Efficient complex radial basis function model for multiuser detection in a space division multiple access/multiple‐input multiple‐output–orthogonal frequency division multiplexing system

Bagadi, Kala Praveen; Das, Susmita

doi:10.1049/iet-com.2012.0688

Cited by 24 publications

(3 citation statements)

References 31 publications

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“…Apart from these, ML algorithms are designed to estimate multipath fading channel and transmitted data sequence jointly. The algorithm operates on the iterative approach and does not require any prior channel information [12,[20][21][22][23][24].…”

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

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show abstract

“…Different forms of index modulation have extended their applications to wide variety, such as high speed vehicular communication, 32 mm-wave communication system, 33 visible light communication (VLC), 34 multi-user multiple input multiple output (MIMO) system 35,36 and many others. 7 Performance of OFDM-IM in the field of MIMO, 37 cognitive radio, 38 and underwater acoustic communication 39 have already been investigated.…”

Section: Introductionmentioning

confidence: 99%

Generalized index and mode modulatedOFDMwith improved spectral and energy efficiency

Sengupta,

Dasgupta,

Das Barman

2024

Trans Emerging Tel Tech

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Recently developed trends in wireless communication encounter extremely high surge in data traffic, which makes it inevitable to employ energy efficient techniques to reduce detrimental consequence of carbon emission over society. This concern has motivated us to upgrade our previous work on index and mode modulated orthogonal frequency division multiplexing (IMM‐OFDM) for achieving dual benefits in terms of spectral and energy efficiency. In this paper, we have proposed a generalized index and mode modulated OFDM scheme with variable number of subcarrier activation. Novelty of this generalized scheme is its capability to act as a unified model for classic OFDM and three other benchmark index modulated OFDM schemes along with our previously proposed IMM‐OFDM scheme. This new scheme outperforms those five descendent schemes in terms of energy efficiency and error performance as indicated by simulation results. Spectral efficiency improvement in this scheme is achieved through optimum sets of active subcarrier number, which are determined to gain most optimized trade‐off between spectral and energy efficiency with least detector complexity. This generalized parent scheme can replace individual models of its five descendent schemes and consequently can be considered to be one of the most promising candidates for next generation mobile communication system.

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“…Unlike traditional computing approaches that rely on precise logic and mathematical models, softcomputing techniques offer approximate solutions that effectively handle uncertain and incomplete data. Due to their merits, these techniques have been widely applied to various engineering problems [12][13][14][15][16]. This paper presents a heterogeneous-based 5G network model incorporating macro and small cells, data, and control planes.…”

Section: Introductionmentioning

confidence: 99%

Smart 5G Small Cell Mobile Networking with Sleep Strategy Using Novel Swarm Optimization

Yamarthi,

Yenuga,

Meda

et al. 2024

JAIT

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Due to its major contribution to the overall energy consumption in Information and Communication Technologies (ICT), lowering the energy consumption of mobile communication networks has attracted a lot of attention. This study presents the implementation of a 5G network model based on heterogeneity, employing macro cells and small cells, in conjunction with diverse users and control techniques. In this work, the analysis is performed between the consumption of energy and the performance of users in the cellular networks. The objective is to address the identified problem which is related to energy conservation and proposed a solution utilizing the Modified Particle Swarm Optimization (MPSO) algorithm, which is then compared with the existing Iterative Optimization Algorithm (IOA). The sleep strategy involved in this work helps to save energy by overlapping the cells. The evaluation of the implemented solution focuses on various parameters, including contract rate, power, earnings, and energy efficiency.Comparing the outcomes achieved through the two optimization algorithms, the MPSO-based evaluation demonstrates superior performance over the iterative optimization algorithm in terms of energy efficiency and power consumption. Before applying sleep strategy, the energy efficiency is 2.6%, after applying sleep strategy with IOA having 4% and with suggested approach efficiency is obtained is 6%. The evaluation is conducted using the Matlab software tool.

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Efficient complex radial basis function model for multiuser detection in a space division multiple access/multiple‐input multiple‐output–orthogonal frequency division multiplexing system

Cited by 24 publications

References 31 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

Generalized index and mode modulatedOFDMwith improved spectral and energy efficiency

Smart 5G Small Cell Mobile Networking with Sleep Strategy Using Novel Swarm Optimization

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