Island genetic algorithm based MUD for MC-CDMA system

Umair, Muhammad; Khan, Muhammad Adnan; Choudry, Muhammad Aamer Saleem

doi:10.1109/icict.2015.7469588

Cited by 10 publications

(11 citation statements)

References 6 publications

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“…Moreover, heuristics approaches like those that Genetic Algorithm (GA), Pirahna Fish optimization (PFO), and Particle Swarm Optimization (PSO) are used along with ML-based multi-user data detection because these have the capability to decrease the search space and computational complexity of ML algorithms [14][15][16][17][18][19]. In MIMO based systems, the DE algorithm has also reduced the ML algorithm's search space and computational complexity of symbol detection 10, [16][17][18][19]. Apart from these, ML algorithms are designed to estimate multipath fading channel and transmitted data sequence jointly.…”

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

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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%

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

Abbas¹,

Khan²,

Ata³

et al. 2019

NNW

View full text Add to dashboard Cite

show abstract

“…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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“…Computational Intelligence approaches like Fuzzy system [22,23], Neural Network [24], Swarm Intelligence [25] & Evolutionary Computing [26] like Genetic Algorithm [27,28], DE, Island GA [29], Island DE [29,30] are strong candidate solution in the field of smart city [31,32] and smart health [34,35,36,37] etc.…”

Section: Literature Reviewmentioning

confidence: 99%

Diagnosis of Arthritis Using Adaptive Hierarchical Mamdani Fuzzy Type-1 Expert System

Siddiqui

Hussnain²,

Siddiqui³

et al. 2018

ICST Transactions on Scalable Information Systems

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The adroit system is frequently used in artificial intelligence in medicine (AIM). They comprise medical information about a dedicated task and prone to purpose with data from case studies to produce lucid results. Though there are many irregularities, the information with an adroit network is derived with a set of expert rules to produce accurate results. Arthritis is the stiffness of one or more joints and about three fourth of the victims are suffering from it. Late detection of that chronic disease may cause the severity of the sickness at greater risk. So the idea is to contemplate a mechanism for the detection of arthritis using an adaptive hierarchical Mamdani fuzzy expert system (DA-AH-MFES). It is a befitting source to process ambiguity and inaccuracy. Physical and some medical parameters with the expertise of doctors can be mapped using MFES. The ability of MFES completely depends on the rules which are finalized by a discussion with an expert. The expert system has eight input variables at layer-I and four input variables at layer-II. At layer-I input variables are rest pain, morning stiffness, body pain, joint infection, swelling, redness, past injury and age that detects output condition of arthritis to be normal, infection and/or other problem. The further input variables of layer-II are RF, ANA, HLA-B27, ANTI-CCP that determine the output condition of arthritis. The performance of proposed Diagnose arthritis disease using an adaptive hierarchical mamdani fuzzy expert system is evaluated with expert observations of Cavan General Hospital Lisdaran, Cavan, Ireland and Jinnah Hospital Lahore, Pakistan. The accuracy of the expert system (DA-AH-MFES) is 95.6%.

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Island genetic algorithm based MUD for MC-CDMA system

Cited by 10 publications

References 6 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

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

Diagnosis of Arthritis Using Adaptive Hierarchical Mamdani Fuzzy Type-1 Expert System

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