CDE using improved opposite based swarm optimization for MIMO systems

Khan, Muhammad Adnan; Umair, Muhammad; Saleem, Muhammad; Ali, Muhammad Nadeem; Abbas, Sagheer

doi:10.3233/jifs-181127

Cited by 28 publications

(10 citation statements)

References 3 publications

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“…As a result, the computational complexity of the system is also increased [10]. The adaptive implementation of the MIMO system is better to approach in order to overcome the computation complexity problem [10,36,37].…”

Section: • Training Based Methodsmentioning

confidence: 99%

“…There are numerous strategies like Neural Network [25][26][27]41], Genetic Algorithm (GA) [31][32][33] Differential Equation (DE), Cooperative Co-Evolutionary (CC) Algorithms [34], Particle Swarm Optimization (PSO) [40], Maximum Likelihood (ML) [5,6], Partial Opposite Mutant Particle Swarm Optimization (POMPSO), Total Opposite Mutant Particle Swarm Optimization (TOMPSO) [35][36][37], Island GA, Differential Equation (DE) and Island DE has been proposed which further enhance the performance of the 5-th generation communication network [20,38,39,41,42].…”

Section: • Training Based Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Multi user detection using fuzzy logic empowered adaptive back propagation neural network

Abbas¹,

Khan²,

Ata³

et al. 2019

NNW

Self Cite

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In Wireless communication, Multiple Input and Multiple Output (MIMO) systems have always been quite popular. Multicarrier systems are established along with different techniques of space-time coding to accomplish the demands of these systems. One of the most popular techniques is Multi-Carrier Code Division Multiple Access (MC-CDMA) with Alamouti's Space-Time Block Codes (STBC). This article, proposed the Fuzzy Logic empowered Adaptive Back Propagation Neural Network (FLeABPNN) based Multi User Detection (MUD) system, which is used to determine the receiver weights of MC-CDMA with the scheme of two variations. The proposed FLeABPNN approach takes advantage of a neuro-fuzzy hybrid system which conglomerates the competences of both fuzzy logic and neural networks for multi-user detection. It is observed that due to the fuzzy logic-based learning rate, proposed FLeABPNN based receiver without relationship & with relationship achieved the 3.04 × 10 −06 and 2.05 × 10 −06 Bit Error Rate (BER) respectively. The proposed FLeABPNN based receiver gives fast convergence rate & low BER as compared to other suboptimal published techniques like GA & LMS. It also observed that the Computational Complexity of the proposed FLeABPNN based MC-CDMA receiver is less then LMS based receiver up to 18 users, but higher than GA based receiver.

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Section: • Training Based Methodsmentioning

confidence: 99%

Section: • Training Based Methodsmentioning

confidence: 99%

Multi user detection using fuzzy logic empowered adaptive back propagation neural network

Abbas¹,

Khan²,

Ata³

et al. 2019

NNW

Self Cite

View full text Add to dashboard Cite

show abstract

“…Deep & Machine learning arose over the last two decades from the increasing capacity of computers to process large amounts of data empowered with cloud computing [27,28]. Computational Intelligence approaches like Swarm Intelligence [29], Evolutionary Computing [30] like Genetic Algorithm [31], Neural Network [32], Deep Extreme Machine learning [33] and Fuzzy system [34][35][36][37][38] are strong candidate solutions in the field of the smart city [39][40][41], smart health empowered with cloud computing [42,43], and wireless communication [44,45,46], etc.…”

Section: Software As a Service (Saas's) Qosmentioning

confidence: 99%

Intelligent Model for Predicting the Quality of Services Violation

Khan¹,

Kanwal²,

Abbas³

et al. 2022

Computers, Materials &Amp; Continua

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Cloud computing is providing IT services to its customer based on Service level agreements (SLAs). It is important for cloud service providers to provide reliable Quality of service (QoS) and to maintain SLAs accountability. Cloud service providers need to predict possible service violations before the emergence of an issue to perform remedial actions for it. Cloud users' major concerns; the factors for service reliability are based on response time, accessibility, availability, and speed. In this paper, we, therefore, experiment with the parallel mutant-Particle swarm optimization (PSO) for the detection and predictions of QoS violations in terms of response time, speed, accessibility, and availability. This paper also compares Simple-PSO and Parallel Mutant-PSO. In simulation results, it is observed that the proposed Parallel Mutant-PSO solution for cloud QoS violation prediction achieves 94% accuracy which is many accurate results and is computationally the fastest technique in comparison of conventional PSO technique.

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“…Other benefits of HTTPS include data confidentiality; data integrity checks and ensures reliable transmission. Computational Intelligence approaches like Fuzzy system [10,11,12,13,20,21,22,25,27,30], Neural Network [21,24,25,29], Swarm Intelligence [22,25,31,32] & Evolutionary Computing [14,15,16,23] like Genetic Algorithm [14,15], Differential Evolutionary (DE), Island GA [17], Island DE [18,19], Deep Extreme Learning Machine [25,26,28] are strong candidate solutions in the field of IoT enabled smart city [11,12,20,24], IoT enabled Smart health [13,25,27,30], Cryptography [33] and wireless communication [22,24,25,26,28] etc. Computational Approaches are hot research area which is also used in IoT based System.…”

Section: Literaturementioning

confidence: 99%

Analytical Method to Improve the Security of Internet of Things with Limited Resources

Khan

Siddiqui

Irshad

et al. 2019

EAI Endorsed Trans IoT

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This research is about the information security of very obliged gadgets. Design Science Research (DSR) Method is utilized for this reason. It let us pick up the fundamental thought and exploration of the primary issue space. This is a procedure of combining distinctive pre-affirmed examines to pick up the goal. Symmetric cryptography will be utilized as a noteworthy device in various information items and entryway gadgets. The principle target of this exploration is to give security to exceptionally constrained gadgets as they are not ready to convey utilizing TLS or DTLS given a deficiency of assets. This arrangement is a finished bundle to give credibility, information honesty and privacy, either information is making a trip to entryway, gadgets or the web. At the information interface layer, AES symmetric encryption is utilized and information questions likewise are encoded utilizing a similar encryption strategy. Assessment is performed using wire shark.

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CDE using improved opposite based swarm optimization for MIMO systems

Cited by 28 publications

References 3 publications

Multi user detection using fuzzy logic empowered adaptive back propagation neural network

Multi user detection using fuzzy logic empowered adaptive back propagation neural network

Intelligent Model for Predicting the Quality of Services Violation

Analytical Method to Improve the Security of Internet of Things with Limited Resources

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