a primary user (transmitter, for example, a Ground Control Station (GCS)) servicing a group of secondary users (receivers, for example, drones) under hostile interference. We formulate this multi-link communication connectivity problem, where the channels are affected by Rayleigh fading, as a zero-sum power resource allocation game between a transmitter and an adversary (jammer). The transmitter's objective is to maximize the probability of communication connectivity with all the receivers. It is proven that the problem has unique equilibrium in power allocation strategies, and the equilibrium is derived in closed form. Moreover, we reduce the problem of designing the equilibrium in power resource allocation strategies to the problem of finding a fixed point of a real-valued function. An algorithm based on the bisection method to find the fixed point (and so equilibrium strategies) is developed, and its convergence is proven.

scholarly journals Secure Data Transmission by Detecting Different Attacks in CRN to improve the throughput

2019 ◽  
Vol 9 (2) ◽  
pp. 5488-5494
Keyword(s):  
Resource Allocation ◽  
Cognitive Radio ◽  
Data Transmission ◽  
Cognitive Radio Network ◽  
Primary User ◽  
Radio Networks ◽  
Radio Network ◽  
Secondary Users ◽  
Security Issues ◽  
Secure Data Transmission

Cognitive Radio (CR) is a technology that promises to solve the data transmission problem by allowing secondary users to coexist with primary user without causing any interference to the communication. It means to improve the usage of the radio assets to improve the throughput. Despite the fact that the operational parts of CR are being investigated broadly, its security viewpoints have increased little consideration. In this work, present a CRN architecture , Different Protocol, with complete rundown of major known security dangers and assaults inside a Cognitive Radio Network (CRN). Our goal in this paper is to dissect the distinctive security issues of the primary ongoing advancements of Cognitive Radio Networks with proper resource allocation to improve the throughput.

Aadptive Subcarrier Allocation for Multiple Cognitive Users over Fading Channels

2013 ◽  
Vol 765-767 ◽  
pp. 647-652
Author(s):  
Xiao Rong Xu ◽  
Ai Ping Huang ◽  
Jian Rong Bao ◽  
Hang Guan Shan
Keyword(s):  
Resource Allocation ◽  
Fading Channels ◽  
Spectral Efficiency ◽  
Power Distribution ◽  
Spectrum Sharing ◽  
Low Complexity ◽  
Primary User ◽  
Subcarrier Allocation ◽  
Spectrum Utilization ◽  
Secondary Users

In Cognitive Radio Network (CRN), where Primary User (PU) and multiple Secondary Users (SUs) wish to communicate with their corresponding receivers simultaneously over fading channels, spectrum utilization and efficient resource allocation are both significant points for CRN. Interference between PU and SUs should be eliminated in order to realize spectrum sharing. Multi-user resource allocation with the target of maximizing the spectral efficiency of SUs and satisfying the proportional rate constraint between SUs are proposed under the conditions of total SU interference constraint. An adaptive low-complexity suboptimal algorithm for subcarrier and power joint allocation is presented based on Rate Adaptive (RA) criterion, where adaptive subcarrier allocation is performed by assuming equal power distribution, while each subcarrier is assigned in accordance with subcarrier efficiency function. Moreover, linear water-filling algorithm for power allocation is applied within each subcarrier. Simulation results indicate that, with the proposed adaptive subcarrier allocation, spectral efficiency of multiple SUs is superior to traditional subcarrier power joint allocation algorithm. Low computational complexity and adaptive features make it available for implementation.

scholarly journals Deep reinforcement learning for resource allocation with network slicing in cognitive radio network

2020 ◽  
pp. 55-55
Author(s):  
Siyu Yuan ◽  
Yong Zhang ◽  
Wenbo Qie ◽  
Tengteng Ma ◽  
Sisi Li
Keyword(s):  
Resource Allocation ◽  
Cognitive Radio ◽  
Spectral Efficiency ◽  
Primary User ◽  
Spectrum Efficiency ◽  
Cognitive Network ◽  
Secondary Users ◽  
Network Resource ◽  
Resource Allocation Algorithm ◽  
Efficient Performance

