A Survey on Advanced Multiple Access Techniques for 5G and Beyond Wireless Communications

Mathur, Harshita; Deepa, T.

doi:10.1007/s11277-021-08115-w

Cited by 34 publications

(34 citation statements)

References 54 publications

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“…A detailed derivation of this system model for MIMO GFDM along with characterization of H T , H C and H R can be found in [25]. The model in (4) shows the innate ability of the tensor framework from (3) to incorporate additional domains in the system model.…”

Section: Examples Of Practical Systemsmentioning

confidence: 99%

“…As Internet of Things (IoT) gains prominence, the massive increase in the number of devices requiring wireless connectivity along with extremely high data rates present significant challenges for future communication systems and networks, such as 5G and beyond. To meet such competitive objectives, various technologies are being proposed including Large multiple-input multiple-output (MIMO) [1], Millimeter-Wave [2], non-orthogonal multiple-access schemes [3,4], machine-to-machine communications, and network densification [5]. These trends create the need for communication systems with transceivers that incorporate an eclectic mix of domains.…”

Section: Introductionmentioning

confidence: 99%

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Multi-Domain Communication Systems and Networks: A Tensor-Based Approach

Pandey

Venugopal

Leib

2021

Network

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Most modern communication systems, such as those intended for deployment in IoT applications or 5G and beyond networks, utilize multiple domains for transmission and reception at the physical layer. Depending on the application, these domains can include space, time, frequency, users, code sequences, and transmission media, to name a few. As such, the design criteria of future communication systems must be cognizant of the opportunities and the challenges that exist in exploiting the multi-domain nature of the signals and systems involved for information transmission. Focussing on the Physical Layer, this paper presents a novel mathematical framework using tensors, to represent, design, and analyze multi-domain systems. Various domains can be integrated into the transceiver design scheme using tensors. Tools from multi-linear algebra can be used to develop simultaneous signal processing techniques across all the domains. In particular, we present tensor partial response signaling (TPRS) which allows the introduction of controlled interference within elements of a domain and also across domains. We develop the TPRS system using the tensor contracted convolution to generate a multi-domain signal with desired spectral and cross-spectral properties across domains. In addition, by studying the information theoretic properties of the multi-domain tensor channel, we present the trade-off between different domains that can be harnessed using this framework. Numerical examples for capacity and mean square error are presented to highlight the domain trade-off revealed by the tensor formulation. Furthermore, an application of the tensor framework to MIMO Generalized Frequency Division Multiplexing (GFDM) is also presented.

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Section: Examples Of Practical Systemsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Multi-Domain Communication Systems and Networks: A Tensor-Based Approach

Pandey

Venugopal

Leib

2021

Network

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“…After producing initial solutions and calculating their fitness, the selection phase generates the Mainting Pool and the Offspring matrixes. Since the data collection problem on WSNs is considered a minimization one, the selection probability of the chromosome to transfer the Mainting Pool matrix is defined as (3). IRGA aims to shift the solutions with a lower cost to the Mainting Pool matrix with a higher probability, but the more senior cost chromosomes also have little chance.…”

Section: -2 Selection Phasementioning

confidence: 99%

“…Over the last decades, wireless communications have been significantly expanded to offer services in modern environments [1][2][3]. Wireless Sensor Networks (WSNs) are among the hottest communication technologies that affect the various domains of human life [4,5].…”

Section: Introductionmentioning

confidence: 99%

An Integrated Routing Mechanism on Homogenous Wireless Sensor Networks using Genetic Algorithm

Danehchin

2021

Preprint

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Data collection on Wireless Sensor Networks (WSNs) is a significant challenge to satisfy the requirements of various applications. Providing an energy-efficient routing technique is the primary step in data collection over WSNs. The existing data collection techniques in the WSNs field struggle with the imbalance load distribution and the short lifetime of the network. This paper proposes a novel mechanism to select cluster-heads, cluster the wireless sensor nodes, and determine the optimal route from source nodes to the sink. We employ the genetic algorithm to solve the routing problem considering the hop-count of the cluster-heads to the sink, the number of each cluster member, residual energy of cluster-heads, and the number of cluster-heads connected to the sink as the fitness criteria. Our proposed mechanism uses a greedy approach to calculate the hop-count of each cluster-head to the sink for integrating the clustering and routing process on WSNs. The simulation results demonstrate that our proposed mechanism improves the energy consumption, the number of live nodes, and the lifetime of the network compared to other data collection approaches on WSNs.

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“…The literature studies innovation based on the management perspective and argues that energy creation is not enough to rely only on technological improvements, but also on other potential behaviors to improve the wealth creation of resources [ 7 ], such as management innovation. The literature includes institutional innovation as an endogenous variable in the innovation process and the empirical analysis of maritime transport productivity over the period 1600–1850 concludes that institutional improvements are more likely to cause productivity growth than technological changes [ 8 ]. Thus the literature argues that institutional innovation determines technological innovation rather than technological innovation determining institutional innovation.…”

Section: Relevant Studiesmentioning

confidence: 99%

Optimization of STP Innovation Management Mechanisms Driven by Advanced Evolutionary IoT Arithmetic

Wang

Qing

Li³

2021

Computational Intelligence and Neuroscience

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Since industrialization, manufacturing has been an important pillar of a country’s economic development. Under the dual pressure of the new trend of global manufacturing development and the loss of competitive advantage of manufacturing industry, it is especially important to accelerate the enhancement of national high technology innovation capacity and the optimization of high technology policy innovation management mechanism driven by advanced evolutionary Internet of Things (IoT) arithmetic. The main of this paper thus introduces the effective method of optimization of high technology policy innovation management mechanism driven by advanced evolutionary IoT arithmetic. To study the optimization of high technology policy innovation management mechanism, a conceptual analysis of currently popular information technologies, such as big data technologies, artificial intelligence technologies, and Internet of Things technologies, and an overview of the application of these technologies in microgrids are given. In the paper, all factors are studied using the STP innovation management mechanism-based approach, and finally, all factors are classified into two categories of cause and effect factors by this approach, and the importance of all factors is ranked. Secondly, a wind power prediction algorithm based on data mining technology and an improved algorithm and a PV power prediction algorithm based on a deep neural network were established with the technical support of high-tech information technology such as big data and artificial intelligence. Finally, the majorization of high technology policy innovation management mechanism driven by advanced evolutionary IoT arithmetic is proposed.

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A Survey on Advanced Multiple Access Techniques for 5G and Beyond Wireless Communications

Cited by 34 publications

References 54 publications

Multi-Domain Communication Systems and Networks: A Tensor-Based Approach

Multi-Domain Communication Systems and Networks: A Tensor-Based Approach

An Integrated Routing Mechanism on Homogenous Wireless Sensor Networks using Genetic Algorithm

Optimization of STP Innovation Management Mechanisms Driven by Advanced Evolutionary IoT Arithmetic

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