scholarly journals Security Aware Resource Allocation, Scheduling for Cognitive-NOMA Network

2020 ◽  
Vol 9 (4) ◽  
pp. 35-44
Keyword(s):  
Resource Allocation ◽  
Cognitive Radio ◽  
Multiple Access ◽  
Transmission Rate ◽  
Optimization Strategy ◽  
User Scheduling ◽  
Combined Model ◽  
Eavesdropping Attack ◽  
Multiple Access Schemes

The demand of real-time wireless communication is increasing drastically where users demand for better Quality of Service (QoS) for various applications. In order to satisfy the communication requirement, communication spectrum must be utilized efficiently and all the available resource must be allocated appropriately. Recently, the cognitive radio network has gained attraction in this field of communication due to its efficient nature of spectrum sensing and sharing. However, the interference between primary and secondary user is a tedious task which can degrade the performance. Hence, multiple-access schemes are introduced and Non-Orthogonal Multiple Access (NOMA) is considered as most promising technique. Several models have been introduced based on the combined model of CR (Cognitive Radio) and NOMA but dynamic resource allocation, channel state information and eavesdropping are the most challenging task in this field. Moreover, user scheduling is also an important parameter which improves the resource utilization. In this work, we have focused on downlink communication for CR-NOMA network and presented a new approach for resource allocation and user scheduling by presenting an optimization strategy. In order to address the eavesdropping attack, the secrecy transmission rate and secrecy capacity are introduced. Finally, simulation study is carried out and the performance of proposed approach is compared with the existing techniques which shows that the proposed approach achieves higher throughput and improve outage probability.

scholarly journals Autonomous Power Decision for the Grant Free Access MUSA Scheme in the mMTC Scenario

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 116
Author(s):  
Wissal Ben Ameur ◽  
Philippe Mary ◽  
Jean-François Hélard ◽  
Marion Dumay ◽  
Jean Schwoerer
Keyword(s):  
Interference Cancellation ◽  
Error Propagation ◽  
Multiple Access ◽  
Transmission Rate ◽  
Free Access ◽  
Decoding Complexity ◽  
Machine Type ◽  
Machine Type Communications ◽  
Multiple Access Schemes ◽  
Lower Complexity

Non-orthogonal multiple access schemes with grant free access have been recently highlighted as a prominent solution to meet the stringent requirements of massive machine-type communications (mMTCs). In particular, the multi-user shared access (MUSA) scheme has shown great potential to grant free access to the available resources. For the sake of simplicity, MUSA is generally conducted with the successive interference cancellation (SIC) receiver, which offers a low decoding complexity. However, this family of receivers requires sufficiently diversified received user powers in order to ensure the best performance and avoid the error propagation phenomenon. The power allocation has been considered as a complicated issue especially for a decentralized decision with a minimum signaling overhead. In this paper, we propose a novel algorithm for an autonomous power decision with a minimal overhead based on a tight approximation of the bit error probability (BEP) while considering the error propagation phenomenon. We investigate the efficiency of multi-armed bandit (MAB) approaches for this problem in two different reward scenarios: (i) in Scenario 1, each user reward only informs about whether its own packet was successfully transmitted or not; (ii) in Scenario 2, each user reward may carry information about the other interfering user packets. The performances of the proposed algorithm and the MAB techniques are compared in terms of the successful transmission rate. The simulation results prove that the MAB algorithms show a better performance in the second scenario compared to the first one. However, in both scenarios, the proposed algorithm outperforms the MAB techniques with a lower complexity at user equipment.

Resource Allocation Strategies in Cognitive Radio Networks Under QoS Constraints

2013 ◽  
pp. 81-104
Author(s):  
Stavroula Vassaki ◽  
Marios I. Poulakis ◽  
Athanasios D. Panagopoulos ◽  
Philip Constantinou
Keyword(s):  
Resource Allocation ◽  
Cognitive Radio ◽  
Effective Capacity ◽  
Future Research ◽  
Capacity Theory ◽  
Wireless Users ◽  
Future Research Directions ◽  
Resource Allocation Schemes ◽  
Efficient Mechanisms

The rapid growth of spectral resources’ demands, as well as the increasing Quality of Service (QoS) requirements of wireless users have led to the necessity for new resource allocation schemes which will take into account the differentiated QoS needs of each wireless user. Towards this direction, the researchers have introduced the concept of effective capacity, which is defined as the maximum rate that the channel can support in order to guarantee a specified QoS requirement. This concept has been considered as a “bridge” among the physical layer characteristics and the upper-layer metrics of QoS. During the last years, it has been widely employed for resource allocation problems in various wireless networks leading to efficient mechanisms. This chapter focuses on the employment of the effective capacity theory in Cognitive Radio (CR) systems, presenting an extensive survey on QoS-driven resource allocation schemes proposed in the literature. Some useful conclusions are presented and future research directions on this subject are highlighted and discussed.

scholarly journals Resource Allocation in the Cognitive Radio Network-Aided Internet of Things for the Cyber-Physical-Social System: An Efficient Jaya Algorithm

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3649 ◽  
Author(s):  
Xiong Luo ◽  
Zhijie He ◽  
Zhigang Zhao ◽  
Long Wang ◽  
Weiping Wang ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Cognitive Radio ◽  
Internet Of Things ◽  
Social System ◽  
Orthogonal Frequency Division Multiplexing ◽  
Transmission Rate ◽  
Radio Networks ◽  
Jaya Algorithm ◽  
Network Bandwidth ◽  
Computational Performance