With the development of wireless communication technology, the requirement for data rate is growing rapidly. Mobile communication system faces the problem of shortage of spectrum resources. Cognitive radio technology allows secondary users to use the frequencies authorized to the primary user with the permission of the primary user, which can effectively improve the utilization of spectrum resources. In this article, we establish a cognitive network model based on under1 lay model and propose a cognitive network resource allocation algorithm based on DDQN (Double Deep Q Network). The algorithm jointly optimizes the spectrum efficiency of the cognitive network and QoE (Quality of Experience) of cognitive users through channel selection and power control of the cognitive users. Simulation results show that proposed algorithm can effectively improve the spectral efficiency and QoE. Compared with Q-learning and DQN, this algorithm can converge faster and obtain higher spectral efficiency and QoE. The algorithm shows a more stable and efficient performance.

scholarly journals Balancing scarce hospital resources during the COVID-19 pandemic using discrete-event simulation

2021 ◽  
Author(s):  
G.J. Melman ◽  
A.K. Parlikad ◽  
E.A.B. Cameron
Keyword(s):  
Resource Allocation ◽  
Discrete Event Simulation ◽  
Elective Surgery ◽  
Discrete Event ◽  
Specific Patient ◽  
Event Simulation ◽  
The Impact ◽  
Allocation Decisions ◽  
Allocation Strategies ◽  
Resource Allocation Decisions

AbstractCOVID-19 has disrupted healthcare operations and resulted in large-scale cancellations of elective surgery. Hospitals throughout the world made life-altering resource allocation decisions and prioritised the care of COVID-19 patients. Without effective models to evaluate resource allocation strategies encompassing COVID-19 and non-COVID-19 care, hospitals face the risk of making sub-optimal local resource allocation decisions. A discrete-event-simulation model is proposed in this paper to describe COVID-19, elective surgery, and emergency surgery patient flows. COVID-19-specific patient flows and a surgical patient flow network were constructed based on data of 475 COVID-19 patients and 28,831 non-COVID-19 patients in Addenbrooke’s hospital in the UK. The model enabled the evaluation of three resource allocation strategies, for two COVID-19 wave scenarios: proactive cancellation of elective surgery, reactive cancellation of elective surgery, and ring-fencing operating theatre capacity. The results suggest that a ring-fencing strategy outperforms the other strategies, regardless of the COVID-19 scenario, in terms of total direct deaths and the number of surgeries performed. However, this does come at the cost of 50% more critical care rejections. In terms of aggregate hospital performance, a reactive cancellation strategy prioritising COVID-19 is no longer favourable if more than 7.3% of elective surgeries can be considered life-saving. Additionally, the model demonstrates the impact of timely hospital preparation and staff availability, on the ability to treat patients during a pandemic. The model can aid hospitals worldwide during pandemics and disasters, to evaluate their resource allocation strategies and identify the effect of redefining the prioritisation of patients.

scholarly journals Large discreet resource allocation: a hybrid approach based on dea efficiency measurement

2008 ◽  
Vol 28 (3) ◽  
pp. 597-608 ◽  
Author(s):  
Eliane Gonçalves Gomes ◽  
João Carlos Correia Baptista Soares de Mello ◽  
Lidia Angulo Meza
Keyword(s):  
Resource Allocation ◽  
Hybrid Approach ◽  
Data Envelopment ◽  
Efficiency Measures ◽  
Starting Point ◽  
Computational Work ◽  
Research Problems ◽  
Dea Models ◽  
Dea Efficiency ◽  
Zero Sum

Resource allocation is one of the traditional Operations Research problems. In this paper we propose a hybrid model for resource allocation that uses Data Envelopment Analysis efficiency measures. We use Zero Sum Gains DEA models as the starting point to decrease the computational work for the step-bystep algorithm to allocate integer resources in a DEA context. Our approach is illustrated by a numerical example.

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