Evidential Obstacle Learning in Millimeter wave D2D communication using Spatial correlation

2022 ◽  
Author(s):  
Harish Ganesan ◽  
Sasthi C. Ghosh
Keyword(s):  
Spatial Correlation ◽  
Millimeter Wave ◽  
D2d Communication

Packet Retransmission in Hybrid Millimeter-Wave and Microwave D2D Communication System

2019 ◽  
Vol 110 (3) ◽  
pp. 1251-1270 ◽  
Author(s):  
Greisy Melissa Muñoz Prado ◽  
Paulo Cardieri ◽  
José Marcos Camara Brito
Keyword(s):  
Millimeter Wave ◽  
Communication System ◽  
D2d Communication ◽  
Packet Retransmission

Full-Duplex Relaying for D2D Communication in Millimeter Wave-based 5G Networks

2018 ◽  
Vol 17 (7) ◽  
pp. 4417-4431 ◽  
Author(s):  
Bojiang Ma ◽  
Hamed Shah-Mansouri ◽  
Vincent W. S. Wong
Keyword(s):  
Millimeter Wave ◽  
D2d Communication ◽  
Full Duplex ◽  
5G Networks

scholarly journals Manifold Discriminative Learning Inspired Hybrid Beamforming for Millimeter-Wave Massive MIMO Systems

2021 ◽  
Vol 09 (11) ◽  
Author(s):  
Xiaoping Zhou ◽  
Keyword(s):  
Spatial Correlation ◽  
Millimeter Wave ◽  
Massive Mimo ◽  
Mimo Systems ◽  
High Dimensional ◽  
Discriminative Learning ◽  
Hybrid Precoding ◽  
User Clustering ◽  
Sum Rate ◽  
Low Dimensional

Millimeter-wave (mmWave) massive MIMO (multiple-input multiple-output) is a promising technology as it provides significant beamforming gains and interference reduction capabilities due to the large number of antennas. However, mmWave massive MIMO is computationally demanding, as the high antenna count results in high-dimensional matrix operations when conventional MIMO processing is applied. Hybrid precoding is an effective solution for the mmWave massive MIMO systems to significantly decrease the number of radio frequency (RF) chains without an apparent sum-rate loss. In this paper, we propose user clustering hybrid precoding to enable efficient and low-complexity operation in high-dimensional mmWave massive MIMO, where a large number of antennas are used in low-dimensional manifolds. By modeling each user set as a manifold, we formulate the problem as clustering-oriented multi-manifolds learning. The manifold discriminative learning seek to learn the embedding low-dimensional manifolds, where manifolds with different user cluster labels are better separated, and the local spatial correlation of the high-dimensional channels within each manifold is enhanced. Most of the high-dimensional channels are embedded in the low-dimensional manifolds by manifold discriminative learning, while retaining the potential spatial correlation of the high-dimensional channels. The nonlinearity of high-dimensional channel is transformed into global and local nonlinearity to achieve dimensionality reduction. Through proper user clustering, the hybrid precoding is investigated for the sum-rate maximization problem by manifold quasi conjugate gradient methods. The high signal to interference plus noise ratio (SINR) is achieved and the computational complexity is reduced by avoiding the conventional schemes to deal with high-dimensional channel parameters. Performance evaluations show that the proposed scheme can obtain near-optimal sum-rate and considerably higher spectral efficiency than some existing solutions

scholarly journals Resource Allocation in Millimeter-Wave Device-to-Device Networks

2019 ◽  
Vol 2019 ◽  
pp. 1-16 ◽  
Author(s):  
Filbert Onkundi Ombongi ◽  
Heywood Ouma Absaloms ◽  
Philip Langat Kibet
Keyword(s):  
Resource Allocation ◽  
Millimeter Wave ◽  
Base Stations ◽  
D2d Communication ◽  
System Capacity ◽  
Fourth Generation ◽  
Live Streaming ◽  
Data Traffic ◽  
Research Issues ◽  
Device To Device

Recently, the mobile wireless communication has seen explosive growth in data traffic which might not be supported by the current Fourth Generation (4G) networks. The Fifth Generation (5G) networks will overcome this challenge by exploiting a higher spectrum available in millimeter-wave (mmwave) band to improve network throughput. The integration of the millimeter-wave communication with device-to-device communication can be an enabling 5G scheme in providing bandwidth-intensive proximity-based services such as video sharing, live streaming of data, and socially aware networking. Furthermore, the current cellular network traffic can also be offloaded by the D2D user devices thereby reducing loading at Base Stations (BSs), which would then increase the system capacity. However, the mmwave D2D communication is associated with numerous challenges, which include signal blockages, user mobility, high-computational complexity resource allocation algorithms, and increase in interuser interference for dense D2D user scenario. The paper presents review of existing channel and power allocation approaches and mathematical resource optimization solution techniques. In addition, the paper discusses the challenges hindering the realization of an effective allocation scheme in mmwave D2D communication and gives open research issues for further study.

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