Distributed Detection for Centralized and Decentralized Millimeter Wave Massive MIMO Sensor Networks

Chawla, Apoorva; Singh, Rakesh; Patel, Adarsh; Jagannatham, Aditya K.; Hanzo, Lajos

doi:10.1109/tvt.2021.3089669

Cited by 9 publications

(3 citation statements)

References 49 publications

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“…Network area provided with multiple base stations ensuring load balancing Based on the above approaches many numerous descendant approaches exist -Centralized, Decentralized Clustering,Hierarchical Clustering [9], Protocols based on processing, Data Aggregation with Clustering [10], Location Aware Clustering [11]Gossiping, Flooding [12] 2. Related Work…”

Section: Multiple Base Stationmentioning

confidence: 99%

Fault Tolerance and Energy Efficient Multi-Hop Clustering with Dual Base Stations in Large Scale Wireless Sensor Network

Rajeshwari¹,

Devi

2023

SN COMPUT. SCI.

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Wireless sensor network (WSN) with the recent advancement in wireless technologies and numerous applications gaining its impact and market value. WSNs are the collection and connection of low-cost sensor nodes deployed over some monitoring areas where human monitoring is quite di cult. At the same time, the limitation of these low-cost sensor nodes has identi ed numerous issues and implementation challenges. In this paper a brief introduction to WSN and its market statistic and impact. Some of the major issues and challenges are identi ed and addressed in this paper. The main contribution of this research work is to design a fault tolerance in the network with multiple base stations. The multiple base station will work with the multi-hop cluster head based on the shortest distance in the WSNs.

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Section: Multiple Base Stationmentioning

confidence: 99%

Fault Tolerance and Energy Efficient Multi-Hop Clustering with Dual Base Stations in Large Scale Wireless Sensor Network

Rajeshwari¹,

Devi

2023

SN COMPUT. SCI.

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“…Decentralized detection is an important element in a wide range of modern applications, such as the Internet of Things [ 1 ], smart grids [ 2 ], cognitive radio [ 3 ], and millimeter-wave communications [ 4 ]. However, many classical results in decentralized detection assume that agents’ observations are independent, conditioned on the underlying hypothesis.…”

Section: Introductionmentioning

confidence: 99%

Joint Detection and Communication over Type-Sensitive Networks

Shaska,

Mitra

2023

Entropy

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Due to the difficulty of decentralized inference with conditional dependent observations, and motivated by large-scale heterogeneous networks, we formulate a framework for decentralized detection with coupled observations. Each agent has a state, and the empirical distribution of all agents’ states or the type of network dictates the individual agents’ behavior. In particular, agents’ observations depend on both the underlying hypothesis as well as the empirical distribution of the agents’ states. Hence, our framework captures a high degree of coupling, in that an individual agent’s behavior depends on both the underlying hypothesis and the behavior of all other agents in the network. Considering this framework, the method of types, and a series of equicontinuity arguments, we derive the error exponent for the case in which all agents are identical and show that this error exponent depends on only a single empirical distribution. The analysis is extended to the multi-class case, and numerical results with state-dependent agent signaling and state-dependent channels highlight the utility of the proposed framework for analysis of highly coupled environments.

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“…The massive MIMO improves spectral efficiency and reduces energy consumption [12]. The centralized MIMO leads to high diversity gains by beamforming, which provides the greatest performance and flexibility [13]. It can adapt the antenna array radiation pattern in massive MIMO.…”

Section: Introductionmentioning

confidence: 99%

BlockCRN-IoCV: Secure Spectrum Access and Beamforming for Defense Against Attacks in mmWave Massive MIMO CRN in 6G Internet of Connected Vehicles

Pari

Jaisankar

2022

IEEE Access

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Cognitive Radio (CR) is a wireless communication system that is used for intelligent vehicles to solve spectrum scarcity and improve the utilization of the spectrum. However, spectrum sensing and data sharing are difficult due to the presence of malicious nodes which degrades the performance. To overcome these issues, we proposed the BlockCRN-IoCV method which includes authentication, density aware clustering, dual agent based spectrum access and secure beamforming. Here, authentication is performed for both Primary Users (PUs) and Secondary Users (SUs) using the Hybrid Advanced Encryption Standard and Hyper-elliptic Curve Cryptography (AES-HCC) algorithm by considering ID, PUF and location which ensures the legitimacy of the users. To address the mobility of the vehicle we perform density aware clustering using Density aware Dynamic Radius Clustering (DADRC) by considering location, distance and direction for increasing throughput. After completing clustering, we perform efficient spectrum access by using the Dual Agent based Twin Delayed (DA-TD3) algorithm which includes two agents, the first agent performs spectrum sensing by considering SNR, noise level and trust, and the second agent performs spectrum allocation by considering Channel State Information (CSI), in which the CSI is predicted by Quasi-Newton Iterative Unscented Kalman Filter (QNIUKF) algorithm for effective data transmission. Finally, secure beamforming is performed using Bi-Gated Recurrent Neural Network (BiGRU-CapsNet) by considering CSI, beam score, array factor, and direction of angle. The simulation is carried out by OMNET++ and SUMO simulation tools and the performance of this work is evaluated by throughput, packet delivery ratio, SNR, detection accuracy, BER, and delay. The simulation result shows that the proposed work achieves superior performance compared to existing work for secure spectrum sensing and beamforming.

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Distributed Detection for Centralized and Decentralized Millimeter Wave Massive MIMO Sensor Networks

Cited by 9 publications

References 49 publications

Fault Tolerance and Energy Efficient Multi-Hop Clustering with Dual Base Stations in Large Scale Wireless Sensor Network

Fault Tolerance and Energy Efficient Multi-Hop Clustering with Dual Base Stations in Large Scale Wireless Sensor Network

Joint Detection and Communication over Type-Sensitive Networks

BlockCRN-IoCV: Secure Spectrum Access and Beamforming for Defense Against Attacks in mmWave Massive MIMO CRN in 6G Internet of Connected Vehicles

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