Currently, there is a growing demand for the use of communication network bandwidth for the Internet of Things (IoT) within the cyber-physical-social system (CPSS), while needing progressively more powerful technologies for using scarce spectrum resources. Then, cognitive radio networks (CRNs) as one of those important solutions mentioned above, are used to achieve IoT effectively. Generally, dynamic resource allocation plays a crucial role in the design of CRN-aided IoT systems. Aiming at this issue, orthogonal frequency division multiplexing (OFDM) has been identified as one of the successful technologies, which works with a multi-carrier parallel radio transmission strategy. In this article, through the use of swarm intelligence paradigm, a solution approach is accordingly proposed by employing an efficient Jaya algorithm, called PA-Jaya, to deal with the power allocation problem in cognitive OFDM radio networks for IoT. Because of the algorithm-specific parameter-free feature in the proposed PA-Jaya algorithm, a satisfactory computational performance could be achieved in the handling of this problem. For this optimization problem with some constraints, the simulation results show that compared with some popular algorithms, the efficiency of spectrum utilization could be further improved by using PA-Jaya algorithm with faster convergence speed, while maximizing the total transmission rate.

scholarly journals Interference Minimization Resource Allocation for V2X Communication Underlaying 5G Cellular Networks

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Xiaoqin Song ◽  
Kuiyu Wang ◽  
Lei Lei ◽  
Liping Zhao ◽  
Yong Li ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Power Allocation ◽  
Communication Networks ◽  
Transmission Rate ◽  
Transmission Power ◽  
Interference Minimization ◽  
Initial Power ◽  
Cellular Mobile ◽  
Optimization Mechanism

In this paper, the resource allocation for vehicle-to-everything (V2X) underlaying 5G cellular mobile communication networks is considered. The optimization problem is modeled as a mixed binary integer nonlinear programming (MBINP), which minimizes the interference to 5G cellular users (CUs) subject to the quality of service (QoS), the total available power, the interference threshold, and the minimal transmission rate. To achieve that, the original MBINP is decomposed into three steps: transmission power initialization, subchannel assignment, and power allocation. Firstly, the minimum transmission power required by the V2X users (VUs) is set as the initial power value. Secondly, the Hungarian algorithm is used to obtain the appropriate subchannel. Finally, an optimization mechanism is proposed to the power allocation. Simulation results show that the proposed algorithm can not only ensure the minimal transmission rate of VUs but also further improve the CUs’ channel capacity under the premise of guaranteeing the QoS of the CUs.

scholarly journals Optimal Resource Allocation For Video Streaming Over Cognitive Radio Network Via Geometric Programming

2021 ◽  
Author(s):  
Bo Guan
Keyword(s):  
Resource Allocation ◽  
Cognitive Radio ◽  
Video Streaming ◽  
Cognitive Radio Networks ◽  
Geometric Programming ◽  
Single Channel ◽  
Transmission Rate ◽  
Radio Networks ◽  
Spectrum Utilization ◽  
Queuing Delay

Cognitive Radio (CR) is a new paradigm in wireless communications to enhance utilization of limited spectrum resources. In the cognitive radio networks, each secondary user can use wireless channels for data transmission to improve the spectrum utilization. This thesis focus on the resource allocation problem for video streaming over cognitive radio networks, where secondary users and primary users transmit data simultaneously in a common frequency band. Respectively, we investigate CR in both single channel and multiple channels scenarios for single-layered and multi-layered streaming video, which is encoded into multiple layers delivered over a separate channel. Moreover, the source rate, the transmission rate, and the transmission power at each video session in each channel are jointly optimized to provide Quality of Service (QoS) guarantee to all video sessions in the secondary network. The optimization problem is formulated into a Geometric Programming (GP) problem, which can be solved efficiently. In the simulations, we demonstrate that the proposed scheme can achieve a lower Packet Loss Rate (PLR) and queuing delay, thus leading to a higher video quality for the video streaming sessions, compared to the uniform scheme.

scholarly journals Radio Resource Allocation with The Fairness Metric for Low Density Signature OFDM in Underlay Cognitive Radio Networks

Sensors ◽  
2019 ◽  
Vol 19 (8) ◽  
pp. 1921 ◽  
Author(s):  
Linda Meylani ◽  
Adit Kurniawan ◽  
M. Sigit Arifianto
Keyword(s):  
Resource Allocation ◽  
Cognitive Radio ◽  
Cognitive Radio Networks ◽  
Orthogonal Frequency Division Multiplexing ◽  
Multiple Access ◽  
Radio Networks ◽  
Low Density ◽  
Small Set ◽  
Underlay Cognitive Radio ◽  
Code Division Multiple

Low density signature orthogonal frequency division multiplexing (LDS-OFDM), one type of non-orthogonal multiple access (NOMA), is a special case of multi-carrier code division multiple access (MC-CDMA). In LDS-OFDM, each user is allowed to spread its symbols in a small set of subcarriers, and there is only a small group of users that are permitted to share the same subcarrier. In this paper, we study the resource allocation for LDS-OFDM as the multiple access model in cognitive radio networks. In our scheme, SUs are allocated to certain d v subcarriers based on minimum interference or higher SINR in each subcarrier. To overcome the problem where SUs were allocated less than the d v subcarriers, we propose interference limit-based resource allocation with the fairness metric (ILRA-FM). Simulation results show that, compared to the ILRA algorithm, the ILRA-FM algorithm has a lower outage probability and higher fairness metric value and also a higher throughput fairness index.

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